The impact of patient-centered medical home certification on quality of care for patients with diabetes.

OBJECTIVE: To identify the impact of changes surrounding certification as a patient-centered medical home (PCMH) on outcomes for patients with diabetes. STUDY SETTING: Minnesota legislation established mandatory quality reporting for patients with diabetes and statewide standards for certification as a PCMH. Patient-level quality reporting data (2008-2018) were used to study the impact of transition to a PCMH. STUDY DESIGN: Achievement of Minnesota's optimal diabetes care standard-in aggregate and by component-was modeled for adult patients with Type 1 or Type 2 diabetes as a function of time relative to the year the patient's primary care practice achieved PCMH certification. Patients from uncertified practices were used to control for general trend. Practice-level random effects captured time-invariant characteristics of practices and the practices' average patient. DATA COLLECTION: Electronic health record data were submitted by 695 Minnesota practices capturing components of the quality standard: blood sugar control, cholesterol control, blood pressure control, nonsmoking status, and use of aspirin. PRINCIPAL FINDINGS: The first cohort of practices achieving PCMH certification (July 2010-June 2014) showed statistically insignificant changes in optimal care. The next cohort of practices (July 2014-June 2018) achieved larger, clinically meaningful increases in quality of care during the time prior to and following certification. Specifically, this second cohort of practices was estimated to achieve a 12.8 percentage-point improvement (P < .001) in the predicted probability of providing optimal diabetes care over the period spanning 3 years before to 3 years after certification. CONCLUSIONS: Our results suggest that the initial cohort of certified practices was already performing at a high level before certification, perhaps requiring little change in their operations to achieve PCMH certification. The second cohort, on the other hand, made meaningful, quality-improving changes in the years surrounding certification. Differences by cohort may partially explain the inconsistent PCMH impacts found in the literature.

Changes in Quality of Health Care Delivery after Vertical Integration.

OBJECTIVES: To fill an empirical gap in the literature by examining changes in quality of care measures occurring when multispecialty clinic systems were acquired by hospital-owned, vertically integrated health care delivery systems in the Twin Cities area. DATA SOURCES/STUDY SETTING: Administrative data for health plan enrollees attributed to treatment and control clinic systems, merged with U.S. Census data. STUDY DESIGN: We compared changes in quality measures for health plan enrollees in the acquired clinics to enrollees in nine control groups using a differences-in-differences model. Our dataset spans 2 years prior to and 4 years after the acquisitions. We estimated probit models with errors clustered within enrollees. DATA COLLECTION/EXTRACTION METHODS: Data were assembled by the health plan's informatics team. PRINCIPAL FINDINGS: Vertical integration is associated with increased rates of colorectal and cervical cancer screening and more appropriate emergency department use. The probability of ambulatory care-sensitive admissions increased when the acquisition caused disruption in admitting patterns. CONCLUSIONS: Moving a clinic system into a vertically integrated delivery system resulted in limited increases in quality of care indicators. Caution is warranted when the acquisition causes disruption in referral patterns.

Sources of information used in selection of surgeons.

OBJECTIVES: We explored the process of physician selection, focusing on selection of surgeons for knee and hip replacement to increase the probability of a new relationship, making cost and quality scorecard information more relevant. STUDY DESIGN: We collected data using a mailed survey sent to patients with knee or hip replacement surgery shortly after March 1, 2010. This time period followed a period of publicity about the new cost and quality scorecard. METHODS: We used multivariate probit models to predict awareness of the scorecard and willingness to switch providers. Multinomial logit methods were used to predict the primary factor influencing the choice of surgeon (physician referral, family or friend referral, surgeon location, previous experience with the surgeon, or other). RESULTS: Internet access and higher neighborhood incomes are associated with an increased probability of being aware of the scorecards. Male patients and patients with Internet access or in highly educated neighborhoods are more likely to be willing to switch providers for a reduced copay. Urban residents are more likely to rely on physician referrals, and rural patients on family/friend referrals when selecting a surgeon; Internet access reduces importance of surgeon location. CONCLUSIONS: Additional research is needed to determine whether Internet access is causal in improved responsiveness to market information and incentives, or a proxy for other factors. In addition, we see evidence that efforts to improve healthcare quality and costs through market forces should be tailored to the patient's place of residence.