Minority Health Archive

Leveling the field: addressing health disparities through diabetes disease management.

White, Richard O and DeWalt, Darren A and Malone, Robert M and Osborn, Chandra Y and Pignone, Michael P and Rothman, Russell L (2010) Leveling the field: addressing health disparities through diabetes disease management. The American journal of managed care, 16 (1). pp. 42-48. ISSN 1936-2692

Full text not available from this repository.

Abstract

OBJECTIVES: To examine the relationships among patient characteristics, labor inputs, and improvement in glycosylated hemoglobin (A1C) level in a successful primary care-based diabetes disease management program (DDMP). STUDY DESIGN: We performed subanalyses to examine the relationships among patient characteristics, labor inputs, and improvement in A1C level within a randomized controlled trial. Control patients received usual care, while intervention patients received usual care plus a comprehensive DDMP. METHODS: The primary outcome was improvement in A1C level over 12 months stratified by intervention status and patient characteristics. Process outcomes included the number of actions or contacts with patients, time spent with patients, and number of glucose medication titrations or additions. RESULTS: One hundred ninety-three of 217 enrolled patients (88.9%) had complete 12-month followup data. Patients in the intervention group had significantly greater improvement in A1C level than the control group (-2.1% vs -1.2%, P = .007). In multivariate analysis, no significant differences were observed in improvement in A1C level when stratified by age, race/ethnicity, income, or insurance status, and no interaction effect was observed between any covariate and intervention status. Among intervention patients, we observed similar labor inputs regardless of age, race/ethnicity, sex, education, or whether goal A1C level was achieved. CONCLUSIONS: Among intervention patients in a successful DDMP, improvement in A1C level was achieved regardless of age, race/ethnicity, sex, income, education, or insurance status. Labor inputs were similar regardless of age, race/ethnicity, sex, or education and may reflect the nondiscriminatory nature of providing algorithm-based disease management care.


Export/Citation:EndNote | BibTeX | Dublin Core | ASCII (Chicago style) | HTML Citation | OpenURL | Reference Manager
Social Networking:

Item Type: Article
Additional Information: This article is available at the publisher’s Web site. Access to the full text is subject to the publisher’s access restrictions.
Subjects: Health > Disparities
Health > Public Health > Chronic Illness & Diseases > Diabetes
Practice > interventions
Research
Related URLs:
Depositing User: Users 141 not found.
Date Deposited: 07 Aug 2011 20:44
Last Modified: 07 Aug 2011 20:44
Link to this item (URI): http://health-equity.pitt.edu/id/eprint/3006

Actions (login required)

View Item