Early Financial Impact of the COVID-19 Pandemic on U.S. Hospitals.

GOAL: The COVID-19 pandemic has left a significant impact on hospitals' operations, expenses, and revenues. However, little is known about the pandemic's financial impact on rural and urban hospitals. Our main objective was to analyze how hospital profitability changed during the first year of the pandemic. We specifically studied the association between COVID-19 infections and hospitalizations and county-level variables with operating margins (OMs) and total margins (TMs). METHODS: We obtained data from Medicare Cost Reports, the American Hospital Association Annual Survey Database, and the Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry (CDC/ATSDR) for 2012-2020. Our final dataset consisted of an unbalanced panel with 17,510 observations for urban hospitals and 17,876 observations for rural hospitals. We estimated separate hospital fixed-effects models for urban and rural hospitals' OMs and TMs. The fixed-effects models controlled for time-invariant differences across hospitals. PRINCIPAL FINDINGS: In our review of the early impact of the COVID-19 pandemic on rural and urban hospitals' profits as well as trends in OMs and TMs from 2012 to 2020, we found that OMs were inversely related to the duration of hospitals' exposure to infections in urban and rural locations. In contrast, TMs and hospitals' exposures had a positive relationship. Government relief funds, a source of nonoperating revenue, apparently allowed most hospitals to avoid financial distress from the pandemic. We also found a positive relationship between the magnitude of weekly adult hospitalizations and OMs in urban and rural hospitals. Size, participation in group purchasing organizations (GPOs), and occupancy rates were positively related to OMs, with size and participation in GPOs relating to scale economies and occupancy rates reflecting capital efficiencies. PRACTICAL APPLICATIONS: Hospitals' OMs have been declining since 2014. The pandemic made this decline worse, especially for rural hospitals. Federal relief funds, along with investment income, helped hospitals remain financially solvent during the pandemic. However, investment income and temporary federal aid are insufficient to sustain financial well-being. Executives need to explore cost-saving opportunities such as joining a GPO. Small rural hospitals with low occupancy and low community COVID-19 hospitalization rates have been particularly vulnerable to the financial impact of the pandemic. Although federal relief funds have limited hospital financial distress induced by the pandemic, we maintain that the funds should have been more effectively targeted, as the mean TM increased to its highest level in a decade. The disparate results of our analysis of OMs and TMs illustrate the utility of using multiple measures of profitability.

Assessing overall, technical, and scale efficiency among home health care agencies.

While home health care agencies (HHAs) play a vital role in the production of health, little research has been performed gauging their efficiency. Employing a robust approach to data envelopment analysis (DEA) we assessed overall, technical, and scale efficiency on a nationwide sample of HHAs. After deriving the three efficiency measures, we regressed these scores on a variety of environmental factors. We found that HHAs, on average, could proportionally reduce inputs by 28 % (overall efficiency), 23 % (technical efficiency) and 6 % (scale efficiency). For-profit ownership was positively associated with improvements in overall efficiency and technical efficiency and chain ownership was positively associated with global efficiency. There were also state-by-state variations on all the efficiency measures. As home health becomes an increasingly important player in the health care system, and its share of national health expenditures increases, it has become important to understand the cost structure of the industry and the potential for efficiencies. Therefore, further research is recommended as this sector continues to grow.

Inefficiency differences between critical access hospitals and prospectively paid rural hospitals.

The Medicare prospective payment system (PPS) contains incentives for hospitals to improve efficiency by placing them at financial risk to earn a positive margin on services rendered to Medicare patients. Concerns about the financial viability of small rural hospitals led to the implementation of the Medicare Rural Hospital Flexibility Program (Flex Program) of 1997, which allows facilities designated as critical access hospitals (CAHs) to be paid on a reasonable cost basis for inpatient and outpatient services. This article compares the cost inefficiency of CAHs with that of nonconverting rural hospitals to contrast the performance of hospitals operating under the different payment systems. Stochastic frontier analysis (SFA) was used to estimate cost inefficiency. Analysis was performed on pooled time-series, cross-sectional data from thirty-four states for the period 1997-2004. Average estimated cost inefficiency was greater in CAHs (15.9 percent) than in nonconverting rural hospitals (10.3 percent). Further, there was a positive association between length of time in the CAH program and estimated cost inefficiency. CAHs exhibited poorer values for a number of proxy measures for efficiency, including expenses per admission and labor productivity (full-time-equivalent employees per outpatient-adjusted admission). Non-CAH rural hospitals had a stronger correlation between cost inefficiency and operating margin than CAH facilities did.

Specialty hospital market proliferation: Strategic implications for general hospitals.

BACKGROUND: Since the early 1990s, specialty hospitals have been continuously increasing in number. A moratorium was passed in 2003 that prohibited physicians' referrals of Medicare patients to newly established specialty hospitals if the physician has ownership stakes in the hospital. Although this moratorium expired in effect in 2007, many are still demanding that the government pass new policies to discourage the proliferation of specialty hospitals. PURPOSE: This study aimed at examining the regulatory and environmental forces that influence specialty hospitals founding rate. Specifically, we use the resource partitioning theory to investigate the relationship between general hospitals closure rates and the market entry of specialty hospitals. This study will help managers of general hospitals in their strategic thinking and planning. METHODOLOGY: We rely on secondary data resources, which include the American Hospital Association, Area Resource file, census, and Center for Medicare and Medicaid Services data, to perform a longitudinal analysis of the founding rate of specialty hospital in the 48 states. Specifically, we use the negative binomial generalized estimating equation approach available through Stata 9.0 to study the effect of general hospitals closure rate and environmental variables on the proliferation of specialty hospitals. FINDINGS: Specialty hospitals founding rate seems to be significantly related to general hospitals closure rates. Moreover, results indicate that economic, supply, regulatory, and financial conditions determine the founding rate of specialty hospitals in different states. PRACTICE IMPLICATIONS: The results from this study indicate that the closure of general hospitals creates market conditions that encourage the market entry of specialized health care delivery forms such as specialty hospitals. Managers of surviving general hospitals have to view the closure of other general hospitals not just as an opportunity to increase market share but also as a threat of competition from new forms of health care organizations.

Stochastic frontier analysis of hospital inefficiency: a review of empirical issues and an assessment of robustness.

Twenty stochastic frontier analysis (SFA) studies of hospital inefficiency in the United States were analyzed. Results from best-practice methods were compared against previously used methods in hospital studies to ascertain the robustness of SFA in estimating cost inefficiency. To compare past studies and analyze new data, SFA methods were varied by (a) the assumptions of the structure of costs and distribution of the error term, (b) inclusion of quality and product descriptor measures, and (c) use of simultaneous and two-stage estimation techniques. SFA results were relatively insensitive to several model variations.

Hospital efficiency and debt.

U.S. Hospitals rely heavily on debt financing to fund major capital investments. Hospital efficiency is at least partly determined by the amount and quality of plant and equipment it uses. As such, a hospital's access to debt and credit rating may be related to its efficiency. This study explores this relationship using a broad sample of hospitals and associated bond issuance histories. Employing stochastic frontier analysis (SFA), we measure cost inefficiency to gauge the impact of debt issuance and debt rating. We find that hospitals with recent bond issues were less inefficient. Although we do not find a perfectly linear relationship between debt rating and inefficiency, we have evidence that hints at such a relation. Finally, we find an increase in inefficiency in the years following bond issues, consistent with the possibility of a debt death spiral.

Hospital inefficiency: what is the impact of membership in different types of systems?

The primary objective of this study is to assess whether systematic differences in inefficiency are associated with hospital membership in different types of systems. We employed the Battese/Coelli simultaneous stochastic frontier analysis (SFA) technique to estimate hospital cost inefficiency. Mean estimated inefficiency was 8.42%. Membership in different types of systems was related to estimated cost inefficiency (p < .05). Compared to hospitals that were members of centralized health systems, membership in centralized physician/insurance or decentralized systems was associated with decreased inefficiency; membership in independent systems was associated with increased inefficiency.

Correlates of hospital provision of prevention and health promotion services.

This study investigates the factors associated with hospital provision of prevention and health promotion services. The authors conceptualize the provision of these services as a hospital response to the community health concerns of environmental stakeholders. The response depends on hospital recognition and interpretation of institutional and resource dependence pressures and is related to interorganizational linkages, resource dependencies, and information processing structure. Data for the study came from 3,453 U.S. hospitals. The authors found that hospital provision of prevention and health promotion services is positively related to alliance and network membership, the diffusion of such services among other area hospitals, the use of community health status information, and hospital size. Also, for-profit hospitals provide fewer prevention and health promotion services than not-for-profit hospitals. These findings have policy and management implications.

Performance of major teaching hospitals during the 1990s: adapting to turbulent times.

A panel design was used to analyze changes in performance variables related to profitability, volume, and efficiency in a national sample of major teaching hospitals from 1990 to 1999. After steady increases beginning in 1990, the average total margin ratio peaked in 1996 and by 1999 it declined by almost 50 percent. Average operating margins were negative every year. Major teaching hospitals responded to financial pressures by expanding outpatient activity, reducing length of stay, downsizing inpatient capacity, and increasing labor productivity. Membership in multi-hospital systems increased by over 70 percent through the 1990s. Increases in average real cost per adjusted admission peaked in 1994 and fell by 6 percent from 1994 to 1999.

The association of hospital cost-inefficiency with certificate-of-need regulation.

Certificate-of-need (CON) regulations can promote hospital efficiency by reducing duplication of services; however, there are practical and theoretical reasons why they might be ineffective, and the empirical evidence generated has been mixed. This study compares the cost-inefficiency of urban, acute care hospitals in states with CON regulations against those in states without CON requirements. Stochastic frontier analysis was performed on pooled time-series, cross-sectional data from 1,552 hospitals in 37 states for the period 2005 to 2009 with controls for variations in hospital product mix, quality, and patient burden of illness. Average estimated cost-inefficiency was less in CON states (8.10%) than in non-CON states (12.46%). Results suggest that CON regulation may be an effective policy instrument in an era of a new medical arms race. However, broader analysis of the effects of CON regulation on efficiency, quality, access, prices, and innovation is needed before a policy recommendation can be made.

What have we learned from the application of stochastic frontier analysis to U.S. hospitals?

This article focuses on the lessons learned from stochastic frontier analysis studies of U.S. hospitals, of which at least 27 have been published. A brief discussion of frontier techniques is provided, but a technical review of the literature is not included because overviews of estimation issues have been published recently. The primary focus is on the correlates of hospital inefficiency. In addition to examining the association of market pressures and hospital inefficiency, the authors also examined the relationship between inefficiency and hospital behavior (e.g., hospital exits) and inefficiency and other measures of hospital performance (e.g., outcome measures of quality). The authors found that consensus is emerging on the relationship of some factors to hospital efficiency; however, further research is needed to better understand others. The application of stochastic frontier analysis to specific policy issues is in its infancy; however, the methodology holds promise for being useful in certain contexts.

Response to modeling and notation of DEA with strong and weak disposable outputs.

In this brief communiction we respond to comments on our earlier publication, which contained some notational errors.

Translating frontiers into practice: taking the next steps toward improving hospital efficiency.

Frontier techniques, including data envelopment analysis (DEA) and stochastic frontier analysis (SFA), have been used to measure health care provider efficiency in hundreds of published studies. Although these methods have the potential to be useful to decision makers, their utility is limited by both methodological questions concerning their application, as well as some disconnect between the information they provide and the insight sought by decision makers. The articles in this special issue focus on the application of DEA and SFA to hospitals with the hope of making these techniques more accurate and accessible to end users. This introduction to the special issue highlights the importance of measuring the efficiency of health care providers, provides a background on frontier techniques, contains an overview of the articles in the special issue, and suggests a research agenda for DEA and SFA.

Hospital quality, efficiency, and input slack differentials.

OBJECTIVE: To use an advance in data envelopment analysis (DEA) called congestion analysis to assess the trade-offs between quality and efficiency in U.S. hospitals. STUDY SETTING: Urban U.S. hospitals in 34 states operating in 2004. STUDY DESIGN AND DATA COLLECTION: Input and output data from 1,377 urban hospitals were taken from the American Hospital Association Annual Survey and the Medicare Cost Reports. Nurse-sensitive measures of quality came from the application of the Patient Safety Indicator (PSI) module of the Agency for Healthcare Research and Quality (AHRQ) Quality Indicator software to State Inpatient Databases (SID) provided by the Healthcare Cost and Utilization Project (HCUP). DATA ANALYSIS: In the first step of the study, hospitals' relative output-based efficiency was determined in order to obtain a measure of congestion (i.e., the productivity loss due to the occurrence of patient safety events). The outputs were adjusted to account for this productivity loss, and a second DEA was performed to obtain input slack values. Differences in slack values between unadjusted and adjusted outputs were used to measure either relative inefficiency or a need for quality improvement. PRINCIPAL FINDINGS: Overall, the hospitals in our sample could increase the total amount of outputs produced by an average of 26 percent by eliminating inefficiency. About 3 percent of this inefficiency can be attributed to congestion. Analysis of subsamples showed that teaching hospitals experienced no congestion loss. We found that quality of care could be improved by increasing the number of labor inputs in low-quality hospitals, whereas high-quality hospitals tended to have slack on personnel. CONCLUSIONS: Results suggest that reallocation of resources could increase the relative quality among hospitals in our sample. Further, higher quality in some dimensions of care need not be achieved as a result of higher costs or through reduced access to health care.

Measuring hospital inefficiency: the effects of controlling for quality and patient burden of illness.

OBJECTIVE: To assess the impact of employing a variety of controls for hospital quality and patient burden of illness on the mean estimated inefficiency and relative ranking of hospitals generated by stochastic frontier analysis (SFA). STUDY SETTING: This study included urban U.S. hospitals in 20 states operating in 2001. DATA DESIGN/DATA COLLECTION: We took hospital data for 1,290 hospitals from the American Hospital Association Annual Survey and the Medicare Cost Reports. We employed a variety of controls for hospital quality and patient burden of illness. Among the variables we used were a subset of the quality indicators generated from the application of the Patient Safety Indicator and Inpatient Quality Indicator modules of the Agency for Healthcare Research and Quality, Quality Indicator software to the Healthcare Cost and Utilization Project (HCUP), State Inpatient Databases. Measures of a component of patient burden of illness came from the application of the Comorbidity Software to HCUP data. DATA ANALYSIS: We used SFA to estimate hospital cost-inefficiency. We tested key assumptions of the SFA model with likelihood ratio tests. PRINCIPAL FINDINGS: The measures produced by the Comorbidity Software appear to account for variations in patient burden of illness that had previously been masquerading as inefficiency. Outcome measures of quality can provide useful insight into a hospital's operations but may have little impact on estimated inefficiency once controls for structural quality and patient burden of illness have been employed. CONCLUSIONS: Choices about controlling for quality and patient burden of illness can have a nontrivial impact on mean estimated hospital inefficiency and the relative ranking of hospitals generated by SFA.

Analysis of uncompensated hospital care using a DEA model of output congestion.

Uncompensated care can create financial difficulties for hospitals. The problem is likely to worsen as the number of individuals lacking health insurance continues to grow. The objective of this study is to measure how uncompensated care affects hospitals' ability to provide the services for which they do receive compensation. Applying output-based data envelopment analysis (DEA) under various assumptions on the disposability of outputs to a sample of Pennsylvania hospitals, we find that, on average, hospitals could have produced 7% more output if they had all operated on the best-practice frontier and that uncompensated care reduced the production of other hospital outputs by 2%. Thus, even if hospitals were to operate efficiently, they might still face financial distress as a result of providing uncompensated care. The findings in our study suggest that policy makers should continue looking at ways to increase funding to hospitals providing uncompensated care while not distorting economic incentives to reduce excessive costs.

East-west: does it make a difference to hospital efficiencies in Ukraine?

Ukraine's history has given it a split personality (e.g. divergent cultural influences on economic and managerial behavior), as was observed in the recent political developments both prior to and following the December 2004 elections. Eastern regions were heavily influenced by Russo-Soviet rule, while western regions have more of a European outlook. This study, which is largely exploratory, compares recent trends in hospital efficiency in Ukraine to see if this split personality manifests itself in differential rates of improvement. Given the inflexibility of Soviet-style planned economies, it is hypothesized that western regions will show greater improvement in economic efficiency that can be attributed to higher levels of managerial and medical entrepreneurship. Data for this study comes from three oblasts (i.e. geopolitical regions), one in the west and two in the east, spanning from 1997 to 2001. Data envelopment analysis (DEA) was used to estimate technical efficiency for the hospitals. After correcting for bias, a second-stage Tobit regression was estimated. Results indicate that hospitals in the west improved efficiencies, while those in the east stayed constant. These western areas of the nation, being more amenable to western management and medical 'business' practice, may be quicker to pick up on new techniques to increase healthcare delivery efficiencies. This may stem from the more limited effects of a shorter history of incorporation into a Soviet-style planned and controlled economy in which individual decision-making and entrepreneurship was suppressed in favor of central decision-making by the state.

Impact of network and system use on hospital X-inefficiency.

A significant part of the restructuring in the health care industry has involved hospitals joining health networks and health systems. While the proclaimed purpose of this strategy has been to improve hospital performance, studies have found that not all member hospitals reap the desired outcomes. Variations in performance have been linked to, among other things, service provision at the network/system level versus individual hospital level. This study examined the impact of network and system use to provide services on hospital X-inefficiency (i.e., the difference between actual and optimal costs) in a national sample (n = 1,368) of U.S. urban, general, hospitals. Stochastic frontier analysis (SFA) revealed a mean hospital X-inefficiency of 14.85%. Results suggest that hospitals providing a moderate to high proportion of services at the network or system level were more efficient than hospitals that did not use networks or systems for service provision. Low users of networks or systems and nonusers had comparable levels of efficiency.

Service collaboration and hospital cost performance: direct and moderating effects.

BACKGROUND: Growing reliance on service provision through systems and networks creates the need to better understand the nature of the relationship between service collaboration and hospital performance and the conditions that affect this relationship. OBJECTIVE: We examine 1) the effects of service provision through health systems and health networks on hospital cost performance and 2) the moderating effects of market conditions and service differentiation on the collaboration-cost relationship. RESEARCH DESIGN: We used moderated regression analysis to test the direct and moderating effects. Data on 1368 private hospitals came from the 1998 AHA Annual Survey, Medicare Cost Reports, and Solucient. MEASURES: Service collaboration was measured as the proportion of hospital services provided at the system level and at the network level. Market conditions were measured by the levels of managed care penetration and competition in the hospital's market. RESULTS: The proportion of hospital services provided at the system level had a negative relationship with hospital cost. The relationship was curvilinear for network use. Degree of managed care penetration moderated the relationship between network-based collaboration and hospital cost. CONCLUSION: The benefits of service collaboration through systems and networks, as measured by reduced cost, depend on degree of collaboration rather than mere membership. In loosely structured collaborations such as networks, costs reduce initially but increase later as the extent of collaboration increases. The effect of network-based collaboration is also tempered by managed care penetration. These effects are not seen in more tightly integrated forms such as systems.