Literature DB >> 20074429

The impact of a physician-directed health information technology system on diabetes outcomes in primary care: a pre- and post-implementation study.

Jacquelyn S Hunt1, Joseph Siemienczuk, William Gillanders, Benjamin H LeBlanc, Yelena Rozenfeld, Kerry Bonin, Ginger Pape.   

Abstract

PURPOSE: To determine the impact of a physician-directed, multifaceted health information technology (HIT) system on diabetes outcomes.
METHODS: A pre/post-interventional study. SETTING AND PARTICIPANTS: The setting was Providence Primary Care Research Network in Oregon, with approximately 71 physicians caring for 117 369 patients in 13 clinic locations. The study covered Network patients with diabetes age 18 years and older. INTERVENTION: The study intervention included implementation of the CareManager HIT system which augments an electronic medical record (EMR) by automating physician driven quality improvement interventions, including point-of-care decision support and care reminders, diabetes registry with care prompts, performance feedback with benchmarking and access to published evidence and patient educational materials. MEASURES: The primary clinical measures included the change in mean value for low density lipoprotein (LDL) target <100 mg/dL or 2.6 mmol/l, blood pressure (BP) target <130/80 mmHg and glycated haemoglobin (HbA1c) target <7%, and the proportion of patients meeting guideline-recommended targets for those measures. All measures were analysed using closed and open cohort approaches.
RESULTS: A total of 6072 patients were identified at baseline, 70% of whom were continuously enrolled during the 24-month study. Significant improvements were observed in all diabetes related outcomes except mean HbA1c. LDL goal attainment improved from 32% to 56% (P=0.002), while mean LDL decreased by 13 mg/dL (0.33 mmol/l, P=0.002). BP goal attainment increased significantly from 30% to 52%, with significant decreases in both mean systolic and diastolic BP. The proportion of patients with an HbA1c below 7% was higher at the end of the study (P=0.008). Mean patient satisfaction remained high, with no significant difference between baseline and follow-up. Total Relative Value Units per patient per year significantly increased as a result of an increase in the number of visits in year one and the coding complexity throughout.
CONCLUSION: Implementation of a physician-directed, multifaceted HIT system in primary care was associated with significantly improved diabetes process and outcome measures.

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Year:  2009        PMID: 20074429     DOI: 10.14236/jhi.v17i3.731

Source DB:  PubMed          Journal:  Inform Prim Care        ISSN: 1475-9985


  16 in total

1.  Using Arden Syntax to identify registry-eligible very low birth weight neonates from the Electronic Health Record.

Authors:  Indra Neil Sarkar; Elizabeth S Chen; Paul T Rosenau; Matthew B Storer; Beth Anderson; Jeffrey D Horbar
Journal:  AMIA Annu Symp Proc       Date:  2014-11-14

Review 2.  Review of electronic decision-support tools for diabetes care: a viable option for low- and middle-income countries?

Authors:  Mohammed K Ali; Seema Shah; Nikhil Tandon
Journal:  J Diabetes Sci Technol       Date:  2011-05-01

3.  Diabetes Self-management Education and Support in Type 2 Diabetes: A Joint Position Statement of the American Diabetes Association, the American Association of Diabetes Educators, and the Academy of Nutrition and Dietetics.

Authors:  Margaret A Powers; Joan Bardsley; Marjorie Cypress; Paulina Duker; Martha M Funnell; Amy Hess Fischl; Melinda D Maryniuk; Linda Siminerio; Eva Vivian
Journal:  Clin Diabetes       Date:  2016-04

4.  Implementation of an electronic medical record does not change delivery of preventive care for HIV-positive patients.

Authors:  Andrew E Petroll; Jenise K Phelps; Kathlyn E Fletcher
Journal:  Int J Med Inform       Date:  2013-12-27       Impact factor: 4.046

5.  Systematic Review and Meta-analysis of the Effectiveness of Implementation Strategies for Non-communicable Disease Guidelines in Primary Health Care.

Authors:  Eva Kovacs; Ralf Strobl; Amanda Phillips; Anna-Janina Stephan; Martin Müller; Jochen Gensichen; Eva Grill
Journal:  J Gen Intern Med       Date:  2018-05-04       Impact factor: 5.128

6.  Personalized decision support in type 2 diabetes mellitus: current evidence and future directions.

Authors:  Michael J Wilkinson; Aviva G Nathan; Elbert S Huang
Journal:  Curr Diab Rep       Date:  2013-04       Impact factor: 4.810

7.  Translating What Works: A New Approach to Improve Diabetes Management.

Authors:  Lawrence S Phillips; Diana Barb; Chun Yong; Anne M Tomolo; Sandra L Jackson; Darin E Olson; Mary K Rhee; Ingrid M Duva; Qing He; Qi Long
Journal:  J Diabetes Sci Technol       Date:  2015-03-09

8.  Effects of benchmarking on the quality of type 2 diabetes care: results of the OPTIMISE (Optimal Type 2 Diabetes Management Including Benchmarking and Standard Treatment) study in Greece.

Authors:  Vasilis Tsimihodimos; Michael S Kostapanos; Alexandros Moulis; Nikos Nikas; Moses S Elisaf
Journal:  Ther Adv Endocrinol Metab       Date:  2015-10       Impact factor: 3.565

9.  The danish model for improvement of diabetes care in general practice: impact of automated collection and feedback of patient data.

Authors:  Henrik Schroll; René Depont Christensen; Janus Laust Thomsen; Morten Andersen; Søren Friborg; Jens Søndergaard
Journal:  Int J Family Med       Date:  2012-07-24

Review 10.  The role of Decision Support System (DSS) in prevention of cardiovascular disease: a systematic review and meta-analysis.

Authors:  Raghupathy Anchala; Maria P Pinto; Amir Shroufi; Rajiv Chowdhury; Jean Sanderson; Laura Johnson; Patricia Blanco; Dorairaj Prabhakaran; Oscar H Franco
Journal:  PLoS One       Date:  2012-10-10       Impact factor: 3.240

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