BACKGROUND: Efforts to improve primary care diabetes management have assessed strategies across heterogeneous groups of patients and practices. However, there is substantial variability in how well practices implement interventions and achieve desired outcomes. OBJECTIVE: To examine practice contextual features that moderate intervention effectiveness. DESIGN: Secondary analysis of data from a cluster randomized trial of three approaches for implementing the Chronic Care Model to improve diabetes care. PARTICIPANTS: Forty small to mid-sized primary care practices participated, with 522 clinician and staff member surveys. Outcomes were assessed for 822 established patients with a diagnosis of type 2 diabetes who had at least one visit to the practice in the 18 months following enrollment. MAIN MEASURES: The primary outcome was a composite measure of diabetes process of care, ascertained by chart audit, regarding nine quality measures from the American Diabetes Association Physician Recognition Program: HgA1c, foot exam, blood pressure, dilated eye exam, cholesterol, nephropathy screen, flu shot, nutrition counseling, and self-management support. Data from practices included structural and demographic characteristics and Practice Culture Assessment survey subscales (Change Culture, Work Culture, Chaos). KEY RESULTS: Across the three implementation approaches, demographic/structural characteristics (rural vs. urban + .70(p = .006), +2.44(p < .001), -.75(p = .004)); Medicaid: < 20 % vs. ≥ 20 % (-.20(p = .48), +.75 (p = .08), +.60(p = .02)); practice size: < 4 clinicians vs. ≥ 4 clinicians (+.56(p = .02), +1.96(p < .001), +.02(p = .91)); practice Change Culture (high vs. low: -.86(p = .048), +1.71(p = .005), +.34(p = .22)), Work Culture (high vs. low: -.67(p = .18), +2.41(p < .001), +.67(p = .005)) and variability in practice Change Culture (high vs. low: -.24(p = .006), -.20(p = .0771), -.44(p = .0019) and Work Culture (high vs. low: +.56(p = .3160), -1.0(p = .008), -.25 (p = .0216) were associated with trajectories of change in diabetes process of care, either directly or differentially by study arm. CONCLUSIONS: This study supports the need for broader use of methodological approaches to better examine contextual effects on implementation and effectiveness of quality improvement interventions in primary care settings.
RCT Entities:
BACKGROUND: Efforts to improve primary care diabetes management have assessed strategies across heterogeneous groups of patients and practices. However, there is substantial variability in how well practices implement interventions and achieve desired outcomes. OBJECTIVE: To examine practice contextual features that moderate intervention effectiveness. DESIGN: Secondary analysis of data from a cluster randomized trial of three approaches for implementing the Chronic Care Model to improve diabetes care. PARTICIPANTS: Forty small to mid-sized primary care practices participated, with 522 clinician and staff member surveys. Outcomes were assessed for 822 established patients with a diagnosis of type 2 diabetes who had at least one visit to the practice in the 18 months following enrollment. MAIN MEASURES: The primary outcome was a composite measure of diabetes process of care, ascertained by chart audit, regarding nine quality measures from the American Diabetes Association Physician Recognition Program: HgA1c, foot exam, blood pressure, dilated eye exam, cholesterol, nephropathy screen, flu shot, nutrition counseling, and self-management support. Data from practices included structural and demographic characteristics and Practice Culture Assessment survey subscales (Change Culture, Work Culture, Chaos). KEY RESULTS: Across the three implementation approaches, demographic/structural characteristics (rural vs. urban + .70(p = .006), +2.44(p < .001), -.75(p = .004)); Medicaid: < 20 % vs. ≥ 20 % (-.20(p = .48), +.75 (p = .08), +.60(p = .02)); practice size: < 4 clinicians vs. ≥ 4 clinicians (+.56(p = .02), +1.96(p < .001), +.02(p = .91)); practice Change Culture (high vs. low: -.86(p = .048), +1.71(p = .005), +.34(p = .22)), Work Culture (high vs. low: -.67(p = .18), +2.41(p < .001), +.67(p = .005)) and variability in practice Change Culture (high vs. low: -.24(p = .006), -.20(p = .0771), -.44(p = .0019) and Work Culture (high vs. low: +.56(p = .3160), -1.0(p = .008), -.25 (p = .0216) were associated with trajectories of change in diabetes process of care, either directly or differentially by study arm. CONCLUSIONS: This study supports the need for broader use of methodological approaches to better examine contextual effects on implementation and effectiveness of quality improvement interventions in primary care settings.
Authors: William L Miller; Benjamin F Crabtree; Paul A Nutting; Kurt C Stange; Carlos Roberto Jaén Journal: Ann Fam Med Date: 2010 Impact factor: 5.166
Authors: Benjamin F Crabtree; Paul A Nutting; William L Miller; Reuben R McDaniel; Kurt C Stange; Carlos Roberto Jaen; Elizabeth Stewart Journal: Med Care Date: 2011-12 Impact factor: 2.983
Authors: Stephen M Shortell; Jill A Marsteller; Michael Lin; Marjorie L Pearson; Shin-Yi Wu; Peter Mendel; Shan Cretin; Mayde Rosen Journal: Med Care Date: 2004-11 Impact factor: 2.983
Authors: Margie Sherwood Danz; Susanne Hempel; Yee-Wei Lim; Roberta Shanman; Aneesa Motala; Susan Stockdale; Paul Shekelle; Lisa Rubenstein Journal: BMJ Qual Saf Date: 2013-07-05 Impact factor: 7.035
Authors: Michael L Parchman; Polly H Noel; Steven D Culler; Holly J Lanham; Luci K Leykum; Raquel L Romero; Raymond F Palmer Journal: Implement Sci Date: 2013-08-22 Impact factor: 7.327
Authors: Ann M Nguyen; Allison Cuthel; Deborah K Padgett; Paulomi Niles; Erin Rogers; Hang Pham-Singer; Diane Ferran; Sue A Kaplan; Carolyn Berry; Donna Shelley Journal: J Gen Intern Med Date: 2019-10-21 Impact factor: 5.128
Authors: Kimberly S Hsiung; Jason B Colditz; Elizabeth A McGuier; Galen E Switzer; Helena M VonVille; Barbara L Folb; David J Kolko Journal: J Gen Intern Med Date: 2020-11-02 Impact factor: 5.128
Authors: Elaine H Morrato; Borsika Rabin; Jeff Proctor; Lisa C Cicutto; Catherine T Battaglia; Anne Lambert-Kerzner; Bonnie Leeman-Castillo; Michelle Prahl-Wretling; Bridget Nuechterlein; Russell E Glasgow; Allison Kempe Journal: Implement Sci Date: 2015-07-04 Impact factor: 7.327
Authors: Kyle E Knierim; Tristen L Hall; L Miriam Dickinson; Donald E Nease; Dionisia R de la Cerda; Douglas Fernald; Molly J Bleecker; Robert L Rhyne; W Perry Dickinson Journal: JAMA Netw Open Date: 2019-08-02
Authors: Bethany M Kwan; L Miriam Dickinson; Russell E Glasgow; Martha Sajatovic; Mark Gritz; Jodi Summers Holtrop; Don E Nease; Natalie Ritchie; Andrea Nederveld; Dennis Gurfinkel; Jeanette A Waxmonsky Journal: Trials Date: 2020-01-10 Impact factor: 2.728