Relative Productivity of For-Profit Hospitals: A Big or a Little Deal?

This study asks: Does the empirical evidence support the conclusion that for-profit (FP) hospitals are more productive or efficient than private not-for-profit (NFP) hospitals or non-federal public (PUB) hospitals? Alternative theories of NFP behavior are described. Our review of individual empirical hospital studies of quality, service mix, community benefit, and cost/efficiency in the United States published since 2000 indicates that no systematic difference exists in cost/efficiency, provision of uncompensated care, and quality of care. But FPs are more likely to provide profitable services, higher service intensity, have lower shares of uninsured and Medicaid patients, and are more responsive to external financial incentives. That FP hospitals are not more efficient runs counter to property rights theory, but their relative responsiveness to financial incentives supports it. There is little evidence that FP market presence changes NFP behaviors. Observed differences between FP and NFP hospitals are mostly a "little deal."

Biased technical change in hospital care and the demand for physicians.

BACKGROUND: The development of labour productivity is relevant for accurately planning future staffing requirements, especially in sectors where technological developments may drive labour substitution. The present study investigates how labour productivity has developed across Dutch medical specialists (2007-2017) and discusses its implications for workforce planning, also in relation to the existing literature. METHODS: A regression model is developed in which the number of full-time equivalents is related to production (admissions), hospital characteristics and a trend parameter. The trend parameter captures the average annual change in the number of full-time equivalents per production output and is a measure for labour productivity. The model is applied to a micro-data set of Dutch hospitals in the period 2007-2017 across 24 different specialties using regression methods. RESULTS: The results indicate an increase in the number of full-time equivalents per admission has increased for most specialisms and that labour productivity has thus decreased. However, there is considerable heterogeneity and uncertainty across different specialisms. CONCLUSIONS: The results amplify the issue of medical personnel shortages driven by the growing demand for health care. The research outcomes are linked to the existing literature regarding physicians' productivity. Changes in accountability such as using relative value units, incentive payments, use of staff and mid-level providers, and technology have been discussed, and some consensus has been reached.

A robust analysis of hospital efficiency and factors affecting variability.

The objectives of this paper are to use data envelopment analysis to measure hospital inefficiency in a way that accounts for patient outcomes and to study the association between organizational factors, such as hospital-physicians integration level and teaching status, and market competition with hospital inefficiency. We apply the robust data envelopment analysis approach to a sample of private (both not-for-profit and for-profit) hospitals operating in the United States. Our data envelopment analysis model includes mortality and readmission rates as bad outputs and admissions, surgeries, emergency room, and other visits as good outputs. Therefore, our measurement of hospital inefficiency accounts for quality. We then use a subsampling regression analysis to determine the predictors of hospital inefficiency. For-profit, fully integrated and teaching hospitals were more efficient than their counterparts. Also hospitals located in more competitive markets were more efficient than those located in less competitive markets. Incorporating quality in the measurement of hospital efficiency is key for producing valid efficiency scores. Hospitals in less competitive markets need to improve their efficiency levels. Moreover, high levels of hospital physician integration might be instrumental in ensuring that hospitals achieve their efficiency goals.

Work Impact and Emotional Stress Among Informal Caregivers for Older Adults.

OBJECTIVES: With the growing aging population and reliance on informal caregivers in the United States, many individuals will take on the role of caregiver as an adult. We examined whether informal caregivers experience work interference or a change in work status (i.e., retiring/quitting) due to caregiving. We also explored whether experiencing work interference or a change in work status was associated with greater emotional stress. METHOD: This secondary analysis is drawn from the Fifth National Survey of Older Americans Act (OAA) program participants, which included 1,793 family caregivers. The present analysis is on caregivers of working age (18-64 years) providing care to another adult, which included 922 caregivers. Ordinal logit models were used to assess associations between experiencing work interference or a change in work status and emotional stress. Study weights were applied for all analyses. RESULTS: At the time of the survey, more than half (52.9%) of caregivers were employed full- or part-time. Among nonworking caregivers (i.e., not working or retired) at the time of the survey, 39.8% responded that they had quit or retired early due to caregiving demands. Among employed caregivers, 52.4% reported that informal caregiving had interfered with their employment. Importantly, those respondents who reported work interference or a change in work status were more likely to report higher levels of emotional stress associated with caregiving demands. DISCUSSION: These findings suggest the need to further explore work among informal caregivers and associations with emotional stress, as well as consider work-based policy approaches, organizational and/or societal, to support informal caregivers.

Concentrating Emergency Rooms: Penny-Wise and Pound-Foolish? An Empirical Research on Scale Economies and Chain Economies in Emergency Rooms in Dutch Hospitals.

In this paper, we address the issue of whether it is economically advantageous to concentrate emergency rooms (ERs) in large hospitals. Besides identifying economies of scale of ERs, we also focus on chain economies. The latter term refers to the effects on a hospital's costs of ER patients who also need follow-up inpatient or outpatient hospital care. We show that, for each service examined, product-specific economies of scale prevail indicating that it would be beneficial for hospitals to increase ER services. However, this seems to be inconsistent with the overall diseconomies of scale for the hospital as a whole. This intuitively contradictory result is indicated as the economies of scale paradox. This scale paradox also explains why, in general, hospitals are too large. There are internal (departmental) pressures to expand certain services, such as ER, in order to benefit from the product-specific economies of scale. However, the financial burden of this expansion is borne by the hospital as a whole. The policy implications of the results are that concentrating ERs seems to be advantageous from a product-specific perspective, but is far less advantageous from the hospital perspective. © 2016 The Authors. Health Economics Published by John Wiley & Sons, Ltd.

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.

Opportunities for Prevention: Assessing Where Low-Income Patients Seek Care for Preventable Coronary Artery Disease.

The Affordable Care Act has many aspects that are aimed at improving health care for all Americans, including mandated insurance coverage for individuals, as well as required community health needs assessments (CHNAs), and reporting of investments in community benefit by nonprofit hospitals in order to maintain tax exemptions. Although millions of Americans have gained access to health insurance, many--often the most vulnerable--remain uninsured, and will continue to depend on hospital community benefits for care. Understanding where patients go for care can assist hospitals and communities to develop their CHNA and implementation plans in order to focus resources where the need for prevention is greatest. This study evaluated patient care-seeking behavior among patients with coronary artery disease (CAD) in Florida in 2008--analyzed in 2013--to assess whether low-income patients accessed specific safety net hospitals for treatment or received care from hospitals that were geographically closer to their residence. This study found evidence that low-income patients went to hospitals that treated more low-income patients, regardless of where they lived. The findings demonstrate that hospitals-especially public safety net hospitals with a tradition of treating low-income patients suffering from CAD-should focus prevention activities where low-income patients reside.

Technology diffusion in hospitals: a log odds random effects regression model.

This study identifies the factors that affect the diffusion of hospital innovations. We apply a log odds random effects regression model on hospital micro data. We introduce the concept of clustering innovations and the application of a log odds random effects regression model to describe the diffusion of technologies. We distinguish a number of determinants, such as service, physician, and environmental, financial and organizational characteristics of the 60 Dutch hospitals in our sample. On the basis of this data set on Dutch general hospitals over the period 1995-2002, we conclude that there is a relation between a number of determinants and the diffusion of innovations underlining conclusions from earlier research. Positive effects were found on the basis of the size of the hospitals, competition and a hospital's commitment to innovation. It appears that if a policy is developed to further diffuse innovations, the external effects of demand and market competition need to be examined, which would de facto lead to an efficient use of technology. For the individual hospital, instituting an innovations office appears to be the most prudent course of action.

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.

Measuring economies of scale at the city market level.

Data envelopment analysis (DEA) techniques have been applied to the assessing efficiency and productivity among individual hospitals. In this article, we employ DEA to address whether economies of scale exist among hospital markets by first assessing individual hospitals operating in 2005 in the State of Florida and then by comparing hospital markets' efficiency relative to each other. The interest in hospital markets stems from issues relating to mergers among hospitals or the reallocation of services (inputs) among hospitals in a market area, particularly as occupancy rates and reimbursements are tending to fall. Facing more competition and stringent financial conditions, hospitals would benefit from decreasing costs by exploiting economies of scale.

Environmental factors and productivity on Dutch hospitals: a semi-parametric approach.

This paper describes the efficiency of Dutch hospitals using the method of Data Envelopment Analysis (DEA). In particular the analysis focuses on explaining cost inefficiency measures due to each hospital's operating environment. In previous works, the resulting DEA score is regressed on environmental factors via a Tobit approach. Previously, these approaches have been used (Simar and Wilson, J Prod Anal 7(1):63-80, 2000) but later these authors (Simar and Wilson 2007) demonstrated that bias is incurred since the efficiency score is a point estimate without a probability distribution around it that is required by the Tobit methodology. In this paper we use the Simar and Wilson bootstrapping techniques in order to obtain more efficient estimates of the environmental effects. It is shown that differences in estimated effects exist between the non-bootstrapped and bootstrapped models.

The impact of CON regulation on hospital efficiency.

In this paper we propose an empirically implementable measure of aggregate-level efficiency along the lines of Debreu's (1951) coefficient of resource utilization but restricted to the production side. The efficiency measure is based on directional distance functions, which allows the overall measure of efficiency to be decomposed into measures of technical and "structural" efficiency. The latter measure, which captures inefficiencies associated with the organization of production within an industry, is further decomposed into measures of scale and mix efficiency. The measures developed in the paper are illustrated using U.S. hospital data. The illustration sheds light on the efficacy of certificate of need (CON) regulations.

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.

Do public health clinics reduce rehospitalizations?: the urban diabetes study.

Safety-net health clinics have been shown to reduce hospitalizations for ambulatory care-sensitive conditions. Their impact on rehospitalization after hospital discharge is unknown. We hypothesized that use of publicly-funded safety-net health clinics would reduce rates of rehospitalization among patients with diabetes. We expected this effect to be most evident among the most vulnerable patients. Linking data from the Philadelphia Health Care Centers (HCCs) with statewide hospital discharge data for 1994-2001 for patients with diabetes, we found that patients enrolled in the HCCs prior to hospitalization were rehospitalized 22% of the time, the same rate as other Philadelphians. Among those at higher risk of rehospitalization because pre-existing diabetes was not noted in hospital records, odds of rehospitalization were reduced by 24% for HCC patients. Given that patients in the HCCs are overwhelmingly poor and uninsured or underinsured, these findings suggest that access to primary care through the HCCs may have a protective effect against the poor health outcomes typically associated with lower socioeconomic status. Enrollment in publicly-funded safety-net health clinics may have prevented rehospitalizations for some vulnerable patients with diabetes.

Is more better? An analysis of hospital outcomes and efficiency with a DEA model of output congestion.

This paper applies a new methodology to the study of hospital efficiency and quality of care. Using a data set of hospitals from several states, we jointly evaluate desirable hospital patient care output (e.g., patient stays) and the simultaneous undesirable output (e.g., risk-adjusted patient mortality) that occurs. With a DEA based approach under two different sets of assumptions, we are able to include multiple quality indicators as outputs. The results show that lower technical efficiency is associated with poorer risk-adjusted quality outcomes in the study hospitals. They are consistent with other studies linking poor quality outcomes to higher cost.

Nutritionist visits, diabetes classes, and hospitalization rates and charges: the Urban Diabetes Study.

OBJECTIVE: We evaluated the association of different types of educational visits for diabetic patients of the eight Philadelphia Health Care Centers (PHCCs) (public safety-net primary care clinics), with hospital admission rates and charges reported to the Pennsylvania Health Care Cost Containment Council. RESEARCH DESIGN AND METHODS: The study population included 18,404 patients who had a PHCC visit with a diabetes diagnosis recorded between 1 March 1993 and 31 December 2001 and had at least 1 month follow-up time. RESULTS: A total of 31,657 hospitalizations were recorded for 7,839 (42.6%) patients in the cohort. After adjustment for demographic variables, baseline comorbid conditions, hospitalizations before the diabetes diagnosis, and number of other primary care visits, having had any type of educational visit was associated with 9.18 (95% CI 5.02-13.33) fewer hospitalizations per 100 person-years and $11,571 ($6,377 to $16,765) less in hospital charges per person. Each nutritionist visit was associated with 4.70 (2.23-7.16) fewer hospitalizations per 100 person-years and a $6,503 ($3,421 to $9,586) reduction in total hospital charges. CONCLUSIONS: Any type of educational visit was associated with lower hospitalization rates and charges. Nutritionist visits were more strongly associated with reduced hospitalizations than diabetes classes. Each nutritionist visit was associated with a substantial reduction in hospital charges, suggesting that providing these services in the primary care setting may be highly cost-effective for the health care system.