Cost efficiency of US hospitals: a stochastic frontier approach

This study examined the impact of managed care and other environmental factors on hospital inefficiency in 1631 US hospitals during the period 1990-1996. A panel, stochastic frontier regression model was used to estimate inefficiency parameters and inefficiency scores. The results suggest that mean estimated inefficiency decreased by about 28% during the study period. Inefficiency was negatively associated with health maintenance organization (HMO) penetration and industry concentration. It was positively related with Medicare share and for-profit ownership status.     

Cost Inefficiency in Washington Hospitals: A Stochastic Frontier Approach Using Panel Data

We analyze a sample of Washington State hospitals with a stochastic frontier panel data model, specifying the cost function as a generalized Leontief function which, according to a Hausman test, performs better in this case than the translog form. A one-stage FGLS estimation procedure which directly models the inefficiency effects improves the efficiency of our estimates. We find that hospitals with higher casemix indices or more beds are less efficient while for-profit hospitals and those with higher proportion of Medicare patient days are more efficient. Relative to the most efficient hospital, the average hospital is only about 67% efficient.     

Measuring hospital efficiency with frontier cost functions

This paper uses a stochastic frontier multiproduct cost function to derive hospital-specific measures of inefficiency. The cost function includes direct measures of illness severity, output quality, and patient outcomes to reduce the likelihood that the inefficiency estimates are capturing unmeasured differences in hospital outputs. Models are estimated using data from the AHA Annual Survey, Medicare Hospital Cost Reports, and MEDPAR. We explicitly test the assumption of output endogeneity and reject it in this application. We conclude that inefficiency accounts for 13.6 percent of total hospital costs. This estimate is robust with respect to model specification and approaches to pooling data across distinct groups of hospitals.     

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.     

How reliable are hospital efficiency estimates? Exploiting the dual to homothetic production

For scientific use, stochastic frontier estimates of hospital efficiency must be robust to plausible departures from the assumptions made by the investigator. Comparisons of alternative study designs, each well within the 'accepted' range according to current practice, generate similar mean inefficiencies but substantially different hospital rankings. The three alternative study contrasts feature (1) pooling vs partitioned estimates, (2) a cost function dual to a homothetic production process vs the translog, and (3) two conceptually valid but empirically different cost-of-capital measures. The results suggest caution regarding the use of frontier methods to rank individual hospitals, a use that seems to be required for reimbursement incentives, but they are robust when generating comparisons of hospital group mean inefficiencies, such as testing models that compare non-profits and for-profits by economic inefficiency. Demonstrations find little or no efficiency differences between these paired groups: non-profit vs for-profit; teaching vs non-teaching; urban vs rural; high percent of Medicare reliant vs low percent; and chain vs independent hospitals.     

Cost inefficiency and hospital health outcomes

This study explores the association between cost inefficiency and health outcomes in a national sample of acute-care hospitals in the US over the period 1999-2001, with health outcomes being measured by both mortality and complications rates. The empirical analysis examines health outcomes as a function of cost inefficiency and other determinants of outcomes, using stochastic frontier analysis to obtain hospital cost inefficiency scores. The results showed no systematic pattern of association between cost inefficiency and hospital health outcomes; the basic results were unchanged regardless of whether cost inefficiency was measured with or without using instrumental variables. The analysis also indicated, however, that the association between cost inefficiency and health outcomes may vary substantially across geographical regions. The study highlights the importance of distinguishing between 'good' costs that reflect the efficient use of resources and 'bad' costs that stem from waste and other forms of inefficiency. In particular, the study's results suggest that hospital programs focused on reducing cost inefficiency are unlikely to be associated with worsened hospital-level mortality or complications rates, while, on the other hand, across-the-board reductions in cost could well have adverse consequences on health outcomes by reducing efficient as well as inefficient costs.     

U.S. hospital efficiency and adoption of health information technology

This study empirically examines the association between hospital inefficiency and the decision to introduce electronic medical records (EMR) and computerized physician order entry (CPOE) in a national sample of U.S. general hospitals in urban areas in 2006. The main research question is whether the presence of hospital cost inefficiency or other factors driving inefficiency in the production process of a hospital explain low adoption rates of health information technology (HIT) in a hospital setting. We estimated a logistic regression of HIT adoption as a function of hospital cost inefficiency scores obtained using a stochastic frontier analysis. The results demonstrate that hospitals with a greater degree of cost inefficiency were more likely to introduce EMR, suggesting that the benefits of EMR implementation in terms of improved efficiency were likely to outweigh the costs of adoption compared to hospitals that are more efficient. The results showed no association between cost inefficiency and the CPOE adoption decision.     

Cost inefficiency and mortality rates in Florida hospitals

This study examines the relationship between health outcomes and cost inefficiency in Florida hospitals over the period 1999-2001, with health outcomes measured by risk-adjusted in-hospital mortality rates. Previous research has come to conflicting conclusions regarding the relationship between costs and health outcomes. We hypothesize that these seemingly conflicting findings are due to the fact that total cost has two components--cost that reflects the best use of resources under current circumstances and cost associated with waste or inefficiency. By isolating costs due to inefficiency, we can examine directly their relationship, if any, to hospital mortality rates, and begin to assess whether policies that create incentives for hospitals to increase efficiency have adverse effects on health outcomes. We regress an in-hospital mortality index for each hospital on a measure of the hospital's cost inefficiency, obtained from a stochastic cost frontier estimation, as well as on predicted mortality and a set of variables linked to mortality performance. Our results indicate a positive and significant relationship between a hospital's mortality performance and its inefficiency: on average, a one percentage point reduction in cost inefficiency would be associated with one fewer in-hospital death per 10,000 discharges, holding patient risk and other factors constant.     

Hospital mission and cost differences.

The results show no significant differences on average length of stay, cost per patient day, or cost per admission among non-profit, government, and for-profit hospitals when controlling for bed capacities, occupancy rates, number of Medicare/Medicaid days, and hospitals without nurseries. For-profit hospital manhours per patient day were significantly lower than non-profit and government hospitals. This is an important finding because patient-care delivery is labor-intensive. A majority of for-profit hospitals do not have nurseries, which means that they should have more manhours per patient day. As indicated earlier, the manhours for hospitals with nurseries are higher than those for hospitals without nurseries. This indicates cost-cutting behavior on the part of a majority of for-profit hospitals. This method of limiting expenditures by decreasing labor costs associated with certain services is consistent with profit-maximization. The findings of this study with regard to cost differences among non-profit and for-profit hospitals contradict previous research. However, a recent study by Kralewski, Gifford and Porter (1988) noted that whereas ownership, when considered alone, differentiates hospitals, when evaluated within each community, most of the investor-owned and non-for-profit hospital differences disappear. Similar questions have been raised as to whether non-profit hospitals truly differ from for-profit hospitals (Pauly 1987). Caution needs to be exercised in attempting to extrapolate the findings of this study, because of the dynamic health care environment. Hospital ownership changes over time, reimbursement rules affect behavior, and internal factors in organizational operation affect outcomes. These should be considered in future studies exploring organizational mission and cost differences.     

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.     

Cost and efficiency in nursing homes: a stochastic frontier approach

The average level of cost inefficiency in New York nursing homes is estimated at 29%, based on a two-year panel of 164 Skilled Nursing Facilities and 443 combination Skilled and Health Related Facilities. The stochastic frontier cost function is fit to the data utilizing the composed error model, wherein statistical noise and allocative and technical inefficiency are jointly estimated. There is no change in efficiency between 1987 and 1990, and it does not vary between for-profit and not-for-profit homes. Excessive managerial and supervisory personnel and diseconomies of size are linked to inefficient operation. Chronic excess demand is suggested as a cause of the high level of inefficiency.     

Comparing high- and low-performing hospitals using risk-adjusted excess mortality and cost inefficiency

This study examines characteristics associated with high- and low-performing hospitals, where performance is defined in terms of both mortality outcomes and efficiency. In particular, we use data for Florida hospitals in 1999-2001 to classify hospitals into performance groups based on both risk-adjusted excess mortality and cost efficiency. The results indicate that hospitals in the high-performing group were more likely to be for-profit, had higher occupancy rates, had proportionately more Medicare and proportionately fewer Medicaid and self-pay patients, used fewer patient-care personnel per admission, and had higher operating margins than all other hospitals. Hospitals in the low-performing group, on the other hand, were less likely to be for-profit, had more beds, used more patient-care personnel per admission, had lower pay per patient-care personnel, had higher average costs, and had lower operating margins than all other hospitals. Interestingly, managed care presence, measured by proportion of HMO-PPO admissions, was not a significant factor in differentiating hospital performance groups.     

医院效率评价方法的研究

目的探讨数据包络分析、随机前沿与岭回归3种评价模型之间的关系及特点，为今后医院效率的评价提供简捷的方法。方法对我国铁路系统1999年101家综合性医院的病案统计和业务收支资料，分别采用数据包络分析模型、随机前沿模型与岭回归模型进行分析。采用DEA、SPSSl0．0、LIMDEP统计软件处理数据。结果数据包络分析模型与随机前沿模型的效率值具有很强的线性关系（rs=0．866，P〈0．001）；岭回归模型的相对误差与随机前沿模型的低效率值存在着高度的正相关（rs=0．922，P〈0．001）。结论在评价单位的运行效率时，采用数据包络分析、随机前沿与岭回归3种评价方法结论是一致的。     

A Market, Operation, and Mission Assessment of Large Rural For-Profit Hospitals With Positive Cash Flow

CONTEXT: National benchmark data for 2002 indicate that large rural for-profit hospitals have a median cash flow margin of 19.5% compared to 9.2% for their nonprofit counterparts. PURPOSE: This study aims to gain insight regarding the driving factors behind the high cash flow performance of large rural for-profit hospitals. METHODS: Using 3 annual periods of Centers for Medicare and Medicaid cost report data with the last fiscal year ending between September 30, 2002, and August 30, 2003, the study found a cash flow margin of 21.5% for the large rural for-profit hospitals. All these facilities were owned by hospital management companies. To assess their underlying market, operational, and mission factors, these hospitals were compared to a similar comparison group of large rural nonprofit hospitals that are system owned and have positive cash flows. FINDINGS: Using logistic regression analysis, the study found lower operating expense per adjusted discharge and salary expense as a percentage of total operating expense among large rural for-profit, system-owned hospitals with positive cash flows relative to nonprofits with similar traits. CONCLUSION: Overall, the findings of this study reflect how these for-profit hospitals, which are owned by hospital management companies, focus on controlling their labor costs as well as operating costs per discharge in order to achieve a greater positive cash flow position.     

Impact of Critical Access Hospital Conversion on Beneficiary Liability

ABSTRACT: Context: While the Medicare Critical Access Hospital (CAH) program has improved the financial viability of small rural hospitals and enhanced access to care in rural communities, the program puts beneficiaries at risk for paying a larger share of the cost of services covered under the Medicare part B benefit. Purpose: This paper examines the impact of hospital conversion to CAH status on beneficiary out‐of‐pocket coinsurance payments for hospital outpatient services. Methods: The study is based on a retrospective observational design using administrative data from Medicare hospital cost reports and fee‐for‐service beneficiary claims from 1999 to 2003. The study compares changes in beneficiary co‐payments before versus after CAH conversion with payment trends among small rural non‐converting hospitals over the same period. Findings: Conversion to CAH status is associated with an increase in beneficiary coinsurance payments per outpatient visit of $17.19, equivalent to 34% of the sample average. However, CAH designation had no significant effect on the share of outpatient costs paid by the beneficiary. Most of the increase in beneficiary liability associated with conversion is attributable to the provision of more services per outpatient visit. Conclusions: While this and other studies show that conversion to CAH status results in more intensive outpatient care, CAH conversion does not appear to inadvertently create financial barriers to accessing ambulatory services in remote rural communities by forcing beneficiaries to pay a higher share of their Medicare part B costs.     

随机前沿成本模型在中医院技术效率评价中的应用

目的 分析全国中医院技术效率现状，探讨低效率的影响因素，提出针对性建议。方法 运用平行数据随机前沿成本模型，分析全国60所中医院的技术效率；运用多元逐步回归分析，探讨低效率的影响因素。结果 60所中医院的平均低效率为22．59％，且随东部、中部、西部有低效率增加的趋势；病床使用率、卫生技术人员占全院职工数的比例等5个指标对总成本增加的影响有统计学意义。结论 平行数据随机前沿成本模型是评价中医院技术效率的一种较适宜的方法。在对中医院低效率的现状及其影响因素进行分析的基础上，提出加强科学管理、提高资源利用率，减少不必要浪费等建议。     

Do HMO and its for‐profit expansion jeopardize the survival of hospital safety net services?

This study examines the effect of health maintenance organizations (HMOs) and for-profit HMO share on the survival of safety net services in hospitals between 1990 and 2004. The primary data sources are the American Hospital Association Annual Surveys, the Medicare hospital cost reports, and the HMO enrollment and ownership data from Interstudy. I analyze the risks of shutting down each safety net service separately using the proportional hazard models. I find that the risks of shutting down hospital safety net services do not vary by different levels of overall HMO penetration. However, conditional on the overall HMO penetration level, increasing for-profit presence of HMO does increase the risks of shutting down several safety net services. Policies evaluating the for-profit expansion or ownership conversion of health plans should take this potential adverse effect into consideration.     

Hospital ownership and cost and quality of care: is there a dime's worth of difference?

Nonprofit organizations may predominate when output quality is difficult to monitor. Hospital care has this characteristic. This study compared program cost and quality of care for Medicare patients hospitalized following onset of four common conditions by hospital ownership. Payments on behalf of Medicare patients admitted to for-profit hospitals during the first 6 months following a health shock were higher than for those admitted to other hospitals. With quality measured in terms of survival, changes in functional and cognitive status, and living arrangements, we found no differences in outcomes by hospital ownership.     

Cost inefficiency under financial strain: a stochastic frontier analysis of hospitals in Washington State through the Great Recession

The importance of increasing cost efficiency for community hospitals in the United States has been underscored by the Great Recession and the ever-changing health care reimbursement environment. Previous studies have shown mixed evidence with regards to the relationship between linking hospitals’ reimbursement to quality of care and cost efficiency. Moreover, current evidence suggests that not only inherently financially disadvantaged hospitals (e.g., safety-net providers), but also more financially stable providers, experienced declines to their financial viability throughout the recession. However, little is known about how hospital cost efficiency fared throughout the Great Recession. This study contributes to the literature by using stochastic frontier analysis to analyze cost inefficiency of Washington State hospitals between 2005 and 2012, with controls for patient burden of illness, hospital process of care quality, and hospital outcome quality. The quality measures included in this study function as central measures for the determination of recently implemented pay-for-performance programs. The average estimated level of hospital cost inefficiency before the Great Recession (10.4 %) was lower than it was during the Great Recession (13.5 %) and in its aftermath (14.1 %). Further, the estimated coefficients for summary process of care quality indexes for three health conditions (acute myocardial infarction, pneumonia, and heart failure) suggest that higher quality scores are associated with increased cost inefficiency.     

The effect of chain membership on hospital costs.

OBJECTIVE: To compare the cost structures of hospitals in multihospital systems and independently owned hospitals. DATA SOURCES: The American Hospital Association's Annual Survey from 1990 for data on hospital costs and attributes. Area characteristics came from the Area Resource File, and the Medicare case-mix index came from the Health Care Financing Administration. Data on wages are from the Bureau of the Census' State and Metropolitan Area Data Book. The Guide to Hospital Performance from HCIA, Inc. provided data on quality of care. STUDY DESIGN: Separate cost functions were estimated for chain and independent hospitals. Hybrid translog cost functions included measures of outputs, input prices, and hospital and area characteristics. The estimation method accounted for the simultaneous determination of costs and chain membership, and for any nonrandom selection of hospitals into chains. Several economic cost measures were calculated to compare the cost structures of the two types of hospitals. DATA EXTRACTION METHODS: Data from all sources were merged at the hospital level to form the study sample. PRINCIPAL FINDINGS: Hospitals in multihospital systems were less costly than independently owned hospitals. Among independent hospitals, for-profits had the highest costs. There were no statistically significant differences in costs by ownership among chain members. Economies of scale were enjoyed in both types of hospitals only at high volumes of output, while economies of scope occurred at all volumes for chain hospitals, but only at low and medium volumes for independent hospitals. CONCLUSIONS: This study provides support for the idea that growth of the multihospital system sector can provide a market solution to the problem of constraining costs. It does not, however, support the property rights theory that proprietary hospitals are more efficient than nonprofit hospitals.