Access, quality, and costs of care at physician owned hospitals in the United States: observational study.

OBJECTIVE: To compare physician owned hospitals (POHs) with non-POHs on metrics around patient populations, quality of care, costs, and payments. DESIGN: Observational study. SETTING: Acute care hospitals in 95 hospital referral regions in the United States, 2010. PARTICIPANTS: 2186 US acute care hospitals (219 POHs and 1967 non-POHs). MAIN OUTCOME MEASURES: Proportions of patients using Medicaid and those from ethnic and racial minority groups; hospital performance on patient experience metrics, care processes, risk adjusted 30 day mortality, and readmission rates; costs of care; care payments; and Medicare market share. RESULTS: The 219 POHs were more often small (<100 beds), for profit, and in urban areas. 120 of these POHs were general (non-specialty) hospitals. Compared with patients from non-POHs, those from POHs were younger (77.4 v 78.4 years, P<0.001), less likely to be admitted through an emergency department (23.2% v. 29.0%, P<0.001), equally likely to be black (5.1% v 5.5%, P=0.85) or to use Medicaid (14.9% v 15.4%, P=0.75), and had similar numbers of chronic diseases and predicted mortality scores. POHs and non-POHs performed similarly on patient experience scores, processes of care, risk adjusted 30 day mortality, 30 day readmission rates, costs, and payments for acute myocardial infarction, congestive heart failure, and pneumonia. CONCLUSION: Although POHs may treat slightly healthier patients, they do not seem to systematically select more profitable or less disadvantaged patients or to provide lower value care.

Association between hospital conversions to for-profit status and clinical and economic outcomes.

IMPORTANCE: An increasing number of hospitals have converted to for-profit status, prompting concerns that these hospitals will focus on payer mix and profits, avoiding disadvantaged patients and paying less attention to quality of care. OBJECTIVE: To examine characteristics of US acute care hospitals associated with conversion to for-profit status and changes following conversion. DESIGN, SETTING, AND PARTICIPANTS: Retrospective cohort study conducted among 237 converting hospitals and 631 matched control hospitals. Participants were 1,843,764 Medicare fee-for-service beneficiaries at converting hospitals and 4,828,138 at control hospitals. EXPOSURES: Conversion to for-profit status, 2003-2010. MAIN OUTCOMES AND MEASURES: Financial performance measures, quality process measures, mortality rates, Medicare volume, and patient population for the 2 years prior and the 2 years after conversion, excluding the conversion year, assessed using difference-in-difference models. RESULTS: Hospitals that converted to for-profit status were more often small or medium in size, located in the south, in an urban or suburban location, and were less often teaching institutions. Converting hospitals improved their total margins (ratio of net income to net revenue plus other income) more than controls (2.2% vs 0.4% improvement; difference in differences, 1.8% [ 95% CI, 0.5% to 3.1%]; P = .007). Converting hospitals and controls both improved their process quality metrics (6.0% vs 5.6%; difference in differences, 0.4% [95% CI, -1.1% to 2.0%]; P = .59). Mortality rates did not change at converting hospitals relative to controls for Medicare patients overall (increase of 0.1% vs 0.2%; difference in differences, -0.2% [95% CI, -0.5% to 0.2%], P = .42) or for dual-eligible or disabled patients. There was no change in converting hospitals relative to controls in annual Medicare volume (-111 vs -74 patients; difference in differences, -37 [95% CI, -224 to 150]; P = .70), Disproportionate Share Hospital Index (1.7% vs 0.4%; difference in differences, 1.3% [95% CI, -0.9% to 3.4%], P = .26), the proportion of patients with Medicaid (-0.2% vs 0.4%; difference in differences, -0.6% [95% CI, -2.0% to 0.8%]; P = .38) or the proportion of patients who were black (-0.4% vs -0.1%; difference in differences, -0.3% [95% CI, -1.9% to 1.3%]; P = .72) or Hispanic (0.1% vs -0.1%; difference in differences, 0.2% [95% CI, -0.3% to 0.7%]; P = .50). CONCLUSIONS AND RELEVANCE: Hospital conversion to for-profit status was associated with improvements in financial margins but not associated with differences in quality or mortality rates or with the proportion of poor or minority patients receiving care.

The use of failure mode and effect analysis in a radiation oncology setting: the Cancer Treatment Centers of America experience.

Delivering radiation therapy in an oncology setting is a high-risk process where system failures are more likely to occur because of increasing utilization, complexity, and sophistication of the equipment and related processes. Healthcare failure mode and effect analysis (FMEA) is a method used to proactively detect risks to the patient in a particular healthcare process and correct potential errors before adverse events occur. FMEA is a systematic, multidisciplinary team-based approach to error prevention and enhancing patient safety. We describe our experience of using FMEA as a prospective risk-management technique in radiation oncology at a national network of oncology hospitals in the United States, capitalizing not only on the use of a team-based tool but also creating momentum across a network of collaborative facilities seeking to learn from and share best practices with each other. The major steps of our analysis across 4 sites and collectively were: choosing the process and subprocesses to be studied, assembling a multidisciplinary team at each site responsible for conducting the hazard analysis, and developing and implementing actions related to our findings. We identified 5 areas of performance improvement for which risk-reducing actions were successfully implemented across our enterprise.

Hospital ownership and efficiency: a review of studies with particular focus on Germany.

The German hospital market has been subject over the past two decades to a variety of healthcare reforms. Particularly the introduction of diagnosis-related groups (DRGs) in 2004 aimed to increase efficiency of hospitals. The objective of the paper is to review recent studies comparing the efficiency of German public, private non-profit and private for-profit hospitals. The results of the studies are quite mixed. However, in line with the evidence found in studies from other countries, especially the US, the evidence from Germany suggests that private ownership (i.e., private non-profit and private for-profit) is not necessarily associated with higher efficiency compared to public ownership. This may be a surprising result to many policy makers as private for-profit hospitals are often perceived the most efficient ownership type by the public.

Comparing public and private hospitals in China: evidence from Guangdong.

BACKGROUND: The literature comparing private not-for-profit, for-profit, and government providers mostly relies on empirical evidence from high-income and established market economies. Studies from developing and transitional economies remain scarce, especially regarding patient case-mix and quality of care in public and private hospitals, even though countries such as China have expanded a mixed-ownership approach to service delivery. The purpose of this study is to compare the operations and performance of public and private hospitals in Guangdong Province, China, focusing on differences in patient case-mix and quality of care. METHODS: We analyze survey data collected from 362 government-owned and private hospitals in Guangdong Province in 2005, combining mandatorily reported administrative data with a survey instrument designed for this study. We use univariate and multi-variate regression analyses to compare hospital characteristics and to identify factors associated with simple measures of structural quality and patient outcomes. RESULTS: Compared to private hospitals, government hospitals have a higher average value of total assets, more pieces of expensive medical equipment, more employees, and more physicians (controlling for hospital beds, urban location, insurance network, and university affiliation). Government and for-profit private hospitals do not statistically differ in total staffing, although for-profits have proportionally more support staff and fewer medical professionals. Mortality rates for non-government non-profit and for-profit hospitals do not statistically differ from those of government hospitals of similar size, accreditation level, and patient mix. CONCLUSIONS: In combination with other evidence on health service delivery in China, our results suggest that changes in ownership type alone are unlikely to dramatically improve or harm overall quality. System incentives need to be designed to reward desired hospital performance and protect vulnerable patients, regardless of hospital ownership type.

Designing a balanced scorecard for a tertiary care hospital in Pakistan: a modified Delphi group exercise.

Balanced Scorecards (BSC) are being implemented in high income health settings linking organizational strategies with performance data. At this private university hospital in Pakistan an elaborate information system exists. This study aimed to make best use of available data for better performance management. Applying the modified Delphi technique an expert panel of clinicians and hospital managers reduced a long list of indicators to a manageable size. Indicators from existing documents were evaluated for their importance, scientific soundness, appropriateness to hospital's strategic plan, feasibility and modifiability. Panel members individually rated each indicator on a scale of 1-9 for the above criteria. Median scores were assigned. Of an initial set of 50 indicators, 20 were finally selected to be assigned to the four BSC quadrants. These were financial (n = 4), customer or patient (n = 4), internal business or quality of care (n = 7) and innovation/learning or employee perspectives (n = 5). A need for stringent definitions, international benchmarking and standardized measurement methods was identified. BSC compels individual clinicians and managers to jointly work towards improving performance. This scorecard is now ready to be implemented by this hospital as a performance management tool for monitoring indicators, addressing measurement issues and enabling comparisons with hospitals in other settings.

Hospital type and patient outcomes: an empirical examination using AMI readmission and mortality records.

This paper investigates whether there are differences in patient outcomes across different types of hospitals using patient-level data on readmission and mortality associated with acute myocardial infarction (AMI). Hospitals are grouped according to their ownership type (private, public teaching, public non-teaching) and their location (metropolitan, country and remote country). Using data collected from 130 Victorian hospitals on 19,000 patients admitted to a hospital with their first AMI between January 2001 and December 2003, we consider how the likelihood of unplanned re-admission and mortality varies across hospital type. We find that there are significant differences across hospital types in the observed patient outcomes - private hospitals persistently outperform public hospitals.

Evidence-based algorithms for diagnosing and treating ventilator-associated pneumonia.

BACKGROUND: Ventilator-associated pneumonia (VAP) is widely recognized as a serious and common complication associated with high morbidity and high costs. Given the complexity of caring for heterogeneous populations in the intensive care unit (ICU), however, there is still uncertainty regarding how to diagnose and manage VAP. OBJECTIVE: We recently conducted a national collaborative aimed at reducing health care-associated infections in ICUs of hospitals operated by the Hospital Corporation of America (HCA). As part of this collaborative, we developed algorithms for diagnosing and treating VAP in mechanically ventilated patients. In the current article, we (1) review the current evidence for diagnosing VAP, (2) describe our approach for developing these algorithms, and (3) illustrate the utility of the diagnostic algorithms using clinical teaching cases. DESIGN: This was a descriptive study, using data from a national collaborative focused on reducing VAP and catheter-related bloodstream infections. SETTING: The setting of the study was 110 ICUs at 61 HCA hospitals. INTERVENTION: None. MEASUREMENTS AND RESULTS: We assembled an interdisciplinary team that included infectious disease specialists, intensivists, hospitalists, statisticians, critical care nurses, and pharmacists. After reviewing published studies and the Centers for Disease Control and Prevention VAP guidelines, the team iteratively discussed the evidence, achieved consensus, and ultimately developed these practical algorithms. The diagnostic algorithms address infant, pediatric, immunocompromised, and adult ICU patients. CONCLUSIONS: We present practical algorithms for diagnosing and managing VAP in mechanically ventilated patients. These algorithms may provide evidence-based real-time guidance to clinicians seeking a standardized approach to diagnosing and managing this challenging problem.

Specialty and full-service hospitals: a comparative cost analysis.

OBJECTIVE: To compare the costs of physician-owned cardiac, orthopedic, and surgical single specialty hospitals with those of full-service hospital competitors. DATA SOURCES: The primary data sources are the Medicare Cost Reports for 1998-2004 and hospital inpatient discharge data for three of the states where single specialty hospitals are most prevalent, Texas, California, and Arizona. The latter were obtained from the Texas Department of State Health Services, the California Office of Statewide Health Planning and Development, and the Agency for Healthcare Research and Quality Healthcare Cost and Utilization Project. Additional data comes from the American Hospital Association Annual Survey Database. STUDY DESIGN: We identified all physician-owned cardiac, orthopedic, and surgical specialty hospitals in these three states as well as all full-service acute care hospitals serving the same market areas, defined using Dartmouth Hospital Referral Regions. We estimated a hospital cost function using stochastic frontier regression analysis, and generated hospital specific inefficiency measures. Application of t-tests of significance compared the inefficiency measures of specialty hospitals with those of full-service hospitals to make general comparisons between these classes of hospitals. PRINCIPAL FINDINGS: Results do not provide evidence that specialty hospitals are more efficient than the full-service hospitals with whom they compete. In particular, orthopedic and surgical specialty hospitals appear to have significantly higher levels of cost inefficiency. Cardiac hospitals, however, do not appear to be different from competitors in this respect. CONCLUSIONS: Policymakers should not embrace the assumption that physician-owned specialty hospitals produce patient care more efficiently than their full-service hospital competitors.

Variation in quality of care within health systems.

BACKGROUND: Although many hospitals belong to health care systems, little is known about the quality of care provided by those systems, or whether characteristics of health care systems are related to the quality of care patients receive. Dimensions of the quality of care provided in 73 hospital systems were examined using hospital quality data publicly reported by the Centers for Medicare & Medicaid Services (CMS). The hospital systems consisted of six or more acute care hospitals and represented 1,510 hospitals. The study was designed to determine whether these dimensions of system quality could be reliably measured, to describe how systems varied with respect to quality of care, and to explore system characteristics potentially related to care quality. METHODS: Data were made available by CMS for 19 indicators of care quality for pneumonia, surgical infection prevention, acute myocardial infarction (AMI), and congestive heart failure. RESULTS: At the system level, reliable measures (alphas > .70) were constructed for each of the four clinical areas, and these measures were combined into a single measure of quality (alpha = .85). Variability in system quality was substantial, ranging from 94% to 70% on the combined quality measure. On the clinical area measures, the smallest range was for AMI (99%-85%), whereas the largest was for surgical infection prevention (95%-54%). System ownership and system centralization were significant predictors of quality, accounting for 30% of variance in the combined quality measure. Geographic region, inclusion of teaching hospitals, and system size were unrelated to quality. DISCUSSION: Systems vary greatly in terms of quality of care in each of the four clinical areas, with for-profit and more decentralized systems appreciably lower in quality of care. System-level quality measures and data could be used to compare processes within systems and to drive improvement efforts.

Hospital ownership and performance: evidence from stroke and cardiac treatment in Taiwan.

This paper compares program expenditure and treatment quality of stroke and cardiac patients between 1997 and 2000 across hospitals of various ownership types in Taiwan. Because Taiwan implemented national health insurance in 1995, the analysis is immune from problems arising from the complex setting of the U.S. health care market, such as segmentation of insurance status or multiple payers. Because patients may select admitted hospitals based on their observed and unobserved characteristics, we employ instrument variable (IV) estimation to account for the endogeneity of ownership status. Results of IV estimation find that patients admitted to non-profit hospitals receive better quality care, either measured by 1- or 12-month mortality rates. In terms of treatment expenditure, our results indicate no difference between non-profits and for-profits index admission expenditures, and at most 10% higher long-term expenditure for patients admitted to non-profits than to for-profits.

Hospital ownership and quality of care: what explains the different results in the literature?

This systematic review examines what factors explain the diversity of findings regarding hospital ownership and quality. We identified 31 observational studies written in English since 1990 that used multivariate analysis to examine quality of care at nonfederal general acute, short-stay US hospitals. We find that pooled estimates of ownership effects are sensitive to the subset of studies included and the extent of overlap among hospitals analyzed in the underlying studies. Ownership does appear to be systematically related to differences in quality among hospitals in several contexts. Whether studies find for-profit and government-controlled hospitals to have higher mortality rates or rates of adverse events than their nonprofit counterparts depends on data sources, time period, and region covered. Policymakers should be aware of the underlying reasons for conflicting evidence in this literature, and the strengths and weaknesses of meta-analytic synthesis. The 'true' effect of ownership appears to depend on institutional context, including differences across regions, markets, and over time.

The impact of for-profit hospital status on the care and outcomes of patients with non-ST-segment elevation myocardial infarction: results from the CRUSADE Initiative.

OBJECTIVES: We sought to determine whether for-profit status influenced hospitals' care or outcomes among non-ST-segment elevation myocardial infarction (NSTEMI) patients. BACKGROUND: While for-profit hospitals potentially have financial incentives to selectively care for younger, healthier patients, perform highly reimbursed procedures, reduce costs by limiting access to expensive medications, and encourage shorter in-patient length of stay, there are limited data available to investigate these issues objectively. METHODS: Using data from the CRUSADE (Can Rapid risk stratification of Unstable angina patients Suppress ADverse outcomes with Early implementation of the American College of Cardiology/American Heart Association guidelines) Initiative, we investigated whether for-profit status influenced hospitals' patient case mix, care, or outcomes among 145,357 patients with NSTEMI treated between January 1, 2001, and December 31, 2005, at 532 U.S. hospitals. Impact of for-profit status on care and outcomes was analyzed overall and after adjustment for clinical and facility factors using regression modeling. RESULTS: Patients (n = 11,658) treated at 58 for-profit hospitals were of similar age and gender, but were more likely to be nonwhite (black, Asian, Hispanic, and other) and have health maintenance organization/private insurance, diabetes mellitus, congestive heart failure, hypertension, and renal insufficiency compared with 133,699 patients treated at 474 nonprofit hospitals. For-profit hospitals were less likely to use discharge beta-blockers, but all other treatments were similar including the use of interventional procedures (cardiac catheterization and revascularization procedures) compared with nonprofit centers. In-hospital length of stay and mortality were also similar by hospital type. CONCLUSIONS: We found no evidence that for-profit hospitals selectively treat less sick patients, provide less evidence-based care, limit in-hospital stays, or have patients with worse acute outcomes than nonprofit centers.