Explore the vast range of titles available.

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.

IntroductionTo 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 analysisThe 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 disseminationThe 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.

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.

Ownership of healthcare providers has been considered as one factor that might influence their health and healthcare related performance. The aim of this article was to provide an overview of what is known about the effects on economic, administrative and health related outcomes of different types of ownership of healthcare providers--namely public, private non-for-profit (PNFP) and private for-profit (PFP)--based on the findings of systematic reviews (SR). An overview of systematic reviews was performed. Different databases were searched in order to select SRs according to an explicit comprehensive criterion. Included SRs were assessed to determine their methodological quality. Of the 5918 references reviewed, fifteen SR were included, but six of them were rated as having major limitations, so they weren't incorporated in the analyses. According to the nine analyzed SR, ownership does seem to have an effect on health and healthcare related outcomes. In the comparison of PFP and PNFP providers, significant differences in terms of mortality of patients and payments to facilities have been found, both being higher in PFP facilities. In terms of quality and economic indicators such as efficiency, there are no concluding results. When comparing PNFP and public providers, as well as for PFP and public providers, no clear differences were found. PFP providers seem to have worst results than their PNFP counterparts, but there are still important evidence gaps in the literature that needs to be covered, including the comparison between public and both PFP and PNFP providers. More research is needed in low and middle income countries to understand the impact on and development of healthcare delivery systems.

Background Reducing patient expenditure and expanding healthcare access through private sector hospitals is widely touted strategy for governments to achieve Universal Health Care, including in India. However, private sector engagement in India’s publicly funded health insurance schemes (PFHIS) remains low and is uneven across geographies and by hospitals size. This paper examines challenges to achieving effective private sector engagement in PFHIS by analysing private sector participation and exploring diverse stakeholder perspectives. Methods This case study used sequential mixed methods design and was conducted in 2023-24 in Maharashtra, India. We combined quantitative analysis of the geographic distribution of empanelled private hospitals (993 across Maharashtra’s 36 districts) and qualitative interviews ( n  = 16) with diverse stakeholders to understand why some facilities do not engage. The analysis was guided by our framework on private sector engagement that examined policy factors, hospital level factors and operational factors. Results Only 13% of private hospitals were empanelled in Maharashtra’s PFHIS, with higher empanelment in urban areas and among small and medium sized hospitals; rural areas had few empanelled hospitals and few large private hospitals participated. Districts with few empanelled private hospitals had lower overall hospitalization rates, suggesting persistent unmet population need for affordable hospitals. Low private sector engagement was driven by multiple factors: at the policy level, insufficient state budgets, low reimbursement rates, fixed scheme packages, strict empanelment criteria, complex claims processes, and delayed reimbursements; at the hospital level, economic non-viability, concerns about patient load and profile, and limited administrative capacities; and at the operational level, inadequate monitoring mechanisms for PFHIS and empanelled hospitals, gaps in the empanelment process, and delays in patient pre-authorization and claims processing. Conclusion This study enhances understanding of private sector engagement challenges and provides insights for improving PFHIS and UHC in India. The framework developed can also be applied beyond India to assess the complexities of intent, capacity, and interactions between private and public actors in PFHIS. To create an enabling environment for private sector engagement and achieve the scheme’s objectives, the state could increase reimbursement rates, implement responsive grievance redressal, regulate private hospitals, and improve governance processes. A two-fold strategy of strengthening the public health system and engaging with regulated private hospitals could enhance the scheme’s effectiveness.

Background Many LMICs have implemented Publicly Funded Health Insurance (PFHI) programmes to improve access and financial protection. The national PFHI scheme implemented in India for a decade has been recently modified and expanded to cover free hospital care for 500 million persons. Since increase in annual cover amount is one of the main design modifications in the new programme, the relevant policy question is whether such design change can improve financial protection for hospital care. An evaluation of state-specific PFHI programmes with vertical cover larger than RSBY can help answer this question. Three states in Southern India - Andhra Pradesh, Karnataka and Tamil Nadu have been pioneers in implementing PFHI with a large insurance cover. Methods The current study was meant to evaluate the PFHI in above three states in improving utilisation of hospital services and financial protection against expenses of hospitalization. Two cross-sections from National Sample Survey’s health rounds, the 60th round done in 2004 and the 71st round done in 2014 were analysed. Instrumental Variable method was applied to address endogeneity or the selection problem in insurance. Results Enrollment under PFHI was not associated with increase in utilisation of hospital care in the three states. Private hospitals dominated the empanelment of facilities under PFHI as well as utilisation. Out of Pocket Expenditure and incidence of Catastrophic Health Expenditure did not decrease with enrollment under PFHI in the three states. The size of Out of Pocket Expenditure was significantly greater for utilisation in private sector, irrespective of insurance enrollment. Conclusion PFHI in the three states used substantially larger vertical cover than national scheme in 2014. The three states are known for their good governance. Yet, the PFHI programmes in all three states failed in fulfilling their fundamental purpose. Increasing vertical cover of PFHI and using either ‘Trusts’ or Insurance-companies as purchasers may not give desired results in absence of adequate regulation. The study raises doubts regarding effectiveness of contracting under PFHIs to influence provider-behavior in the Indian context. Further research is required to find solutions for addressing gaps that contribute to poor financial outcomes for patients under PFHI.

Background Hospitals possess distinct characteristics that influence their capital structures, particularly in China, where the hospital industry is predominantly public but includes private not-for-profit and private for-profit hospitals. There is currently limited empirical evidence on how operational and financial factors influence the debt-to-asset decisions of hospitals in China. Methods This study analyzed data from 909 hospitals in China collected in 2013 and 2014 through the China National Health Statistical Information Report. Using a two-part model, we examined the effects of ownership, hospital type, revenue stream diversification, market share, and other characteristics on short-term, long-term, and total debt-to-asset ratios. Results The analysis revealed that private for-profit (FP) hospitals and specialized hospitals did not significantly reduce the probability of assuming short-term debt. However, private FP hospitals with less diversified revenue streams were more likely to rely on short-term debt to meet operational needs. Private ownership also reduced the probability of assuming long-term debt. Higher returns on assets (ROA) were significantly associated with a lower probability of assuming any debt or short-term debt but had no significant effect on the likelihood of assuming long-term debt. Most hospital characteristics were not significant predictors of short-term or long-term debt-to-asset ratios, with the exception that being a general hospital was linked to higher long-term debt-to-asset ratios. Notably, private FP hospitals with higher ROA were associated with increased long-term debt-to-asset ratios, indicating that profitability plays a key role in their long-term borrowing decisions. Conclusion This study highlights the influence of financial and operational factors on hospital capital structures in China. The results emphasize the need for policies to support private hospitals, particularly in obtaining long-term loans and diversifying financing options, to promote equitable access to funding and improve healthcare delivery. These insights contribute to the understanding of hospital debt dynamics and provide implications for healthcare policy and management.

Background The Government of Turkey has initiated a series of major health reforms in 2003 with an objective of increasing access to health care services and improving efficiency of public and private hospitals. This study attempts to understand the technical efficiency of public and private hospitals in Turkey to better guide hospital reform. Methods We use data from 1079 public and private hospitals and translog stochastic production frontier was adopted to estimate technical inefficiency of hospitals. Results Results indicate that there is no statistically significant difference in the degree of inefficiency of hospitals by geographic location or its level of economic development. Efficiency scores vary significantly across hospital types with Ministry of Health (MoH) General Hospitals being the most efficient followed by MoH teaching hospitals. Better performance of MoH hospitals may be due to successful implementation of 2003 health reforms in Turkey, which intended to improve resource utilization within and across MoH hospitals. Among MoH hospital types, integrated county hospitals were the least efficient. Since the hospital outcome measure did not include the value of medical training, efficiency scores of university hospitals became relatively low. Wide variability of efficiency scores of private general hospitals implies the existence of both highly efficient and inefficient hospitals in the private sector. Conclusions Efficiency differences of various hospital types can be leveraged to guide future reforms by emphasizing the strengths of general hospitals and improving the referral system from county hospitals to general hospitals. Encouraging resource sharing across hospitals, as being done by the 2011 reforms, should further improve hospital efficiency. Promoting private hospitals may not necessarily be efficiency enhancing due to high variability of private hospitals in terms of efficiency scores. Similarly, implementation of common productivity standards and quality control measures are likely to improve hospital technical efficiency scores further.

Background India launched a national health insurance scheme named Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (AB-PMJAY) in 2018 as a key policy for universal health coverage. The ambitious scheme covers 100 million poor households. None of the studies have examined its impact on the quality of care. The existing studies on the impact of AB-PMJAY on financial protection have been limited to early experiences of its implementation. Since then, the government has improved the scheme’s design. The current study was aimed at evaluating the impact of AB-PMJAY on improving utilisation, quality, and financial protection for inpatient care after four years of its implementation. Methods Two annual waves of household surveys were conducted for years 2021 and 2022 in Chhattisgarh state. The surveys had a sample representative of the state’s population, covering around 15,000 individuals. Quality was measured in terms of patient satisfaction and length of stay. Financial protection was measured through indicators of catastrophic health expenditure at different thresholds. Multivariate adjusted models and propensity score matching were applied to examine the impacts of AB-PMJAY. In addition, the instrumental variable method was used to address the selection problem. Results Enrollment under AB-PMJAY was not associated with increased utilisation of inpatient care. Among individuals enrolled under AB-PMJAY who utilised private hospitals, the proportion incurring catastrophic health expenditure at the threshold of 10% of annual consumption expenditure was 78.1% and 70.9% in 2021 and 2022, respectively. The utilisation of private hospitals was associated with greater catastrophic expenditure irrespective of AB-PMJAY coverage. Enrollment under AB-PMJAY was not associated with reduced out-of-pocket expenditure or catastrophic health expenditure. Conclusions AB-PMJAY has achieved a large coverage of the population but after four years of implementation and an evidence-based increase in reimbursement prices for hospitals, it has not made an impact on improving utilisation, quality, or financial protection. The private hospitals contracted under the scheme continued to overcharge patients, and purchasing was ineffective in regulating provider behaviour. Further research is recommended to assess the impact of publicly funded health insurance schemes on financial protection in other low- and middle-income countries.

Out-of-pocket expenditure (OOPE) directly reflects households’ financial burden for healthcare. Despite efforts to enhance accessibility and affordability through government initiatives and insurance schemes, OOPE remains problematic, especially in rural areas with inadequate public healthcare infrastructure. This study examines factors influencing OOPE in Karnataka’s Dakshina Kannada, Udupi, and Shimoga districts, investigating socioeconomic characteristics, healthcare infrastructure, and accessibility to inform policies for equitable healthcare access and reduced household financial strain. Using purposive sampling, 61 semi-structured interviews were conducted in rural and urban South Karnataka, recorded in Kannada after obtaining consent, and thematically analyzed. Results revealed mixed perceptions of healthcare quality, cost, and accessibility between government and private hospitals. Government facilities were lauded for improved infrastructure and affordability, while private hospitals were preferred for quality and personalized care despite higher costs. Health insurance significantly impacted OOPE reduction. Participants emphasized the need for increased awareness of government insurance programs and improved quality in public hospitals. The study concludes that private hospitals are favored for superior care despite expenses, while government hospitals are valued for affordability. Expanding insurance coverage and improving public awareness are crucial for enhancing healthcare accessibility and affordability.