Comparison of the market share of public and private hospitals under different Medical Alliances: an interrupted time-series analysis in rural China.

BACKGROUND: China initiated the Medical Alliances (MAs) reform to enhance resource allocation efficiency and ensure equitable healthcare. In response to challenges posed by the predominance of public hospitals, the reform explores public-private partnerships within the MAs. Notably, private hospitals can now participate as either leading or member institutions. This study aims to evaluate the dynamic shifts in market share between public and private hospitals across diverse MAs models. METHODS: Data spanning April 2017 to March 2019 for Dangyang County's MA and January 2018 to December 2019 for Qianjiang County's MA were analyzed. Interrupted periods occurred in April 2018 and January 2019. Using independent sample t-tests, chi-square tests, and interrupted time series analysis (ITSA), we compared the proportion of hospital revenue, the proportion of visits for treatment, and the average hospitalization days of discharged patients between leading public hospitals and leading private hospitals, as well as between member public hospitals and member private hospitals before and after the reform. RESULTS: After the MAs reform, the revenue proportion decreased for leading public and private hospitals, while member hospitals saw an increase. However, ITSA revealed a notable rise trend in revenue proportion for leading private hospitals (p < 0.001), with a slope of 0.279% per month. Member public and private hospitals experienced decreasing revenue proportions, with outpatient visits proportions declining in member public hospitals by 0.089% per month (p < 0.05) and inpatient admissions proportions dropping in member private hospitals by 0.752% per month (p < 0.001). The average length of stay in member private hospitals increased by 0.321 days per month after the reform (p < 0.01). CONCLUSIONS: This study underscores the imperative to reinforce oversight and constraints on leading hospitals, especially private leading hospitals, to curb the trend of diverting patients from member hospitals. At the same time, for private hospitals that are at a disadvantage in competition and may lead to unreasonable prolongation of hospital stay, this kind of behavior can be avoided by strengthening supervision or granting leadership.

Charges, length of stay, and complication associations with trauma center ownership in adult patients with mild to moderate trauma.

BACKGROUND: For-profit (FP) trauma centers (TCs) charge more for trauma care than not-for-profit (NFP) centers. We sought to determine charges, length of stay (LOS), and complications associations with TC ownership status (FP, NFP, and government) for three diagnoses among patients with overall low injury severity. METHODS: Adult patients treated at TCs with an International Classification of Diseases-based injury severity score (ICISS) survival probability ≥ 0.85 were identified. Only those who with a principal diagnosis of femur, tibial or rib fractures were included. RESULTS: Total charges were significantly higher at FP centers than NFP and lower at government centers (89.6% and -12.8%, respectively). FP TCs had a 12.5% longer LOS and government TCs had a 20.4% longer LOS than NFP TCs. CONCLUSION: Patients presenting to FP TCs with mild/moderate femur, tibial, or rib fractures experienced higher charges and increased LOS compared with government or NFP centers. There was no difference in overall complication rates.

Determinants of hospital inefficiency. The case of Polish county hospitals.

Local hospitals play a crucial role in the healthcare system. In this study, the efficiency of Polish county hospitals is assessed by considering characteristics of hospitals that may determine their performance, such as the form of ownership, size, and staff structure. The main goal was to analyze the effect of three possible determinants on efficiency: ownership, the presence of an Emergency Department, and the presence of an Intensive Care Unit. The study covered different subgroups of hospitals and different approaches of inputs and outputs. An input-oriented radial super-efficiency DEA model under variable returns to scale was used for the efficiency analysis, and then differences between distributions of efficient and inefficient units were evaluated using a Chi-square test. A Kruskal-Wallis test was also used to analyze differences in mean efficiency. Inefficiency scores were regressed with hospital characteristics to test for other determinants. These results did not confirm differences in efficiency concerning ownership. However, in some subgroups of hospitals, running an Emergency Department or an Intensive Care Unit had a significant effect. Tobit regression results provided additional insight into how an Emergency Department or Intensive Care Unit can affect efficiency. Both cases had an effect of increasing inefficiency, and the data suggested that the department/unit size plays an important role.

Gynecologic oncology treatment modifications or delays in response to the COVID-19 pandemic in a publicly funded versus privately funded North American tertiary cancer center.

OBJECTIVE: To compare gynecologic oncology surgical treatment modifications and delays during the first wave of the COVID-19 pandemic between a publicly funded Canadian versus a privately funded American cancer center. METHODS: This is a retrospective cohort study of all planned gynecologic oncology surgeries at University Health Network (UHN) in Toronto, Canada and Brigham and Women's Hospital (BWH) in Boston, USA, between March 22,020 and July 302,020. Surgical treatment delays and modifications at both centers were compared to standard recommendations. Multivariable logistic regression was performed to adjust for confounders. RESULTS: A total of 450 surgical gynecologic oncology patients were included; 215 at UHN and 235 at BWH. There was a significant difference in median time from decision-to-treat to treatment (23 vs 15 days, p < 0.01) between UHN and BWH and a significant difference in treatment delays (32.56% vs 18.29%; p < 0.01) and modifications (8.37% vs 0.85%; p < 0.01), respectively. On multivariable analysis adjusting for age, race, treatment site and surgical priority status, treatment at UHN was an independent predictor of treatment modification (OR = 9.43,95% CI 1.81-49.05, p < 0.01). Treatment delays were higher at UHN (OR = 1.96,95% CI 1.14-3.36 p = 0.03) and for uterine disease (OR = 2.43, 95% CI 1.11-5.33, p = 0.03). CONCLUSION: During the first wave of COVID-19 pandemic, gynecologic oncology patients treated at a publicly funded Canadian center were 9.43 times more likely to have a surgical treatment modification and 1.96 times more likely to have a surgical delay compared to an equal volume privately funded center in the United States.

Taking Care of Business: Privileging Private Sector Hospitals During the COVID Crisis.

In the early days of the COVID crisis, many commentators argued that it presented opportunities for progressive change, notably toward redress of structural inequalities in health. As with the financial slump of 2008, however, such notions have proved almost ridiculously optimistic as it has been capital, through its near symbiosis with the state, that has been best able to respond, with the English government-the devolved nations adopted a markedly different approach-taking every opportunity to ensure the pandemic has proved a bonanza for private-sector healthcare interests. However, this has not just been about individual contracts in, for example, test and trace, vaccination, or personal protective equipment; the crisis has been used to both rescue the private acute market following 2 years of contracted revenues and to provide enormous stimulus for its future growth. This has required the support of several organizations acting in concert, including the NHS Confederation and the Royal Colleges. While the pandemic has served to illuminate such relationships, the author also argues that the oft-recurring governmental praise of the NHS needs to be matched by genuine investment in public hospitals.

Evaluation of Hospital Cesarean Delivery-Related Profits and Rates in the United States.

Importance: A high cesarean delivery rate in US hospitals indicates the potential overuse of this procedure; however, underlying causes of the excessive use of cesarean procedures in the US have not been fully understood. Objective: To investigate the association between the probability of cesarean delivery at the patient-level and profit per procedure from cesarean deliveries. Design, Setting, and Participants: This observational, cross-sectional study used a nationally representative sample of hospital discharge data from women at low risk for cesarean birth who delivered newborns between 2010 and 2014 in the US. Data were gathered from the Nationwide Readmissions Database from the Healthcare Cost and Utilization Project, compiled by the Agency for Healthcare Research and Quality. Data cleaning and analyses were conducted between August 2019 and May 2020. Exposures: Hospital-level median value of profits from cesarean deliveries, defined as the difference between the charge and the cost for cesarean delivery calculated for each hospital. Main Outcomes and Measures: Our primary outcome was the individual-level probability of undergoing a cesarean delivery. We examined the association with the hospital-level median value of profits per procedure for cesarean delivery (defined as the difference between the charge and the cost for cesarean delivery) using hierarchical regression models adjusted for patient and hospital characteristics and year-fixed effects. Results: A total of 13 215 853 deliveries were included in our analyses (mean [SE] age, 27.4 [0] years), of which 2 202 632 (16.7%) were cesarean deliveries. After adjusting for potential confounders, pregnant women were more likely to have a cesarean birth when they delivered at hospitals with higher profits per procedure from cesarean deliveries. Women cared for at hospitals with the highest (adjusted odds ratio, 1.08; 95% CI, 1.02-1.14; P = .005) and second-highest profit quartiles (adjusted odds ratio, 1.07; 95% CI, 1.02-1.13; P = .007) had higher probabilities of a cesarean delivery compared with those cared for at hospitals in the lowest profit quartile. Conclusions and Relevance: In this cross-sectional study of US nationally representative hospital discharge data, hospitals with higher profits per cesarean procedure were associated with an increased probability of delivering newborns through cesarean birth. These findings highlight the potential influence financial incentives play in determining a high cesarean delivery rate in the US.

Does social health insurance prevent financial hardship in Mongolia? Inpatient care: A case in point.

BACKGROUND: Protecting people from financial hardship and impoverishment due to health care costs is one of the fundamental purposes of the Mongolian health system. However, the inefficient, oversized hospital sector is considered one of the main shortcomings of the system. The aim of this study is to contribute to policy discussions by estimating the extent of catastrophic health expenditure and impoverishment due to inpatient care at secondary-level and tertiary-level public hospitals and private hospitals. METHODS: Data were derived from a nationally representative survey, the Household Socio-Economic Survey 2012, conducted by the National Statistical Office of Mongolia. A total of 12,685 households were involved in the study. "Catastrophic health expenditure" is defined as out-of-pocket payments for inpatient care that exceed a threshold of 40% of households' non-discretionary expenditure. The "impoverishment" effect of out-of-pocket payments for inpatient care was estimated as the difference between the poverty level before health care payments and the poverty level after these payments. RESULTS: At the threshold of 40% of capacity to pay, 0.31%, 0.07%, and 0.02% of Mongolian households suffered financially as a result of their member(s) staying in tertiary-level and secondary-level public hospitals and private hospitals respectively. About 0.13% of the total Mongolian population was impoverished owing to out-of-pocket payments for inpatient care at tertiary-level hospitals. Out-of-pocket payments for inpatient care at secondary-level hospitals and private hospitals were responsible for 0.10% and 0.09% respectively of the total population being pushed into poverty. CONCLUSIONS: Although most inpatient care at public hospitals is covered by the social health insurance benefit package, patients who utilized inpatient care at tertiary-level public hospitals were more likely to push their households into financial hardship and poverty than the inpatients at private hospitals. Improving the hospital sector's efficiency and financial protection for inpatients would be a crucial means of attaining universal health coverage in Mongolia.

Specialist shortage in developing countries: comprehending delays in care.

We describe a case of a middle-aged woman who presented with progressive jaundice and was suspected to have rebound choledocholithiasis, which was initially managed with balloon extraction through endoscopic retrograde cholangiopancreatography at her first presentation. Healthcare in Pakistan, like many other developing countries, is divided into public and private sectors. The public sector is not always completely free of cost. Patients seeking specialised care in the public sector may find lengthy waiting times for an urgent procedure due to a struggling system and a lack of specialists and technical expertise. Families of many patients find themselves facing 'catastrophic healthcare expenditure', an economic global health quandary much ignored.

Hospital Taxes, Medicaid Supplemental Payments, and State Budgets.

The federal Medicaid statute provides states an incentive to tax hospitals (even otherwise tax-exempt ones) as a means of raising revenue and then leverage federal matching funds by returning at least some of the tax back to the hospitals in the form of Medicaid supplemental payments. The potential for supplemental payments is attractive to hospitals, especially those struggling to recoup the costs of treating Medicaid and uninsured patients, and has resulted in political support from hospitals for states to create hospital "taxes" in name only-hospitals and states both end up with more money than they did when they started because of the federal match. When state officials begin to perceive, however, that nonprofit hospitals may be serving private rather than public interests, they are able to use these hospital taxes as a way to incrementally chip away at the historic governmental support provided through tax exemption by redirecting the revenue raised from the hospital tax to general fund purposes rather than Medicaid supplemental payments. This article looks at how states have been using hospital taxes and supplemental payments to balance state budgets and whether this practice is consistent with the Medicaid program objectives that make the taxes politically feasible.

Strategic management in local hospital markets: service duplication or service differentiation.

BACKGROUND: The purpose of this study is to assess the influences of market structure on hospitals' strategic decision to duplicate or differentiate services and to assess the relationship of duplication and differentiation to hospital performance. This study is different from previous research because it examines how a hospital decides which services to be duplicated or differentiated in a dyadic relationship embedded in a complex competitive network. METHODS: We use Linear Structural Equations (LISREL) to simultaneously estimate the relationships among market structure, duplicated and differentiated services, and performance. All non-federal, general acute hospitals in urban counties in the United States with more than one hospital are included in the sample (n = 1726). Forty-two high-tech services are selected for the study. Data are compiled from the American Hospital Association Annual Survey of Hospitals, Area Resource File, and CMS cost report files. State data from HealthLeaders-InterStudy for 2015 are also used. RESULTS: The findings provide support that hospitals duplicate and differentiate services relative to rivals in a local market. Size asymmetry between hospitals is related to both service duplication (negatively) and service differentiation (positively). With greater size asymmetry, a hospital utilizes its valuable resources for its own advantage to thwart competition from rivals by differentiating more high-tech services and reducing service duplication. Geographic distance is positively related to service duplication, with duplication increasing as distance between hospitals increases. Market competition is associated with lower service duplication. Both service differentiation and service duplication are associated with lower market share, higher costs, and lower profits. CONCLUSIONS: The findings underscore the role of market structure as a check and balance on the provision of high-tech services. Hospital management should consider cutting back some services that are oversupplied and/or unprofitable and analyze the supply and demand in the market to avoid overdoing both service duplication and service differentiation.

Effect of health insurance program for the poor on out-of-pocket inpatient care cost in India: evidence from a nationally representative cross-sectional survey.

BACKGROUND: In India, Out-of-pocket expenses accounts for about 62.6% of total health expenditure - one of the highest in the world. Lack of health insurance coverage and inadequate coverage are important reasons for high out-of-pocket health expenditures. There are many Public Health Insurance Programs offered by the Government that cover the cost of hospitalization for the people below poverty line (BPL), but their coverage is still not complete. The objective of this research is to examine the effect of Public Health Insurance Programs for the Poor on hospitalizations and inpatient Out-of-Pocket costs. METHODS: Data from the recent national survey by the National Sample Survey Organization, Social Consumption in Health 2014 are used. Propensity score matching was used to identify comparable non-enrolled individuals for individuals enrolled in health insurance programs. Binary logistic regression model, Tobit model, and a Two-part model were used to study the effects of enrolment under Public Health Insurance Programs for the Poor on the incidence of hospitalizations, length of hospitalization, and Out-of- Pocket payments for inpatient care. RESULTS: There were 64,270 BPL people in the sample. Individuals enrolled in health insurance for the poor have 1.21 higher odds of incidence of hospitalization compared to matched poor individuals without the health insurance coverage. Enrollment under the poor people health insurance program did not have any effect on length of hospitalization and inpatient Out-of-Pocket health expenditures. Logistic regression model showed that chronic illness, household size, and age of the individual had significant effects on hospitalization incidence. Tobit model results showed that individuals who had chronic illnesses and belonging to other backward social group had significant effects on hospital length of stay. Tobit model showed that days of hospital stay, education and age of patient, using a private hospital for treatment, admission in a paying ward, and having some specific comorbidities had significant positive effect on out-of-pocket costs. CONCLUSIONS: Enrolment in the public health insurance programs for the poor increased the utilization of inpatient health care. Health insurance coverage should be expanded to cover outpatient services to discourage overutilization of inpatient services. To reduce out-of-pocket costs, insurance needs to cover all family members rather than restricting coverage to a specific maximum defined.

For-Profit Hospitals Out of Business? Financial Sustainability During the COVID-19 Epidemic Emergency Response.

This perspective argues that for-profit hospitals will be heavily affected by epidemic crises, including the current coronavirus disease 2019 (COVID-19) outbreak. Policy-makers should be aware that for-profit hospitals in particular are likely to face financial distress. The suspension of all non-urgent elective surgery and the relegation of market-based mechanisms that determines the allocation and compensation of care puts the financial state of these hospitals at serious risk. We identify three organisational factors that determine which hospitals might be most affected (ie, care-portfolio, size and whether it is private equity [PE]-owned). In addition, we analyse contextual factors that could explain the impact of financial distress among for-profit hospitals on the wider healthcare system.

Establishing reference costs for the health benefit packages under universal health coverage in India: cost of health services in India (CHSI) protocol.

INTRODUCTION: To achieve universal health coverage, the Government of India has introduced Ayushman Bharat - Pradhan Mantri Jan Arogya Yojana (AB - PMJAY), a large tax-funded national health insurance scheme for the provision of secondary and tertiary care services in public and private hospitals. AB - PMJAY reimburses care for 1573 health benefit packages (HBPs). HBPs are designed to cover the treatment of diseases/conditions with high incidence/prevalence or which contribute to high out-of-pocket expenditure. However, there is a dearth of reference cost data against which provider payment rates can be assessed. METHODS AND ANALYSIS: The CHSI (Cost of Health Services in India) study will collect cost data from 13 Indian states covering 52 public and 40 private hospitals, using a mixed economic costing methodology (top-down and bottom-up), to generate unit costs for the HBPs. States will be sampled to capture economic status, development indicators and health service utilisation heterogeneity. The public sector hospitals will be chosen at secondary and tertiary care level. One tertiary facility will be selected from each state. At secondary level, three districts per state will be selected randomly from the district composite development score ranking. The private sector hospital sample will be stratified by nature of ownership (for-profit and not-for-profit), type of city (tier 1, 2 or 3) and size of the hospital (number of beds). Average costs for each HBP will be calculated across the different facility types. Multiple scenarios will be used to suggest rates which could be negotiated with the providers. Overall, the study will provide economic cost data for price setting, strategic purchasing, health technology assessment and a national cost database of India. ETHICS AND DISSEMINATION: The approval has been obtained from the Institutional Ethics Committee and Institutional Collaborative Committee of the Post Graduate Institute of Medical Education and Research, Chandigarh, India. The results shall be disseminated in conferences and peer-reviewed articles.

Optimal hospital payment rules under rationing by waiting.

We derive optimal rules for paying hospitals for non-emergency care when providers choose quality and capacity, and patient demand is rationed by waiting time. Waiting for treatment is costly for patients, so that hospital payment rules should take account of their effect on waiting time as well as on quality. Since deterministic waiting time models imply that profit maximising hospitals will never choose to have both positive quality and positive waiting time, we develop a stochastic model of rationing by waiting in which both quality and expected waiting are positive in equilibrium. We use it to show that, although a prospective output price gives hospitals an incentive to attract patients by raising quality and reducing waiting times, it must be supplemented by a price attached to hospital decisions on quality or capacity or to a performance indicator which depends on those decisions (such as average waiting time, or average length of stay). A prospective output price by itself can support the optimal quality and waiting time distribution only if the welfare function respects patient preferences over quality and waiting time, if patients' marginal rates of substitution between quality and waiting time are independent of income, and if waiting for treatment does not reduce the productivity of patients. If these conditions do not hold, supplementing the output price with a reward linked to the hospital's cost can increase welfare, though it is possible that costs should be taxed rather than subsidised.

Dialysis Care and Dialysis Funding in Asia.

Asia is the largest and most populated continent in the world, with a high burden of kidney failure. In this Policy Forum article, we explore dialysis care and dialysis funding in 17 countries in Asia, describing conditions in both developed and developing nations across the region. In 13 of the 17 countries surveyed, diabetes is the most common cause of kidney failure. Due to great variation in gross domestic product per capita across Asian countries, disparities in the provision of kidney replacement therapy (KRT) exist both within and between countries. A number of Asian nations have satisfactory access to KRT and have comprehensive KRT registries to help inform practices, but some do not, particularly among low- and low-to-middle-income countries. Given these differences, we describe the economic status, burden of kidney failure, and cost of KRT across the different modalities to both governments and patients and how changes in health policy over time affect outcomes. Emerging trends suggest that more affluent nations and those with universal health care or access to insurance have much higher prevalent dialysis and transplantation rates, while in less affluent nations, dialysis access may be limited and when available, provided less frequently than optimal. These trends are also reflected by an association between nephrologist prevalence and individual nations' incomes and a disparity in the number of nephrologists per million population and per thousand KRT patients.

Evaluation of costs and outcomes of physician-owned hospitals across common surgical procedures.

INTRODUCTION: The Affordable Care Act introduced restrictions on the creation of new physician-owned hospitals (POH). We sought to define whether POH status was associated with differences in care. METHODS: Patients undergoing one of ten surgical procedures were identified using Medicare Standard Analytic Files. Patient and hospital-level characteristics and outcomes between POH and non-POH were compared. RESULTS: Among 1,255,442 patients identified, 14,560 (1.2%) were treated at POH. A majority of POHs were in urban areas (n = 30, 90.9%) and none were in low socioeconomic status areas. Patients at POH were slightly younger (POH:72, IQR:68-77 vs. non-POH:73, IQR:69-79) and healthier (CCI; POH:2; IQR: 1-3 vs. non-POH: 3; IQR: 1-4). Patients at non-POH had higher odds of postoperative complications (OR:1.67, 95%CI:1.55-1.80) and slightly higher medical expenditures (POH:$11,347, IQR:$11,139-$11,936 vs. non-POH:$13,389, IQR:$11,381-$19,592). CONCLUSIONS: POH were more likely to be located in socioeconomic advantaged areas, treat healthier patients and have lower associated expenditures.

Technical Efficiency of Public and Private Hospitals in Beijing, China: A Comparative Study.

Objective: With the participation of private hospitals in the health system, improving hospital efficiency becomes more important. This study aimed to evaluate the technical efficiency of public and private hospitals in Beijing, China, and analyze the influencing factors of hospitals' technical efficiency, and thus provide policy implications to improve the efficiency of public and private hospitals. Method: This study used a data set of 154-232 hospitals from "Beijing's Health and Family Planning Statistical Yearbooks" in 2012-2017. The data envelopment analysis (DEA) model was employed to measure technical efficiency. The propensity score matching (PSM) method was used for matching "post-randomization" to directly compare the efficiency of public and private hospitals, and the Tobit regression was conducted to analyze the influencing factors of technical efficiency in public and private hospitals. Results: The technical efficiency, pure technical efficiency and scale efficiency of public hospitals were higher than those of private hospitals during 2012-2017. After matching propensity scores, although the scale efficiency of public hospitals remained higher than that of their private counterparts, the pure technical efficiency of public hospitals was lower than that of private hospitals. Panel Tobit regression indicated that many hospital characteristics such as service type, level, and governance body affected public hospitals' efficiency, while only the geographical location had an impact on private hospitals' efficiency. For public hospitals in Beijing, those with lower average outpatient and inpatient costs per capita had better performance in technical efficiency, and bed occupancy rate, annual visits per doctor, and the ratio of doctors to nurses also showed a positive sign with technical efficiency. For private hospitals, the average length of stay was negatively associated with technical efficiency, but the bed occupancy rate, annual visits per doctor, and average outpatient cost were positively associated with technical efficiency. Conclusions: To improve technical efficiency, public hospitals should focus on improving the management standards, including the rational structure of doctors and nurses as well as appropriate reduction of hospitalization expenses. Private hospitals should expand their scale with proper restructuring, mergers, and acquisitions, and pay special attention to shortening the average length of stay and increasing the bed occupancy rate.