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 impact of patient-centered medical homes on medication adherence?

Accreditation of providers helps resolve the pervasive information asymmetries in health care markets. However, meeting accreditation standards typically involves flexibility in implementation, leading to heterogeneity in performance. For example, the patient-centered medical home (PCMH) is a leading model for recognizing high-performing primary care practices. Flexibility in PCMH implementation allows for varying degrees of emphasis on processes designed to enhance medication adherence. To assess the impact of the PCMH on adherence, we combine 6 years of detailed patient claims data with a novel dataset containing detailed practice-level PCMH attributes. We study the effects of the number and configuration of adherence-relevant capabilities, using variation in the timing of PCMH adoption to estimate its impact. While PCMH adoption improved overall medication adherence, when combining claims data with the unique recognition data detailing what PCMH capabilities were adopted, we find that these gains are concentrated among patients in practices that adopted more adherence-relevant capabilities. Despite mixed evidence in the literature concerning costs and utilization, our results indicate that PCMH recognition improves medication adherence.

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.

Preterm Infant Attendance at Health Supervision Visits.

OBJECTIVES: To assess the adherence of premature infants with the American Academy of Pediatrics health supervision visit schedule, factors affecting adherence, and the association of adherence with preventive care. METHODS: Retrospective cohort of all infants ≤35 weeks' gestation, born 2005 to 2009, receiving care at a 30-site primary care network for at least 24 months (n = 1854). Adherence was defined as having a health supervision visit within each expected time period during the first 18 months of life. Logistic regression identified sociodemographic and medical factors associated with nonadherence and risk-adjusted association between nonadherence and outcomes. RESULTS: Only 43% received all expected health supervision visits. Those with Medicaid insurance (adjusted odds ratio [AOR] 0.46, 95% confidence interval [CI] 0.35-0.60), a visit without insurance (AOR 0.46, 95% CI 0.32-0.67), chronic illness (AOR 0.7, 95% CI 0.51-0.97), and black race (AOR 0.7, 95% CI 0.50-0.98) were less adherent, whereas provider continuity of care (AOR 2.89, 95% CI 1.92-4.37) and lower birth weight (AOR 1.67, 95% CI 1.02-2.73) increased adherence. Infants <100% adherent were less likely to be up to date with immunizations and receive recommended preventive care. In nearly half of missed visit windows, no health supervision visit was scheduled. CONCLUSIONS: Fewer than half of premature infants were fully adherent with the preventive health schedule with associated gaps in health monitoring and immunization delays. These data suggest the importance of health supervision visits and the need to explore scheduling facilitators for those at risk for nonadherence.

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.

Acute kidney injury, renal function, and the elderly obese surgical patient: a matched case-control study.

OBJECTIVE: To investigate the association between obesity and perioperative acute kidney injury (AKI), controlling for preoperative kidney dysfunction. BACKGROUND: More than 30% of patients older than 60 years are obese and, therefore, at risk for kidney disease. Postoperative AKI is a significant problem. METHODS: We performed a matched case-control study of patients enrolled in the Obesity and Surgical Outcomes Study, using data of Medicare claims enriched with detailed chart review. Each AKI patient was matched with a non-AKI control similar in procedure type, age, sex, race, emergency status, transfer status, baseline estimated glomerular filtration rate, admission APACHE score, and the risk of death score with fine balance on hospitals. RESULTS: We identified 514 AKI cases and 694 control patients. Of the cases, 180 (35%) followed orthopedic procedures and 334 (65%) followed colon or thoracic surgery. After matching, obese patients undergoing a surgical procedure demonstrated a 65% increase in odds of AKI within 30 days from admission (odds ratio = 1.65, P < 0.005) when compared with the nonobese patients. After adjustment for potential confounders, the odds of postoperative AKI remained elevated in the elderly obese (odds ratio = 1.68, P = 0.01.) CONCLUSIONS: : Obesity is an independent risk factor for postoperative AKI in patients older than 65 years. Efforts to optimize kidney function preoperatively should be employed in this at-risk population along with keen monitoring and maintenance of intraoperative hemodynamics. When subtle reductions in urine output or a rising creatinine are observed postoperatively, timely clinical investigation is warranted to maximize renal recovery.

Obesity and readmission in elderly surgical patients.

BACKGROUND: Reducing readmissions has become a focus in efforts by Medicare to improve health care quality and reduce costs. This study aimed to determine whether causes for readmission differed between obese and nonobese patients, possibly allowing for targeted interventions. METHODS: A matched case control study of Medicare patients admitted between 2002 and 2006 who were readmitted after hip or knee surgery, colectomy, or thoracotomy was performed. Patients were matched exactly for procedure, while also balancing on hospital, age, and sex. Conditional logistic regression was used to study the odds of readmission for very obese cases (body mass index >35 kg/m2) versus normal weight patients (body mass index of 20-30 kg/m2) after also controlling for race, transfer-in and emergency status, and comorbidities. RESULTS: Among 15,914 patient admissions, we identified 1,380 readmitted patients and 2,760 controls. The risk of readmission was increased for obese compared to nonobese patients both before and after controlling for comorbidities (before: odds ratio, 1.35; P = .003; after: odds ratio, 1.25; P = .04). Reasons for readmission varied by procedure but were not different by body mass index category. CONCLUSION: Obese patients have an increased risk of readmission, yet the reasons for readmission in obese patients appear to be similar to those for nonobese patients, suggesting that improved postdischarge management for the obese cannot focus on a few specific causes of readmission but must instead provide a broad range of interventions.

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.