Access the full text.
Sign up today, get DeepDyve free for 14 days.
S. Shea, W. DuMouchel, L. Bahamonde (1996)
A meta-analysis of 16 randomized controlled trials to evaluate computer-based clinical reminder systems for preventive care in the ambulatory setting.Journal of the American Medical Informatics Association : JAMIA, 3 6
(2002)
Interventions that increase use of adult immunization and cancer screening services: a meta-analysis
C. Jarque, Anil Bera (1980)
Efficient tests for normality, homoscedasticity and serial independence of regression residualsEconomics Letters, 6
Stephen Persell, D. Kaiser, N. Dolan, B. Andrews, Sue Levi, J. Khandekar, T. Gavagan, Jason Thompson, Elisha Friesema, D. Baker (2011)
Changes in Performance After Implementation of a Multifaceted Electronic-Health-Record-Based Quality Improvement SystemMedical Care, 49
K. Kawamoto, C. Houlihan, A. Balas, D. Lobach (2005)
Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to successBMJ : British Medical Journal, 330
(2009)
Tseries: time series analysis and computational finance. R Package Version 0.10-18
P. Tang, Mary Ralston, Michelle Arrigotti, Lubna Qureshi, Justin Graham (2007)
Research Paper: Comparison of Methodologies for Calculating Quality Measures Based on Administrative Data versus Clinical Data from an Electronic Health Record System: Implications for Performance MeasuresJournal of the American Medical Informatics Association : JAMIA, 14 1
S. Shapiro, M. Wilk (1965)
An Analysis of Variance Test for Normality (Complete Samples)Biometrika, 52
L. Hicks, T. Sequist, J. Ayanian, S. Shaykevich, D. Fairchild, E. Orav, D. Bates (2008)
Impact of Computerized Decision Support on Blood Pressure Management and Control: A Randomized Controlled TrialJournal of General Internal Medicine, 23
D. Hunt, R. Haynes, S. Hanna, Kristin Smith (1998)
Effects of computer-based clinical decision support systems on physician performance and patient outcomes: a systematic review.JAMA, 280 15
B. Chaudhry, Jerome Wang, Shinyi Wu, M. Maglione, W. Mojica, E. Roth, S. Morton, P. Shekelle (2006)
Systematic Review: Impact of Health Information Technology on Quality, Efficiency, and Costs of Medical CareAnnals of Internal Medicine, 144
T. Sequist, T. Gandhi, A. Karson, J. Fiskio, Donald Bugbee, M. Sperling, E. Cook, E. Orav, D. Fairchild, D. Bates (2005)
A randomized trial of electronic clinical reminders to improve quality of care for diabetes and coronary artery disease.Journal of the American Medical Informatics Association : JAMIA, 12 4
E. Kerr, Dylan Smith, M. Hogan, S. Krein, L. Pogach, T. Hofer, R. Hayward (2002)
Comparing clinical automated, medical record, and hybrid data sources for diabetes quality measures.The Joint Commission journal on quality improvement, 28 10
Wilk Mb, R. Gnanadesikan (1968)
Probability plotting methods for the analysis of data.Biometrika, 55 1
Stephen Persell, N. Dolan, Elisha Friesema, Jason Thompson, D. Kaiser, D. Baker (2010)
Frequency of Inappropriate Medical Exceptions to Quality MeasuresAnnals of Internal Medicine, 152
M. Wilk, R. Gnanadesikan (1968)
Probability plotting methods for the analysis for the analysis of dataBiometrika, 55
H. Akaike (1974)
A new look at the statistical model identificationIEEE Transactions on Automatic Control, 19
E. Rogers (1964)
Diffusion of innovationsEncyclopedia of Sport Management
AbstractObjective We have reported that implementation of an electronic health record (EHR) based quality improvement system that included point-of-care electronic reminders accelerated improvement in performance for multiple measures of chronic disease care and preventive care during a 1-year period. This study examined whether providing pre-visit paper quality reminders could further improve performance, especially for physicians whose performance had not improved much during the first year.Design Time-series analysis at a large internal medicine practice using a commercial EHR. All patients eligible for each measure were included (range approximately 100–7500).Measurements The proportion of eligible patients in the practice who satisfied each of 15 quality measures after removing those with exceptions from the denominator. To analyze changes in performance for individual physicians, two composite measures were used: prescribing seven essential medications and completion of five preventive services.Results During the year after implementing pre-encounter reminders, performance continued to improve for eight measures, remained stable for four, and declined for three. Physicians with the worst performance at the start of the pre-encounter reminders showed little absolute improvement over the next year, and most remained below the median performance for physicians in the practice.Conclusions Paper pre-encounter reminders did not appear to improve performance beyond electronic point-of-care reminders in the EHR alone. Lagging performance is likely not due to providers' EHR workflow alone, and trying to step backwards and use paper reminders in addition to point-of-care reminders in the EHR may not be an effective strategy for engaging slow adopters.
Journal of the American Medical Informatics Association – Oxford University Press
Published: Nov 9, 2011
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.