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Introduction: Continuity of care by family physicians in primary care settings may play a role in reducing health resource utilization and improving clinical outcomes andsatisfactionof patients withchronic obstructivepulmonary disease. Clear evi- dence on the impact of continuity of care will support clinical programing and integration of services across health settings. Methods: The association between continuity of care and unplanned health service utilization in persons with a diag- nosis of chronic obstructive pulmonary disease in a rural region in Ontario, Canada was evaluated. A retrospective cohort study was conducted using population-level health administrative data. The main exposure variable was con- tinuity of care. Results: A continuity of care index was calculated for patients with at least ﬁve visits to a healthcare provider during the 5-year follow-up period (n = 40,033). Higher continuity of care (n = 20,008) and lower continuity of care (n = 20,025), based on the median continuity of care score were calculated. Patients with lower continuity of care had an increased adjusted relative risk of 2.12 (2.08, 2.33) of an emergency department visit, 2.81 (2.72, 2.9) risk of hos- pitalization, and 3.52 (3.24, 3.82) of being readmitted to hospital compared to those with higher continuity of care. Discussion: An association between continuity of care and unplanned health services utilization, where a lower use of unplanned health services was observed in the cohort of patients with chronic obstructive pulmonary disease experiencing higher continuity of care. Continuity of care makes philosophical and social sense in that care is pro- vided by a known provider to a known patient and unnecessary investigations can be avoided. Keywords Continuity of care, chronic obstructive airway disease, longitudinal study, mortality, disease management those with COPD compared to 8.2 per 1000 for those Introduction without COPD in Canada. Chronic obstructive pulmonary disease (COPD) is a Effective COPD management aims to prevent disease chronic lung disease characterized by ongoing airﬂow lim- progression, relieve symptoms, improve exercise tolerance itation with respiratory symptoms. COPD is common, pre- and health status, as well as prevent and treat complications ventable, and treatable. Known causes include sustained 3 and exacerbations. This is achieved through proper exposure to noxious gases, such as cigaret smoke and environmental pollutants. The international organization Global Initiative for Chronic Obstructive Lung Disease esti- School of Nursing, Queen’s University, Kingston, Ontario, Canada mates the prevalence worldwide at over 6%, while the Department of Chemical Engineering, Queen’s University, Kingston, ON, Canadian Chronic Disease Surveillance System (CCDSS) Canada reported a prevalence of 9.4% in the population of adults Quinte Health Care, Belleville, ON, Canada over the age of 35 in 2011–2012. COPD contributes to Institute for Clinical Evaluative Sciences, Queen’s University, Toronto, Ontario, Canada the highest rates of hospital admissions among major chronic illnesses and to the death of approximately 3 Corresponding author: million people globally. The Canadian Chronic Disease Jennifer Medves, Queen’s University, 92 Barrie Street, Kingston, ON K7L Surveillance System reported the age standardized all- 3N6, Canada. cause mortality rates in 2011–2012 was 22.2 per 1000 for Email: email@example.com 40 International Journal of Care Coordination 25(1) assessment and monitoring of the disease, reduction of risk associated with lower hospitalization with those who have 18,19 factors, and management of a stable COPD as well as diabetes. As such, poor (or lack of) continuity of care exacerbations. Care for patients with COPD is provided often translates into higher unplanned health services utili- in large part by family physicians in the primary care zation in the acute care setting (admissions and readmis- setting and by specialists, with patients receiving the most sions), with added costs to the health system and to the 4 20 appropriate level of care from this team of providers. patient’s quality of life. Despite advances in medical care and implementation of Therefore, the overall goal of this study was to determine national disease management guidelines, barriers such as the association between COC and unplanned health service uti- geographic distance, specialist access, and poor care coord- lization in persons with a diagnosis of COPD. Focus of the ination inﬂuence the provision of care and leads to differ- study was on one region in southeastern Ontario (Local ences in outcomes for this population of patients. Health Integration Network) as there was concern raised by Patients with chronic illnesses beneﬁt from consistent regional health system planners about high emergency use care by the same care provider or team of providers in and hospitalization rates for patients with COPD. Information primary care. Even with known treatments, the progressive was needed to inform the planning of regional health services. nature of chronic illnesses necessitates a continuous and coordinated care approach. Care coordination has been Methods extensively studied, as it a crucial element of and support for patient-centered quality care. While deﬁnitions of care This population-based retrospective cohort was conducted coordination vary between studies, a review of literature using de-identiﬁed Ontario administrative datasets held by by Schultz & McDonald identiﬁed ﬁve important themes ICES. Ontario represents over 38% of Canada’s population, that describe care coordination: “care coordination (1) with 13.45 million Ontarians on May 10, 2016. In involves numerous participants, (2) is necessitated by inter- Ontario, COPD prevalence has increased steadily in past dependence among participants and activities, (3) requires years to reach 9.5% in 2007 (male and females combined; knowledge of others’ roles and resources, (4) relies on all age groups combined), with females bearing the information exchange, and (5) aims to facilitate appropriate largest increase. healthcare delivery. ” When implemented within and This study focused on the South East Local Health across health settings, care coordination supports seamless Integration Network (LHIN) region, which includes the sub- interactions between providers across multiple settings, regions of Quinte, Rural Hastings, Rural Frontenac, Lennox and therefore facilitates continuity of care. & Addington, Kingston, and Lanark, and Leeds & Grenville. Continuity of care, especially in the context of primary The South East LHIN is home to approximately 496,400 care, is characterized as care over time with a particular people, or 3.6% of the Ontario population. Forty-ﬁve patient that is consistent, patient focused, and encompasses percent of the population lives in a rural area and a quarter 8–11 23 both health and illness. In the context of chronic disease of the population in a large urban center. The South East management though, continuity of care can be “seen as the LHIN has the highest proportion of seniors in Ontario, with delivery of services by different providers in a coherent, 21% of residents of the South East LHIN aged >65 years. 8,12,13 logical, and timely fashion.” In this study using Relative to the province, the South East LHIN has a lower administrative data, continuity of care was measured rate of population growth now and projected over the next using the Bice-Boxerman’s Concentration of Care Index 20 years, a lower proportion of immigrants (8.5% vs (COC) that captured the care across different providers 28.5% in Ontario), and a lower proportion of visible minorities as well as the care coordination back to the family physi- (3% vs 26% in Ontario). In comparison to Ontario, the South cian. This index was shown to accurately measure the dis- East LHIN has a higher prevalence of people who are over- 15 23 persion and concentration of care in similar studies. weight or obese and reporting activity limitations. Continuity of care is a key component of quality health The cohort included all patients residing within the care. A comprehensive systematic review of literature of 22 South East LHIN region with a diagnosis of COPD as of studies concluded that an increase in continuity of care by April 1, 2013. Individuals meeting the following criteria doctors was associated with lower mortality rates. This were included in the study cohort: 1) age 35 to 99 years observation was also reported by Maarsingh et al. in a and living in Ontario; 2) diagnosed with COPD on or robust 17-year prospective study in the Netherlands, prior to April 1, 2013; 3) residing within the South East where mortality was increased by 20% for those with the Local Health Integration Network region; 4) valid Ontario lowest level of continuity of care compared to those with health card number for the duration of the 5-year follow-up the highest level. Continuity of care by family physicians period; and 5) at least one health care interaction (emer- is associated with a lower number of hospital admissions gency department visit, hospitalization or physician visit) for ambulatory care sensitive conditions and this effect during the 5-year follow-up period. Individuals with was stronger for patients who were considered heavy COPD were identiﬁed using a case deﬁnition algorithm of users of primary care. Continuity of care has also been 1 or more physician billing claims and/or 1 or more hospital Medves et al. 41 discharges with a diagnosis of COPD as per the following into the cohort for which a continuity of care (COC) codes: 491, 492, 496 (Ontario Health Insurance Plan and index was calculated. Individuals were assigned to the International Classiﬁcation of Diseases, Ninth Revision higher or lower continuity of care sub-group based on codes) or J41, J42, J43, J44 (International Statistical their individual COC score relative to the median continuity Classiﬁcation of Diseases, 10th Revision codes). The of care index (individual score > median COC for the popu- cohort was then followed for ﬁve years (April 1, 2013 to lation = higher COC group). As presented in Table 1, the March 31, 2018). Demographic characteristics, socioeco- demographic and clinical characteristics of patients in the nomic status, and comorbidities were determined for lower and higher COC populations were similar for age descriptive purposes and used as covariates in modeling. (M = 66.56, SD = 12.82) for the lower COC vs 65.50 The following databases were linked to provide the (SD = 12.40) for higher COC, for the proportion of required data: Hospital Discharge Abstract Database, females (52.6% for lower COC vs 55.4% for higher National Ambulatory Care Reporting System, ICES- COC), socioeconomic status, and the average time that derived COPD cohort, Ontario Health Insurance Plan patients had been diagnosed with COPD prior to the start Claims Database, Ontario Marginalization Index, Postal of the study (M = 9.58 years, SD = 6.54) for the lower Code Conversion File, and Registered Persons Database. COC group vs 9.61 (SD = 6.47) year for the higher COC COC was calculated using billing codes for any outpati- group). Both groups also had similar proportion of patients ent family physician and specialty (respiratory and internal with concurrent asthma, diabetes and hypertension. In con- medicine) visits over the 5-year observation window and trast, the distribution of patients enrolled in the various excluding participants who had less than 5 visits. As well, primary care models and their distribution in relation to analysis was performed to identify the usual provider of the distance to their usual provider of care were different, care (UPC). The UPC reﬂects the concentration of care as was the rate of residential instability (M = 3.50, SD = with a single provider or group of providers across time. 1.24 for lower COC vs 3.42 (SD = 1.23) for higher COC UPC was measured by using the highest number of visits group). In addition, the proportion of patients admitted to to a single practitioner or a group of practitioner and then long-term care during the 5-year study window was statisti- divided by the total number of visits. cally signiﬁcantly different (1.0% for the lower COC vs A cross-tabulations and descriptive statistics for the base- 4.2% in the higher COC; standardized difference = 0.21), line characteristics of the study cohort was conducted. as was the risk of dying during the 5-year study period Dichotomous data is presented as N and percentage; continu- (26.8% in the lower COC vs 12.6% in the higher COC ous variables are presented as mean with standard deviation. group; standardized difference = 0.36). Further analyses Generalized linear models were used to estimate the risk were performed to better understand the large difference ratio between continuity of care and each study outcome observed in death rate between the two groups (see Table 3). (ER visits, hospital admission and readmission). Standardized differences were calculated and represent Health services utilization for adults with COPD the difference in mean outcome between groups divided with lower and higher COC by the standard deviation of outcome among participants and is considered signiﬁcant when ≥ 0.1. Standardized dif- Statistically signiﬁcant differences were observed in the ferences were used as they better represent differences of measured utilization of healthcare services. As reported in clinical relevance when analysing very large datasets. Table 2, patients with lower COC were 2.12 times (95% The full adjusted models included all available variables: CI 2.08, 2.16) more likely to visit the emergency depart- age, sex, income quintile, socioeconomic status, material ment (for any reasons), 2.81 times (95% CI 2.72, 2.9) deprivation quintile, rural/urban residence, and comorbidity more likely to be admitted to hospital (for any reason), (major ADGs). and 3.52 times (CI 3.24, 3.82) more likely to be readmitted All analyses were conducted using SAS©. This study to hospital within 30 days of discharge, compared to those received ethics clearance from the Queen’s University experiencing higher COC. Health Sciences and Afﬁliated Hospitals Research Ethics Board (NURS-472-19). Characteristics of adults with COPD who died during follow-up period Results Further to the observation that the death rate of the cohort was statistically different between those who had lower Demographic and clinical characteristics COC compared to higher COC (Table 1), additional ana- of the study cohort lyses were conducted to identify potential differences As of 2013, there were 42,916 adults with COPD residing between the two groups who died [lower COC = 5313 in the South East LHIN. Of those, 40,033 had at least ﬁve patients, higher COC = 2023 patients] (Table 3). Overall, visits to a healthcare provider and were therefore entered fewer patients within the lower COC group were never 42 International Journal of Care Coordination 25(1) Table 1. Demographic and clinical characteristics of the study cohort of adult patients with COPD as of April 1, 2013 and residing within the south east LHIN region and experiencing lower or higher continuity of care (COC). Lower COC Higher COC N of patients = N of patients = Standardized Characteristics 20,025 20,008 P-Value difference* Age Mean ± SD 66.56 ± 12.82 65.50 ± 12.40 <.001 0.08 Median (IQR) 66 (57–76) 65 (56–74) <.001 0.09 Age groups (N (%)) 31–40 282 (1.4%) 222 (1.1%) <.001 41–50 2051 (10.2%) 2068 (10.3%) 51–64 6552 (32.7%) 7410 (37.0%) 65+ 11,140 (55.6%) 10,308 (51.5%) Sex (N (%)) F 10,539 (52.6%) 11,092 (55.4%) <.001 0.06 M 9486 (47.4%) 8916 (44.6%) 0.06 Time from diagnosis to entry to cohort (mean in years 9.58 ± 6.54 9.61 ± 6.47 0.696 0 ± SD) Admitted to Long-Term Care (N (%) 195 (1.0%) 849 (4.2%) <.001 0.21 Death during 5-year follow-up period (N (%)) 5367 (26.8%) 2529 (12.6%) <.001 0.36 Socioeconomic status (DA factor score) (mean ± SD) 1. Dependency 4.03 ± 1.14 4.06 ± 1.12 0.012 0.03 2. Material deprivation 3.40 ± 1.34 3.31 ± 1.34 <.001 0.07 3. Ethnic concentration 1.56 ± 0.82 1.56 ± 0.80 0.594 0.01 4. Residential instability 3.50 ± 1.24 3.42 ± 1.23 <.001 0.06 Income quintile (N (%)) 1 5779 (29.0%) 5453 (27.4%) 0.002 0.04 2 4521 (22.7%) 4647 (23.3%) 0.02 3 3663 (18.4%) 3694 (18.6%) 0 4 3552 (17.8%) 3545 (17.8%) 0 5 (highest) 2402 (12.1%) 2566 (12.9%) 0.03 ADG comorbidity score (N (%)) 0 317 (1.6%) 248 (1.2%) <.001 1–4 4199 (21.0%) 5136 (25.7%) 5–9 8656 (43.2%) 9627 (48.1%) 10+ 6853 (34.2%) 4997 (25.0%) Asthma as a comorbidity N (%)) 5947 (29.7%) 5256 (26.3%) 0.08 Diabetes as a comorbidity (N (%)) 5079 (25.4%) 4634 (23.2%) 0.05 Hypertension as a comorbidity (N (%)) 11,742 (58.6%) 11,699 (58.5%) 0 Rural status (N (%)) Urban 10,893 (54.4%) 10,722 (53.6%) 0.105 0.02 Rural 9132 (45.6%) 9286 (46.4%) 0.02 Primary health patient enrollment model (N (%)) Capitation (FHN, FHO) 6870 (34.4%) 7561 (37.8%) <.001 0.07 Comprehensive care model 738 (3.7%) 1105 (5.5%) 0.09 Family health group 1463 (7.3%) 1911 (9.6%) 0.08 Family health team 9273 (46.4%) 8261 (41.3%) 0.1 Physician not in PEM 864 (4.3%) 816 (4.1%) 0.01 No physician** 785 (3.9%) 332 (1.7%) 0.14 Distance to usual provider of care in km N (%)) 0–49 17,377 (87.0%) 18,818 (94.2%) <.001 50–99 1333 (6.7%) 614 (3.1%) 100–149 397 (2.0%) 184 (0.9%) 150+ 865 (4.3%) 363 (1.8%) *Standardized difference represents the difference in mean outcome between groups divided by the standard deviation of outcome among participants (Higgins et al. 2019) and is considered signiﬁcant when≥ 0.1. **Patient had no Core Primary Care Fee-codes for 2 years prior to April 1, 2013. Higgins JPT, Li T, Deeks JJ. Chapter 6 Choosing effect measures and computing estimates of effect. In Cochrane Handbook for Systematic Reviews of Interventions 2019 (second ed). Online ISBN: 9781119536604. Medves et al. 43 Table 2. Relative risk of emergency department (ED) visits, and death were analyzed over a ﬁve-year follow-up period. hospital admissions and readmissions for residents of the south Overall, the patients within the lower and higher COC east LHIN during the 5-year follow-up period (April 1, 2013– groups had similar demographic and clinical characteristics, March 31, 2018). but the patients in the lower COC group were signiﬁcantly more likely to die during the follow-up period, to require Relative risk adjusted (95% conﬁdence interval) admission to hospital and readmission within 30 days, had Emergency longer hospital stays, and were less likely to be admitted to Patient department 30-day long-term care. Patients in the lower COC group also lived characteristics visits Admissions readmissions signiﬁcantly further away from their usual care provider. As the South East Local Health Integration Network region Higher 1 (reference) 1 1 boasts the highest proportion of residents living in rural continuity areas of Ontario who cannot rely on a well-developed of care public transportation system, a large proportion of the Lower 2.12 (2.08, 2.16) 2.81 (2.72, 2.9) 3.52 (3.24, 3.82) SELHIN patients must have access to a car and/or drive to continuity of care reach the major community and level 3 hospitals in the south- ern border along Lake Ontario and the St Lawrence River. *Relative risk adjusted includes controlling for sex, age, ADG, It is important to note that while the mortality rate for socioeconomic status, income, rurality and comorbidity. those with COPD was calculated to be approximately 20% over a ﬁve-year period (combined higher and lower admitted during the 5-year follow-up period (55.8% of COC groups; study data), higher continuity of care was patients for the lower COC group were not admitted vs associated with a lower mortality rate. 74.1% of patients in the higher COC group; standardized Continuity of Care is considered a benchmark of quality difference = 0.5053), patients within the lower COC had especially for those with complex health conditions and is a more ER visits that resulted in hospital admission (8.7% goal of primary care, as it has been shown to improve for the lower COC cohort never had to be admitted follow- patient satisfaction, decrease hospitalizations and reduces ing an ER visit vs 31.1% of the higher COC cohort; standar- health care costs. As such, this study provides much dized difference = 0.832), and were more often readmitted needed population-level data to support integrated teams within 30 days (28.3% for the lower COC group were read- of health care providers working to meet individual mitted within 30 days vs 9.2% of patients in the higher COC patient needs and will help in planning improved supports cohort; standardized difference = 0.5). The length of stay for a patient-centric network of care in which providers (and in hospital for the lower COC was also longer (M = 2.83, services) collaborate at the community level to deliver com- SD = 9.86 for lower COC vs 0.69 days (SD = 3.90) for prehensive and seamless care to patients with COPD. This higher COC; standardized difference = 0.29). The distance knowledge may also form a strong basis for the develop- to the usual provider of care was also longer for patients in ment of coordinated care for other chronic conditions. the lower COC cohort (88.4% within 50 km of their provi- Additionally, patients with lower continuity of care were der for the lower COC group vs 96.1% for the higher COC more likely to visit the emergency room, be admitted as a group; standardized difference = 0.3185). In contrast, result of the visit and subsequently require readmission those with lower COC were on average younger (mean within 30 days, suggesting a disconnect or poor transition 74.82 for patients in the lower COC group vs 77.95 years between the acute care setting and subsequent community for patients in the higher COC group; standardized differ- care, to prevent a further exacerbation of COPD. ence = 0.28) and less likely to be admitted to long-term Those with lower COC had a higher rate of residential care (3.0% for the lower COC group vs 21.1% for the instability compared to patients experiencing higher COC. higher COC group; standardized difference = 0.58). It could be hypothesized that those who move more often (higher residential instability) may ﬁnd it more difﬁcult to establish a stable relationship with a new family physician Discussion than those who live in the same place for longer periods The study was undertaken to understand the potential associ- of time. ation between continuity of care experienced by a cohort of It is interesting to note that patients from the higher COC patients diagnosed with chronic obstructive pulmonary group who died within the 5-year follow-up period were on disease (COPD) and living in the South East Local Health average older (median difference four years) and more Integration Network (SELHIN) region, and patterns of likely to be admitted to LTC, which makes sense in that unplanned health services utilization. As such, the demo- they lived long enough to become frail and needing 24-h graphic and clinical characteristics of this population, as nursing care not available in the home. well as the frequency of ED visits, hospital admissions and Finding from this population-level study support the readmission within 30 days, admission to long-term care beneﬁts of providing high continuity of care to patients 44 International Journal of Care Coordination 25(1) Table 3. Study population who died during the 5-year follow-up period (April 1, 2013–March 31, 2018). Lower COC Higher COC Standardized (n = 5313) (n = 2023) P-value difference Number of hospital admissions (for COPD) (N 0 2967 (55.8%) 1500 (74.1%) <.001 0.5053 (%)) 1–5 2183 (41.1%) 520 (25.7%) 6–10 134 (2.5%) <= 5 (0.1%) >10 29 (0.5%) 0 (0.0%) 30-day readmission (N (%)) 1504 (28.3%) 187 (9.2%) <.001 0.5 Length of stay for readmission in days (Mean ± SD) 2.83 ± 9.86 0.69 ± 3.90 <.001 0.29 Number of ER visits with hospital admission (N 0 460 (8.7%) 630 (31.1%) <.001 0.832 (%)) 1–5 4377 (82.4%) 1369 (67.7%) 6–10 393 (7.4%) 23 (1.1%) >10 83 (1.6%) <= 5 (0.0%) Age (years) Mean ± SD 74.82 ± 77.95 ± <.001 0.28 11.16 11.09 Median 76 (67–83) 80 (71–86) <.001 0.29 (IQR) Admitted to long-term care (N (%)) No 5156 (97.0%) 1597 (78.9%) <.001 0.58 Yes 157 (3.0%) 426 (21.1%) Distance to usual provider of care in km (N (%)) 0–49 4687 (88.4%) 1942 (96.1%) <.001 0.3185 50–99 376 (7.1%) 53 (2.6%) 100–149 81 (1.5%) 10 (0.5%) 150+ 157 (3.0%) 15 (0.7%) living with a chronic condition such as COPD, as it reduces signiﬁcantly more often, were admitted and then stayed the relative risk of unplanned health service utilization longer, which can be interpreted that they were more (Emergency Department visits, admissions, and readmis- unstable and required more aggressive treatment for longer sions within 30 days). than those who beneﬁted from higher continuity of care. Shortly after the completion of this study, the option to deliver virtual care by family physician and specialists has Implications for health services delivery been more widely implemented and ﬁnancially supported, in response to the COVID-19 pandemic. As the SELHIN COPD is a disease that requires a combination of self-care region boasts the highest proportion of residents living in management by patients and their families, and disease man- rural areas of Ontario and patients living rurally struggle agement by a variety of healthcare providers, to ensure a good with poorly developed public transportation, there is the pos- quality of life. Care provided by consistent health care provi- sibility that this new care delivery method has improved con- ders or teams of providers who work collaboratively has been tinuity of care for some populations and had an impact on the shown to allow optimal symptom management in the com- provision of urgent and unplanned care for patients living munity, decrease the number of exacerbations of the disease with COPD. Future research would have to account for and minimize unplanned visits to the hospital. those who live at a distance from their care providers may Chronic disease management in general requires careful have better access to care and are less likely to be in a oversight and, if possible, allow for the practitioner to lower continuity of care cohort. With the pandemic in provide a patient-centered and holistic management of the 2020, care models have shifted to virtual model and future patients’ various diseases. Primary care teams of physicians, studies need to assess the best models of continuity in care nurse practitioners, and nurses are ideally set up to provide that are adaptable to virtual/in person hybrid models. this care to patients and their families, and to act as liaison The main strength of the study was the ability to pre- with the acute healthcare system to seamlessly and quickly cisely examine if there was there a difference in emergency transition patients into community care. As such, any room visits, admission to hospital and readmission in their patient admitted to hospital for acute treatment would sub region compared to the rest of the region as the study beneﬁt from transitioning to a team of care providers imme- design and analysis allowed for a follow-up of a speciﬁc diately upon release from the hospital, to ensure an optimal cohort of patients diagnosed with COPD over ﬁve years. disease management in the community, and decrease the Limitations of the study include not having access to pre- number of admissions for COPD. This requires an increased scribed and dispensed medication to the cohort, nor the effort to liaise with the community providers proactively. status on screening for COPD using spirometry, as this It was clearly shown in this cohort that those who lacked data is unavailable. continuity of care accessed the emergency department Medves et al. 45 14. Bice TW and Boxerman SB. A qualitative measure of con- Declaration of conﬂicting interests tinuity of care. Med Care 1977; 15: 347–349. The authors declared no potential conﬂicts of interest with respect 15. Reid RJ, Haggerty JL and McKendry R. Defusing the confu- to the research, authorship, and/or publication of this article. sion: concepts and measures of continuity of healthcare. Canadian Health Services Research Foundation, 2002. Funding 16. Periera Gray D, Sidaway-Lee K, White E, et al. Continuity of care with doctors – A matter of life and death? A systematic The authors disclosed receipt of the following ﬁnancial support for the review of continuity of care and mortality. BMJ Open 2018; research, authorship, and/or publication of this article: This study was 8: e021161. funded by an Ontario Ministry of Health and Long-Term Care 17. Maarsingh O, Henry Y, van de Ven P, et al. Continuity of care (MOHLTC) Applied Health Research Question grant (Project Trim in primary care and association with survival in older people: 2020 0950 052 000). This study was supported by the Institute for a 17-year prospective cohort study. Br J Gen Pract 2016; 66: Clinical Evaluative Sciences (ICES), which is funded by an annual e531–e539. grant from the MOHLTC. The opinions, results and conclusions 18. Manns BJ, Tonelli M, Zhang J, et al. Enrolment in primary reported in this paper are those of the authors and are independent care networks: impact on outcomes and processes of care from the funding sources. No endorsement by ICES or the Ontario for patients with diabetes. CMAJ 2012; 184: E144–E152. MOHLTC is intended or should be inferred. 19. Austin PC, Shah BR, Newman A, et al. Using the johns Hopkins’ aggregated diagnosis groups (ADGs) to predict ORCID iD 1-year mortality in population-based cohorts of patients with diabetes in ontario, Canada. Diabet Med 2011; 29: 1134–1141. 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International Journal of Care Coordination – SAGE
Published: Dec 28, 2021
Keywords: Continuity of care; chronic obstructive airway disease; longitudinal study; mortality; disease management
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