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Decision Aids for Patients Considering Options Affecting Cancer Outcomes: Evidence of Efficacy and Policy Implications

Decision Aids for Patients Considering Options Affecting Cancer Outcomes: Evidence of Efficacy... Abstract Some cancer screening and treatment decisions are not clear cut because outcomes are uncertain or options have different benefit/risk profiles. “Decision aids” have been developed as adjuncts to counseling so that patients can learn about benefits and risks, can consider their personal values, and can participate with their practitioner in decision making. The purpose of this paper is to review published evidence about the efficacy of decision aids focused on cancer outcomes and to outline research and dissemination issues. Studies evaluating cancer-related decision aids demonstrate that they are acceptable to patients and help those who are uncertain at baseline to make choices. They also increase the likelihood that choices are based on better knowledge, realistic expectations of outcomes, and personal values. Decision aids reduce some dimensions of decisional conflict, and their effect on decisions is variable. Few studies examine the downstream effects of decision aids on long-term persistence with choices, regret, and quality of life. The differences between simpler and more intensive methods of decision support appear to be negligible in terms of knowledge and satisfaction as well as variable in terms of decisions and decisional conflict. However, more intensive methods are superior in terms of user acceptability and of the extent to which choices are based on realistic expectations and personal values. The clinical importance of these differences and the cost-effectiveness remain to be established. On the basis of this review, several recommendations for research are made, and dissemination issues are identified. Some cancer screening and treatment decisions are not clear cut because of the uncertainty of the evidence on outcomes or the lack of consensus that the benefits outweigh the risks (1). Practice guidelines for these difficult decisions often recommend that practitioners exercise judgement in applying them to individual patients and that patients' values for the outcomes be considered (2,3). Accordingly, decision support interventions, known as “ decision aids” or “shared decision-making programs,” are being developed as adjuncts to practitioners' counseling (4-10) so that patients can 1) understand the probable benefits and risks of options, 2) consider the value they place on benefits versus risks, and 3) participate actively with their practitioners in deciding about options (2). The purpose of this paper is to review published evidence about the efficacy of decision aids focused on cancer outcomes and to outline research and policy implications. We will define decision aids, examine the reasons for their development, present their theoretical underpinnings, review the evidence of their efficacy, and discuss implications. What Is a Patient Decision Aid? Decision aids are used as adjuncts to practitioners' counseling to prepare patients for decision making. According to the Cochrane definition (11), they are interventions designed to help people make specific and deliberative choices among options by providing (at the minimum) information on the options and outcomes relevant to the person's health status. Additional strategies may include information on the disease or condition, probabilities of outcomes tailored to a person's health risk factors, an explicit values-clarification exercise, information on others' opinions, and guidance or coaching in the steps of decision making and communicating with others. Decision aids may be administered with the use of various media, such as decision boards, interactive videodiscs, personal computers, audiotapes, audio-guided workbooks, pamphlets, and group presentations. Excluded from the definition of decision aids are passive informed consent materials, educational interventions that are not geared to a specific decision, or interventions designed to promote compliance with a recommended option rather than a choice based on personal values. Why Are Patient Decision Aids Developed? The development of decision aids in several centers in the United States, the United Kingdom, and Canada is motivated by several trends: (a) the rise of consumerism with an emphasis on informed choice rather than informed consent, (b) the evidence-based practice movement disseminating evidence to consumers as well as to practitioners, (c) the interest in consumer-focused strategies to reduce large practice variations caused by supplier-induced demand, (d) the identification of treatment decisions that are “ utility” or “value” sensitive from decision analyses, (e) the proliferation of overviews and outcome studies that provide estimates of outcomes for use in decision aids, and (f) the evolution of patient preference-oriented health policy that reserves interventions for those patients who consider the treatment benefits to outweigh the risks (e.g., reserving palliative surgery for patients who consider symptom relief worth the surgical risks, rather than basing a surgical policy on the average patient's utilities). Kassirer (3) lists some indications for explicitly eliciting patients' preferences in clinical practice: 1) Options have major differences in outcomes or complications, 2) decisions require making trade-offs between near-term and long-term outcomes, 3) one choice can result in a small chance of a grave outcome, or 4) marginal differences are found in outcomes between options. Patient characteristics may also determine the need for a decision aid, e.g., if patients are very risk averse or attach unusual importance to certain possible outcomes. Another useful strategy for determining the need for a decision aid is to classify treatment policies as standards, guidelines, or options using definitions by Eddy (1). Table 1 summarizes the approach. For standards of care in which outcomes are known and patients' preferences are generally consistent in favoring an intervention, decision aids may be less useful, and conventional informed consent procedures are more appropriate. In contrast, decision aids may be indicated for treatment guidelines or options because outcomes may be more uncertain, or values for the benefits relative to the risks are more variable or unknown. For example, the guidelines (2) for postmenopausal hormone replacement therapy (HRT) recommend that decisions be tailored to a woman's hysterectomy status and risk of coronary heart disease (CHD), osteoporosis, and breast cancer. Moreover, a woman needs to consider her values in balancing the potential benefits of reducing the risk of osteoporosis and CHD and relief of menopausal symptoms against the potential risk of endometrial and breast cancers, the side effects of HRT, and her attitudes toward taking medication for a natural aging process. A recent example of an “option” emerged in 1998 following the early completion of the U.S. National Cancer Institute (NCI) Tamoxifen Prevention Trial. Although two smaller trials demonstrated no benefit, the NCI trial showed that tamoxifen reduced the incidence of breast cancer in high-risk women but also increased the risk of endometrial cancer, pulmonary embolus, and deep-vein thrombosis. Within 6 months of stopping the NCI trial, (a) NCI published the results on the Internet, including a statement that the decision about treatment depends on a woman's personal health history and how she weighs the benefits and risks; (b) the results of the three prevention trials were published; (c) tamoxifen was approved by the Food and Drug Administration (FDA) for use in women at high-risk for breast cancer; and (d) a “risk disk” to help practitioners and women identify personal risks for breast cancer and understand benefits and risks of tamoxifen was developed and disseminated. Note that the public and practitioners had simultaneous access to the information. How Are Decision Aids Designed to Work? Although the developers of decision aids have different conceptual frameworks of decision support (12-19), most are based on decision theories from economics and cognitive psychology (20-22) that structure decisions according to options, outcomes, and probabilities of outcomes so that patients are better able to judge the value of the benefits versus the risks. Many frameworks broaden this cognitive perspective by including emotional, social, or environmental dimensions (23-27). For example, the Ottawa Framework (12) identifies several determinants of health care decisions that may be suboptimal and are potentially modifiable by decision aids. Patients and practitioners may have problems with (a) perceptions of the decision (e.g., inadequate knowledge, unrealistic expectations of outcomes, unclear values, high uncertainty. or decisional conflict); (b) perceptions of others (e.g., biased or limited perceptions of the variation in others' opinions and practices, social pressures, or inadequate support); and (c) personal and external resources to make the decision (e.g., limited skills in shared decision making). Decision aids are designed to address these problematic determinants of choice by providing accurate, balanced, and tailored information; by clarifying patients' values; and by augmenting skills in shared decision making. For example, knowledge may be improved by providing information on options and outcomes. Unrealistic expectations (perceived probabilities of outcomes) may be realigned by presenting probabilities of outcomes that are tailored to the patient's clinical risk and by describing outcomes so that they are easy to imagine and to identify with (21). Unclear values are addressed by describing outcomes in familiar, simple, and experiential terms so as to better judge their value (22) and by providing the opportunity to weigh the benefits versus the risks. Biased perceptions of the variation in others' opinions may be corrected by presenting all options and, in some cases, by providing examples of others' choices and statistics on variation in choices. Shared decision-making skills may be improved by providing structure and guidance in deliberating about the personal issues involved in the choice and in communicating preferences (28-35). As a consequence of these interventions, patients presenting with uncertainty or decisional conflict caused by these problems may become more certain about what to choose and may be more likely to implement these choices (36). On the basis of the Ottawa framework, one can hypothesize that decision aids will improve the determinants of choice so that decisions are more likely to be 1) informed (i.e., based on better knowledge and realistic expectations), 2) consistent with personal values, and 3) implemented. Moreover, patients' comfort with the decision-making process (e.g., decisional conflict, self-confidence, and satisfaction with decision making) may be improved. On the basis of the results of other educational interventions (28,29,37-39) designed to promote realistic expectations of outcomes and informed active involvement in one's care, it is also reasonable to hypothesize that patients may be more likely to persist with decisions, to report less distress with the consequences of their decisions, and to experience improved health-related quality of life. Do Decision Aids Work? To date, there have been two published documents describing the efficacy of decision aids: an annotated bibliography (40,41) and a report to the Agency for Health Care Policy and Research (15). A Cochrane collaboration systematic overview (11) of randomized trials of decision aids is currently in progress. This paper summarizes the evaluative studies from the annotated bibliography (41), including an update to early 1998. The following databases were searched: MEDLINE®, CINAHL®, PsycINFO®, and Current Contents®. We also hand searched Medical Decision Making and Health Expectations. In this paper, we limited our review to studies of interventions that would be classified as decision support according to the Cochrane definition (see previous section). We included three types of studies 1) before/after studies that evaluated decision aids with patients at the point of decision making, 2) randomized trials that evaluated decision aids in comparison to “usual care” with patients at the point of decision making, and 3) randomized experiments comparing different methods of decision support in decision aids either with patients at the point of decision making or with volunteers making hypothetical choices. We included studies of decision aids that were not cancer related because of the small numbers of studies available in this emerging field of research. Types of Decision Aids Studied Table 2 summarizes the decisions aids that were identified in this review. Over half of the studies focused on cancer-related topics. Most decision aids focused on surgical or medical therapies, although a few considered preventive, end-of-life, and clinical trial participation decisions. Various media were used for delivering the decision aids. In some of the studies, it was difficult to ascertain what exactly was done in the “black box” of the decision aid. Although all decision aids included information on the options, benefits, and risks, they varied considerably in their presentation of this information. Moreover, there was considerable variability in whether other decision-support strategies were included in the decision aid. It was also sometimes difficult to ascertain what was involved in “usual care” or in the comparative intervention. Evaluative Studies of Efficacy Table 3 summarizes the results of the evaluative studies with patients at the point of decision making in which before/after designs and randomized trials with usual care controls were used. Effect on Variation in Choices One of the main rationales for using decision aids has been to reduce “ inappropriate” practice variation. It is assumed that, if the asymmetry of information available to practitioners and patients regarding options, outcomes, and patients' values is corrected by decision aids, then choices may more appropriately reflect patients' preferences. The direction of the shift in choices will depend on the cause of the practice variation. For example, if overuse is caused by supplier-induced demand involving knowledgeable practitioners who assume patients' values are similar to their own and uninformed patients, rates of use may decline if patients' informed valuing of options does not correspond to those of their practitioners. If there is underuse of interventions because of uninformed practitioners or patients, rates of use may increase. The before/after studies (12,42-45,60), including two cancer-related studies (12,60), are consistent in showing that decision aids have the greatest effect on the choices of those who are undecided at baseline. Approximately 18%-30% of patients were undecided before using decision aids, and 44%-68% of the undecided made a choice after using aids. The fact that over a third of the undecided still could not make up their mind after using a decision aid underscores the difficulty of these decisions and the need for follow-up counseling by practitioners. In contrast, decision aids are less likely to change the decisions of the 70%-82% of individuals who have a stated preference at baseline (12,42-44). Changes occurred in only 5%-13% of those preferring a more intensive treatment at baseline and in 11%-18% of those preferring a less intensive treatment. However, in some studies (45,54,60), the decision aid did shift preferences toward the less intensive option, e.g., toward breast-conserving surgery for breast cancer (60). The randomized trials comparing decision aids with usual care also suggest that decision aids affect decisions. They reduced the proportion of undecided in one trial (46) and showed a trend toward reducing preferences for more intensive options by 22%-48% in six of seven trials. Flood et al. (47) underscore the importance of predisposition and financial incentives in changing the decisions of patients. Two trials (47,51) showed that men who were exposed to decision aid about the prostate-specific antigen (PSA) before a routine scheduled fee-for-service visit had close to half the rates of PSA testing than usual-care control subjects. In contrast, the rates of PSA testing in another study (47) were comparable in those exposed to a decision aid (98%) versus a general education video (100%) in a clinic where men attended specifically for a free PSA test. However, the men receiving the free test differed in intentions toward having future PSA tests (which they would presumably have to pay for); in the decision-aid group, 74% had strong intentions to have a PSA test compared with 90% in the education video group. Effect on Determinants of and Comfort With Decision Making The most important question is: Are these observed changes in decisions after using a decision aid accompanied by commensurate improvements in the determinants of the choices? In Table 3, the before/after studies of decision aids focused on cancer and other outcomes are consistent in demonstrating that patients' choices are more likely to be based on better knowledge (8,12,42,43,52), more realistic expectations of outcomes (12,53-58), and personal values for outcomes (12,58,59) after patients use decision aids. Moreover, patients' comfort with their decisions, as measured by the Decisional Conflict Scale, is improved (12,54,55,58,60). The randomized trials, including two trials of PSA decision aids (47,51), have confirmed that decision aids are superior to usual care in improving knowledge (46,48), but the benefit is confined to feeling more informed about options, benefits, and risks. These results point to one of the main mechanisms explaining the potentially conservative effect of decision aids on decision making. The decision aids are better than usual care at moderating patients' exaggerated perceptions of risk of disease without the intervention and their exaggerated perceptions of the benefits of interventions. The aid also gives them a better appreciation of the potential risks associated with the more intensive intervention. Therefore, fewer patients are likely to judge that the potential benefits of the intensive option outweigh the potential harms. There have been no trials examining the effect of cancer-related decision aids on patients' satisfaction with decision making. For other trials of decision aids, most have shown no impact. Effect on Outcomes of Decisions Although outcomes of decisions are difficult to judge when decisions are based on personal values, it is still useful to examine how decision aids affect long-term persistence with choices, distress, regret, and health-related quality of life. There are no cancer studies examining the downstream effects of decision aids. The two noncancer studies (4,49) examining quality of life had variable results. Patients' Reactions to Decision Aids Before/after studies (6,42-44,57-60,62-64) are generally consistent in demonstrating that decision aids are acceptable to patients and are feasible to use. Further evaluations are needed to establish acceptability to practitioners and to patient groups who vary by age, education, ethnicity, and preferences for participation in decision making. Randomized Experiments Comparing Simpler With More Intensive Methods of Decision Support Table 4 summarizes the trials comparing simpler with more intensive methods of decision support. All but two of the trials focused on decision aids with cancer outcomes. In all of the decision-support interventions being compared, patients were provided with some information on the options and the outcomes, but there may have been differences in the complexity of the medium of delivery; the amount of information on options and outcomes; the use of probabilities; the inclusion of examples of other patients' decision making; and the guidance in deliberation regarding the personal issues, such as perceptions of the probabilities of outcomes, personal values, questions, and choices or leanings. There are too few studies to draw substantive conclusions; therefore, the following summary is considered preliminary. Although the decision aids are known to improve baseline knowledge (8,12,72), when different methods of decision support were compared with one another, no one method was superior at increasing knowledge (8,7,52,70,71,73). This null result is likely because of the overlap in information provided by the alternative interventions. Possibly, more sensitive knowledge tests may be able to detect differences, but one needs to be careful that the knowledge that is tested is considered essential to patients for decision making. The methods used in decision aids do affect patients' expectations of outcomes. Patients have more realistic expectations if they are exposed to quantitative presentations of probabilities (7,65) and if outcomes are framed (66) positively (e.g., chance of remaining free of treatment side effects = 95%) rather than negatively (e.g., chance of having a side effect = 5%). However, the effect on decisions of creating more realistic expectations is more variable. It did dampen patients' enthusiasm for participating in a hypothetical clinical trial (65) but had no effect on whether a patient took HRT (7) or accepted an influenza vaccine (66). However, those exposed to positive frames reported fewer vaccine side effects and less absenteeism from work (66). Methods in decision aids do affect whether choices reflect personal values. The correlation between personal values and choices improves when decision aids provide detailed and probabilistic information on outcomes and when patients are asked to deliberate about the personal probabilities and values for each outcome (5,7,67,68). The incremental benefit of asking patients to consider their values is an understudied area; one study (68) that used a “weigh scale” values clarification exercise found little overall incremental benefit, except possibly in those patients who were considering a change from the status quo. The effect of values clarification exercises needs to be studied in groups that are actively considering change to confirm these results and to determine if they improve the quality of discourse with practitioners regarding values, as well as if they have an effect on long-term persistence with decisions. Methods in decision aids do affect some decisions, although it is difficult to determine which components in the decision aid produced these effects; e.g., it is not clear whether decisions are influenced by providing examples of how others make decisions. The two studies (68,73) that varied the inclusion of examples and showed a possible effect on choices were confounded by varying other aspects of the decision aid. Moreover, in both of these studies, the decision was hypothetical, thereby limiting the generalizabilty of results to patients who actually face the decision and who use more than the information in an aid to make their decisions. The use of examples is controversial. Some decision aids do not include them to remain “ neutral”; others use them to convey the variability in other patients' choices. Few studies have examined the separate effects of guidance or coaching in deliberation about options and communication of preferences. Coaching has had a beneficial effect on patient outcomes (28-35), and whether it can augment the beneficial effects of decision aid remains to be seen. Few studies have been conducted that compared only the medium of delivery, usually because some methods of decision support require more complicated delivery technologies. In the two studies that did compare media, one (70) showed that an interactive computer program increased entry decisions for a hypothetical clinical trial compared with an audiotape. Another study (73) comparing multimedia with a pamphlet found a trend toward decreased preferences for mastectomy but no differences in involvement in decision making. The different methods used in decision aids had no affect on satisfaction with the decision. There is a need to reexamine the way satisfaction is measured, given its lackluster performance, in discriminating not only between decision aids but also between decision aids and usual care. It may be more appropriate to measure satisfaction with preparation for decision making (which presumably decision aids do well) than satisfaction with the process of decision making and with the practitioner (which depends on many factors outside the control of decision aids). Moreover, investigators may need to acknowledge the difficulty in demonstrating improvements in satisfaction with the decision when choices are inherently difficult to make because of competing benefits and risks. Furthermore, once the decision is made, patients may find it more psychologically comforting to say that they are satisfied with it rather than entertain doubts about what they chose (61). Perhaps a better indication of satisfaction with the decision is persistence with the choice; unfortunately, this indicator is only useful for revocable decisions. In a current trial (O'Connor A et al.: unpublished data), we have had success using a scale that elicits patients' and practitioners' satisfaction with patients' preparation for decision making. The scale discriminates well (effect size 1.8) between a pamphlet decision aid regarding HRT and one with the full range of interventions delivered via audio-guided workbook. The acceptability of decision aids was affected by methods when the differences between interventions were large. For example, users found that pamphlets (with less detail, no illustrations, no probabilities, no examples, and no guidance in personal deliberation) were less acceptable than audio-guided workbooks that included these strategies. However, there was no overall difference in acceptability when more subtle differences in decision aids were compared (e.g., the addition of graphical displays to accompany numerical probabilities or the addition of a weigh scale values clarification exercise). Conclusions About Evaluative and Methodologic Studies In the evaluative studies of cancer-related decision aids conducted to date, the aids are acceptable to patients and help those who are uncertain at baseline to make a choice. They also increase the likelihood that choices are based on better knowledge, realistic expectations of outcomes, and personal values. They reduce some dimensions of decisional conflict, and their effect on decisions is variable. Few studies examine the downstream effects of decision aids on long-term persistence with choices, regret, and quality of life. In terms of methods used in decision aids, there has been minimal investigation of what works in the “black box” of decision aids. When simpler methods are compared with more intensive methods of decision support, the differences are negligible in terms of knowledge and satisfaction and are variable in terms of decisions and decisional conflict. However, more intensive methods are generally superior in terms of user acceptability and the extent to which choices are based on realistic expectations and personal values. The clinical importance of these differences and the cost-effectiveness of decision aids remain to be established. Research Implications Evaluation of Decision Aids There are several gaps in research on decision aids. More research is needed on (a) how decision aids perform for different clinical decisions; (b) their acceptability to practitioners; (c) their acceptability to diverse patient groups; (d) their effect on patient-practitioner communication; (e) their downstream effects on persistence with the decision, distress, regret, and health-related quality of life; and (f) the optimal strategies for disseminating and for implementation. Most evaluation studies are fraught with methodologic difficulties. They cannot be double-blind studies. Those studies that randomize patients rather than practitioners have contamination problems that narrow the differences that will be detected. Those studies that randomize practitioners need to be very large because of cluster sampling. Moreover, they may have selection biases because clinicians, knowing their assignment, may (a) be more or less enthusiastic about recruiting patients or (b) recruit different types of patients. Despite the researchers' best efforts, it is very difficult in a real-world setting to present the decision aid at the appropriate time to patients who are eligible to consider all of the options in the aid. Furthermore, efficacious interventions may have no effect if either patients or practitioners, or both, are extremely polarized toward one of the options at baseline. When postintervention measures are administered after the consequences of the choice are known, it is very difficult to avoid having the outcome color the patients' evaluation of satisfaction with the decision-making process and the decision. We recommend that future studies should Examine the effect of decision aids on a broader range of decisions with a more comprehensive range of patient and practitioner outcomes; Select patients who are at the point of decision making for whom the choices in the aid are relevant; Measure patients' and practitioners' baseline predispositions toward the choices; Have sample sizes large enough to detect clinically meaningful differences in decisions among the undecided subgroup of patients; Measure patients' perceptions of practitioners' opinions; Have a usual care arm and describe clearly what usual care comprises; and Describe clearly what was in the decision aid and how it was used in the diagnostic or treatment trajectory. Evaluation of Methods in Decision Aids The incremental efficacy of including different strategies in decision aids should be explored. A starting point would be to evaluate the additional strategies outlined in the Cochrane definition (11). Entwistle et al. (18) also outline several important issues regarding the presentational aspects of decision aids. Care should be taken in deciding which methods should be compared, considering the expense of an adequately powered study and the rather small differences observed in previous work. The use of nonpatient groups should be considered carefully. Although they make the study more feasible, it is difficult to generalize results to patients who are actually facing the decision and relying on more than the information in the aids to make their decisions. We recommend the following: 1) The selection of strategies for evaluation should be based on whether the studies have the potential to exert a strong influence on decisions; vary considerably in their use in current decision aids; and contribute significantly to the cost, complexity, and time required to administer decision aids. 2) Clinically important differences should be defined a priori, and studies should be adequately powered. 3) Ideally, methods studies should include patients actually faced with the decisions and should evaluate cost-effectiveness. Coordinating the Future Development of Decisions Aids Decision aids have been developed on the basis of academic expertise and interest and sometimes evidence of population need. As the field matures, there is a need to focus more attention on systematic and standardized approaches to needs assessment, development, and evaluation. In Table 5, we have posed seven key questions that may be considered when deciding whether and how to develop a decision aid. These questions should be considered not only by individual research teams but also by cancer agencies with a system perspective. The order and depth of investigation of each question depend on the type of decision, the extent of previous research in the area, and the constraints and perspectives of the developers. The seven questions are as follows: 1) Is there a need for a decision aid? Needs assessment involves the compilation of evidence about the nature of the decision difficulty, the numbers affected, practice and preference variation, availability of aids elsewhere, and demand for the aid. Methods for needs assessment are varied, and data are obtained from primary or secondary sources or both. It is important that needs are defined from the perspective of potential users, both patients and practitioners. 2) Is it feasible to develop a decision aid? Feasibility is assessed to determine that the aid can be developed with available evidence and resources and can be delivered and updated in a timely, accessible, and acceptable manner. 3) What are the objectives of the decision aid? The objectives of the decision aid should be stated explicitly. Examples are identified in Table 5. The objectives drive the selection of the framework, intervention strategies, and evaluation methods. 4) Which framework will drive its development? Depending on the objectives, several frameworks are available to guide decision aid development (8,12-19). 5) Which methods will be included in the decision aid? In selecting the decision support methods, the developer needs to determine how much emphasis will be placed on preparing the patient and the practitioner. The specific decision support methods, content, and delivery methods depend on the nature of the decision, the needs of the decision maker, the feasibility constraints, and the objectives of the decision aid. 6) Which designs and measures will be used to develop and evaluate the decision aid? Development and evaluation depend on the objectives of decision aids. Developers need to decide on the sampling and design architecture, the criteria for evaluation, and the measurement tools that will be used to operationalize the criteria. A key issue is what are the primary criteria that should be used to evaluate efficacy? Examples of criteria currently in use are listed in Table 5. Entwistle et al. (19) provide an excellent overview of potential criteria depending on the model of patient involvement (shared decision making, individual informed choice, professional as agent for the patient, promotion of rational decision making, promotion of a particular choice). One of the biggest dilemmas is defining efficacy when choices depend on personal values for the outcomes. We maintain that decisions and outcomes of decisions should be evaluated from the perspective of the patients' values. Our assumptions are that 1) patients are unlikely to be able to value an option and communicate it to others unless they know what is involved and what outcomes are likely; and 2) once informed about options, patients are unlikely to implement or persist with an option that does not reflect personal values. Therefore, we consider a values-sensitive decision to be a good one if it is informed (based on adequate knowledge of options and outcomes and realistic expectations), based on personal values, and implemented. Moreover, the outcomes of a good decision should improve health outcomes (assessed using values-based measures) and persistence with choices (especially when the underlying reason for nonpersistence is a mismatch in values). Another challenge is measuring the degree to which a decision is “consistent with personal values.” This has been assessed with the use of the self-reports of patients (12,67), percentage accuracy in discrimination between values and choice (68), odds ratios from logistic regression predicting choices from preferences (59), congruence between recommendations on the basis of expected utilities and choices (5), and agreement between choices and patients' treatment thresholds for median survival (58). The relative advantages of these methods and others, such as preference-based health outcomes and quality-adjusted life years, should be explored. 7) How should the decision aid be disseminated? Dissemination involves the targeted distribution and promotion of the use of the decision aid. Six key elements of research transfer and use (74) are presented: potential adopters, practice environment, the evidence-based innovation (e.g., the decision aid), strategies for transferring the evidence into practice, evidence adoption, and outcomes. These elements are systematically monitored before, during, and after any research transfer efforts. The data generated by monitoring are used to 1) identify potential barriers and supports to research use associated with the potential adopters, the practice environment, and evidence-based innovation; 2) provide direction for selecting and tailoring transfer strategies; 3) track the progress of the transfer effort; and 4) assess the adoption of the evidence and its effect on outcomes of interest. Although dissemination is identified as a final step, it should be addressed early in the development process so that the aid is acceptable to potential users and has a greater potential for adoption. Therefore, dissemination questions can be posed during the needs and feasibility phases. Development and review panels can include potential users (practitioners and patients) and partners who may assist with dissemination (consumer groups, health professional organizations, disease foundations, and public education agencies). Standards for Developing Future Decision Aids The definition of a patient decision aid is open to broad interpretation, and materials of variable quality have been produced. Consumers expect to receive free health information and may have difficulty distinguishing the wheat from the “free” chaff unless certain standards are set in their development. Many of the better decision aids have the following characteristics: (a) They use evidence-based statements of benefits and risks from credible sources, refer to the quality and consistency of empirical studies, and use systematic overviews that extend shelf life and enhance updating. (b) They are balanced in presenting all options (including doing nothing), benefits and risks, and, when included, examples of others' decisions and opinions. (c) They identify the qualifications of the developers, including multidisciplinary expertise as evidence interpreters, communicators, practitioners, consumers, or disseminators, as well as conflicts of interest. (d) They demonstrate commitment to update by 1) using expiry dates indicating the expected shelf life of the information, 2) mentioning upcoming trials that may shift policy, and 3) demonstrating linkage to an ongoing and credible evidence-analysis process (e.g., the Cochrane overview groups, the AHCPR PORTS or evidence centers, or the Cancer Care Ontario Practice Guidelines Initiative). (e) They state the sources of funding in development, including potential conflicts of interest. (f) They describe the efficacy of the decision aid in promoting evidence-informed choice, including acceptability, improvements in knowledge, etc. Dissemination Issues Table 6 describes how Lomas (75) applies his “research to policy” framework to shared decision-making programs. For each stage, from hypothesis generation to policy applications, he identifies key issues. Since the publication of the framework in November 1997, remarkable progress has been made in promoting shared decision making. Conceptual frameworks have been developed. Aids focused on cancer outcomes have been developed and pilot tested. Efficacy trials have been completed or are in progress. The results have been communicated broadly. Moreover, some of the aids are now being used by practitioners and patients. One controversial issue is that of disseminating decision aids before large efficacy trials are completed with all relevant endpoints. Entwistle et al. (18) clarified the conflict by describing two rationales for promoting “evidence-informed patient choice” via mechanisms such as decision aids. The first is that one has a basic moral obligation to provide individuals with information and choice about their health care. Therefore, evidence-informed patient choice is the desired end. If decision aids can accomplish this end, as they have consistently demonstrated to date, then the tools should be disseminated. Much of the educational material available to patients has not been developed and tested as rigorously as decision aids. Moreover, some materials are developed by industries with vested interests in promoting increased use of their products. The public and nongovernmental organizations (NGOs) are clamoring for good decision support tools. NGOs and research institutes have sponsored the dissemination of decision aids that have been demonstrated to promote informed patient choice. The second rationale is a consequentialist argument, based on the hypothesis that informed patient choice will lead to other beneficial outcomes. It is, therefore, a means to a desirable end, such as greater clinical effectiveness, health gain, individually appropriate utilization, reduced expenditures on inappropriate interventions, reduced litigation, and so forth. According to Entwistle et al. (18), accepting the consequentialist argument means that we need to examine the benefits and harms of promoting evidence-informed patient choice across a whole range of health care decisions, patient groups, health care settings, and forms of decision support. Bernstein et al. (49) also argued for more studies of cost-effectiveness, given the expense of developing and disseminating these tools and the modest benefits observed in the trials to date. Therefore, proponents of this rationale would argue for more investigation before wide-scale dissemination. A practical solution may be 1) to distribute aids that are needed, that are affordable, and that have been demonstrated to promote evidence-informed patient choice; 2) to continue to examine the downstream effects of decision aids in trials with usual care controls for new clinical decisions; and 3) to continue to explore (in methods studies) the most cost-effective strategies for achieving evidence-informed choice. Conclusion In this paper, the published evidence of the efficacy of decision aids has been presented. Although we know decision aids improve decision making, the downstream effect on persistence with decisions, health-related quality of life, and costs remain to be established. The implications for further research have been identified. There are outstanding issues regarding coordination, standards, and dissemination. Table 1. Determining need for patient decision aids on the basis of the Eddy (1) classification of health policy decisions   Practice standards   Practice guideline       Practice options   Likelihood of outcomes  Known  Known  Known/unknown  Agreement in patients' values/preferences for outcomes  Known, unanimous (⩾95% agreement)  Known, majority (⩾60% agreement)  Known, evenly split Unknown  Recommendation for treatment  Yes  Variable  No  Patient participation in decision making  Passive, informed consent  Variable  Active, informed choice  Practitioner intervention needed  Counseling followed by verbal or written consent  When recommendation states the decision should be based on patients preference, patient decision aid can be used with follow-up counseling  Patient decision aid and follow-up counseling    Practice standards   Practice guideline       Practice options   Likelihood of outcomes  Known  Known  Known/unknown  Agreement in patients' values/preferences for outcomes  Known, unanimous (⩾95% agreement)  Known, majority (⩾60% agreement)  Known, evenly split Unknown  Recommendation for treatment  Yes  Variable  No  Patient participation in decision making  Passive, informed consent  Variable  Active, informed choice  Practitioner intervention needed  Counseling followed by verbal or written consent  When recommendation states the decision should be based on patients preference, patient decision aid can be used with follow-up counseling  Patient decision aid and follow-up counseling  View Large Table 2. Types of decision aids evaluated Type of decision (reference No.)*   Medium of delivery*   Medical or surgical treatments  Cancer, breast (6, 52, 60, 62, 71, 73, 93)  Interactive videodisc, decision board, brochure, interactive mutimedia program, audio-guided workbook  Cancer, lung (55, 58)  Audio-guided workbook, personal interview with trade-off exercise  Cancer, leukemia (63)  Decision board  Cancer, lymphoma (53)  Poster  Atrial fibrillation (56, 56)  Audio-guided workbook  Benign prostatic hypertrophy (4, 43, 45, 59)  Interactive videodisc  Low back pain (42)  Interactive videodisc  Circumcision (50)  Written materials  Ischemic heart disease (44, 48, 49)  Interactive videodisc, video  Screening or diagnostic tests  Colon cancer screening (64, 76)  Computer program  Prostate-specific antigen tests (47, 51, 69, 72)  Video, pamphlet, scripted counseling  Amniocentesis (9, 54)  Audio-guided workbook  Preventive therapies  Hormone therapy (7, 8, 12, 67, 68)  Audio-guided workbook, brochure, group workshops  Hepatitis B vaccine (5)  Written materials  Clinical trial participation  Breast cancer therapy (65)  Written vignettes  Cancer chemotherapy (70)  Audiotape, computer, interactive computer  End-of-life  Resuscitation in seniors (57)  Written outcome data  Type of decision (reference No.)*   Medium of delivery*   Medical or surgical treatments  Cancer, breast (6, 52, 60, 62, 71, 73, 93)  Interactive videodisc, decision board, brochure, interactive mutimedia program, audio-guided workbook  Cancer, lung (55, 58)  Audio-guided workbook, personal interview with trade-off exercise  Cancer, leukemia (63)  Decision board  Cancer, lymphoma (53)  Poster  Atrial fibrillation (56, 56)  Audio-guided workbook  Benign prostatic hypertrophy (4, 43, 45, 59)  Interactive videodisc  Low back pain (42)  Interactive videodisc  Circumcision (50)  Written materials  Ischemic heart disease (44, 48, 49)  Interactive videodisc, video  Screening or diagnostic tests  Colon cancer screening (64, 76)  Computer program  Prostate-specific antigen tests (47, 51, 69, 72)  Video, pamphlet, scripted counseling  Amniocentesis (9, 54)  Audio-guided workbook  Preventive therapies  Hormone therapy (7, 8, 12, 67, 68)  Audio-guided workbook, brochure, group workshops  Hepatitis B vaccine (5)  Written materials  Clinical trial participation  Breast cancer therapy (65)  Written vignettes  Cancer chemotherapy (70)  Audiotape, computer, interactive computer  End-of-life  Resuscitation in seniors (57)  Written outcome data  * Decision aids focused on cancer outcomes are in bold. View Large Table 3. Evidence of effectiveness of patient decision aids   Before/after studies detecting change from baseline after decision aid (reference No.)*   Randomized trials of decision aids vs. usual care controls (reference No.)*   Do decision aids affect decisions?    Yes  Yes    Help undecided (12, 60, 42-45)  Help undecided (46)    Reduce preference for intensive option (60, 45, 54)  Reduce preference for intensive option (47, 51, 46)      Trend decision aid reduces preference for intensive option (448, 49)      No (50)  Do decision aids improve determinants of decisions?  Choice based on better knowledge of options, benefits, or risks  Yes (8, 12, 52, 42, 43) and no (57)  Yes (47, 51, 4, 46, 49, 49) and no (50)  Choice based on more realistic expectations (agreement between perceived probability of outcomes and estimates derived from evidence)  Yes (12, 53, 55, 58, 54, 56, 57)  Yes (47,46, 51,46)  Choice based on personal values (correlation between personal values for outcomes and choice)  Yes (12, 58, 59)  —  Do decision aids improve comfort with decision making?  Reduce decisional conflict (feeling uncertain, uninformed, unclear about values, unsupported in decision making)  Yes (12, 55, 58, 60, 54)  Yes, benefit limited to informed dimension (46, 48)  More satisfied with decision-making process  —  Yes (4) and no (46, 48, 49)  More satisfied with decision  Yes (58)  No (4, 48, 49)  More satisfied with treatment  —  Less satisfied (49)  Do decision aids improve outcomes of decisions?  Better health-related quality of life  —  Yes (4) and no (49)  Better compliance/persistence with decision  —  —  Reduced morbidity  —  —  Do decision aids produce favorable reactions from patients?  Acceptable to patients (comprehensibility, length, clarity, usefulness, interest, balance, or recommend to others)  Yes (6, 58, 59, 60, 62, 42-44, 57)  Feasible to use  Yes (63, 64)  —    Before/after studies detecting change from baseline after decision aid (reference No.)*   Randomized trials of decision aids vs. usual care controls (reference No.)*   Do decision aids affect decisions?    Yes  Yes    Help undecided (12, 60, 42-45)  Help undecided (46)    Reduce preference for intensive option (60, 45, 54)  Reduce preference for intensive option (47, 51, 46)      Trend decision aid reduces preference for intensive option (448, 49)      No (50)  Do decision aids improve determinants of decisions?  Choice based on better knowledge of options, benefits, or risks  Yes (8, 12, 52, 42, 43) and no (57)  Yes (47, 51, 4, 46, 49, 49) and no (50)  Choice based on more realistic expectations (agreement between perceived probability of outcomes and estimates derived from evidence)  Yes (12, 53, 55, 58, 54, 56, 57)  Yes (47,46, 51,46)  Choice based on personal values (correlation between personal values for outcomes and choice)  Yes (12, 58, 59)  —  Do decision aids improve comfort with decision making?  Reduce decisional conflict (feeling uncertain, uninformed, unclear about values, unsupported in decision making)  Yes (12, 55, 58, 60, 54)  Yes, benefit limited to informed dimension (46, 48)  More satisfied with decision-making process  —  Yes (4) and no (46, 48, 49)  More satisfied with decision  Yes (58)  No (4, 48, 49)  More satisfied with treatment  —  Less satisfied (49)  Do decision aids improve outcomes of decisions?  Better health-related quality of life  —  Yes (4) and no (49)  Better compliance/persistence with decision  —  —  Reduced morbidity  —  —  Do decision aids produce favorable reactions from patients?  Acceptable to patients (comprehensibility, length, clarity, usefulness, interest, balance, or recommend to others)  Yes (6, 58, 59, 60, 62, 42-44, 57)  Feasible to use  Yes (63, 64)  —  Decision aids focused on cancer outcomes are in bold. View Large Table 4. Randomized trials comparing different methods in decision aids Decision (reference No.) *  Delivery *†   Options *†   Outcomes *†   Probabilities *†   Examples *†   Guidance in personal deliberation *†   Hormones (8, 67)  (a) Pamphlet  Detailed  Detailed  Yes  Yes  No    (b) Group  Detailed  Detailed  Yes  Yes ‡  No    (c) Group  Detailed  Detailed  Yes  Yes ‡  Yes—probabilities, values, choice    Hormones (7)  (a) Pamphlet  Brief  Brief  No  No  No    (b) Audio-guided workbook  Detailed  Detailed  Yes  Yes  Yes—probabilities, values, choice    Hormones (68)  (a) Audio-guided workbook  Detailed  Detailed  Yes  No  Probabilities, questions    (b) Audio-guided workbook  Detailed  Detailed  Yes  Yes  Probabilities, questions, values, choice    Breast cancer surgery (71)  (a) Pamphlet  Brief  Brief  No  No  No    (b) Audio-guided workbook  Detailed  Detailed graphic  Yes  Yes  Yes—values, choice    Hepatitis B Vaccine (5)  (a) Written  Brief  Brief  No  No  No    (b) Written  Detailed  Detailed  Yes  No  No    (c) Written  Detailed  Detailed  Yes  No  Yes—probabilities, values    Trial entry (65)  (a) Vignette  Brief  Brief  Qualitative  —  —    (b) Vignette  Brief  Brief  Quantitative  —  —    Flu vaccine (66)  (a) Chart/poster  Detailed  Detailed  Positive frame  —  —    (b) Chart/poster  Detailed  Detailed  Negative frame    Transplant (53)  (a) Chart/poster  Detailed  Detailed  Numbers  —  —    (b) Chart/poster  Detailed  Detailed  Numbers/graph    PSA test (72)  (a) Pamphlet  Brief  Brief  No information    (b) Pamphlet  Brief  Brief  False positive/negative    PSA tests (69)  (a) Verbal  Sentence  Very brief  None  No    (b) Verbal  Sentence  Detailed  Quantitative  No    Breast cancer surgery (52)  (a) Booklet  Detailed  Detailed  Yes  No    (b) Video  Detailed  Detailed  Yes  Yes    Breast cancer surgery (73)  (a) Pamphlet  Briefer  Briefer    No    (b) Multimedia  Detailed  Detailed    Yes      Trial (70)  (a) Audiotape  Detailed  Detailed  Yes  No  No    (b) Computer  Detailed  Detailed  Yes  No  Choice of order of information  (Table continues)  Decision (reference No.) *  Delivery *†   Options *†   Outcomes *†   Probabilities *†   Examples *†   Guidance in personal deliberation *†   Hormones (8, 67)  (a) Pamphlet  Detailed  Detailed  Yes  Yes  No    (b) Group  Detailed  Detailed  Yes  Yes ‡  No    (c) Group  Detailed  Detailed  Yes  Yes ‡  Yes—probabilities, values, choice    Hormones (7)  (a) Pamphlet  Brief  Brief  No  No  No    (b) Audio-guided workbook  Detailed  Detailed  Yes  Yes  Yes—probabilities, values, choice    Hormones (68)  (a) Audio-guided workbook  Detailed  Detailed  Yes  No  Probabilities, questions    (b) Audio-guided workbook  Detailed  Detailed  Yes  Yes  Probabilities, questions, values, choice    Breast cancer surgery (71)  (a) Pamphlet  Brief  Brief  No  No  No    (b) Audio-guided workbook  Detailed  Detailed graphic  Yes  Yes  Yes—values, choice    Hepatitis B Vaccine (5)  (a) Written  Brief  Brief  No  No  No    (b) Written  Detailed  Detailed  Yes  No  No    (c) Written  Detailed  Detailed  Yes  No  Yes—probabilities, values    Trial entry (65)  (a) Vignette  Brief  Brief  Qualitative  —  —    (b) Vignette  Brief  Brief  Quantitative  —  —    Flu vaccine (66)  (a) Chart/poster  Detailed  Detailed  Positive frame  —  —    (b) Chart/poster  Detailed  Detailed  Negative frame    Transplant (53)  (a) Chart/poster  Detailed  Detailed  Numbers  —  —    (b) Chart/poster  Detailed  Detailed  Numbers/graph    PSA test (72)  (a) Pamphlet  Brief  Brief  No information    (b) Pamphlet  Brief  Brief  False positive/negative    PSA tests (69)  (a) Verbal  Sentence  Very brief  None  No    (b) Verbal  Sentence  Detailed  Quantitative  No    Breast cancer surgery (52)  (a) Booklet  Detailed  Detailed  Yes  No    (b) Video  Detailed  Detailed  Yes  Yes    Breast cancer surgery (73)  (a) Pamphlet  Briefer  Briefer    No    (b) Multimedia  Detailed  Detailed    Yes      Trial (70)  (a) Audiotape  Detailed  Detailed  Yes  No  No    (b) Computer  Detailed  Detailed  Yes  No  Choice of order of information  (Table continues)  * Decision aids focused on cancer outcomes are in bold. HRT = hormone replacement therapy; PSA = prostate-specific antigen. † Components are bolded to signify differences between methods used. ‡ Patients in the two groups were exposed to more examples than those using the brochure. View Large Table 4 (continued). Randomized trials comparing different methods in decision aids Choice   Knowledge   Expectations   Correlation values and choice   Decision conflict   Satisfaction   Other     No difference    —  Worse  No difference  No difference        —  —    Persistence        Better  —    With choice    No difference  No difference  —  —  —      More realistic  Better clarity of values  Better    More acceptable    —      —  No difference    No difference Acceptability  Trend, increased HRT      Trend, better in those changing status quo (choosing HRT)          No difference      No overall difference    —          Trend, better in uncertain patients    More acceptable, no difference in anxiety    —      —  —      —  Increased vaccine      Better    —    —  Decreased trial entry    More realistic    No difference    More realistic    No difference    Decreased symptoms and work loss      —        —    No difference    No difference        No difference in acceptability    —    —  Trend, decreased PSA    More realistic    —  Decreased PSA    —  No difference  Decreased mastectomy    —  —          No difference in decision-making involvement  Trend, decreased mastectomy  Trend increased    —  No difference        No difference  Increased trial entry  Choice   Knowledge   Expectations   Correlation values and choice   Decision conflict   Satisfaction   Other     No difference    —  Worse  No difference  No difference        —  —    Persistence        Better  —    With choice    No difference  No difference  —  —  —      More realistic  Better clarity of values  Better    More acceptable    —      —  No difference    No difference Acceptability  Trend, increased HRT      Trend, better in those changing status quo (choosing HRT)          No difference      No overall difference    —          Trend, better in uncertain patients    More acceptable, no difference in anxiety    —      —  —      —  Increased vaccine      Better    —    —  Decreased trial entry    More realistic    No difference    More realistic    No difference    Decreased symptoms and work loss      —        —    No difference    No difference        No difference in acceptability    —    —  Trend, decreased PSA    More realistic    —  Decreased PSA    —  No difference  Decreased mastectomy    —  —          No difference in decision-making involvement  Trend, decreased mastectomy  Trend increased    —  No difference        No difference  Increased trial entry  View Large Table 5. Developing and evaluating decision aids: questions and methods Issue   Method (reference No.)   1. Is there a need for a decision aid?  What are the decision-making needs of patients and practitioners?  Conduct key informant interviews, focus groups, or surveys to elicit patients' and practitioners' perceptions of decisions perceived as important and difficult, usual roles and decision-making practices, barriers and facilitators in providing or accessing decision support, potential strategies for overcoming barriers  What makes the decision difficult?  Review systematic overviews, decision analyses, and preference studies to determine whether benefits marginal or uncertain, risks material or uncertan, value trade-offs between benefits and risks, and variation in preferences, for outcomes  Are sufficient numbers affected and how are they affected?  Review databases, demographic or morbidity statistics, and population surveys  Is there sufficient variation in use?  Review practice atlases, utilization data, or practice variation studies  Are there decision aids available to meet these needs?  Review published overviews, reports; contact centers that produce aids  Is there a demand for decision aids and what methods are preferred?  Conduct market surveys (81)  2. Is it feasible to develop a decision aid?  Are there adequate resources?  Assess finances, availability of experts with credibility, networks, and commitment to ongoing update; link to established overview and dissemination networks  Is there enough evidence of benefits and risks to incorporate into a decision aid?  Review systematic overviews with appraisals of the quality of evidence  How quickly is the evidence expected to change?  Review ongoing trials  Will aid be accessible or acceptable to users?  Conduct focus groups or market surveys  3. What are the objectives of the decision aid?  Objectives focused on improved decision making  Improve knowledge of the clinical problem, options, outcomes, and variation in patient or practitioner opinions and practices.    Create realistic expectations of outcomes, consistent with available evidence.    Clarify personal values for outcomes and promote congruence between patients' values and choice.    Reduce patients' and practitioners' decisional conflict (uncertainty) about the course of action to take.    Promote implementation of choices.    Improve patients' or practitioners' satisfaction with decision making.  Objectives focused on outcomes of decision  Promote patients' persistence with choice.    Reduce patients' distress from consequences of decision.    Improve patients' health-related quality of life. Promote informed use of resources by patients and practitioners.  4. Which framework will drive its development?    Charles et al. (13) distinguish shared decision making from other decision-making approaches.    Entwistle et al. (18, 19) define evidence-informed choice and outline different criteria for evaluations depending on objective.    The Hershey et al. framework (15) developed for AHCPR has a health services and informatics perspective.    The Llewellyn-Thomas framework (14) has a special focus on types of preferences and placement in sociopolitical context.    Mulley (16) places shared decision making in the context of outcomes research.    Ottawa Decision Support Framework (12) prepares practitioner and patient and has a clinical and behavioral focus.    Rothert et al. (8, 17) describe mutual roles of patients and practitioners in decision making; they focus on information and values.  5. Which methods will be included in the decision aid?  Patient or client decision support  Information regarding options and outcomes    • Content: clinical problem, options, outcomes    • Detail in describing outcomes: define outcomes; describe physical, emotional, social effect; use narrative/scenario styles    • Probabilities: none; numerical frequencies or percents (7), graphic pie charts (6), 100 people (4, 12), qualitative (low, moderate, high)    • Tailored probabilities: not tailored; stratified by personal risk factors    • Evidence for statements: references included or not    Values clarification    • Implicit (4, 6 )    • Explicit methods such as weigh scale exercise (7), treatment trade-off task (82), relevance chart (8), decisional balance sheets (83), formal utility assessments (5, 9)    Information on others    • None    • Cases of different choices (4, 8, 12)    • Statistics on variation in patients' decisions or practitioners' opinions     Coaching or guidance in deliberation, communication, and implementation    • Not included    • Steps in weighing the benefits or risks (8, 12)    • Steps in discussing decision with a practitioner (8, 12)    • Tips on managing consequences of choices    Delivery (personal counseling supplemented by)    • Generic tools    • Decision board (6)    • Take home audio-guided workbook (7)    • Interactive videodisc or linear video (4)    • Computer-based tool (70)    • Group lecture or workshop (18)  Practitioner decision support  Content: scientific evidence regarding decision, rationale for decision aid, efficacy of decision aid, timing and use in practice, scientific references    Delivery: manual, video, lecture, workshop, hot line, academic detailing  6. Which designs and measures will be used to develop and evaluate decision aid?  Development panel  Participants (researchers, clinicians, educators, patients, opinion leaders)    Methods (iterations of drafts, feedback, revisions, feedback, etc.)  Review panels  Participants (potential users: practitioners, patients who have already made decisions)    Methods (focus groups, personal interviews, questionnaires to elicit acceptability, etc.)  Pilot studies  Participants (patients at the point of decision making)    Designs*    XO XO: test-retest 2 weeks apart (stability of preferences and reliability of measures)    OXO: before/after study uses baseline questionnaire, decision aid, or posttest questionnaire    XO: posttest only, usually with preestablished criteria for success (e.g., 70% on knowledge test)  Trials  Participants (patients at point of decision making, practitioners)    Designs*    Quasi experiment OCO OXO    Randomized trial (with unit of randomization either the patient or practitioner) ROXO ROCO  What are the criteria for evaluation?   Knowledge  Knowledge or comprehension test (4, 7, 8, 47)   Expectations of outcomes  Probability scales (7, 84-87), likelihood scales (26)   Clarity of values  Values subscale of Decisional Conflict Scale (7, 36, 68)   Agreement between choice and values  Statistical relationship between values and choices ( 5, 7, 12, 58, 59, 67, 68)   Realistic perceptions of others  Perceptions of percentage of practitioners or patients choosing options; subjective norms (26)   Decision  Choice question (option x, option y, unsure); choice predisposition (7)   Decisional conflict  Decisional conflict scales for patients (7, 36, 88) and providers (89)   Skill in decision making  Self-efficacy scale (8, 88), implementation data   Satisfaction with decision making  Decision satisfaction inventory (4); satisfaction with decision (8, 90); satisfaction with preparation for decision making (O'Connor A, et al.: unpublished data)   Acceptability  Acceptability questionnaires—shared decision-making tool (42-45), Ottawa tool (68)   Use of decision aid  Utilization data   Participation according to needs  Congruence between preferred and actual role in decision making (91, 92)   Persistence with decisions  Survey of decision over time; implementation data   Reduced distress from outcomes  Condition-specific symptom and side effects distress scales   Health-related quality of life  Generic, condition-specific, preference-based   Use of resources  Analysis of utilization data   Costs  See the Hersey et al. (15) framework and the Nease and Owens (94) cost-effectiveness model  7. How should the decision aid be disseminated (74)?  What are potential adopters: attitudes toward innovation or change; knowledge, attitudes, and skills to use aid; preference for shared decision making?  Conduct focus groups, key informant interviews, environmental scans, or surveys of potential users  What are the environmental barriers and supporters?  Conduct focus groups or surveys to identify the following factors:    • Social (likely supporters and opposers; presence of opinion leaders as supporters; predominant belief system regarding shared decision making)    • Structural (operational tools and processes, regulations, quality assurance criteria, to encourage or hinder use of aid; resources to support dissemination of aid)    • Other incentives and disincentives  Will the evidence-based innovation meet expectations of target audience?  Conduct focus groups or surveys  Which transer strategies should be used?  Tailor strategies according to needs; diffusion strategies (advertisements, publications, or Internet); dissemination strategies (targeted mailings); implementation strategies (education programs or administrative changes)  Is the aid being adopted, and is it having the expected effect on outcomes?  Analyze databases; conduct quality assurance studies, surveys, and implementation studies to determine whether the aid is being used by the expected audience in the expected manner and whether it is having the expected effect on health and economic outcomes and evidence-based decision making among patients or clinicians  Issue   Method (reference No.)   1. Is there a need for a decision aid?  What are the decision-making needs of patients and practitioners?  Conduct key informant interviews, focus groups, or surveys to elicit patients' and practitioners' perceptions of decisions perceived as important and difficult, usual roles and decision-making practices, barriers and facilitators in providing or accessing decision support, potential strategies for overcoming barriers  What makes the decision difficult?  Review systematic overviews, decision analyses, and preference studies to determine whether benefits marginal or uncertain, risks material or uncertan, value trade-offs between benefits and risks, and variation in preferences, for outcomes  Are sufficient numbers affected and how are they affected?  Review databases, demographic or morbidity statistics, and population surveys  Is there sufficient variation in use?  Review practice atlases, utilization data, or practice variation studies  Are there decision aids available to meet these needs?  Review published overviews, reports; contact centers that produce aids  Is there a demand for decision aids and what methods are preferred?  Conduct market surveys (81)  2. Is it feasible to develop a decision aid?  Are there adequate resources?  Assess finances, availability of experts with credibility, networks, and commitment to ongoing update; link to established overview and dissemination networks  Is there enough evidence of benefits and risks to incorporate into a decision aid?  Review systematic overviews with appraisals of the quality of evidence  How quickly is the evidence expected to change?  Review ongoing trials  Will aid be accessible or acceptable to users?  Conduct focus groups or market surveys  3. What are the objectives of the decision aid?  Objectives focused on improved decision making  Improve knowledge of the clinical problem, options, outcomes, and variation in patient or practitioner opinions and practices.    Create realistic expectations of outcomes, consistent with available evidence.    Clarify personal values for outcomes and promote congruence between patients' values and choice.    Reduce patients' and practitioners' decisional conflict (uncertainty) about the course of action to take.    Promote implementation of choices.    Improve patients' or practitioners' satisfaction with decision making.  Objectives focused on outcomes of decision  Promote patients' persistence with choice.    Reduce patients' distress from consequences of decision.    Improve patients' health-related quality of life. Promote informed use of resources by patients and practitioners.  4. Which framework will drive its development?    Charles et al. (13) distinguish shared decision making from other decision-making approaches.    Entwistle et al. (18, 19) define evidence-informed choice and outline different criteria for evaluations depending on objective.    The Hershey et al. framework (15) developed for AHCPR has a health services and informatics perspective.    The Llewellyn-Thomas framework (14) has a special focus on types of preferences and placement in sociopolitical context.    Mulley (16) places shared decision making in the context of outcomes research.    Ottawa Decision Support Framework (12) prepares practitioner and patient and has a clinical and behavioral focus.    Rothert et al. (8, 17) describe mutual roles of patients and practitioners in decision making; they focus on information and values.  5. Which methods will be included in the decision aid?  Patient or client decision support  Information regarding options and outcomes    • Content: clinical problem, options, outcomes    • Detail in describing outcomes: define outcomes; describe physical, emotional, social effect; use narrative/scenario styles    • Probabilities: none; numerical frequencies or percents (7), graphic pie charts (6), 100 people (4, 12), qualitative (low, moderate, high)    • Tailored probabilities: not tailored; stratified by personal risk factors    • Evidence for statements: references included or not    Values clarification    • Implicit (4, 6 )    • Explicit methods such as weigh scale exercise (7), treatment trade-off task (82), relevance chart (8), decisional balance sheets (83), formal utility assessments (5, 9)    Information on others    • None    • Cases of different choices (4, 8, 12)    • Statistics on variation in patients' decisions or practitioners' opinions     Coaching or guidance in deliberation, communication, and implementation    • Not included    • Steps in weighing the benefits or risks (8, 12)    • Steps in discussing decision with a practitioner (8, 12)    • Tips on managing consequences of choices    Delivery (personal counseling supplemented by)    • Generic tools    • Decision board (6)    • Take home audio-guided workbook (7)    • Interactive videodisc or linear video (4)    • Computer-based tool (70)    • Group lecture or workshop (18)  Practitioner decision support  Content: scientific evidence regarding decision, rationale for decision aid, efficacy of decision aid, timing and use in practice, scientific references    Delivery: manual, video, lecture, workshop, hot line, academic detailing  6. Which designs and measures will be used to develop and evaluate decision aid?  Development panel  Participants (researchers, clinicians, educators, patients, opinion leaders)    Methods (iterations of drafts, feedback, revisions, feedback, etc.)  Review panels  Participants (potential users: practitioners, patients who have already made decisions)    Methods (focus groups, personal interviews, questionnaires to elicit acceptability, etc.)  Pilot studies  Participants (patients at the point of decision making)    Designs*    XO XO: test-retest 2 weeks apart (stability of preferences and reliability of measures)    OXO: before/after study uses baseline questionnaire, decision aid, or posttest questionnaire    XO: posttest only, usually with preestablished criteria for success (e.g., 70% on knowledge test)  Trials  Participants (patients at point of decision making, practitioners)    Designs*    Quasi experiment OCO OXO    Randomized trial (with unit of randomization either the patient or practitioner) ROXO ROCO  What are the criteria for evaluation?   Knowledge  Knowledge or comprehension test (4, 7, 8, 47)   Expectations of outcomes  Probability scales (7, 84-87), likelihood scales (26)   Clarity of values  Values subscale of Decisional Conflict Scale (7, 36, 68)   Agreement between choice and values  Statistical relationship between values and choices ( 5, 7, 12, 58, 59, 67, 68)   Realistic perceptions of others  Perceptions of percentage of practitioners or patients choosing options; subjective norms (26)   Decision  Choice question (option x, option y, unsure); choice predisposition (7)   Decisional conflict  Decisional conflict scales for patients (7, 36, 88) and providers (89)   Skill in decision making  Self-efficacy scale (8, 88), implementation data   Satisfaction with decision making  Decision satisfaction inventory (4); satisfaction with decision (8, 90); satisfaction with preparation for decision making (O'Connor A, et al.: unpublished data)   Acceptability  Acceptability questionnaires—shared decision-making tool (42-45), Ottawa tool (68)   Use of decision aid  Utilization data   Participation according to needs  Congruence between preferred and actual role in decision making (91, 92)   Persistence with decisions  Survey of decision over time; implementation data   Reduced distress from outcomes  Condition-specific symptom and side effects distress scales   Health-related quality of life  Generic, condition-specific, preference-based   Use of resources  Analysis of utilization data   Costs  See the Hersey et al. (15) framework and the Nease and Owens (94) cost-effectiveness model  7. How should the decision aid be disseminated (74)?  What are potential adopters: attitudes toward innovation or change; knowledge, attitudes, and skills to use aid; preference for shared decision making?  Conduct focus groups, key informant interviews, environmental scans, or surveys of potential users  What are the environmental barriers and supporters?  Conduct focus groups or surveys to identify the following factors:    • Social (likely supporters and opposers; presence of opinion leaders as supporters; predominant belief system regarding shared decision making)    • Structural (operational tools and processes, regulations, quality assurance criteria, to encourage or hinder use of aid; resources to support dissemination of aid)    • Other incentives and disincentives  Will the evidence-based innovation meet expectations of target audience?  Conduct focus groups or surveys  Which transer strategies should be used?  Tailor strategies according to needs; diffusion strategies (advertisements, publications, or Internet); dissemination strategies (targeted mailings); implementation strategies (education programs or administrative changes)  Is the aid being adopted, and is it having the expected effect on outcomes?  Analyze databases; conduct quality assurance studies, surveys, and implementation studies to determine whether the aid is being used by the expected audience in the expected manner and whether it is having the expected effect on health and economic outcomes and evidence-based decision making among patients or clinicians  * C = control intervention; O = observation of effect; R = randomization; X = decision aid intervention. View Large Table 6. Stages of “Research to Policy” by Lomas (75) applied to shared patient decision making Stages and issues   Progress to November 1998   Hypothesis generation—shared patient decision making is valued  Preference for shared decision making varies by patient characteristics and type of decisions (77-79)    Patients desiring shared decision making do not always have the opportunity (80)    Some evidence that oncologists endorse the concept (81)  Methods development—to elicit patient values and present risk-benefit information  Issues confirmed by AHCPR report (15) and Entwistle et al. (18) paper    Several methods studies completed (Table 4)  Causal model or “theory”—lack of patient involvement leads to “ unwanted interventions”  Several frameworks published; hypothesized effects are observed: help uncertain, base decisions on improved knowledge, realistic expectations, and personal values; effect on satisfaction variable; trend toward reduced preference for more intensive therapies  Study-specific evaluation (efficacy)—randomized trials under ideal controlled decisions  Seven trials show decision aids improve the quality of decisions and show trend in affecting decisions; several trials in progress in the United States, the United Kingdom, Canada, and The Netherlands  Knowledge summary and synthesis  Annotated bibliography (40,41), AHCPR report (15), and Cochrane systematic overview in progress (11)  Results communication—to providers or patients, media, journals, etc.  Conferences, workshops or journals; shared decision-making concept has ben discussed in media (e.g., National Press, magazines, local press, and television)  Application to policy world—what are the barriers to using decision aids under different health care funding and organizational arrangements?  Improving access: Canadian National Forum on Health identified the need to engage public in decision making regarding personal health and to improve access of providers and public to evidence-based information. Funding allocated to improve information systems. U.K. Kings Fund on Informed Choice launched. Some decision aids in hands of providers and consumers  Application in policy world—details of implementing shared patient decision making for specific jurisdiction, institution, or even practitioner  Practice policies: Canadian and U.S. practice guidelines beginning to identify role of patient preferences for some decisions (breast cancer surgery, hormone therapy). Canadian and U.S. nongovernmental agencies have endorsed some of the decision aids and are disseminating information on them    Funding development, evaluation, updating, and dissemination: issue unresolved    Standards for decision aids: issue unresolved: evidence-based, sponsorship, expiration dates    Regulating/legislating use under certain conditions: several states have legislated that women with breast cancer should be offered mastectomy or lumpectomy options. Canada has a practice guideline. Institute for Clinical Evaluative Sciences atlas confirms practice variation in mastectomy or lumpectomy use.    U.S. National Committee on Quality Assurance expands criteria to include quality of counseling on options that incorporates personal risk and preferences    Service delivery: U.S. Foundation for Informed Medical Decision Making delivering decision support services for third-party payers  Stages and issues   Progress to November 1998   Hypothesis generation—shared patient decision making is valued  Preference for shared decision making varies by patient characteristics and type of decisions (77-79)    Patients desiring shared decision making do not always have the opportunity (80)    Some evidence that oncologists endorse the concept (81)  Methods development—to elicit patient values and present risk-benefit information  Issues confirmed by AHCPR report (15) and Entwistle et al. (18) paper    Several methods studies completed (Table 4)  Causal model or “theory”—lack of patient involvement leads to “ unwanted interventions”  Several frameworks published; hypothesized effects are observed: help uncertain, base decisions on improved knowledge, realistic expectations, and personal values; effect on satisfaction variable; trend toward reduced preference for more intensive therapies  Study-specific evaluation (efficacy)—randomized trials under ideal controlled decisions  Seven trials show decision aids improve the quality of decisions and show trend in affecting decisions; several trials in progress in the United States, the United Kingdom, Canada, and The Netherlands  Knowledge summary and synthesis  Annotated bibliography (40,41), AHCPR report (15), and Cochrane systematic overview in progress (11)  Results communication—to providers or patients, media, journals, etc.  Conferences, workshops or journals; shared decision-making concept has ben discussed in media (e.g., National Press, magazines, local press, and television)  Application to policy world—what are the barriers to using decision aids under different health care funding and organizational arrangements?  Improving access: Canadian National Forum on Health identified the need to engage public in decision making regarding personal health and to improve access of providers and public to evidence-based information. Funding allocated to improve information systems. U.K. Kings Fund on Informed Choice launched. Some decision aids in hands of providers and consumers  Application in policy world—details of implementing shared patient decision making for specific jurisdiction, institution, or even practitioner  Practice policies: Canadian and U.S. practice guidelines beginning to identify role of patient preferences for some decisions (breast cancer surgery, hormone therapy). Canadian and U.S. nongovernmental agencies have endorsed some of the decision aids and are disseminating information on them    Funding development, evaluation, updating, and dissemination: issue unresolved    Standards for decision aids: issue unresolved: evidence-based, sponsorship, expiration dates    Regulating/legislating use under certain conditions: several states have legislated that women with breast cancer should be offered mastectomy or lumpectomy options. Canada has a practice guideline. 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Decision Aids for Patients Considering Options Affecting Cancer Outcomes: Evidence of Efficacy and Policy Implications

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Oxford University Press
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Oxford University Press
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1052-6773
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1745-6614
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10.1093/oxfordjournals.jncimonographs.a024212
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Abstract

Abstract Some cancer screening and treatment decisions are not clear cut because outcomes are uncertain or options have different benefit/risk profiles. “Decision aids” have been developed as adjuncts to counseling so that patients can learn about benefits and risks, can consider their personal values, and can participate with their practitioner in decision making. The purpose of this paper is to review published evidence about the efficacy of decision aids focused on cancer outcomes and to outline research and dissemination issues. Studies evaluating cancer-related decision aids demonstrate that they are acceptable to patients and help those who are uncertain at baseline to make choices. They also increase the likelihood that choices are based on better knowledge, realistic expectations of outcomes, and personal values. Decision aids reduce some dimensions of decisional conflict, and their effect on decisions is variable. Few studies examine the downstream effects of decision aids on long-term persistence with choices, regret, and quality of life. The differences between simpler and more intensive methods of decision support appear to be negligible in terms of knowledge and satisfaction as well as variable in terms of decisions and decisional conflict. However, more intensive methods are superior in terms of user acceptability and of the extent to which choices are based on realistic expectations and personal values. The clinical importance of these differences and the cost-effectiveness remain to be established. On the basis of this review, several recommendations for research are made, and dissemination issues are identified. Some cancer screening and treatment decisions are not clear cut because of the uncertainty of the evidence on outcomes or the lack of consensus that the benefits outweigh the risks (1). Practice guidelines for these difficult decisions often recommend that practitioners exercise judgement in applying them to individual patients and that patients' values for the outcomes be considered (2,3). Accordingly, decision support interventions, known as “ decision aids” or “shared decision-making programs,” are being developed as adjuncts to practitioners' counseling (4-10) so that patients can 1) understand the probable benefits and risks of options, 2) consider the value they place on benefits versus risks, and 3) participate actively with their practitioners in deciding about options (2). The purpose of this paper is to review published evidence about the efficacy of decision aids focused on cancer outcomes and to outline research and policy implications. We will define decision aids, examine the reasons for their development, present their theoretical underpinnings, review the evidence of their efficacy, and discuss implications. What Is a Patient Decision Aid? Decision aids are used as adjuncts to practitioners' counseling to prepare patients for decision making. According to the Cochrane definition (11), they are interventions designed to help people make specific and deliberative choices among options by providing (at the minimum) information on the options and outcomes relevant to the person's health status. Additional strategies may include information on the disease or condition, probabilities of outcomes tailored to a person's health risk factors, an explicit values-clarification exercise, information on others' opinions, and guidance or coaching in the steps of decision making and communicating with others. Decision aids may be administered with the use of various media, such as decision boards, interactive videodiscs, personal computers, audiotapes, audio-guided workbooks, pamphlets, and group presentations. Excluded from the definition of decision aids are passive informed consent materials, educational interventions that are not geared to a specific decision, or interventions designed to promote compliance with a recommended option rather than a choice based on personal values. Why Are Patient Decision Aids Developed? The development of decision aids in several centers in the United States, the United Kingdom, and Canada is motivated by several trends: (a) the rise of consumerism with an emphasis on informed choice rather than informed consent, (b) the evidence-based practice movement disseminating evidence to consumers as well as to practitioners, (c) the interest in consumer-focused strategies to reduce large practice variations caused by supplier-induced demand, (d) the identification of treatment decisions that are “ utility” or “value” sensitive from decision analyses, (e) the proliferation of overviews and outcome studies that provide estimates of outcomes for use in decision aids, and (f) the evolution of patient preference-oriented health policy that reserves interventions for those patients who consider the treatment benefits to outweigh the risks (e.g., reserving palliative surgery for patients who consider symptom relief worth the surgical risks, rather than basing a surgical policy on the average patient's utilities). Kassirer (3) lists some indications for explicitly eliciting patients' preferences in clinical practice: 1) Options have major differences in outcomes or complications, 2) decisions require making trade-offs between near-term and long-term outcomes, 3) one choice can result in a small chance of a grave outcome, or 4) marginal differences are found in outcomes between options. Patient characteristics may also determine the need for a decision aid, e.g., if patients are very risk averse or attach unusual importance to certain possible outcomes. Another useful strategy for determining the need for a decision aid is to classify treatment policies as standards, guidelines, or options using definitions by Eddy (1). Table 1 summarizes the approach. For standards of care in which outcomes are known and patients' preferences are generally consistent in favoring an intervention, decision aids may be less useful, and conventional informed consent procedures are more appropriate. In contrast, decision aids may be indicated for treatment guidelines or options because outcomes may be more uncertain, or values for the benefits relative to the risks are more variable or unknown. For example, the guidelines (2) for postmenopausal hormone replacement therapy (HRT) recommend that decisions be tailored to a woman's hysterectomy status and risk of coronary heart disease (CHD), osteoporosis, and breast cancer. Moreover, a woman needs to consider her values in balancing the potential benefits of reducing the risk of osteoporosis and CHD and relief of menopausal symptoms against the potential risk of endometrial and breast cancers, the side effects of HRT, and her attitudes toward taking medication for a natural aging process. A recent example of an “option” emerged in 1998 following the early completion of the U.S. National Cancer Institute (NCI) Tamoxifen Prevention Trial. Although two smaller trials demonstrated no benefit, the NCI trial showed that tamoxifen reduced the incidence of breast cancer in high-risk women but also increased the risk of endometrial cancer, pulmonary embolus, and deep-vein thrombosis. Within 6 months of stopping the NCI trial, (a) NCI published the results on the Internet, including a statement that the decision about treatment depends on a woman's personal health history and how she weighs the benefits and risks; (b) the results of the three prevention trials were published; (c) tamoxifen was approved by the Food and Drug Administration (FDA) for use in women at high-risk for breast cancer; and (d) a “risk disk” to help practitioners and women identify personal risks for breast cancer and understand benefits and risks of tamoxifen was developed and disseminated. Note that the public and practitioners had simultaneous access to the information. How Are Decision Aids Designed to Work? Although the developers of decision aids have different conceptual frameworks of decision support (12-19), most are based on decision theories from economics and cognitive psychology (20-22) that structure decisions according to options, outcomes, and probabilities of outcomes so that patients are better able to judge the value of the benefits versus the risks. Many frameworks broaden this cognitive perspective by including emotional, social, or environmental dimensions (23-27). For example, the Ottawa Framework (12) identifies several determinants of health care decisions that may be suboptimal and are potentially modifiable by decision aids. Patients and practitioners may have problems with (a) perceptions of the decision (e.g., inadequate knowledge, unrealistic expectations of outcomes, unclear values, high uncertainty. or decisional conflict); (b) perceptions of others (e.g., biased or limited perceptions of the variation in others' opinions and practices, social pressures, or inadequate support); and (c) personal and external resources to make the decision (e.g., limited skills in shared decision making). Decision aids are designed to address these problematic determinants of choice by providing accurate, balanced, and tailored information; by clarifying patients' values; and by augmenting skills in shared decision making. For example, knowledge may be improved by providing information on options and outcomes. Unrealistic expectations (perceived probabilities of outcomes) may be realigned by presenting probabilities of outcomes that are tailored to the patient's clinical risk and by describing outcomes so that they are easy to imagine and to identify with (21). Unclear values are addressed by describing outcomes in familiar, simple, and experiential terms so as to better judge their value (22) and by providing the opportunity to weigh the benefits versus the risks. Biased perceptions of the variation in others' opinions may be corrected by presenting all options and, in some cases, by providing examples of others' choices and statistics on variation in choices. Shared decision-making skills may be improved by providing structure and guidance in deliberating about the personal issues involved in the choice and in communicating preferences (28-35). As a consequence of these interventions, patients presenting with uncertainty or decisional conflict caused by these problems may become more certain about what to choose and may be more likely to implement these choices (36). On the basis of the Ottawa framework, one can hypothesize that decision aids will improve the determinants of choice so that decisions are more likely to be 1) informed (i.e., based on better knowledge and realistic expectations), 2) consistent with personal values, and 3) implemented. Moreover, patients' comfort with the decision-making process (e.g., decisional conflict, self-confidence, and satisfaction with decision making) may be improved. On the basis of the results of other educational interventions (28,29,37-39) designed to promote realistic expectations of outcomes and informed active involvement in one's care, it is also reasonable to hypothesize that patients may be more likely to persist with decisions, to report less distress with the consequences of their decisions, and to experience improved health-related quality of life. Do Decision Aids Work? To date, there have been two published documents describing the efficacy of decision aids: an annotated bibliography (40,41) and a report to the Agency for Health Care Policy and Research (15). A Cochrane collaboration systematic overview (11) of randomized trials of decision aids is currently in progress. This paper summarizes the evaluative studies from the annotated bibliography (41), including an update to early 1998. The following databases were searched: MEDLINE®, CINAHL®, PsycINFO®, and Current Contents®. We also hand searched Medical Decision Making and Health Expectations. In this paper, we limited our review to studies of interventions that would be classified as decision support according to the Cochrane definition (see previous section). We included three types of studies 1) before/after studies that evaluated decision aids with patients at the point of decision making, 2) randomized trials that evaluated decision aids in comparison to “usual care” with patients at the point of decision making, and 3) randomized experiments comparing different methods of decision support in decision aids either with patients at the point of decision making or with volunteers making hypothetical choices. We included studies of decision aids that were not cancer related because of the small numbers of studies available in this emerging field of research. Types of Decision Aids Studied Table 2 summarizes the decisions aids that were identified in this review. Over half of the studies focused on cancer-related topics. Most decision aids focused on surgical or medical therapies, although a few considered preventive, end-of-life, and clinical trial participation decisions. Various media were used for delivering the decision aids. In some of the studies, it was difficult to ascertain what exactly was done in the “black box” of the decision aid. Although all decision aids included information on the options, benefits, and risks, they varied considerably in their presentation of this information. Moreover, there was considerable variability in whether other decision-support strategies were included in the decision aid. It was also sometimes difficult to ascertain what was involved in “usual care” or in the comparative intervention. Evaluative Studies of Efficacy Table 3 summarizes the results of the evaluative studies with patients at the point of decision making in which before/after designs and randomized trials with usual care controls were used. Effect on Variation in Choices One of the main rationales for using decision aids has been to reduce “ inappropriate” practice variation. It is assumed that, if the asymmetry of information available to practitioners and patients regarding options, outcomes, and patients' values is corrected by decision aids, then choices may more appropriately reflect patients' preferences. The direction of the shift in choices will depend on the cause of the practice variation. For example, if overuse is caused by supplier-induced demand involving knowledgeable practitioners who assume patients' values are similar to their own and uninformed patients, rates of use may decline if patients' informed valuing of options does not correspond to those of their practitioners. If there is underuse of interventions because of uninformed practitioners or patients, rates of use may increase. The before/after studies (12,42-45,60), including two cancer-related studies (12,60), are consistent in showing that decision aids have the greatest effect on the choices of those who are undecided at baseline. Approximately 18%-30% of patients were undecided before using decision aids, and 44%-68% of the undecided made a choice after using aids. The fact that over a third of the undecided still could not make up their mind after using a decision aid underscores the difficulty of these decisions and the need for follow-up counseling by practitioners. In contrast, decision aids are less likely to change the decisions of the 70%-82% of individuals who have a stated preference at baseline (12,42-44). Changes occurred in only 5%-13% of those preferring a more intensive treatment at baseline and in 11%-18% of those preferring a less intensive treatment. However, in some studies (45,54,60), the decision aid did shift preferences toward the less intensive option, e.g., toward breast-conserving surgery for breast cancer (60). The randomized trials comparing decision aids with usual care also suggest that decision aids affect decisions. They reduced the proportion of undecided in one trial (46) and showed a trend toward reducing preferences for more intensive options by 22%-48% in six of seven trials. Flood et al. (47) underscore the importance of predisposition and financial incentives in changing the decisions of patients. Two trials (47,51) showed that men who were exposed to decision aid about the prostate-specific antigen (PSA) before a routine scheduled fee-for-service visit had close to half the rates of PSA testing than usual-care control subjects. In contrast, the rates of PSA testing in another study (47) were comparable in those exposed to a decision aid (98%) versus a general education video (100%) in a clinic where men attended specifically for a free PSA test. However, the men receiving the free test differed in intentions toward having future PSA tests (which they would presumably have to pay for); in the decision-aid group, 74% had strong intentions to have a PSA test compared with 90% in the education video group. Effect on Determinants of and Comfort With Decision Making The most important question is: Are these observed changes in decisions after using a decision aid accompanied by commensurate improvements in the determinants of the choices? In Table 3, the before/after studies of decision aids focused on cancer and other outcomes are consistent in demonstrating that patients' choices are more likely to be based on better knowledge (8,12,42,43,52), more realistic expectations of outcomes (12,53-58), and personal values for outcomes (12,58,59) after patients use decision aids. Moreover, patients' comfort with their decisions, as measured by the Decisional Conflict Scale, is improved (12,54,55,58,60). The randomized trials, including two trials of PSA decision aids (47,51), have confirmed that decision aids are superior to usual care in improving knowledge (46,48), but the benefit is confined to feeling more informed about options, benefits, and risks. These results point to one of the main mechanisms explaining the potentially conservative effect of decision aids on decision making. The decision aids are better than usual care at moderating patients' exaggerated perceptions of risk of disease without the intervention and their exaggerated perceptions of the benefits of interventions. The aid also gives them a better appreciation of the potential risks associated with the more intensive intervention. Therefore, fewer patients are likely to judge that the potential benefits of the intensive option outweigh the potential harms. There have been no trials examining the effect of cancer-related decision aids on patients' satisfaction with decision making. For other trials of decision aids, most have shown no impact. Effect on Outcomes of Decisions Although outcomes of decisions are difficult to judge when decisions are based on personal values, it is still useful to examine how decision aids affect long-term persistence with choices, distress, regret, and health-related quality of life. There are no cancer studies examining the downstream effects of decision aids. The two noncancer studies (4,49) examining quality of life had variable results. Patients' Reactions to Decision Aids Before/after studies (6,42-44,57-60,62-64) are generally consistent in demonstrating that decision aids are acceptable to patients and are feasible to use. Further evaluations are needed to establish acceptability to practitioners and to patient groups who vary by age, education, ethnicity, and preferences for participation in decision making. Randomized Experiments Comparing Simpler With More Intensive Methods of Decision Support Table 4 summarizes the trials comparing simpler with more intensive methods of decision support. All but two of the trials focused on decision aids with cancer outcomes. In all of the decision-support interventions being compared, patients were provided with some information on the options and the outcomes, but there may have been differences in the complexity of the medium of delivery; the amount of information on options and outcomes; the use of probabilities; the inclusion of examples of other patients' decision making; and the guidance in deliberation regarding the personal issues, such as perceptions of the probabilities of outcomes, personal values, questions, and choices or leanings. There are too few studies to draw substantive conclusions; therefore, the following summary is considered preliminary. Although the decision aids are known to improve baseline knowledge (8,12,72), when different methods of decision support were compared with one another, no one method was superior at increasing knowledge (8,7,52,70,71,73). This null result is likely because of the overlap in information provided by the alternative interventions. Possibly, more sensitive knowledge tests may be able to detect differences, but one needs to be careful that the knowledge that is tested is considered essential to patients for decision making. The methods used in decision aids do affect patients' expectations of outcomes. Patients have more realistic expectations if they are exposed to quantitative presentations of probabilities (7,65) and if outcomes are framed (66) positively (e.g., chance of remaining free of treatment side effects = 95%) rather than negatively (e.g., chance of having a side effect = 5%). However, the effect on decisions of creating more realistic expectations is more variable. It did dampen patients' enthusiasm for participating in a hypothetical clinical trial (65) but had no effect on whether a patient took HRT (7) or accepted an influenza vaccine (66). However, those exposed to positive frames reported fewer vaccine side effects and less absenteeism from work (66). Methods in decision aids do affect whether choices reflect personal values. The correlation between personal values and choices improves when decision aids provide detailed and probabilistic information on outcomes and when patients are asked to deliberate about the personal probabilities and values for each outcome (5,7,67,68). The incremental benefit of asking patients to consider their values is an understudied area; one study (68) that used a “weigh scale” values clarification exercise found little overall incremental benefit, except possibly in those patients who were considering a change from the status quo. The effect of values clarification exercises needs to be studied in groups that are actively considering change to confirm these results and to determine if they improve the quality of discourse with practitioners regarding values, as well as if they have an effect on long-term persistence with decisions. Methods in decision aids do affect some decisions, although it is difficult to determine which components in the decision aid produced these effects; e.g., it is not clear whether decisions are influenced by providing examples of how others make decisions. The two studies (68,73) that varied the inclusion of examples and showed a possible effect on choices were confounded by varying other aspects of the decision aid. Moreover, in both of these studies, the decision was hypothetical, thereby limiting the generalizabilty of results to patients who actually face the decision and who use more than the information in an aid to make their decisions. The use of examples is controversial. Some decision aids do not include them to remain “ neutral”; others use them to convey the variability in other patients' choices. Few studies have examined the separate effects of guidance or coaching in deliberation about options and communication of preferences. Coaching has had a beneficial effect on patient outcomes (28-35), and whether it can augment the beneficial effects of decision aid remains to be seen. Few studies have been conducted that compared only the medium of delivery, usually because some methods of decision support require more complicated delivery technologies. In the two studies that did compare media, one (70) showed that an interactive computer program increased entry decisions for a hypothetical clinical trial compared with an audiotape. Another study (73) comparing multimedia with a pamphlet found a trend toward decreased preferences for mastectomy but no differences in involvement in decision making. The different methods used in decision aids had no affect on satisfaction with the decision. There is a need to reexamine the way satisfaction is measured, given its lackluster performance, in discriminating not only between decision aids but also between decision aids and usual care. It may be more appropriate to measure satisfaction with preparation for decision making (which presumably decision aids do well) than satisfaction with the process of decision making and with the practitioner (which depends on many factors outside the control of decision aids). Moreover, investigators may need to acknowledge the difficulty in demonstrating improvements in satisfaction with the decision when choices are inherently difficult to make because of competing benefits and risks. Furthermore, once the decision is made, patients may find it more psychologically comforting to say that they are satisfied with it rather than entertain doubts about what they chose (61). Perhaps a better indication of satisfaction with the decision is persistence with the choice; unfortunately, this indicator is only useful for revocable decisions. In a current trial (O'Connor A et al.: unpublished data), we have had success using a scale that elicits patients' and practitioners' satisfaction with patients' preparation for decision making. The scale discriminates well (effect size 1.8) between a pamphlet decision aid regarding HRT and one with the full range of interventions delivered via audio-guided workbook. The acceptability of decision aids was affected by methods when the differences between interventions were large. For example, users found that pamphlets (with less detail, no illustrations, no probabilities, no examples, and no guidance in personal deliberation) were less acceptable than audio-guided workbooks that included these strategies. However, there was no overall difference in acceptability when more subtle differences in decision aids were compared (e.g., the addition of graphical displays to accompany numerical probabilities or the addition of a weigh scale values clarification exercise). Conclusions About Evaluative and Methodologic Studies In the evaluative studies of cancer-related decision aids conducted to date, the aids are acceptable to patients and help those who are uncertain at baseline to make a choice. They also increase the likelihood that choices are based on better knowledge, realistic expectations of outcomes, and personal values. They reduce some dimensions of decisional conflict, and their effect on decisions is variable. Few studies examine the downstream effects of decision aids on long-term persistence with choices, regret, and quality of life. In terms of methods used in decision aids, there has been minimal investigation of what works in the “black box” of decision aids. When simpler methods are compared with more intensive methods of decision support, the differences are negligible in terms of knowledge and satisfaction and are variable in terms of decisions and decisional conflict. However, more intensive methods are generally superior in terms of user acceptability and the extent to which choices are based on realistic expectations and personal values. The clinical importance of these differences and the cost-effectiveness of decision aids remain to be established. Research Implications Evaluation of Decision Aids There are several gaps in research on decision aids. More research is needed on (a) how decision aids perform for different clinical decisions; (b) their acceptability to practitioners; (c) their acceptability to diverse patient groups; (d) their effect on patient-practitioner communication; (e) their downstream effects on persistence with the decision, distress, regret, and health-related quality of life; and (f) the optimal strategies for disseminating and for implementation. Most evaluation studies are fraught with methodologic difficulties. They cannot be double-blind studies. Those studies that randomize patients rather than practitioners have contamination problems that narrow the differences that will be detected. Those studies that randomize practitioners need to be very large because of cluster sampling. Moreover, they may have selection biases because clinicians, knowing their assignment, may (a) be more or less enthusiastic about recruiting patients or (b) recruit different types of patients. Despite the researchers' best efforts, it is very difficult in a real-world setting to present the decision aid at the appropriate time to patients who are eligible to consider all of the options in the aid. Furthermore, efficacious interventions may have no effect if either patients or practitioners, or both, are extremely polarized toward one of the options at baseline. When postintervention measures are administered after the consequences of the choice are known, it is very difficult to avoid having the outcome color the patients' evaluation of satisfaction with the decision-making process and the decision. We recommend that future studies should Examine the effect of decision aids on a broader range of decisions with a more comprehensive range of patient and practitioner outcomes; Select patients who are at the point of decision making for whom the choices in the aid are relevant; Measure patients' and practitioners' baseline predispositions toward the choices; Have sample sizes large enough to detect clinically meaningful differences in decisions among the undecided subgroup of patients; Measure patients' perceptions of practitioners' opinions; Have a usual care arm and describe clearly what usual care comprises; and Describe clearly what was in the decision aid and how it was used in the diagnostic or treatment trajectory. Evaluation of Methods in Decision Aids The incremental efficacy of including different strategies in decision aids should be explored. A starting point would be to evaluate the additional strategies outlined in the Cochrane definition (11). Entwistle et al. (18) also outline several important issues regarding the presentational aspects of decision aids. Care should be taken in deciding which methods should be compared, considering the expense of an adequately powered study and the rather small differences observed in previous work. The use of nonpatient groups should be considered carefully. Although they make the study more feasible, it is difficult to generalize results to patients who are actually facing the decision and relying on more than the information in the aids to make their decisions. We recommend the following: 1) The selection of strategies for evaluation should be based on whether the studies have the potential to exert a strong influence on decisions; vary considerably in their use in current decision aids; and contribute significantly to the cost, complexity, and time required to administer decision aids. 2) Clinically important differences should be defined a priori, and studies should be adequately powered. 3) Ideally, methods studies should include patients actually faced with the decisions and should evaluate cost-effectiveness. Coordinating the Future Development of Decisions Aids Decision aids have been developed on the basis of academic expertise and interest and sometimes evidence of population need. As the field matures, there is a need to focus more attention on systematic and standardized approaches to needs assessment, development, and evaluation. In Table 5, we have posed seven key questions that may be considered when deciding whether and how to develop a decision aid. These questions should be considered not only by individual research teams but also by cancer agencies with a system perspective. The order and depth of investigation of each question depend on the type of decision, the extent of previous research in the area, and the constraints and perspectives of the developers. The seven questions are as follows: 1) Is there a need for a decision aid? Needs assessment involves the compilation of evidence about the nature of the decision difficulty, the numbers affected, practice and preference variation, availability of aids elsewhere, and demand for the aid. Methods for needs assessment are varied, and data are obtained from primary or secondary sources or both. It is important that needs are defined from the perspective of potential users, both patients and practitioners. 2) Is it feasible to develop a decision aid? Feasibility is assessed to determine that the aid can be developed with available evidence and resources and can be delivered and updated in a timely, accessible, and acceptable manner. 3) What are the objectives of the decision aid? The objectives of the decision aid should be stated explicitly. Examples are identified in Table 5. The objectives drive the selection of the framework, intervention strategies, and evaluation methods. 4) Which framework will drive its development? Depending on the objectives, several frameworks are available to guide decision aid development (8,12-19). 5) Which methods will be included in the decision aid? In selecting the decision support methods, the developer needs to determine how much emphasis will be placed on preparing the patient and the practitioner. The specific decision support methods, content, and delivery methods depend on the nature of the decision, the needs of the decision maker, the feasibility constraints, and the objectives of the decision aid. 6) Which designs and measures will be used to develop and evaluate the decision aid? Development and evaluation depend on the objectives of decision aids. Developers need to decide on the sampling and design architecture, the criteria for evaluation, and the measurement tools that will be used to operationalize the criteria. A key issue is what are the primary criteria that should be used to evaluate efficacy? Examples of criteria currently in use are listed in Table 5. Entwistle et al. (19) provide an excellent overview of potential criteria depending on the model of patient involvement (shared decision making, individual informed choice, professional as agent for the patient, promotion of rational decision making, promotion of a particular choice). One of the biggest dilemmas is defining efficacy when choices depend on personal values for the outcomes. We maintain that decisions and outcomes of decisions should be evaluated from the perspective of the patients' values. Our assumptions are that 1) patients are unlikely to be able to value an option and communicate it to others unless they know what is involved and what outcomes are likely; and 2) once informed about options, patients are unlikely to implement or persist with an option that does not reflect personal values. Therefore, we consider a values-sensitive decision to be a good one if it is informed (based on adequate knowledge of options and outcomes and realistic expectations), based on personal values, and implemented. Moreover, the outcomes of a good decision should improve health outcomes (assessed using values-based measures) and persistence with choices (especially when the underlying reason for nonpersistence is a mismatch in values). Another challenge is measuring the degree to which a decision is “consistent with personal values.” This has been assessed with the use of the self-reports of patients (12,67), percentage accuracy in discrimination between values and choice (68), odds ratios from logistic regression predicting choices from preferences (59), congruence between recommendations on the basis of expected utilities and choices (5), and agreement between choices and patients' treatment thresholds for median survival (58). The relative advantages of these methods and others, such as preference-based health outcomes and quality-adjusted life years, should be explored. 7) How should the decision aid be disseminated? Dissemination involves the targeted distribution and promotion of the use of the decision aid. Six key elements of research transfer and use (74) are presented: potential adopters, practice environment, the evidence-based innovation (e.g., the decision aid), strategies for transferring the evidence into practice, evidence adoption, and outcomes. These elements are systematically monitored before, during, and after any research transfer efforts. The data generated by monitoring are used to 1) identify potential barriers and supports to research use associated with the potential adopters, the practice environment, and evidence-based innovation; 2) provide direction for selecting and tailoring transfer strategies; 3) track the progress of the transfer effort; and 4) assess the adoption of the evidence and its effect on outcomes of interest. Although dissemination is identified as a final step, it should be addressed early in the development process so that the aid is acceptable to potential users and has a greater potential for adoption. Therefore, dissemination questions can be posed during the needs and feasibility phases. Development and review panels can include potential users (practitioners and patients) and partners who may assist with dissemination (consumer groups, health professional organizations, disease foundations, and public education agencies). Standards for Developing Future Decision Aids The definition of a patient decision aid is open to broad interpretation, and materials of variable quality have been produced. Consumers expect to receive free health information and may have difficulty distinguishing the wheat from the “free” chaff unless certain standards are set in their development. Many of the better decision aids have the following characteristics: (a) They use evidence-based statements of benefits and risks from credible sources, refer to the quality and consistency of empirical studies, and use systematic overviews that extend shelf life and enhance updating. (b) They are balanced in presenting all options (including doing nothing), benefits and risks, and, when included, examples of others' decisions and opinions. (c) They identify the qualifications of the developers, including multidisciplinary expertise as evidence interpreters, communicators, practitioners, consumers, or disseminators, as well as conflicts of interest. (d) They demonstrate commitment to update by 1) using expiry dates indicating the expected shelf life of the information, 2) mentioning upcoming trials that may shift policy, and 3) demonstrating linkage to an ongoing and credible evidence-analysis process (e.g., the Cochrane overview groups, the AHCPR PORTS or evidence centers, or the Cancer Care Ontario Practice Guidelines Initiative). (e) They state the sources of funding in development, including potential conflicts of interest. (f) They describe the efficacy of the decision aid in promoting evidence-informed choice, including acceptability, improvements in knowledge, etc. Dissemination Issues Table 6 describes how Lomas (75) applies his “research to policy” framework to shared decision-making programs. For each stage, from hypothesis generation to policy applications, he identifies key issues. Since the publication of the framework in November 1997, remarkable progress has been made in promoting shared decision making. Conceptual frameworks have been developed. Aids focused on cancer outcomes have been developed and pilot tested. Efficacy trials have been completed or are in progress. The results have been communicated broadly. Moreover, some of the aids are now being used by practitioners and patients. One controversial issue is that of disseminating decision aids before large efficacy trials are completed with all relevant endpoints. Entwistle et al. (18) clarified the conflict by describing two rationales for promoting “evidence-informed patient choice” via mechanisms such as decision aids. The first is that one has a basic moral obligation to provide individuals with information and choice about their health care. Therefore, evidence-informed patient choice is the desired end. If decision aids can accomplish this end, as they have consistently demonstrated to date, then the tools should be disseminated. Much of the educational material available to patients has not been developed and tested as rigorously as decision aids. Moreover, some materials are developed by industries with vested interests in promoting increased use of their products. The public and nongovernmental organizations (NGOs) are clamoring for good decision support tools. NGOs and research institutes have sponsored the dissemination of decision aids that have been demonstrated to promote informed patient choice. The second rationale is a consequentialist argument, based on the hypothesis that informed patient choice will lead to other beneficial outcomes. It is, therefore, a means to a desirable end, such as greater clinical effectiveness, health gain, individually appropriate utilization, reduced expenditures on inappropriate interventions, reduced litigation, and so forth. According to Entwistle et al. (18), accepting the consequentialist argument means that we need to examine the benefits and harms of promoting evidence-informed patient choice across a whole range of health care decisions, patient groups, health care settings, and forms of decision support. Bernstein et al. (49) also argued for more studies of cost-effectiveness, given the expense of developing and disseminating these tools and the modest benefits observed in the trials to date. Therefore, proponents of this rationale would argue for more investigation before wide-scale dissemination. A practical solution may be 1) to distribute aids that are needed, that are affordable, and that have been demonstrated to promote evidence-informed patient choice; 2) to continue to examine the downstream effects of decision aids in trials with usual care controls for new clinical decisions; and 3) to continue to explore (in methods studies) the most cost-effective strategies for achieving evidence-informed choice. Conclusion In this paper, the published evidence of the efficacy of decision aids has been presented. Although we know decision aids improve decision making, the downstream effect on persistence with decisions, health-related quality of life, and costs remain to be established. The implications for further research have been identified. There are outstanding issues regarding coordination, standards, and dissemination. Table 1. Determining need for patient decision aids on the basis of the Eddy (1) classification of health policy decisions   Practice standards   Practice guideline       Practice options   Likelihood of outcomes  Known  Known  Known/unknown  Agreement in patients' values/preferences for outcomes  Known, unanimous (⩾95% agreement)  Known, majority (⩾60% agreement)  Known, evenly split Unknown  Recommendation for treatment  Yes  Variable  No  Patient participation in decision making  Passive, informed consent  Variable  Active, informed choice  Practitioner intervention needed  Counseling followed by verbal or written consent  When recommendation states the decision should be based on patients preference, patient decision aid can be used with follow-up counseling  Patient decision aid and follow-up counseling    Practice standards   Practice guideline       Practice options   Likelihood of outcomes  Known  Known  Known/unknown  Agreement in patients' values/preferences for outcomes  Known, unanimous (⩾95% agreement)  Known, majority (⩾60% agreement)  Known, evenly split Unknown  Recommendation for treatment  Yes  Variable  No  Patient participation in decision making  Passive, informed consent  Variable  Active, informed choice  Practitioner intervention needed  Counseling followed by verbal or written consent  When recommendation states the decision should be based on patients preference, patient decision aid can be used with follow-up counseling  Patient decision aid and follow-up counseling  View Large Table 2. Types of decision aids evaluated Type of decision (reference No.)*   Medium of delivery*   Medical or surgical treatments  Cancer, breast (6, 52, 60, 62, 71, 73, 93)  Interactive videodisc, decision board, brochure, interactive mutimedia program, audio-guided workbook  Cancer, lung (55, 58)  Audio-guided workbook, personal interview with trade-off exercise  Cancer, leukemia (63)  Decision board  Cancer, lymphoma (53)  Poster  Atrial fibrillation (56, 56)  Audio-guided workbook  Benign prostatic hypertrophy (4, 43, 45, 59)  Interactive videodisc  Low back pain (42)  Interactive videodisc  Circumcision (50)  Written materials  Ischemic heart disease (44, 48, 49)  Interactive videodisc, video  Screening or diagnostic tests  Colon cancer screening (64, 76)  Computer program  Prostate-specific antigen tests (47, 51, 69, 72)  Video, pamphlet, scripted counseling  Amniocentesis (9, 54)  Audio-guided workbook  Preventive therapies  Hormone therapy (7, 8, 12, 67, 68)  Audio-guided workbook, brochure, group workshops  Hepatitis B vaccine (5)  Written materials  Clinical trial participation  Breast cancer therapy (65)  Written vignettes  Cancer chemotherapy (70)  Audiotape, computer, interactive computer  End-of-life  Resuscitation in seniors (57)  Written outcome data  Type of decision (reference No.)*   Medium of delivery*   Medical or surgical treatments  Cancer, breast (6, 52, 60, 62, 71, 73, 93)  Interactive videodisc, decision board, brochure, interactive mutimedia program, audio-guided workbook  Cancer, lung (55, 58)  Audio-guided workbook, personal interview with trade-off exercise  Cancer, leukemia (63)  Decision board  Cancer, lymphoma (53)  Poster  Atrial fibrillation (56, 56)  Audio-guided workbook  Benign prostatic hypertrophy (4, 43, 45, 59)  Interactive videodisc  Low back pain (42)  Interactive videodisc  Circumcision (50)  Written materials  Ischemic heart disease (44, 48, 49)  Interactive videodisc, video  Screening or diagnostic tests  Colon cancer screening (64, 76)  Computer program  Prostate-specific antigen tests (47, 51, 69, 72)  Video, pamphlet, scripted counseling  Amniocentesis (9, 54)  Audio-guided workbook  Preventive therapies  Hormone therapy (7, 8, 12, 67, 68)  Audio-guided workbook, brochure, group workshops  Hepatitis B vaccine (5)  Written materials  Clinical trial participation  Breast cancer therapy (65)  Written vignettes  Cancer chemotherapy (70)  Audiotape, computer, interactive computer  End-of-life  Resuscitation in seniors (57)  Written outcome data  * Decision aids focused on cancer outcomes are in bold. View Large Table 3. Evidence of effectiveness of patient decision aids   Before/after studies detecting change from baseline after decision aid (reference No.)*   Randomized trials of decision aids vs. usual care controls (reference No.)*   Do decision aids affect decisions?    Yes  Yes    Help undecided (12, 60, 42-45)  Help undecided (46)    Reduce preference for intensive option (60, 45, 54)  Reduce preference for intensive option (47, 51, 46)      Trend decision aid reduces preference for intensive option (448, 49)      No (50)  Do decision aids improve determinants of decisions?  Choice based on better knowledge of options, benefits, or risks  Yes (8, 12, 52, 42, 43) and no (57)  Yes (47, 51, 4, 46, 49, 49) and no (50)  Choice based on more realistic expectations (agreement between perceived probability of outcomes and estimates derived from evidence)  Yes (12, 53, 55, 58, 54, 56, 57)  Yes (47,46, 51,46)  Choice based on personal values (correlation between personal values for outcomes and choice)  Yes (12, 58, 59)  —  Do decision aids improve comfort with decision making?  Reduce decisional conflict (feeling uncertain, uninformed, unclear about values, unsupported in decision making)  Yes (12, 55, 58, 60, 54)  Yes, benefit limited to informed dimension (46, 48)  More satisfied with decision-making process  —  Yes (4) and no (46, 48, 49)  More satisfied with decision  Yes (58)  No (4, 48, 49)  More satisfied with treatment  —  Less satisfied (49)  Do decision aids improve outcomes of decisions?  Better health-related quality of life  —  Yes (4) and no (49)  Better compliance/persistence with decision  —  —  Reduced morbidity  —  —  Do decision aids produce favorable reactions from patients?  Acceptable to patients (comprehensibility, length, clarity, usefulness, interest, balance, or recommend to others)  Yes (6, 58, 59, 60, 62, 42-44, 57)  Feasible to use  Yes (63, 64)  —    Before/after studies detecting change from baseline after decision aid (reference No.)*   Randomized trials of decision aids vs. usual care controls (reference No.)*   Do decision aids affect decisions?    Yes  Yes    Help undecided (12, 60, 42-45)  Help undecided (46)    Reduce preference for intensive option (60, 45, 54)  Reduce preference for intensive option (47, 51, 46)      Trend decision aid reduces preference for intensive option (448, 49)      No (50)  Do decision aids improve determinants of decisions?  Choice based on better knowledge of options, benefits, or risks  Yes (8, 12, 52, 42, 43) and no (57)  Yes (47, 51, 4, 46, 49, 49) and no (50)  Choice based on more realistic expectations (agreement between perceived probability of outcomes and estimates derived from evidence)  Yes (12, 53, 55, 58, 54, 56, 57)  Yes (47,46, 51,46)  Choice based on personal values (correlation between personal values for outcomes and choice)  Yes (12, 58, 59)  —  Do decision aids improve comfort with decision making?  Reduce decisional conflict (feeling uncertain, uninformed, unclear about values, unsupported in decision making)  Yes (12, 55, 58, 60, 54)  Yes, benefit limited to informed dimension (46, 48)  More satisfied with decision-making process  —  Yes (4) and no (46, 48, 49)  More satisfied with decision  Yes (58)  No (4, 48, 49)  More satisfied with treatment  —  Less satisfied (49)  Do decision aids improve outcomes of decisions?  Better health-related quality of life  —  Yes (4) and no (49)  Better compliance/persistence with decision  —  —  Reduced morbidity  —  —  Do decision aids produce favorable reactions from patients?  Acceptable to patients (comprehensibility, length, clarity, usefulness, interest, balance, or recommend to others)  Yes (6, 58, 59, 60, 62, 42-44, 57)  Feasible to use  Yes (63, 64)  —  Decision aids focused on cancer outcomes are in bold. View Large Table 4. Randomized trials comparing different methods in decision aids Decision (reference No.) *  Delivery *†   Options *†   Outcomes *†   Probabilities *†   Examples *†   Guidance in personal deliberation *†   Hormones (8, 67)  (a) Pamphlet  Detailed  Detailed  Yes  Yes  No    (b) Group  Detailed  Detailed  Yes  Yes ‡  No    (c) Group  Detailed  Detailed  Yes  Yes ‡  Yes—probabilities, values, choice    Hormones (7)  (a) Pamphlet  Brief  Brief  No  No  No    (b) Audio-guided workbook  Detailed  Detailed  Yes  Yes  Yes—probabilities, values, choice    Hormones (68)  (a) Audio-guided workbook  Detailed  Detailed  Yes  No  Probabilities, questions    (b) Audio-guided workbook  Detailed  Detailed  Yes  Yes  Probabilities, questions, values, choice    Breast cancer surgery (71)  (a) Pamphlet  Brief  Brief  No  No  No    (b) Audio-guided workbook  Detailed  Detailed graphic  Yes  Yes  Yes—values, choice    Hepatitis B Vaccine (5)  (a) Written  Brief  Brief  No  No  No    (b) Written  Detailed  Detailed  Yes  No  No    (c) Written  Detailed  Detailed  Yes  No  Yes—probabilities, values    Trial entry (65)  (a) Vignette  Brief  Brief  Qualitative  —  —    (b) Vignette  Brief  Brief  Quantitative  —  —    Flu vaccine (66)  (a) Chart/poster  Detailed  Detailed  Positive frame  —  —    (b) Chart/poster  Detailed  Detailed  Negative frame    Transplant (53)  (a) Chart/poster  Detailed  Detailed  Numbers  —  —    (b) Chart/poster  Detailed  Detailed  Numbers/graph    PSA test (72)  (a) Pamphlet  Brief  Brief  No information    (b) Pamphlet  Brief  Brief  False positive/negative    PSA tests (69)  (a) Verbal  Sentence  Very brief  None  No    (b) Verbal  Sentence  Detailed  Quantitative  No    Breast cancer surgery (52)  (a) Booklet  Detailed  Detailed  Yes  No    (b) Video  Detailed  Detailed  Yes  Yes    Breast cancer surgery (73)  (a) Pamphlet  Briefer  Briefer    No    (b) Multimedia  Detailed  Detailed    Yes      Trial (70)  (a) Audiotape  Detailed  Detailed  Yes  No  No    (b) Computer  Detailed  Detailed  Yes  No  Choice of order of information  (Table continues)  Decision (reference No.) *  Delivery *†   Options *†   Outcomes *†   Probabilities *†   Examples *†   Guidance in personal deliberation *†   Hormones (8, 67)  (a) Pamphlet  Detailed  Detailed  Yes  Yes  No    (b) Group  Detailed  Detailed  Yes  Yes ‡  No    (c) Group  Detailed  Detailed  Yes  Yes ‡  Yes—probabilities, values, choice    Hormones (7)  (a) Pamphlet  Brief  Brief  No  No  No    (b) Audio-guided workbook  Detailed  Detailed  Yes  Yes  Yes—probabilities, values, choice    Hormones (68)  (a) Audio-guided workbook  Detailed  Detailed  Yes  No  Probabilities, questions    (b) Audio-guided workbook  Detailed  Detailed  Yes  Yes  Probabilities, questions, values, choice    Breast cancer surgery (71)  (a) Pamphlet  Brief  Brief  No  No  No    (b) Audio-guided workbook  Detailed  Detailed graphic  Yes  Yes  Yes—values, choice    Hepatitis B Vaccine (5)  (a) Written  Brief  Brief  No  No  No    (b) Written  Detailed  Detailed  Yes  No  No    (c) Written  Detailed  Detailed  Yes  No  Yes—probabilities, values    Trial entry (65)  (a) Vignette  Brief  Brief  Qualitative  —  —    (b) Vignette  Brief  Brief  Quantitative  —  —    Flu vaccine (66)  (a) Chart/poster  Detailed  Detailed  Positive frame  —  —    (b) Chart/poster  Detailed  Detailed  Negative frame    Transplant (53)  (a) Chart/poster  Detailed  Detailed  Numbers  —  —    (b) Chart/poster  Detailed  Detailed  Numbers/graph    PSA test (72)  (a) Pamphlet  Brief  Brief  No information    (b) Pamphlet  Brief  Brief  False positive/negative    PSA tests (69)  (a) Verbal  Sentence  Very brief  None  No    (b) Verbal  Sentence  Detailed  Quantitative  No    Breast cancer surgery (52)  (a) Booklet  Detailed  Detailed  Yes  No    (b) Video  Detailed  Detailed  Yes  Yes    Breast cancer surgery (73)  (a) Pamphlet  Briefer  Briefer    No    (b) Multimedia  Detailed  Detailed    Yes      Trial (70)  (a) Audiotape  Detailed  Detailed  Yes  No  No    (b) Computer  Detailed  Detailed  Yes  No  Choice of order of information  (Table continues)  * Decision aids focused on cancer outcomes are in bold. HRT = hormone replacement therapy; PSA = prostate-specific antigen. † Components are bolded to signify differences between methods used. ‡ Patients in the two groups were exposed to more examples than those using the brochure. View Large Table 4 (continued). Randomized trials comparing different methods in decision aids Choice   Knowledge   Expectations   Correlation values and choice   Decision conflict   Satisfaction   Other     No difference    —  Worse  No difference  No difference        —  —    Persistence        Better  —    With choice    No difference  No difference  —  —  —      More realistic  Better clarity of values  Better    More acceptable    —      —  No difference    No difference Acceptability  Trend, increased HRT      Trend, better in those changing status quo (choosing HRT)          No difference      No overall difference    —          Trend, better in uncertain patients    More acceptable, no difference in anxiety    —      —  —      —  Increased vaccine      Better    —    —  Decreased trial entry    More realistic    No difference    More realistic    No difference    Decreased symptoms and work loss      —        —    No difference    No difference        No difference in acceptability    —    —  Trend, decreased PSA    More realistic    —  Decreased PSA    —  No difference  Decreased mastectomy    —  —          No difference in decision-making involvement  Trend, decreased mastectomy  Trend increased    —  No difference        No difference  Increased trial entry  Choice   Knowledge   Expectations   Correlation values and choice   Decision conflict   Satisfaction   Other     No difference    —  Worse  No difference  No difference        —  —    Persistence        Better  —    With choice    No difference  No difference  —  —  —      More realistic  Better clarity of values  Better    More acceptable    —      —  No difference    No difference Acceptability  Trend, increased HRT      Trend, better in those changing status quo (choosing HRT)          No difference      No overall difference    —          Trend, better in uncertain patients    More acceptable, no difference in anxiety    —      —  —      —  Increased vaccine      Better    —    —  Decreased trial entry    More realistic    No difference    More realistic    No difference    Decreased symptoms and work loss      —        —    No difference    No difference        No difference in acceptability    —    —  Trend, decreased PSA    More realistic    —  Decreased PSA    —  No difference  Decreased mastectomy    —  —          No difference in decision-making involvement  Trend, decreased mastectomy  Trend increased    —  No difference        No difference  Increased trial entry  View Large Table 5. Developing and evaluating decision aids: questions and methods Issue   Method (reference No.)   1. Is there a need for a decision aid?  What are the decision-making needs of patients and practitioners?  Conduct key informant interviews, focus groups, or surveys to elicit patients' and practitioners' perceptions of decisions perceived as important and difficult, usual roles and decision-making practices, barriers and facilitators in providing or accessing decision support, potential strategies for overcoming barriers  What makes the decision difficult?  Review systematic overviews, decision analyses, and preference studies to determine whether benefits marginal or uncertain, risks material or uncertan, value trade-offs between benefits and risks, and variation in preferences, for outcomes  Are sufficient numbers affected and how are they affected?  Review databases, demographic or morbidity statistics, and population surveys  Is there sufficient variation in use?  Review practice atlases, utilization data, or practice variation studies  Are there decision aids available to meet these needs?  Review published overviews, reports; contact centers that produce aids  Is there a demand for decision aids and what methods are preferred?  Conduct market surveys (81)  2. Is it feasible to develop a decision aid?  Are there adequate resources?  Assess finances, availability of experts with credibility, networks, and commitment to ongoing update; link to established overview and dissemination networks  Is there enough evidence of benefits and risks to incorporate into a decision aid?  Review systematic overviews with appraisals of the quality of evidence  How quickly is the evidence expected to change?  Review ongoing trials  Will aid be accessible or acceptable to users?  Conduct focus groups or market surveys  3. What are the objectives of the decision aid?  Objectives focused on improved decision making  Improve knowledge of the clinical problem, options, outcomes, and variation in patient or practitioner opinions and practices.    Create realistic expectations of outcomes, consistent with available evidence.    Clarify personal values for outcomes and promote congruence between patients' values and choice.    Reduce patients' and practitioners' decisional conflict (uncertainty) about the course of action to take.    Promote implementation of choices.    Improve patients' or practitioners' satisfaction with decision making.  Objectives focused on outcomes of decision  Promote patients' persistence with choice.    Reduce patients' distress from consequences of decision.    Improve patients' health-related quality of life. Promote informed use of resources by patients and practitioners.  4. Which framework will drive its development?    Charles et al. (13) distinguish shared decision making from other decision-making approaches.    Entwistle et al. (18, 19) define evidence-informed choice and outline different criteria for evaluations depending on objective.    The Hershey et al. framework (15) developed for AHCPR has a health services and informatics perspective.    The Llewellyn-Thomas framework (14) has a special focus on types of preferences and placement in sociopolitical context.    Mulley (16) places shared decision making in the context of outcomes research.    Ottawa Decision Support Framework (12) prepares practitioner and patient and has a clinical and behavioral focus.    Rothert et al. (8, 17) describe mutual roles of patients and practitioners in decision making; they focus on information and values.  5. Which methods will be included in the decision aid?  Patient or client decision support  Information regarding options and outcomes    • Content: clinical problem, options, outcomes    • Detail in describing outcomes: define outcomes; describe physical, emotional, social effect; use narrative/scenario styles    • Probabilities: none; numerical frequencies or percents (7), graphic pie charts (6), 100 people (4, 12), qualitative (low, moderate, high)    • Tailored probabilities: not tailored; stratified by personal risk factors    • Evidence for statements: references included or not    Values clarification    • Implicit (4, 6 )    • Explicit methods such as weigh scale exercise (7), treatment trade-off task (82), relevance chart (8), decisional balance sheets (83), formal utility assessments (5, 9)    Information on others    • None    • Cases of different choices (4, 8, 12)    • Statistics on variation in patients' decisions or practitioners' opinions     Coaching or guidance in deliberation, communication, and implementation    • Not included    • Steps in weighing the benefits or risks (8, 12)    • Steps in discussing decision with a practitioner (8, 12)    • Tips on managing consequences of choices    Delivery (personal counseling supplemented by)    • Generic tools    • Decision board (6)    • Take home audio-guided workbook (7)    • Interactive videodisc or linear video (4)    • Computer-based tool (70)    • Group lecture or workshop (18)  Practitioner decision support  Content: scientific evidence regarding decision, rationale for decision aid, efficacy of decision aid, timing and use in practice, scientific references    Delivery: manual, video, lecture, workshop, hot line, academic detailing  6. Which designs and measures will be used to develop and evaluate decision aid?  Development panel  Participants (researchers, clinicians, educators, patients, opinion leaders)    Methods (iterations of drafts, feedback, revisions, feedback, etc.)  Review panels  Participants (potential users: practitioners, patients who have already made decisions)    Methods (focus groups, personal interviews, questionnaires to elicit acceptability, etc.)  Pilot studies  Participants (patients at the point of decision making)    Designs*    XO XO: test-retest 2 weeks apart (stability of preferences and reliability of measures)    OXO: before/after study uses baseline questionnaire, decision aid, or posttest questionnaire    XO: posttest only, usually with preestablished criteria for success (e.g., 70% on knowledge test)  Trials  Participants (patients at point of decision making, practitioners)    Designs*    Quasi experiment OCO OXO    Randomized trial (with unit of randomization either the patient or practitioner) ROXO ROCO  What are the criteria for evaluation?   Knowledge  Knowledge or comprehension test (4, 7, 8, 47)   Expectations of outcomes  Probability scales (7, 84-87), likelihood scales (26)   Clarity of values  Values subscale of Decisional Conflict Scale (7, 36, 68)   Agreement between choice and values  Statistical relationship between values and choices ( 5, 7, 12, 58, 59, 67, 68)   Realistic perceptions of others  Perceptions of percentage of practitioners or patients choosing options; subjective norms (26)   Decision  Choice question (option x, option y, unsure); choice predisposition (7)   Decisional conflict  Decisional conflict scales for patients (7, 36, 88) and providers (89)   Skill in decision making  Self-efficacy scale (8, 88), implementation data   Satisfaction with decision making  Decision satisfaction inventory (4); satisfaction with decision (8, 90); satisfaction with preparation for decision making (O'Connor A, et al.: unpublished data)   Acceptability  Acceptability questionnaires—shared decision-making tool (42-45), Ottawa tool (68)   Use of decision aid  Utilization data   Participation according to needs  Congruence between preferred and actual role in decision making (91, 92)   Persistence with decisions  Survey of decision over time; implementation data   Reduced distress from outcomes  Condition-specific symptom and side effects distress scales   Health-related quality of life  Generic, condition-specific, preference-based   Use of resources  Analysis of utilization data   Costs  See the Hersey et al. (15) framework and the Nease and Owens (94) cost-effectiveness model  7. How should the decision aid be disseminated (74)?  What are potential adopters: attitudes toward innovation or change; knowledge, attitudes, and skills to use aid; preference for shared decision making?  Conduct focus groups, key informant interviews, environmental scans, or surveys of potential users  What are the environmental barriers and supporters?  Conduct focus groups or surveys to identify the following factors:    • Social (likely supporters and opposers; presence of opinion leaders as supporters; predominant belief system regarding shared decision making)    • Structural (operational tools and processes, regulations, quality assurance criteria, to encourage or hinder use of aid; resources to support dissemination of aid)    • Other incentives and disincentives  Will the evidence-based innovation meet expectations of target audience?  Conduct focus groups or surveys  Which transer strategies should be used?  Tailor strategies according to needs; diffusion strategies (advertisements, publications, or Internet); dissemination strategies (targeted mailings); implementation strategies (education programs or administrative changes)  Is the aid being adopted, and is it having the expected effect on outcomes?  Analyze databases; conduct quality assurance studies, surveys, and implementation studies to determine whether the aid is being used by the expected audience in the expected manner and whether it is having the expected effect on health and economic outcomes and evidence-based decision making among patients or clinicians  Issue   Method (reference No.)   1. Is there a need for a decision aid?  What are the decision-making needs of patients and practitioners?  Conduct key informant interviews, focus groups, or surveys to elicit patients' and practitioners' perceptions of decisions perceived as important and difficult, usual roles and decision-making practices, barriers and facilitators in providing or accessing decision support, potential strategies for overcoming barriers  What makes the decision difficult?  Review systematic overviews, decision analyses, and preference studies to determine whether benefits marginal or uncertain, risks material or uncertan, value trade-offs between benefits and risks, and variation in preferences, for outcomes  Are sufficient numbers affected and how are they affected?  Review databases, demographic or morbidity statistics, and population surveys  Is there sufficient variation in use?  Review practice atlases, utilization data, or practice variation studies  Are there decision aids available to meet these needs?  Review published overviews, reports; contact centers that produce aids  Is there a demand for decision aids and what methods are preferred?  Conduct market surveys (81)  2. Is it feasible to develop a decision aid?  Are there adequate resources?  Assess finances, availability of experts with credibility, networks, and commitment to ongoing update; link to established overview and dissemination networks  Is there enough evidence of benefits and risks to incorporate into a decision aid?  Review systematic overviews with appraisals of the quality of evidence  How quickly is the evidence expected to change?  Review ongoing trials  Will aid be accessible or acceptable to users?  Conduct focus groups or market surveys  3. What are the objectives of the decision aid?  Objectives focused on improved decision making  Improve knowledge of the clinical problem, options, outcomes, and variation in patient or practitioner opinions and practices.    Create realistic expectations of outcomes, consistent with available evidence.    Clarify personal values for outcomes and promote congruence between patients' values and choice.    Reduce patients' and practitioners' decisional conflict (uncertainty) about the course of action to take.    Promote implementation of choices.    Improve patients' or practitioners' satisfaction with decision making.  Objectives focused on outcomes of decision  Promote patients' persistence with choice.    Reduce patients' distress from consequences of decision.    Improve patients' health-related quality of life. Promote informed use of resources by patients and practitioners.  4. Which framework will drive its development?    Charles et al. (13) distinguish shared decision making from other decision-making approaches.    Entwistle et al. (18, 19) define evidence-informed choice and outline different criteria for evaluations depending on objective.    The Hershey et al. framework (15) developed for AHCPR has a health services and informatics perspective.    The Llewellyn-Thomas framework (14) has a special focus on types of preferences and placement in sociopolitical context.    Mulley (16) places shared decision making in the context of outcomes research.    Ottawa Decision Support Framework (12) prepares practitioner and patient and has a clinical and behavioral focus.    Rothert et al. (8, 17) describe mutual roles of patients and practitioners in decision making; they focus on information and values.  5. Which methods will be included in the decision aid?  Patient or client decision support  Information regarding options and outcomes    • Content: clinical problem, options, outcomes    • Detail in describing outcomes: define outcomes; describe physical, emotional, social effect; use narrative/scenario styles    • Probabilities: none; numerical frequencies or percents (7), graphic pie charts (6), 100 people (4, 12), qualitative (low, moderate, high)    • Tailored probabilities: not tailored; stratified by personal risk factors    • Evidence for statements: references included or not    Values clarification    • Implicit (4, 6 )    • Explicit methods such as weigh scale exercise (7), treatment trade-off task (82), relevance chart (8), decisional balance sheets (83), formal utility assessments (5, 9)    Information on others    • None    • Cases of different choices (4, 8, 12)    • Statistics on variation in patients' decisions or practitioners' opinions     Coaching or guidance in deliberation, communication, and implementation    • Not included    • Steps in weighing the benefits or risks (8, 12)    • Steps in discussing decision with a practitioner (8, 12)    • Tips on managing consequences of choices    Delivery (personal counseling supplemented by)    • Generic tools    • Decision board (6)    • Take home audio-guided workbook (7)    • Interactive videodisc or linear video (4)    • Computer-based tool (70)    • Group lecture or workshop (18)  Practitioner decision support  Content: scientific evidence regarding decision, rationale for decision aid, efficacy of decision aid, timing and use in practice, scientific references    Delivery: manual, video, lecture, workshop, hot line, academic detailing  6. Which designs and measures will be used to develop and evaluate decision aid?  Development panel  Participants (researchers, clinicians, educators, patients, opinion leaders)    Methods (iterations of drafts, feedback, revisions, feedback, etc.)  Review panels  Participants (potential users: practitioners, patients who have already made decisions)    Methods (focus groups, personal interviews, questionnaires to elicit acceptability, etc.)  Pilot studies  Participants (patients at the point of decision making)    Designs*    XO XO: test-retest 2 weeks apart (stability of preferences and reliability of measures)    OXO: before/after study uses baseline questionnaire, decision aid, or posttest questionnaire    XO: posttest only, usually with preestablished criteria for success (e.g., 70% on knowledge test)  Trials  Participants (patients at point of decision making, practitioners)    Designs*    Quasi experiment OCO OXO    Randomized trial (with unit of randomization either the patient or practitioner) ROXO ROCO  What are the criteria for evaluation?   Knowledge  Knowledge or comprehension test (4, 7, 8, 47)   Expectations of outcomes  Probability scales (7, 84-87), likelihood scales (26)   Clarity of values  Values subscale of Decisional Conflict Scale (7, 36, 68)   Agreement between choice and values  Statistical relationship between values and choices ( 5, 7, 12, 58, 59, 67, 68)   Realistic perceptions of others  Perceptions of percentage of practitioners or patients choosing options; subjective norms (26)   Decision  Choice question (option x, option y, unsure); choice predisposition (7)   Decisional conflict  Decisional conflict scales for patients (7, 36, 88) and providers (89)   Skill in decision making  Self-efficacy scale (8, 88), implementation data   Satisfaction with decision making  Decision satisfaction inventory (4); satisfaction with decision (8, 90); satisfaction with preparation for decision making (O'Connor A, et al.: unpublished data)   Acceptability  Acceptability questionnaires—shared decision-making tool (42-45), Ottawa tool (68)   Use of decision aid  Utilization data   Participation according to needs  Congruence between preferred and actual role in decision making (91, 92)   Persistence with decisions  Survey of decision over time; implementation data   Reduced distress from outcomes  Condition-specific symptom and side effects distress scales   Health-related quality of life  Generic, condition-specific, preference-based   Use of resources  Analysis of utilization data   Costs  See the Hersey et al. (15) framework and the Nease and Owens (94) cost-effectiveness model  7. How should the decision aid be disseminated (74)?  What are potential adopters: attitudes toward innovation or change; knowledge, attitudes, and skills to use aid; preference for shared decision making?  Conduct focus groups, key informant interviews, environmental scans, or surveys of potential users  What are the environmental barriers and supporters?  Conduct focus groups or surveys to identify the following factors:    • Social (likely supporters and opposers; presence of opinion leaders as supporters; predominant belief system regarding shared decision making)    • Structural (operational tools and processes, regulations, quality assurance criteria, to encourage or hinder use of aid; resources to support dissemination of aid)    • Other incentives and disincentives  Will the evidence-based innovation meet expectations of target audience?  Conduct focus groups or surveys  Which transer strategies should be used?  Tailor strategies according to needs; diffusion strategies (advertisements, publications, or Internet); dissemination strategies (targeted mailings); implementation strategies (education programs or administrative changes)  Is the aid being adopted, and is it having the expected effect on outcomes?  Analyze databases; conduct quality assurance studies, surveys, and implementation studies to determine whether the aid is being used by the expected audience in the expected manner and whether it is having the expected effect on health and economic outcomes and evidence-based decision making among patients or clinicians  * C = control intervention; O = observation of effect; R = randomization; X = decision aid intervention. View Large Table 6. Stages of “Research to Policy” by Lomas (75) applied to shared patient decision making Stages and issues   Progress to November 1998   Hypothesis generation—shared patient decision making is valued  Preference for shared decision making varies by patient characteristics and type of decisions (77-79)    Patients desiring shared decision making do not always have the opportunity (80)    Some evidence that oncologists endorse the concept (81)  Methods development—to elicit patient values and present risk-benefit information  Issues confirmed by AHCPR report (15) and Entwistle et al. (18) paper    Several methods studies completed (Table 4)  Causal model or “theory”—lack of patient involvement leads to “ unwanted interventions”  Several frameworks published; hypothesized effects are observed: help uncertain, base decisions on improved knowledge, realistic expectations, and personal values; effect on satisfaction variable; trend toward reduced preference for more intensive therapies  Study-specific evaluation (efficacy)—randomized trials under ideal controlled decisions  Seven trials show decision aids improve the quality of decisions and show trend in affecting decisions; several trials in progress in the United States, the United Kingdom, Canada, and The Netherlands  Knowledge summary and synthesis  Annotated bibliography (40,41), AHCPR report (15), and Cochrane systematic overview in progress (11)  Results communication—to providers or patients, media, journals, etc.  Conferences, workshops or journals; shared decision-making concept has ben discussed in media (e.g., National Press, magazines, local press, and television)  Application to policy world—what are the barriers to using decision aids under different health care funding and organizational arrangements?  Improving access: Canadian National Forum on Health identified the need to engage public in decision making regarding personal health and to improve access of providers and public to evidence-based information. Funding allocated to improve information systems. U.K. Kings Fund on Informed Choice launched. Some decision aids in hands of providers and consumers  Application in policy world—details of implementing shared patient decision making for specific jurisdiction, institution, or even practitioner  Practice policies: Canadian and U.S. practice guidelines beginning to identify role of patient preferences for some decisions (breast cancer surgery, hormone therapy). Canadian and U.S. nongovernmental agencies have endorsed some of the decision aids and are disseminating information on them    Funding development, evaluation, updating, and dissemination: issue unresolved    Standards for decision aids: issue unresolved: evidence-based, sponsorship, expiration dates    Regulating/legislating use under certain conditions: several states have legislated that women with breast cancer should be offered mastectomy or lumpectomy options. Canada has a practice guideline. Institute for Clinical Evaluative Sciences atlas confirms practice variation in mastectomy or lumpectomy use.    U.S. National Committee on Quality Assurance expands criteria to include quality of counseling on options that incorporates personal risk and preferences    Service delivery: U.S. Foundation for Informed Medical Decision Making delivering decision support services for third-party payers  Stages and issues   Progress to November 1998   Hypothesis generation—shared patient decision making is valued  Preference for shared decision making varies by patient characteristics and type of decisions (77-79)    Patients desiring shared decision making do not always have the opportunity (80)    Some evidence that oncologists endorse the concept (81)  Methods development—to elicit patient values and present risk-benefit information  Issues confirmed by AHCPR report (15) and Entwistle et al. (18) paper    Several methods studies completed (Table 4)  Causal model or “theory”—lack of patient involvement leads to “ unwanted interventions”  Several frameworks published; hypothesized effects are observed: help uncertain, base decisions on improved knowledge, realistic expectations, and personal values; effect on satisfaction variable; trend toward reduced preference for more intensive therapies  Study-specific evaluation (efficacy)—randomized trials under ideal controlled decisions  Seven trials show decision aids improve the quality of decisions and show trend in affecting decisions; several trials in progress in the United States, the United Kingdom, Canada, and The Netherlands  Knowledge summary and synthesis  Annotated bibliography (40,41), AHCPR report (15), and Cochrane systematic overview in progress (11)  Results communication—to providers or patients, media, journals, etc.  Conferences, workshops or journals; shared decision-making concept has ben discussed in media (e.g., National Press, magazines, local press, and television)  Application to policy world—what are the barriers to using decision aids under different health care funding and organizational arrangements?  Improving access: Canadian National Forum on Health identified the need to engage public in decision making regarding personal health and to improve access of providers and public to evidence-based information. Funding allocated to improve information systems. U.K. Kings Fund on Informed Choice launched. Some decision aids in hands of providers and consumers  Application in policy world—details of implementing shared patient decision making for specific jurisdiction, institution, or even practitioner  Practice policies: Canadian and U.S. practice guidelines beginning to identify role of patient preferences for some decisions (breast cancer surgery, hormone therapy). Canadian and U.S. nongovernmental agencies have endorsed some of the decision aids and are disseminating information on them    Funding development, evaluation, updating, and dissemination: issue unresolved    Standards for decision aids: issue unresolved: evidence-based, sponsorship, expiration dates    Regulating/legislating use under certain conditions: several states have legislated that women with breast cancer should be offered mastectomy or lumpectomy options. Canada has a practice guideline. 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