Rural Hospitals Experienced More Patient Volume Variability Than Urban Hospitals During The COVID-19 Pandemic, 2020-21.

Fluctuations in patient volume during the COVID-19 pandemic may have been particularly concerning for rural hospitals. We examined hospital discharge data from the Healthcare Cost and Utilization Project State Inpatient Databases to compare data from the COVID-19 pandemic period (March 8, 2020-December 31, 2021) with data from the prepandemic period (January 1, 2017-March 7, 2020). Changes in average daily medical volume at rural hospitals showed a dose-response relationship with community COVID-19 burden, ranging from a 13.2 percent decrease in patient volume in periods of low transmission to a 16.5 percent increase in volume in periods of high transmission. Overall, about 35 percent of rural hospitals experienced fluctuations exceeding 20 percent (in either direction) in average daily total volume, in contrast to only 13 percent of urban hospitals experiencing similar magnitudes of changes. Rural hospitals with a large change in average daily volume were more likely to be smaller, government-owned, and critical access hospitals and to have significantly lower operating margins. Our findings suggest that rural hospitals may have been more vulnerable operationally and financially to volume shifts during the pandemic, which warrants attention because of the potential impact on these hospitals' long-term sustainability.

Mortality for Time-Sensitive Conditions at Urban vs Rural Hospitals During the COVID-19 Pandemic.

Importance: COVID-19 pandemic-related disruptions to the health care system may have resulted in increased mortality for patients with time-sensitive conditions. Objective: To examine whether in-hospital mortality in hospitalizations not related to COVID-19 (non-COVID-19 stays) for time-sensitive conditions changed during the pandemic and how it varied by hospital urban vs rural location. Design, Setting, and Participants: This cohort study was an interrupted time-series analysis to assess in-hospital mortality during the COVID-19 pandemic (March 8, 2020, to December 31, 2021) compared with the prepandemic period (January 1, 2017, to March 7, 2020) overall, by month, and by community COVID-19 transmission level for adult discharges from 3813 US hospitals in the State Inpatient Databases for the Healthcare Cost and Utilization Project. Exposure: The COVID-19 pandemic. Main Outcomes and Measures: The main outcome measure was in-hospital mortality among non-COVID-19 stays for 6 time-sensitive medical conditions: acute myocardial infarction, hip fracture, gastrointestinal hemorrhage, pneumonia, sepsis, and stroke. Entropy weights were used to align patient characteristics in the 2 time periods by age, sex, and comorbidities. Results: There were 18 601 925 hospitalizations; 50.3% of patients were male, 38.5% were aged 18 to 64 years, 45.0% were aged 65 to 84 years, and 16.4% were 85 years or older for the selected time-sensitive medical conditions from 2017 through 2021. The odds of in-hospital mortality for sepsis increased 27% from the prepandemic to the pandemic periods at urban hospitals (odds ratio [OR], 1.27; 95% CI, 1.25-1.29) and 35% at rural hospitals (OR, 1.35; 95% CI, 1.30-1.40). In-hospital mortality for pneumonia had similar increases at urban (OR, 1.48; 95% CI, 1.42-1.54) and rural (OR, 1.46; 95% CI, 1.36-1.57) hospitals. Increases in mortality for these 2 conditions showed a dose-response association with the community COVID-19 level (low vs high COVID-19 burden) for both rural (sepsis: 22% vs 54%; pneumonia: 30% vs 66%) and urban (sepsis: 16% vs 28%; pneumonia: 34% vs 61%) hospitals. The odds of mortality for acute myocardial infarction increased 9% (OR, 1.09; 95% CI, 1.06-1.12) at urban hospitals and was responsive to the community COVID-19 level. There were significant increases in mortality for hip fracture at rural hospitals (OR, 1.32; 95% CI, 1.14-1.53) and for gastrointestinal hemorrhage at urban hospitals (OR, 1.15; 95% CI, 1.09-1.21). No significant change was found in mortality for stroke overall. Conclusions and Relevance: In this cohort study, in-hospital mortality for time-sensitive conditions increased during the COVID-19 pandemic. Mobilizing strategies tailored to the different needs of urban and rural hospitals may help reduce the likelihood of excess deaths during future public health crises.

Medicare Advantage in rural areas: implications for hospital sustainability.

OBJECTIVES: A growing number of Medicare beneficiaries in rural areas are enrolled in Medicare Advantage plans, which negotiate hospital reimbursement. This study examined the association between Medicare Advantage penetration levels in rural areas and hospital financial distress and closure. STUDY DESIGN: This retrospective cohort study followed rural general acute care hospitals open in 2008 through 2019 or until closure using Healthcare Cost and Utilization Project State Inpatient Databases for 14 states. METHODS: The primary independent variables were the percentage of Medicare Advantage stays out of total Medicare stays at the hospital and the percentage of Medicare Advantage beneficiaries out of total beneficiaries in the hospital's county. Financial distress was defined using the Altman Z score, where values less than or equal to 1.1 indicate financial distress and values greater than 2.8 indicate stability. The Z score was examined as a continuous outcome in hospital and county fixed-effects models. Risk of closure was examined using Cox proportional hazard models adjusted for hospital and market factors. RESULTS: Rural hospital Medicare Advantage penetration grew from 6.5% in 2008 to 20.6% in 2019. A 1-percentage point increase in hospital penetration was associated with an increase in financial stability of 0.04 units on the Altman Z score (95% CI, 0.00-0.08; P = .03) and a 4% reduction in risk of closure (HR, 0.96; 95% CI, 0.92-1.00; P = .04). Results were consistent when measuring Medicare Advantage penetration at the county level. CONCLUSIONS: Our findings counter the notion that Medicare Advantage plans financially hurt rural hospitals because they pay less generously than traditional Medicare.

Risk of Closure Among Independent and Multihospital-Affiliated Rural Hospitals.

Importance: The increase in rural hospital closures has strained access to inpatient care in rural communities. It is important to understand the association between hospital system affiliation and access to care in these communities to inform policy on this issue. Objective: To examine the association between affiliation and rural hospital closure. Design Setting and Participants: This cohort study used survival models with a time-dependent variable for affiliation vs independent status to assess risk of closure among a national cohort of US rural hospitals from January 2007 through December 2019. Data analysis was conducted from March to October 2021. Hospital affiliations were identified from the American Hospital Association Annual Survey and Irving Levin Associates and closures from the University of North Carolina Sheps Center (Chapel Hill). Additional covariates came from the Healthcare Cost and Utilization Project State Inpatient Databases and other national sources. Exposures: Affiliation with another hospital or multihospital health system. Main Outcomes and Measures: Closure was the main outcome. The models included hospital, market, and utilization characteristics and were stratified by financial distress in 2007. Results: Among 2237 rural hospitals operating in 2007, 140 (6.3%) had closed by 2019. The proportion of rural hospitals that were independent decreased from 68.9% in 2007 to 47.0% in 2019; the proportion that were affiliated increased from 31.1% to 46.7%. Among financially distressed hospitals in 2007, affiliation was associated with lower risk of closure compared with being independent (adjusted hazard ratio [aHR], 0.49; 95% CI, 0.26-0.92). Conversely, among hospitals that were financially stable in 2007, affiliation was associated with higher risk of closure compared with being independent (aHR, 2.36; 95% CI, 1.20-4.62). For-profit ownership was also strongly associated with closure for hospitals that were financially stable in 2007 (aHR, 4.08; 95% CI, 1.86-8.97). Conclusions and Relevance: The results of this cohort study suggest that affiliations may be associated with lower risk of closure for some rural hospitals in financial distress. However, among initially financially stable hospitals, an increased risk of closure for hospitals associated with affiliation and proprietary ownership raises concerns about the association of affiliation with closures in some circumstances. Policy interventions to stabilize inpatient care in rural areas should account for these findings.

Access To Obstetric, Behavioral Health, And Surgical Inpatient Services After Hospital Mergers In Rural Areas.

Despite rural hospitals' central role in their communities, they are increasingly in financial distress and may merge with other hospitals or health systems, potentially reducing service lines that are less profitable or duplicative of services that the acquirer also offers. Using hospital discharge data from thirty-two Healthcare Cost and Utilization Project State Inpatient Databases from the period 2007-18, we examined the influence of rural hospital mergers on changes to inpatient service lines at hospitals and within their catchment areas. We found that merged hospitals were more likely than independent hospitals to eliminate maternal/neonatal and surgical care. Whereas the number of mental/substance use disorder-related stays decreased or remained stable at merged hospitals and within their catchment areas, it increased for unaffiliated hospitals and their catchment areas, indicating a potential unmet need in the communities of rural hospitals postmerger. Although a merger could salvage a hospital's sustainability, it also could reduce service lines and responsiveness to community needs.

Quality of Care Before and After Mergers and Acquisitions of Rural Hospitals.

Importance: Rural hospitals are increasingly merging with other hospitals. The associations of hospital mergers with quality of care need further investigation. Objectives: To examine changes in quality of care for patients at rural hospitals that merged compared with those that remained independent. Design, Setting, and Participants: In this case-control study, mergers at community nonrehabilitation hospitals in Federal Office of Rural Health Policy-eligible zip codes during 2009 to 2016 in 32 states were identified from Irving Levin Associates and the American Hospital Association Annual Survey. Outcomes for inpatient stays for select conditions and elective procedures were derived from the Healthcare Cost and Utilization Project State Inpatient Databases. Difference-in-differences linear probability models were used to assess premerger to postmerger changes in outcomes for patients discharged from merged vs comparison hospitals that remained independent. Data were analyzed from February to December 2020. Exposures: Hospital mergers. Main Outcomes and Measures: The main outcome was in-hospital mortality among patients admitted for acute myocardial infarction (AMI), heart failure, stroke, gastrointestinal hemorrhage, hip fracture, or pneumonia, as well as complications during stays for elective surgeries. Results: A total of 172 merged hospitals and 266 comparison hospitals were analyzed. After matching, baseline patient characteristics were similar for 303 747 medical stays and 175 970 surgical stays at merged hospitals and 461 092 medical stays and 278 070 surgical stays at comparison hospitals. In-hospital mortality among AMI stays decreased from premerger to postmerger at merged hospitals (9.4% to 5.0%) and comparison hospitals (7.9% to 6.3%). Adjusting for patient, hospital, and community characteristics, the decrease in in-hospital mortality among AMI stays 1 year postmerger was 1.755 (95% CI, -2.825 to -0.685) percentage points greater at merged hospitals than at comparison hospitals (P < .001). This finding held up to 4 years postmerger (DID, -2.039 [95% CI, -3.388 to -0.691] percentage points; P = .003). Greater premerger to postmerger decreases in mortality at merged vs comparison hospitals were also observed at 5 years postmerger among stays for heart failure (DID, -0.756 [95% CI, -1.448 to -0.064] percentage points; P = .03), stroke (DID, -1.667 [95% CI, -3.050 to -0.283] percentage points; P = .02), and pneumonia (DID, -0.862 [95% CI, -1.681 to -0.042] percentage points; P = .04). Conclusions and Relevance: These findings suggest that rural hospital mergers were associated with better mortality outcomes for AMI and several other conditions. This finding is important to enhancing rural health care and reducing urban-rural disparities in quality of care.

Comparison of 3 Safety-Net Hospital Definitions and Association With Hospital Characteristics.

Importance: No consensus exists on how to define safety-net hospitals (SNHs) for research or policy decision-making. Identifying which types of hospitals are classified as SNHs under different definitions is key to assessing policies that affect SNH funding. Objective: To examine characteristics of SNHs as classified under 3 common definitions. Design, Setting, and Participants: This cross-sectional analysis includes noncritical-access hospitals in the Healthcare Cost and Utilization Project State Inpatient Databases from 47 US states for fiscal year 2015, linked to the Centers for Medicare & Medicaid Services Hospital Cost Reports and to the American Hospital Association Annual Survey. Data were analyzed from March 1 through September 30, 2018. Exposures: Hospital characteristics including organizational characteristics, scope of services provided, and financial attributes. Main Outcomes and Measures: Definitions of SNH based on Medicaid and Medicare Supplemental Security Income inpatient days historically used to determine Medicare Disproportionate Share Hospital (DSH) payments; Medicaid and uninsured caseload; and uncompensated care costs. For each measure, SNHs were defined as those within the top quartile for each state. Results: The 2066 hospitals in this study were distributed across the Northeast (340 [16.5%]), Midwest (587 [28.4%]), South (790 [38.2%]), and West (349 [16.9%]). Concordance between definitions was low; 269 hospitals (13.0%) or fewer were identified as SNHs under any 2 definitions. Uncompensated care captured smaller (200 of 523 [38.2%]) and more rural (65 of 523 [12.4%]) SNHs, whereas DSH index and Medicaid and uncompensated caseload identified SNHs that were larger (264 of 518 [51.0%] and 158 of 487 [32.4%], respectively) and teaching facilities (337 of 518 [65.1%] and 229 of 487 [47.0%], respectively) that provided more essential services than non-SNHs. Uncompensated care also distinguished remarkable financial differences between SNHs and non-SNHs. Under the uncompensated care definition, median (interquartile range [IQR]) bad debt ($27.1 [$15.5-$44.3] vs $12.8 [$6.7-$21.6] per $1000 of operating expenses; P < .001) and charity care ($19.9 [$9.3-$34.1] vs $9.1 [$4.0-$18.7] per $1000 of operating expenses) were twice as high and median (IQR) unreimbursed costs ($32.6 [$12.4-$55.4] vs $23.6 [$9.0-$42.7] per $1000 of operating expenses; P < .001) were 38% higher for SNHs than for non-SNHs. Safety-net hospitals defined by uncompensated care burden had lower median (IQR) total (4.7% [0%-9.9%] vs 5.8% [1.2%-11.2%]; P = .003) and operating (0.3% [-8.0% to 7.2%] vs 2.3% [-3.9% to 8.9%]; P < .001) margins than their non-SNH counterparts, whereas differences between SNH and non-SNH profit margins generally were not statistically significant under the other 2 definitions. Conclusions and Relevance: Different SNH definitions identify hospitals with different characteristics and financial conditions. The new DSH formula, which accounts for uncompensated care, may lead to redistributed payments across hospitals. Our results may inform which types of hospitals will experience funding changes as DSH payment policies evolve.

Early Impact of the Affordable Care Act Coverage Expansion on Safety-Net Hospital Inpatient Payer Mix and Market Shares.

OBJECTIVE: To examine the impact of the Affordable Care Act's coverage expansion on safety-net hospitals (SNHs). STUDY SETTING: Nine Medicaid expansion states. STUDY DESIGN: Differences-in-differences (DID) models compare payer-specific pre-post changes in inpatient stays of adults aged 19-64 years at SNHs and non-SNHs. DATA COLLECTION METHODS: 2013-2014 Healthcare Cost and Utilization Project State Inpatient Databases. PRINCIPAL FINDINGS: On average per quarter postexpansion, SNHs and non-SNHs experienced similar relative decreases in uninsured stays (DID = -2.2 percent, p = .916). Non-SNHs experienced a greater percentage increase in Medicaid stays than did SNHs (DID = 13.8 percent, p = .041). For SNHs, the average decrease in uninsured stays (-146) was similar to the increase in Medicaid stays (153); privately insured stays were stable. For non-SNHs, the decrease in uninsured (-63) plus privately insured (-33) stays was similar to the increase in Medicaid stays (105). SNHs and non-SNHs experienced a similar absolute increase in Medicaid, uninsured, and privately insured stays combined (DID = -16, p = .162). CONCLUSIONS: Postexpansion, non-SNHs experienced a greater percentage increase in Medicaid stays than did SNHs, which may reflect patients choosing non-SNHs over SNHs or a crowd-out of private insurance. More research is needed to understand these trends.

Measuring Mortality Performance: How Did Safety-Net Hospitals Compare With Other Hospitals?

BACKGROUND: Safety-net hospitals (SNHs) tend to be weaker in financial condition than other hospitals, leading to a concern about how the quality of care at these hospitals would compare to other hospitals. OBJECTIVES: To assess mortality performance of SNHs using all-payer databases and measures for a broad range of conditions and procedures. DESIGN: Longitudinal analysis of hospitals from 2006 through 2011 with data from the Healthcare Cost and Utilization Project State Inpatient Databases, the American Hospital Association Annual Survey, and the Area Health Resources File. SUBJECTS: A total of 1891 urban, nonfederal, general acute hospitals from 31 states. METHODS: SNHs were identified by the percentage of Medicaid and uninsured patients. Hospital mortality performance was measured by 2 composites covering 6 common medical conditions and 4 surgical procedures with risk adjustment for patient characteristics. Differences in each composite between SNHs and non-SNHs were estimated through generalized estimating equations to control for hospital factors and community resources. RESULTS: Inpatient mortality rates declined over time for all hospitals. Small differences in risk-adjusted mortality rates between SNHs and non-SNHs were found only among teaching hospitals. After controlling for hospital factors, these differences were substantially reduced and remained significant only for surgical mortality rates. The small gap in surgical mortality rates diminished in later years. CONCLUSIONS: SNHs appeared to perform equally well as other hospitals in medical and surgical mortality measures. Policymakers should continue to monitor the quality of care at SNHs and ensure that it would not decline under the current value-based purchasing program.

An Examination of Hospital Nurse Staffing and Patient Experience with Care: Differences between Cross-Sectional and Longitudinal Estimates.

OBJECTIVE: To study the association between hospital nurse staffing and Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) scores. DATA SOURCES: State hospital financial and utilization reports, Healthcare Cost and Utilization Project State Inpatient Databases, HCAHPS survey, and American Hospital Association Annual Survey of Hospitals. STUDY DESIGN: Retrospective study using cross-sectional and longitudinal models to estimate the effect of nurse staffing levels and skill mix on seven HCAHPS measures. DATA COLLECTION/EXTRACTION METHODS: Hospital-level data measuring nurse staffing, patient experience, and hospital characteristics from 2009 to 2011 for 341 hospitals (977 hospital years) in California, Maryland, and Nevada. PRINCIPAL FINDINGS: Nurse staffing level (i.e., number of licensed practical nurses and registered nurses per 1,000 inpatient days) was significantly and positively associated with all seven HCAHPS measures in cross-sectional models and three of seven measures in longitudinal models. Nursing skill mix (i.e., percentage of all staff who are registered nurses) was significantly and negatively associated with scores on one measure in cross-sectional models and none in longitudinal models. CONCLUSIONS: After controlling for unobserved hospital characteristics, the positive influences of increased nurse staffing levels and skill mix were relatively small in size and limited to a few measures of patients' inpatient experience.

Understanding Patient, Provider, and System Factors Related to Medicaid Readmissions.

BACKGROUND: Efforts on reducing hospital readmissions, which are intended to improve quality and reduce costs, tend to focus on elderly Medicare beneficiaries without recognition of another high-risk population--adult nonmaternal Medicaid patients. This study was undertaken to understand the complexity of Medicaid readmission issues at the patient, provider, and system levels. METHODS: Multiple qualitative methods, including site visits to nine safety-net hospitals, patient/family/caregiver inter views, and semistructured interviews with health plans and state Medicaid agencies, were used in 2012 and 2013 to obtain information on patient, provider, and system issues related to Medicaid readmissions; strategies considered or currently used to address those issues; and any perceived financial, regulatory or, other policy factors inhibiting or facilitating readmission reduction efforts. RESULTS: Significant risk factors for Medicaid readmissions included financial stress, high prevalence of mental health and substance abuse disorders, medication nonadherence, and housing instability. Lacking awareness on Medicaid patients' high risk, a sufficient business case, and proven strategies for reducing readmissions were primary barriers for providers. Major hurdles at the system level included shortage of primary care and mental health providers, lack of coordination among providers, lack of partnerships between health plans and providers, and limited data capacity for realtime monitoring of readmissions. CONCLUSIONS: The intertwining of behavioral, socioeconomic, and health factors; the difficulty of accessing appropriate care in the outpatient setting; the lack of clear financial incentives for health care providers to reduce readmissions; and the fragmentation of the current health care system warrant greater attention and more concerted efforts from all stakeholders to reduce Medicaid readmissions.

Examining the value of inpatient nurse staffing: an assessment of quality and patient care costs.

BACKGROUND: Inpatient quality deficits have important implications for the health and well-being of patients. They also have important financial implications for payers and hospitals by leading to longer lengths of stay and higher intensity of treatment. Many of these costly quality deficits are particularly sensitive to nursing care. OBJECTIVE: To assess the effect of nurse staffing on quality of care and inpatient care costs. DESIGN: Longitudinal analysis using hospital nurse staffing data and the Healthcare Cost and Utilization Project State Inpatient Databases from 2008 through 2011. SUBJECTS: Hospital discharges from California, Nevada, and Maryland (n=18,474,860). METHODS: A longitudinal, hospital-fixed effect model was estimated to assess the effect of nurse staffing levels and skill mix on patient care costs, length of stay, and adverse events, adjusting for patient clinical and demographic characteristics. RESULTS: Increases in nurse staffing levels were associated with reductions in nursing-sensitive adverse events and length of stay, but did not lead to increases in patient care costs. Changing skill mix by increasing the number of registered nurses, as a proportion of licensed nursing staff, led to reductions in costs. CONCLUSIONS: The study findings provide support for the value of inpatient nurse staffing as it contributes to improvements in inpatient care; increases in staff number and skill mix can lead to improved quality and reduced length of stay at no additional cost.

Facing the recession: how did safety-net hospitals fare financially compared with their peers?

OBJECTIVE: To examine the effect of the recession on the financial performance of safety-net versus non-safety-net hospitals. DATA SOURCES/STUDY SETTING: Agency for Healthcare Research and Quality Hospital Cost and Utilization Project State Inpatient Databases, Medicare Cost Reports, American Hospital Association Annual Survey, InterStudy, and Area Health Resource File. STUDY DESIGN: Retrospective, longitudinal panel of hospitals, 2007-2011. Safety-net hospitals were identified using percentage of patients who were Medicaid or uninsured. Generalized estimating equations were used to estimate average effects of the recession on hospital operating and total margins, revenues and expenses in each year, 2008-2011, comparing safety-net with non-safety-net hospitals. DATA COLLECTION/EXTRACTION METHODS: 1,453 urban, nonfederal, general acute hospitals in 32 states with complete data. PRINCIPAL FINDINGS: Safety-net hospitals, as identified in 2007, had lower operating and total margins. The gap in operating margin between safety-net and non-safety-net hospitals was sustained throughout the recession; however, total margin was more negatively affected for non-safety-net hospitals in 2008. Higher percentages of Medicaid and uninsured patients were associated with lower revenue in private hospitals in all years, and lower revenue and expenses in public hospitals in 2011. CONCLUSIONS: Safety-net hospitals may not be disproportionately vulnerable to macro-economic fluctuations, but their significantly lower margins leave less financial cushion to weather sustained financial pressure.

Medicaid admissions and readmissions: understanding the prevalence, payment, and most common diagnoses.

Reducing hospital readmissions is a way to improve care and reduce avoidable costs. However, there have been few studies of readmissions in the Medicaid population. We sought to characterize acute care hospital admissions and thirty-day readmissions in the Medicaid population through a retrospective analysis in nineteen states. We found that Medicaid readmissions were both prevalent (9.4 percent of all admissions) and costly ($77 million per state) and that they represented 12.5 percent of Medicaid payments for all hospitalizations. Five diagnostic groups appeared to drive Medicaid readmissions, accounting for 57 percent of readmissions and 49 percent of hospital payments for readmissions. The most prevalent diagnostic categories were mental and behavioral disorders and diagnoses related to pregnancy, childbirth, and their complications, which together accounted for 31.2 percent of readmissions. This analysis, conducted through the Medicaid Medical Directors Learning Network, allows Medicaid medical directors to better understand the nature and prevalence of hospital use in the Medicaid population and provides a baseline for measuring improvement.

Hospital cost and quality performance in relation to market forces: an examination of U.S. community hospitals in the "post-managed care era".

Managed care substantially transformed the U.S. healthcare sector in the last two decades of the twentieth century, injecting price competition among hospitals for the first time in history. However, total HMO enrollment has declined since 2000. This study addresses whether managed care and hospital competition continued to show positive effects on hospital cost and quality performance in the "post-managed care era." Using data for 1,521 urban hospitals drawn from the Healthcare Cost and Utilization Project, we examined hospital cost per stay and mortality rate in relation to HMO penetration and hospital competition between 2001 and 2005, controlling for patient, hospital, and other market characteristics. Regression analyses were employed to examine both cross-sectional and longitudinal variation in hospital performance. We found that in markets with high HMO penetration, increase in hospital competition over time was associated with decrease in mortality but no change in cost. In markets without high HMO penetration, increase in hospital competition was associated with increase in cost but no change in mortality. Overall, hospitals in high HMO penetration markets consistently showed lower average costs, and hospitals in markets with high hospital competition consistently showed lower mortality rates. Hospitals in markets with high HMO penetration also showed lower mortality rates in 2005 with no such difference found in 2001. Our findings suggest that while managed care may have lost its strength in slowing hospital cost growth, differences in average hospital cost associated with different levels of HMO penetration across markets still persist. Furthermore, these health plans appear to put quality of care on a higher priority than before.

Likelihood of hospital readmission after first discharge: Medicare Advantage vs. fee-for-service patients.

This study tests whether the likelihood of hospital readmission within 30 days of discharge is different for enrollees in Medicare Advantage plans versus the standard fee-for-service program. A key requirement is to control for self-selection into Advantage plans. The study uses statewide inpatient databases maintained by the Agency for Healthcare Research and Quality for five states in 2006. The type of Medicare coverage is known, along with an encrypted patient identifier. We identify eligible first discharges and the first readmission within 30 days. We use selected area characteristics as instrumental variables for enrollment in Advantage plans and apply a bivariate probit analysis. Descriptively, there is a slightly lower likelihood of readmission for Advantage plan enrollees. However, the Advantage plan patients are younger and less severely ill. After risk adjustment and control for self-selection, the enrollees in Advantage plans have a substantially higher likelihood of readmission. Recognizing caveats and limitations, the study supports informing Medicare beneficiaries about the rates of readmission for Advantage plans in their area. Analytical methods to adjust for self-selection into particular plans or plan types should be considered when possible.

Enhancing board oversight on quality of hospital care: an agency theory perspective.

BACKGROUND: Community hospitals in the United States are almost all governed by a governing board that is legally accountable for the quality of care provided. Increasing pressures for better quality and safety are prompting boards to strengthen their oversight function on quality. PURPOSE: In this study, we aimed to provide an update to prior research by exploring the role and practices of governing boards in quality oversight through the lens of agency theory and comparing hospital quality performance in relation to the adoption of those practices. METHODOLOGY: Data on board practices from a survey conducted by The Governance Institute in 2007 were merged with data on hospital quality drawn from two federal sources that measured processes of care and mortality. The study sample includes 445 public and private not-for-profit hospitals. We used factor analysis to explore the underlying dimensions of board practices. We further compared hospital quality performance by the adoption of each individual board practice. FINDINGS: Consistent with the agency theory, the 13 board practices included in the survey appear to center around enhancing accountability of the board, management, and the medical staff. Reviewing the hospital's quality performance on a regular basis was the most common practice. A number of board practices, not examined in prior research, showed significant association with better performance on process of care and/or risk-adjusted mortality: requiring major new clinical programs to meet quality-related criteria, setting some quality goals at the "theoretical ideal" level, requiring both the board and the medical staff to be as involved as management in setting the agenda for discussion on quality, and requiring the hospital to report its quality/safety performance to the general public. PRACTICE IMPLICATIONS: Hospital governing boards should examine their current practices and consider adopting those that would enhance the accountability of the board itself, management, and the medical staff.

Do Medicare Advantage enrollees tend to be admitted to hospitals with better or worse outcomes compared with fee-for-service enrollees?

The hospitals selected by or for Medicare beneficiaries might depend on whether the patient is enrolled in a Medicare Advantage (MA) plan. A theoretical model of profit maximization by MA plans takes into account the tradeoffs of consumer preferences for annual premium versus outcomes of care in the hospital and other attributes of the plan. Hospital discharge databases for 13 states in 2006, maintained by the Agency for Healthcare Research and Quality, are the main source of data. Risk-adjusted mortality rates are available for all non-maternity adult patients in each of 15 clinical categories in about 1,500 hospitals. All-adult postoperative safety event rates covering 9 categories of events are calculated for surgical cases in about 900 hospitals. Instrumental variables are used to address potential endogeneity of the choice of a MA plan. The key findings are these: enrollees in MA plans tend to be treated in hospitals with lower resource cost and higher risk-adjusted mortality compared to Fee-for-Service (FFS) enrollees. The risk-adjusted mortality measure is about 1.5 percentage points higher for MA plan enrollees than the overall mean of 4%. However, the rate of safety events in surgical patients favors MA plan enrollees--the rate is 1 percentage point below the average of 3.5%. These discrepant results are noteworthy and are plausibly due to greater discretion by the health plan in approving patients for elective surgery and as well as selecting hospitals for surgical patients. Emergency patients are generally excluded for the safety outcome measures. In addition, the current mortality measures may not adequately represent all surgical patients. Such caveats should be prominently highlighted when presenting comparative data. With that proviso, the study justifies informing Medicare beneficiaries about the mortality and safety outcome measures for hospitals being used by a MA plan compared to hospitals used by FFS enrollees.

Do patient safety events increase readmissions?

OBJECTIVE: Adverse safety events in the hospital could impose extra costs not only due to longer stays and corrective treatments, but also due to deaths and readmissions. The effects of safety events on readmissions have rarely been analyzed. Large, all-payer and all-diagnosis databases permit new tests. This study will simultaneously test the effects of safety events on risks of deaths and readmission. STUDY DESIGN: The population is a selection of almost 1.5 million adult surgery patients initially treated in 1088 short stay hospitals. These are patients at risk for at least 1 of 9 types of patient safety event, as specified in software in the public domain from the Agency for Healthcare Research and Quality. The main data sources are 7 statewide databases of hospitalizations in 2004, maintained by Agency for Healthcare Research and Quality's Healthcare Cost and Utilization Project. We control for many factors affecting readmission or death, particularly the severity of illness, chronic comorbidities, age, and payer group. Separate models are used for each type of safety event and a composite model is used for any safety event. PRINCIPAL FINDINGS: Among the patients at risk for any of the patient safety events, 2.6% had at least one safety event. The 3-month readmission rate was about 17% for those with no safety event, but about 25% when a safety event was recorded. The corresponding rates for readmission within 1 month were 11% and 16%. The in-hospital death rate was 1.3% with no safety event, but 9.2% with a safety event. After risk adjustment, the relative risk of readmission within 3 months was about 1.20 (P < 0.01), ranging from 1.14 to 1.56 for specific types of events. The risk-adjusted result for readmission within 1 month associated with at least one safety event was 1.17 (P < 0.01). However, the models for specific safety events gave a significantly high risk of readmission within 1 month for only 2 of the more common types of safety events. CONCLUSIONS: Hospital readmissions are one way that safety events can have costly consequences. More attention is warranted to assess the full extra cost of safety events, the factors influencing the rate of safety events, and strategies for health plans to improve incentives for safety.

Board oversight of quality: any differences in process of care and mortality?

In response to legal and accreditation mandates as well as pressures from purchasers and consumers for quality improvement, hospital governing boards seek to improve their oversight of quality of care by adopting various practices. Based on a previous survey of hospital presidents/chief executive officers, this study examines differences in hospital quality performance associated with the adoption of particular practices in board oversight of quality. Quality was measured by performance in process of care and risk-adjusted mortality, using the Hospital Compare data from the Centers for Medicare & Medicaid Services and the Healthcare Cost and Utilization Project inpatient databases of the Agency for Healthcare Research and Quality. Board practices found to be associated with better performance in both process of care and mortality include (1) having a board quality committee; (2) establishing strategic goals for quality improvement; (3) being involved in setting the quality agenda for the hospital; (4) including a specific item on quality in board meetings; (5) using a dashboard with national benchmarks that includes indicators for clinical quality, patient safety, and patient satisfaction; and (6) linking senior executives' performance evaluation to quality and patient safety indicators. Involvement of physician leadership in the board quality committee further enhanced the hospital's quality performance. Taken together, these findings seem to support the will-execution-constancy of purpose framework on improving the effectiveness of hospital boards in overseeing quality. Future study should examine how specific board practices influence the culture and operations of the hospital that lead to better quality of care.