Jose F. Figueroa

Comparison of Hospital Mortality and Readmission Rates for Medicare Patients Treated by Male vs Female Physicians

Importance Studies have found differences in practice patterns between male and female physicians, with female physicians more likely to adhere to clinical guidelines and evidence-based practice. However, whether patient outcomes differ between male and female physicians is largely unknown. Objective To determine whether mortality and readmission rates differ between patients treated by male or female physicians. Design, Setting, and Participants We analyzed a 20% random sample of Medicare fee-for-service beneficiaries 65 years or older hospitalized with a medical condition and treated by general internists from January 1, 2011, to December 31, 2014. We examined the association between physician sex and 30-day mortality and readmission rates, adjusted for patient and physician characteristics and hospital fixed effects (effectively comparing female and male physicians within the same hospital). As a sensitivity analysis, we examined only physicians focusing on hospital care (hospitalists), among whom patients are plausibly quasi-randomized to physicians based on the physician’s specific work schedules. We also investigated whether differences in patient outcomes varied by specific condition or by underlying severity of illness. Main Outcomes and Measures Patients’ 30-day mortality and readmission rates. Results A total of 1 583 028 hospitalizations were used for analyses of 30-day mortality (mean [SD] patient age, 80.2 [8.5] years; 621 412 men and 961 616 women) and 1 540 797 were used for analyses of readmission (mean [SD] patient age, 80.1 [8.5] years; 602 115 men and 938 682 women). Patients treated by female physicians had lower 30-day mortality (adjusted mortality, 11.07% vs 11.49%; adjusted risk difference, –0.43%; 95% CI, –0.57% to –0.28%; P < .001; number needed to treat to prevent 1 death, 233) and lower 30-day readmissions (adjusted readmissions, 15.02% vs 15.57%; adjusted risk difference, –0.55%; 95% CI, –0.71% to –0.39%; P < .001; number needed to treat to prevent 1 readmission, 182) than patients cared for by male physicians, after accounting for potential confounders. Our findings were unaffected when restricting analyses to patients treated by hospitalists. Differences persisted across 8 common medical conditions and across patients’ severity of illness. Conclusions and Relevance Elderly hospitalized patients treated by female internists have lower mortality and readmissions compared with those cared for by male internists. These findings suggest that the differences in practice patterns between male and female physicians, as suggested in previous studies, may have important clinical implications for patient outcomes.

Association between the Value-Based Purchasing pay for performance program and patient mortality in US hospitals: observational study

Objective To determine the impact of the Hospital Value-Based Purchasing (HVBP) program—the US pay for performance program introduced by Medicare to incentivize higher quality care—on 30 day mortality for three incentivized conditions: acute myocardial infarction, heart failure, and pneumonia. Design Observational study. Setting 4267 acute care hospitals in the United States: 2919 participated in the HVBP program and 1348 were ineligible and used as controls (44 in general hospitals in Maryland and 1304 critical access hospitals across the United States). Participants 2 430 618 patients admitted to US hospitals from 2008 through 2013. Main outcome measures 30 day risk adjusted mortality for acute myocardial infarction, heart failure, and pneumonia using a patient level linear spline analysis to examine the association between the introduction of the HVBP program and 30 day mortality. Non-incentivized, medical conditions were the comparators. A secondary outcome measure was to determine whether the introduction of the HVBP program was particularly beneficial for a subgroup of hospital—poor performers at baseline—that may benefit the most. Results Mortality rates of incentivized conditions in hospitals participating in the HVBP program declined at −0.13% for each quarter during the preintervention period and −0.03% point difference for each quarter during the post-intervention period. For non-HVBP hospitals, mortality rates declined at −0.14% point difference for each quarter during the preintervention period and −0.01% point difference for each quarter during the post-intervention period. The difference in the mortality trends between the two groups was small and non-significant (difference in difference in trends −0.03% point difference for each quarter, 95% confidence interval −0.08% to 0.13% point difference, P=0.35). In no subgroups of hospitals was HVBP associated with better outcomes, including poor performers at baseline. Conclusions Evidence that HVBP has led to lower mortality rates is lacking. Nations considering similar pay for performance programs may want to consider alternative models to achieve improved patient outcomes.

Association Between the Centers for Medicare and Medicaid Services Hospital Star Rating and Patient Outcomes

Association Between the Centers for Medicare and Medicaid Services Hospital Star Rating and Patient Outcomes In an effort to help patients choose hospitals based on quality, the Centers for Medicare and Medicaid Services (CMS) recently introduced a 5-star hospital rating system. This rating depends solely on patient experience based on the Hospital Consumer Assessment of Healthcare Providers and Systems, and currently, it does not include measures of quality of care or patients’ health outcomes. Whether hospital stars are associated with better outcomes is unclear, and critics worry that the star rating system may mislead patients into thinking that 5-star hospitals are superior in quality.1-4 Therefore, we investigated whether hospitals with more stars have lower riskadjusted 30-day mortality and readmissions than hospitals with less stars.

Characteristics of hospitals receiving the largest penalties by US pay-for-performance programmes

Healthcare systems around the world are striving to deliver high quality care while controlling costs. One compelling strategy is the use of penalties for low-value care.1 ,2 The US federal government has made significant efforts to shift towards value-based payments for hospitals by introducing three national pay-for-performance (P4P) schemes which employ penalties: Hospital Readmission Reduction Program (HRRP), Hospital Value-Based-Purchasing (VBP) and, more recently, Hospital-Acquired Condition Reduction (HACR) Program. HRRP penalises hospitals with higher-than-expected readmissions; VBP adjusts hospital payments (either a bonus or penalty) based on performance on clinical measures and patient experience and HACR penalises the worst quartile of hospitals on HAC metrics.3 Fiscal year 2015 marks the first time hospitals may be penalised by all three programmes, with Medicare reimbursement rates potentially cut by 5.5%. Although prior work has raised concerns that hospitals serving medically complex or socioeconomically vulnerable populations are at higher risk for penalties by individual programmes,4–7 to our knowledge, there is no study that has examined the characteristics of hospitals that received the most substantial penalties across all three programmes. As …

Safety-net Hospitals Face More Barriers Yet Use Fewer Strategies to Reduce Readmissions

Objective: US hospitals that care for vulnerable populations, “safety-net hospitals” (SNHs), are more likely to incur penalties under the Hospital Readmissions Reduction Program, which penalizes hospitals with higher-than-expected readmissions. Understanding whether SNHs face unique barriers to reducing readmissions or whether they underuse readmission-prevention strategies is important. Design: We surveyed leadership at 1600 US acute care hospitals, of whom 980 participated, between June 2013 and January 2014. Responses on 28 questions on readmission-related barriers and strategies were compared between SNHs and non-SNHs, adjusting for nonresponse and sampling strategy. We further compared responses between high-performing SNHs and low-performing SNHs. Results: We achieved a 62% response rate. SNHs were more likely to report patient-related barriers, including lack of transportation, homelessness, and language barriers compared with non-SNHs (P-values<0.001). Despite reporting more barriers, SNHs were less likely to use e-tools to share discharge summaries (70.1% vs. 73.7%, P<0.04) or verbally communicate (31.5% vs. 39.8%, P<0.001) with outpatient providers, track readmissions by race/ethnicity (23.9% vs. 28.6%, P<0.001), or enroll patients in postdischarge programs (13.3% vs. 17.2%, P<0.001). SNHs were also less likely to use discharge coordinators, pharmacists, and postdischarge programs. When we examined the use of strategies within SNHs, we found trends to suggest that high-performing SNHs were more likely to use several readmission strategies. Conclusions: Despite reporting more barriers to reducing readmissions, SNHs were less likely to use readmission-reduction strategies. This combination of higher barriers and lower use of strategies may explain why SNHs have higher rates of readmissions and penalties under the Hospital Readmissions Reduction Program.

Characteristics and spending patterns of high cost, non-elderly adults in Massachusetts

BACKGROUND Given that health care costs in Massachusetts continue to grow despite great efforts to contain them, we seek to understand characteristics and spending patterns of the costliest non-elderly adults in Massachusetts based on type of insurance. METHODS We used the Massachusetts All-Payer Claims Database (APCD) from 2012 and analyzed demographics, utilization patterns and spending patterns across payers (Medicaid, Medicaid managed care, and private insurers) for high cost patients (those in the top 10% of spending) and non-high cost patients (the remaining 90%). RESULTS We identified 3,712,045 patients between the ages of 18-64 years in Massachusetts in 2012 who met our inclusion criteria. Of this group, 8.5% had Medicaid fee-for-service, 11.1% had Medicaid managed care, and 80.3% had private insurance. High cost patients accounted for 65% of total spending in our sample. We found that high cost patients were more likely to be older (median age 48 vs 40, p<0.001), female (60.2% vs. 51.2%, p<0.001), and have multiple chronic conditions (4.4 vs. 1.3, p<0.001) compared to non-high cost patient patients. Medicaid patients were the most likely to be designated high cost (18.1%) followed by Medicaid managed care (MCO) (13.9%) and private insurance (8.6%). High cost Medicaid patients also had the highest mean annual spending and incurred the most preventable spending compared to high cost MCO and high cost private insurance patients. CONCLUSIONS & IMPLICATIONS We used 2012 claims data from Massachusetts to examine characteristics and spending patterns of the states costliest patients based on type of insurance. Providers and policymakers seeking to reduce costs and increase value under delivery system reform may wish to target the Medicaid population.

The Impact of Financial Incentives on Early and Late Adopters among U.S. Hospitals: Observational Study

Abstract Objective To examine how hospitals that volunteered to be under financial incentives for more than a decade as part of the Premier Hospital Quality Incentive Demonstration (early adopters) compared with similar hospitals where these incentives were implemented later under the Hospital Value-Based Purchasing program (late adopters). Design Observational study. Setting 1189 hospitals in the USA (214 early adopters and 975 matched late adopters), using Hospital Compare data from 2003 through 2013. Participants 1 371 364 patients aged 65 years and older, using 100% Medicare claims. Main outcome measures Clinical process scores and 30 day mortality. Results Early adopters started from a slightly higher baseline of clinical process scores (92) than late adopters (90). Both groups reached a ceiling (98) a decade later. Starting from a similar baseline, just below 13%, early and late adopters did not have significantly (P=0.25) different mortality trends for conditions targeted by the program (0.05% point difference quarterly) or for conditions not targeted by the program (−0.02% point difference quarterly). Conclusions No evidence that hospitals that have been operating under pay for performance programs for more than a decade had better process scores or lower mortality than other hospitals was found. These findings suggest that even among hospitals that volunteered to participate in pay for performance programs, having additional time is not likely to turn pay for performance programs into a success in the future.

Emerging Trends Could Exacerbate Health Inequities In The United States

Health inequities among people of different races and ethnicities, geographical locations, and social classes are not a new phenomenon, although the size of the inequities has changed since researchers first began documenting them. While interventions to improve the health of targeted disadvantaged groups may help combat disparities, broader trends that disproportionately benefit privileged groups or harm vulnerable populations can eclipse the progress made through isolated interventions. These trends threaten equity in health and health care in the United States either through direct effects on health or through impacts on the distribution of resources, risks, and power. We highlight trends in four domains: health care technologies, health reform policies, widening socioeconomic inequality, and environmental hazards. We suggest ways of countering the effects of these trends to promote health equity, focusing on strategies that promise co-benefits across multiple sectors.

Approach for Achieving Effective Care for High-Need Patients

Source of Review Recently, the National Academy of Medicine (NAM), in partnership with the Harvard T. H. Chan School of Public Health, the Bipartisan Policy Center, The Commonwealth Fund, and the Peterson Center on Healthcare, which funded this initiative, held a series of workshops to advance our collective knowledge about how best to care for high-need patients. These workshops and their findings culminated in a NAM report titled Effective Care for High-Need Patients: Opportunities for Improving Outcomes, Value, and Health.1 Most of the evidence for this report ranged from level 2 (prospective comparative studies) to level 5 (expert opinions). In addition, a consensus decision-making process was used to identify the high-need patient taxonomy and successful care models.

Do the stars align? Distribution of high-quality ratings of healthcare sectors across US markets

Background The US government created five-star rating systems to evaluate hospital, nursing homes, home health agency and dialysis centre quality. The degree to which quality is a property of organisations versus geographical markets is unclear. Objectives To determine whether high-quality healthcare service sectors are clustered within US healthcare markets. Design Using data from the Centers for Medicare and Medicaid Services’ Hospital, Dialysis, Nursing Home and Home Health Compare databases, we calculated the mean star ratings of four healthcare sectors in 304 US hospital referral regions (HRRs). For each sector, we ranked HRRs into terciles by mean star rating. Within each HRR, we assessed concordance of tercile rank across sectors using a multirater kappa. Using t-tests, we compared characteristics of HRRs with three to four top-ranked sectors, one to two top-ranked sectors and zero top-ranked sectors. Results Six HRRs (2.0% of HRRs) had four top-ranked healthcare sectors, 38 (12.5%) had three top-ranked health sectors, 71 (23.4%) had two top-ranked sectors, 111 (36.5%) had one top-ranked sector and 78 (25.7%) HRRs had no top-ranked sectors. A multirater kappa across all sectors showed poor to slight agreement (K=0.055). Compared with HRRs with zero top-ranked sectors, those with three to four top-ranked sectors had higher median incomes, fewer black residents, lower mortality rates and were less impoverished. Results were similar for HRRs with one to two top-ranked sectors. Conclusions Few US healthcare markets exhibit high-quality performance across four distinct healthcare service sectors, suggesting that high-quality care in one sector may not be dependent on or improve care quality in other sectors. Policies that promote accountability for quality across sectors (eg, bundled payments and shared quality metrics) may be needed to systematically improve quality across sectors.