PURPOSE: The medical home has gained national attention as a model to reorganize primary care to improve health outcomes. Pennsylvania has undertaken one of the largest state-based, multipayer medical home pilot projects. We used a positive deviance approach to identify and compare factors driving the care models of practices showing the greatest and least improvement in diabetes care in a sample of 25 primary care practices in southeast Pennsylvania. METHODS: We ranked practices into improvement quintiles on the basis of the average absolute percentage point improvement from baseline to 18 months in 3 registry-based measures of performance related to diabetes care: glycated hemoglobin concentration, blood pressure, and low-density lipoprotein cholesterol level. We then conducted surveys and key informant interviews with leaders and staff in the 5 most and least improved practices, and compared their responses. RESULTS: The most improved/higher-performing practices tended to have greater structural capabilities (eg, electronic health records) than the least improved/lower-performing practices at baseline. Interviews revealed striking differences between the groups in terms of leadership styles and shared vision; sense, use, and development of teams; processes for monitoring progress and obtaining feedback; and presence of technologic and financial distractions. CONCLUSIONS: Positive deviance analysis suggests that primary care practices' baseline structural capabilities and abilities to buffer the stresses of change may be key facilitators of performance improvement in medical home transformations. Attention to the practices' structural capabilities and factors shaping successful change, especially early in the process, will be necessary to improve the likelihood of successful medical home transformation and better care.
PURPOSE: The medical home has gained national attention as a model to reorganize primary care to improve health outcomes. Pennsylvania has undertaken one of the largest state-based, multipayer medical home pilot projects. We used a positive deviance approach to identify and compare factors driving the care models of practices showing the greatest and least improvement in diabetes care in a sample of 25 primary care practices in southeast Pennsylvania. METHODS: We ranked practices into improvement quintiles on the basis of the average absolute percentage point improvement from baseline to 18 months in 3 registry-based measures of performance related to diabetes care: glycated hemoglobin concentration, blood pressure, and low-density lipoprotein cholesterol level. We then conducted surveys and key informant interviews with leaders and staff in the 5 most and least improved practices, and compared their responses. RESULTS: The most improved/higher-performing practices tended to have greater structural capabilities (eg, electronic health records) than the least improved/lower-performing practices at baseline. Interviews revealed striking differences between the groups in terms of leadership styles and shared vision; sense, use, and development of teams; processes for monitoring progress and obtaining feedback; and presence of technologic and financial distractions. CONCLUSIONS: Positive deviance analysis suggests that primary care practices' baseline structural capabilities and abilities to buffer the stresses of change may be key facilitators of performance improvement in medical home transformations. Attention to the practices' structural capabilities and factors shaping successful change, especially early in the process, will be necessary to improve the likelihood of successful medical home transformation and better care.
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