Literature DB >> 22354208

Measures of adherence to oral hypoglycemic agents at the primary care clinic level: the role of risk adjustment.

Edwin S Wong1, John D Piette, Chuan-Fen Liu, Mark Perkins, Matthew L Maciejewski, George L Jackson, David K Blough, Stephan D Fihn, David H Au, Chris L Bryson.   

Abstract

BACKGROUND: Prior research found that in the Veterans Affairs health care system (VA), the proportion of patients adherent to oral hypoglycemic agents varies from 50% to 80% across primary care clinics. This study examined whether variation in patient and facility characteristics determined those differences.
METHODS: Retrospective cohort study of 444,418 VA primary care patients with diabetes treated in 559 clinics in fiscal year (FY) 2006-2007. Patients' adherence to each oral hypoglycemic agent was computed for the first 3 months of FY2007, and averaged across agents to produce an adherence score for the patient's overall regimen. Patients with an adherence score over 0.8 were defined as adherent. Risk adjustment used hierarchical logistic regression accounting for patient factors and facility effects by clustering patients within clinics and clinics within parent VA medical centers. We then assessed the influence of risk adjustment using observed-to-expected (O/E) ratios computed for each clinic.
RESULTS: The mean unadjusted proportion of adherent patients in clinics was 0.715 (interdecile range 0.559-0.826). The percent variation in patient's likelihood of being adherent explained at the patient, clinic, and parent VA medical center levels was 2.94%, 0.27%, and 0.76%, respectively. The mean clinic-level observed-to-expected ratio was 1.001 (interdecile range 0.975-1.027).
CONCLUSIONS: The variation in the proportion of patients adherent across clinics remained large after risk adjustment. As patient and facility effects explained only 4% of the variance in adherence, comparing clinics based on unadjusted scores is a reasonable starting point unless more predictive patient, provider, and facility factors are identified.

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Year:  2012        PMID: 22354208     DOI: 10.1097/MLR.0b013e318249cb74

Source DB:  PubMed          Journal:  Med Care        ISSN: 0025-7079            Impact factor:   2.983


  6 in total

1.  Wide clinic-level variation in adherence to oral diabetes medications in the VA.

Authors:  Chris L Bryson; David H Au; Matthew L Maciejewski; John D Piette; Stephan D Fihn; George L Jackson; Mark Perkins; Edwin S Wong; Elizabeth M Yano; Chuan-Fen Liu
Journal:  J Gen Intern Med       Date:  2013-01-31       Impact factor: 5.128

2.  Does the presence of a pharmacist in primary care clinics improve diabetes medication adherence?

Authors:  Beverly Mielke Kocarnik; Chuan-Fen Liu; Edwin S Wong; Mark Perkins; Matthew L Maciejewski; Elizabeth M Yano; David H Au; John D Piette; Chris L Bryson
Journal:  BMC Health Serv Res       Date:  2012-11-13       Impact factor: 2.655

3.  Incretin-based therapies: focus on effects beyond glycemic control alone.

Authors:  Jaime A Davidson
Journal:  Diabetes Ther       Date:  2013-09-21       Impact factor: 2.945

4.  Factors affecting medication adherence: patient perspectives from five veterans affairs facilities.

Authors:  Clarissa Hsu; Jaclyn M Lemon; Edwin S Wong; Elizabeth Carson-Cheng; Mark Perkins; Margaret S Nordstrom; Chuan-Fen Liu; Carol Sprague; Christopher L Bryson
Journal:  BMC Health Serv Res       Date:  2014-11-13       Impact factor: 2.655

5.  An integrated continuity of care measure improves performance in models predicting medication adherence using population-based administrative data.

Authors:  Shenzhen Yao; Lisa Lix; Gary Teare; Charity Evans; David Blackburn
Journal:  PLoS One       Date:  2022-03-03       Impact factor: 3.240

6.  Non-adherence in type 2 diabetes: practical considerations for interpreting the literature.

Authors:  David F Blackburn; Jaris Swidrovich; Mark Lemstra
Journal:  Patient Prefer Adherence       Date:  2013-03-03       Impact factor: 2.711

  6 in total

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