Model Homes: Evaluating Approaches to Patient-centered Medical Home Implementation.

BACKGROUND: The patient-centered medical home (PCMH) model has been widely adopted, but the evidence on its effectiveness remains mixed. One potential explanation for these mixed findings is variation in how the model is implemented by practices. OBJECTIVE: To identify the impact of different approaches to PCMH adoption on health care utilization in a long-term, geographically diverse sample of patients. DESIGN: Difference-in-differences evaluation of PCMH impact on cost and utilization. SUBJECTS: A total of 5,314,284 patient-year observations from the HealthCore Integrated Research Database, and 5943 practices which adopted the PCMH model in 14 states between 2011 and 2015. INTERVENTION: PCMH adoption, as defined by the National Committee for Quality Assurance. MEASUREMENTS: Six claims-based utilization measures, plus total health care expenditures. We employ hierarchical clustering to organize practices into groups based on their PCMH capabilities, then use generalized difference-in-differences models with practice or patient fixed effects to estimate the effect of PCMH recognition (overall and separately by the groups identified by the clustering algorithm) on utilization. RESULTS: PCMH adoption was associated with a >8% reduction in total expenditures. We find significant reductions in emergency department utilization and outpatient care, and both lab and imaging services. In our by-group results we find that while the reduction in outpatient care is significant across all 3 groups, the reduction in emergency department utilization is driven entirely by 1 group with enhanced electronic communications. CONCLUSION: The PCMH model has significant impact on patterns of health care utilization, especially when heterogeneity in implementation is accounted for in program evaluation.

The economics of patient-centered care.

The Patient-Centered Medical Home (PCMH) is a widely-implemented model for improving primary care, emphasizing care coordination, information technology, and process improvements. However, its treatment as an undifferentiated intervention in policy evaluation obscures meaningful variation in implementation. This heterogeneity leads to contracting inefficiencies between insurers and practices and may account for mixed evidence on its success. Using a novel dataset we group practices into meaningful implementation clusters and then link these clusters with detailed patient claims data. We find implementation choice affects performance, suggesting that generally-unobserved features of primary care reorganization influence patient outcomes. Reporting these features may be valuable to insurers and their members.

Assessment of economic vulnerability to infectious disease crises.

Infectious disease crises have substantial economic impact. Yet mainstream macroeconomic forecasting rarely takes account of the risk of potential pandemics. This oversight contributes to persistent underestimation of infectious disease risk and consequent underinvestment in preparedness and response to infectious disease crises. One reason why economists fail to include economic vulnerability to infectious disease threats in their assessments is the absence of readily available and digestible input data to inform such analysis. In this Viewpoint we suggest an approach by which the global health community can help to generate such inputs, and a framework to use these inputs to assess the economic vulnerability to infectious disease crises of individual countries and regions. We argue that incorporation of these risks in influential macroeconomic analyses such as the reports from the International Monetary Fund's Article IV consultations, rating agencies and risk consultancies would simultaneously improve the quality of economic risk forecasting and reinforce individual government and donor incentives to mitigate infectious disease risks.

Do patient-centered medical homes reduce emergency department visits?

OBJECTIVE: To assess whether adoption of the patient-centered medical home (PCMH) reduces emergency department (ED) utilization among patients with and without chronic illness. DATA SOURCES: Data from approximately 460,000 Independence Blue Cross patients enrolled in 280 primary care practices, all converting to PCMH status between 2008 and 2012. RESEARCH DESIGN: We estimate the effect of a practice becoming PCMH-certified on ED visits and costs using a difference-in-differences approach which exploits variation in the timing of PCMH certification, employing either practice or patient fixed effects. We analyzed patients with and without chronic illness across six chronic illness categories. PRINCIPAL FINDINGS: Among chronically ill patients, transition to PCMH status was associated with 5-8 percent reductions in ED utilization. This finding was robust to a number of specifications, including analyzing avoidable and weekend ED visits alone. The largest reductions in ED visits are concentrated among chronic patients with diabetes and hypertension. CONCLUSIONS: Adoption of the PCMH model was associated with lower ED utilization for chronically ill patients, but not for those without chronic illness. The effectiveness of the PCMH model varies by chronic condition. Analysis of weekend and avoidable ED visits suggests that reductions in ED utilization stem from better management of chronic illness rather than expanding access to primary care clinics.

A hospital-specific template for benchmarking its cost and quality.

OBJECTIVE: Develop an improved method for auditing hospital cost and quality tailored to a specific hospital's patient population. DATA SOURCES/SETTING: Medicare claims in general, gynecologic and urologic surgery, and orthopedics from Illinois, New York, and Texas between 2004 and 2006. STUDY DESIGN: A template of 300 representative patients from a single index hospital was constructed and used to match 300 patients at 43 hospitals that had a minimum of 500 patients over a 3-year study period. DATA COLLECTION/EXTRACTION METHODS: From each of 43 hospitals we chose 300 patients most resembling the template using multivariate matching. PRINCIPAL FINDINGS: We found close matches on procedures and patient characteristics, far more balanced than would be expected in a randomized trial. There were little to no differences between the index hospital's template and the 43 hospitals on most patient characteristics yet large and significant differences in mortality, failure-to-rescue, and cost. CONCLUSION: Matching can produce fair, directly standardized audits. From the perspective of the index hospital, "hospital-specific" template matching provides the fairness of direct standardization with the specific institutional relevance of indirect standardization. Using this approach, hospitals will be better able to examine their performance, and better determine why they are achieving the results they observe.

Template matching for auditing hospital cost and quality.

OBJECTIVE: Develop an improved method for auditing hospital cost and quality. DATA SOURCES/SETTING: Medicare claims in general, gynecologic and urologic surgery, and orthopedics from Illinois, Texas, and New York between 2004 and 2006. STUDY DESIGN: A template of 300 representative patients was constructed and then used to match 300 patients at hospitals that had a minimum of 500 patients over a 3-year study period. DATA COLLECTION/EXTRACTION METHODS: From each of 217 hospitals we chose 300 patients most resembling the template using multivariate matching. PRINCIPAL FINDINGS: The matching algorithm found close matches on procedures and patient characteristics, far more balanced than measured covariates would be in a randomized clinical trial. These matched samples displayed little to no differences across hospitals in common patient characteristics yet found large and statistically significant hospital variation in mortality, complications, failure-to-rescue, readmissions, length of stay, ICU days, cost, and surgical procedure length. Similar patients at different hospitals had substantially different outcomes. CONCLUSION: The template-matched sample can produce fair, directly standardized audits that evaluate hospitals on patients with similar characteristics, thereby making benchmarking more believable. Through examining matched samples of individual patients, administrators can better detect poor performance at their hospitals and better understand why these problems are occurring.

Medical and financial risks associated with surgery in the elderly obese.

OBJECTIVE: To study the medical and financial outcomes associated with surgery in elderly obese patients and to ask if obesity itself influences outcomes above and beyond the effects from comorbidities that are known to be associated with obesity. BACKGROUND: Obesity is a surgical risk factor not present in Medicare's risk adjustment or payment algorithms, as BMI is not collected in administrative claims. METHODS: A total of 2045 severely or morbidly obese patients (BMI ≥ 35 kg/m, aged between 65 and 80 years) selected from 15,914 elderly patients in 47 hospitals undergoing hip and knee surgery, colectomy, and thoracotomy were matched to 2 sets of 2045 nonobese patients (BMI = 20-30 kg/m). A "limited match" controlled for age, sex, race, procedure, and hospital. A "complete match" also controlled for 30 additional factors such as diabetes and admission clinical data from chart abstraction. RESULTS: Mean BMI in the obese patients was 40 kg/m compared with 26 kg/m in the nonobese. In the complete match, obese patients displayed increased odds of wound infection: OR (odds ratio) = 1.64 (95% CI: 1.21, 2.21); renal dysfunction: OR = 2.05 (1.39, 3.05); urinary tract infection: OR = 1.55 (1.24, 1.94); hypotension: OR = 1.38 (1.07, 1.80); respiratory events: OR = 1.44 (1.19, 1.75); 30-day readmission: OR = 1.38 (1.08, 1.77); and a 12% longer length of stay (8%, 17%). Provider costs were 10% (7%, 12%) greater in obese than in nonobese patients, whereas Medicare payments increased only 3% (2%, 5%). Findings were similar in the limited match. CONCLUSIONS: Obesity increases the risks and costs of surgery. Better approaches are needed to reduce these risks. Furthermore, to avoid incentives to underserve this population, Medicare should consider incorporating incremental costs of caring for obese patients into payment policy and include obesity in severity adjustment models.