Financial Viability of Private Hospitals Operating Under India’s National Health Insurance Scheme Ayushman Bharat Pradhan Mantri-Jan Arogya Yojana (AB PM-JAY)

Abstract

Background

Private hospitals account for 46% of all hospitals empanelled in India’s national health insurance scheme and contribute to 54% of all the hospitalizations under it. However, insufficient package prices are often cited as a constraint to viable hospital operations. This study assesses the financial viability of establishing such hospitals at district level, with a focus on determining the break-even threshold by forecasting the financial trajectory of hospitals.

Methods

By utilizing primary data from 27 district hospitals across nine states in India on cost of providing healthcare services, a blend of bottom-up and top-down micro-costing methods was used to estimate financial cost across input resource categories, including land procurement, building construction, human resources, equipment, drugs, consumables, maintenance, and overheads. Revenue from inpatient services was estimated using healthcare provider payment rates under India’s largest tax-funded health insurance scheme, coupled with patient volume data stratified by distinct diseases across different specialties. Revenue projections from outpatient services were extrapolated as a fixed proportion of their inpatient counterparts. A 10-year evaluation framework was employed to forecast the hospital operations using revenue–expenditure perspective. Sensitivity analyses were undertaken to assess the extent of variations in the output owing to varying bed-occupancy levels and doctor-to-bed ratios.

Results

For a model 100-bed private hospital operating at district level, the average annual expenditure and revenue are projected to be at Indian Rupee (₹)85.27 million (US $1.03 million) and ₹104.36 million (US $1.26 million), respectively, for the initial 10 years. Human resources constitute the primary share (40%) of total expenditure, followed by spending on drugs and consumables (20%). A sequential evaluation of annual revenue and expenditure reveals that hospitals reach breakeven by their fourth operational year, subsequently transitioning into a profitable phase.

Conclusions

The study suggests a viable financial trajectory for private hospitals at district level, following the pricing structure of government-sponsored health insurance scheme.

Key Points for Decision Makers

Providing empirical evidence, this research challenges the skepticism about payment rates of India’s national health insurance scheme and demonstrates that private hospitals can operate profitably under Ayushman Bharat Pradhan Mantri-Jan Arogya Yojana (AB PM-JAY) model while enhancing healthcare accessibility and affordability in India. The study demonstrates that the private healthcare sector in India should consider the AB PM-JAY scheme as a financially viable payer.

The establishment of private hospitals operating under AB PM-JAY model at the district level in tier 2 and tier 3 cities is a strategic investment opportunity, especially when the demand for health services is rising in these locations at a greater pace across the country.

Government subsidies such as providing free land for hospital construction can significantly improve the financial viability of private healthcare, accelerating breakeven and attracting investment. A sustainable model can be developed where the government supports private hospitals while requiring them to offer care at AB PM-JAY rates, ensuring both profitability and affordable healthcare access.

Introduction

The significant focus on privatization during the 1990s in India spurred remarkable growth in the private healthcare sector. Consequently, the number of private health enterprises (hospitals, nursing homes, and diagnostic centres) surged from 10,000 to 75,000 within a span of 10 years [1]. Subsequent to it, in the year 2000, the Government of India allowed 100% foreign direct investment (FDI) in the hospital sector through automatic route [2]. As a result, foreign investment in the hospital sector increased to Indian Rupee (₹)39.95 billion (US $481.32 million) from 2013 to 2014 from a meagre ₹0.31 billion (US $3.73 million) from 2001 to 2002 [3]. More recently, the Government of India has accorded greater attention to make India a preferred destination for medical tourism globally under the initiative of “heal in India” to promote medical value travel (MVT) in the country [4]. All these factors, together, have contributed to making India’s private hospital industry a lucrative avenue for investment [1]. Such a scenario, however, warrants an assessment of financial viability of private hospitals in India.

The significantly large presence of private hospitals is underscored by the fact that it contributes to 78% of total outpatient visits and 60% of hospitalizations [5]. In the context of India’s national government-funded health insurance scheme, i.e., Ayushman Bharat Pradhan Mantri-Jan Arogya Yojana (AB PM-JAY), private hospitals account for 46% of all hospitals empanelled in this scheme and contribute to 54% of all the hospitalization claims under it [6, 7]. As a result, the private sector hospitals are an important stakeholder in the entire care provision, as well as from the AB PM-JAY perspective. Nevertheless, a recent study conducted in India’s aspirational districts revealed that nine states did not have any private hospitals empanelled in these areas [8]. In addition, the availability of hospitals offering critical tertiary care services was found to be significantly lower in aspirational districts compared with other regions [9]. Similarly, a report on a government-funded health insurance scheme in Maharashtra highlighted that the reluctance of multi-specialty private hospitals to participate in the program adversely impacted the accessibility of essential healthcare services. [10]

An important consideration for the willingness of private hospitals to empanel under the AB PM-JAY is the appropriateness of provider payment rates, such that these adequately cover the cost of care and hospitals remain financially viable [11–13]. However, many private hospitals remain hesitant to join the program [14–17]. A primary reason for this reluctance is the perceived inadequacy of provider payment rates under PM-JAY [15, 16, 18, 19]. These rates, often quoted as 40–50% lower than market prices for similar procedures, are seen as insufficient to cover the actual costs of delivering care, particularly for resource-intensive or specialized services [11, 17, 19]. Other reasons cited for hesitancy of private hospitals to join the scheme are delayed payments for claims creating cash flow challenges and administrative hurdles, including stringent empanelment criteria and the extensive documentation required [14, 16, 20]. These challenges are especially pronounced for smaller hospitals in tier-2 and tier-3 cities, where operational margins are narrower, and any delays or underpayments can significantly impact sustainability.

In a study assessing the factors that motivate the private hospitals to get empanelled in the PM-JAY found that for the large hospitals with better facilities, the primary motivation was to support the needy, clearly stating that they make no discernible profit from it at current reimbursement rates, while some hospitals stated that they have entered the scheme out of fear of losing patients to competing facilities [20]. These findings highlight that private hospitals generally do not perceive operating under the PM-JAY reimbursement rates as a financially sustainable option. Although, to ensure that the prices are appropriate, there have been four revisions of the AB PM-JAY health benefit package, wherein the prices have been significantly rationalized [21].

In view of these contextual and policy developments, we undertook this study to determine the financial viability of operating a private hospital that is solely financed through the AB PM-JAY scheme. This analysis is vital to inform strategies that ensure not only their participation but also their sustained contribution to strengthening India’s healthcare infrastructure. Since there is significant heterogeneity within private hospitals, we analyzed the data from the perspective of a typical district level hospital that matches a public sector district hospital in terms of infrastructure. This is also justified, considering the government’s attempts to strengthen medical care infrastructure in tier-2 and tier-3 cities. The recent directive from the Supreme Court of India, urging the government to standardize charges imposed by private hospitals in alignment with publicly funded health insurance scheme rates, once again underscores the importance of the pricing decision in achieving the objectives of the health system [22].

Materials and Methods

Overview

Assessing the financial viability of setting up and operating private hospitals at the district level entails calculating both the financial costs (expenditure) and income (revenue) associated with these hospitals, followed by a comparison of the two. The assessment of revenue and expenditure was carried out from the hospital’s (health system’s) perspective, employing a time horizon of 10 years. Central to this assessment was the determination of the break-even threshold, wherein revenue generated surpasses operational expenditure, thereby ensuring long-term viability and sustainability. The methodology utilized for estimating financial cost involved a blend of bottom-up and top-down micro-costing approach, drawing on primary data collected from 27 district hospitals spread across nine states in India [23, 24]. We assessed the input resources required for establishing and operating a hospital, wherein the assessment of financial cost encompassed both capital and recurrent resources such as land acquisition, building construction, medical equipment, human resources salaries, drugs and consumables, and overhead costs. The temporal dynamics associated with hospital construction and operationalization were factored in, aligning with established market practices and financing strategies.

In parallel, the estimation of hospital revenue focused on potential revenue generated from inpatient services, utilizing healthcare provider payment rates under India’s largest tax-funded health insurance scheme. [25] Patient volume data, stratified by distinct diseases across different specialties, were used to assess revenue generated from providing inpatient care, considering both cases covered under the health benefit packages defined by the AB PM-JAY and those not covered [26]. Revenue projections factored in anticipated annual increases and modeled outpatient department (OPD) revenue as a proportion of inpatient department (IPD) revenue.

Sensitivity analyses were conducted to explore the impact of potential changes in key inputs and outputs of private hospitals on their financial performance, including variations in bed occupancy levels, bed-to-doctor ratios, and government incentives such as complimentary land for hospital construction. All costs are reported in Indian Rupees (₹) and United States Dollars ($) using the average conversion rate of 1 US $= ₹83 in 2024 [27].

Estimation of Hospital Expenditure

We used the primary data from 27 district hospitals across nine Indian states on cost of providing healthcare services, collected as a part of the Cost of Health Services in India (CHSI) study [23, 24]. A blend of bottom-up and top-down costing methods was used to estimate expenditure across diverse input resource used in establishing and operating a hospital. The data are also part of the National Health System Cost Database released by the Government of India [28–30]. The nine states in the CHSI study were selected considering the heterogeneity on the basis of the geography, human development index (HDI), gross state domestic product (GSDP), and health workforce density. The district hospitals within a given state were selected using stratified sampling. All the districts of a state were stratified in three tertiles on the basis of a composite index drawn from socioeconomic, demographic, and healthcare utilization indicators. In addition, one district hospital was randomly selected from each of the three tertiles. [23]

A 10-year time horizon was employed to forecast the hospital operations using revenue–expenditure perspective. The assessment of hospital expenditure encompassed both capital and recurrent resources. Capital resources, comprising land, building construction, medical and nonmedical equipment, furniture, and vehicles, were valued. Recurrent resources, however, included salaries of human resources, procurement of drugs and consumables (sanitary, surgical, and stationary items), overhead costs such as water, electricity, telephone services, and diesel consumption, as well as maintenance charges.

The assessment of hospital expenditure was also informed by a set of established parameters and assumptions (Table 1). Firstly, the land area required for hospital construction was calculated at 330 square feet (ft²) per bed, as derived from primary data obtained from the CHSI study [11, 24, 31]. Adhering to guidelines for clinical establishments in India, 20% of the total area was allocated for open space [32]. The land purchase cost was determined at ₹5000 (US $60.24) per square foot, on the basis of the prevailing market rates of commercial land in tier-2 and tier-3 cities [33]. Construction costs were estimated at the rate of ₹1800 (US $21.69) per square foot for basic building construction, sourced from a market survey among hospital architect companies and interviews with construction stakeholders [34–36]. In addition, specialized medical infrastructure costs, including the installation of oxygen supply, fire safety systems, and centralized air conditioning and ventilation, were factored in at ₹600 (US $7.23) per square foot, derived from market research conducted with hospital architect firms and insights gathered through interviews with key construction stakeholders [34–36]. In line with standard banking practices informed by the monetary policies of the Reserve Bank of India, the financing strategy for land purchase and building construction involved availing a loan, wherein 20% of the payment constituted a down payment, with the remaining amount being amortized through equated monthly instalments (EMIs) over a period of 40 years [37]. The annual rate of interest for this loan was assumed to be 9% [37].

Table 1.

Key assumptions in estimation of hospital expenditure and revenue

Assumption	Details	Source/justification
Land area required for hospital construction	330 ft2 per bed	Data from 27 district hospitals surveyed under CHSI study [11, 24, 31]
Allocation of open space	20% of the land is allocated for open space	Guidelines for clinical establishments in India [32]
Land purchase cost	₹5000 (US $60.24) per square foot	Prevailing market rates in tier-2 and tier-3 cities of India [33]
Basic building construction cost	₹1800 (US $21.69) per square foot	Market survey data and interviews with construction stakeholders [34–36]
Specialized medical infrastructure cost	₹600 (US $7.23) per square foot for oxygen supply, fire safety systems, and air conditioning	Market survey data and interviews with construction stakeholders [34–36]
Financing strategy for land and construction	20% as down-payment, remaining amount amortized via equated monthly instalments over 40 years at 9% annual interest	Monetary policy of Reserve Bank of India and standard banking regulations [37]
Maintenance cost for equipment and furniture	10% of initial cost annually	Data from 27 district hospitals surveyed under CHSI study [11, 24, 31]
Building maintenance cost	5% of construction costs annually	Data from 27 district hospitals surveyed under CHSI study [11, 24, 31]
Future cost adjustment	7% annual inflation rate	Inflation trend in India over the past decade [38]
Human resource salary increment	8% annual increase	Consumer price inflation-linked norms in India [39]
Expenditure on drugs and consumables	Calculated using patient volume, types of drugs used, and drug prices	Data from 27 district hospitals surveyed under CHSI study [11, 24, 31]
Revenue from OPD services	15% of the IPD services	Annual reports of private hospitals [40, 41]
Bed-to-doctor ratio	8.13	Data from 27 district hospitals surveyed under CHSI study [11, 24, 31]

For ongoing maintenance, annual expenses were projected at 10% of the initial cost for equipment and furniture, a figure corroborated by market surveys and cost data from 27 district hospitals surveyed under the CHSI study [11, 24, 31]. Building maintenance costs were set at 5% of the construction cost [11, 24, 31]. Future costs were adjusted using an annual inflation rate of 7%, extrapolated from inflation trends observed over the past decade [38]. Human resource salary increments were forecasted at 8% annually, aligning with current consumer price inflation-linked norms in India. [39]

We also considered the temporal dynamics associated with the construction and operationalization of a hospital facility. Given that the construction of the hospital building typically spans a 2-year period, it was assumed that the delivery of outpatient and inpatient services, which generate revenue, would commence following the completion of construction [35]. From the onset of construction, costs associated with land acquisition, building construction, and utilities expenditure were considered to accrue from the first year onward. In addition, it was assumed that expenditures related to equipment and furniture procurement would occur during the second year of the construction phase.

For estimation of expenditure on drugs and consumables, first we obtained the primary data on the type of different drugs and consumables utilized in 1 reference year across various specialties from 27 district hospitals surveyed under the CHSI study [11, 24]. Subsequently, utilizing data on patient volume and the prices of respective items, we calculated the average annual per-bed cost that a hospital incurs on drugs and consumables. This implied that data on actual consumption of drugs and consumables for treatment of different diseases were utilized for estimation of expenditure, which was representative of prevailing practices of care delivery at a hospital operational at district level. Nonetheless, recognizing that the 27 district hospitals included in the CHSI study might operate below or above their full capacity, we adjusted these estimates to reflect a 100% bed occupancy rate using data on patient volume, number of beds, and expected length of stay under different diseases.

Estimation of Hospital Revenue

Potential revenue generated from inpatient services was estimated using the healthcare provider payment rates under India’s largest tax-funded health insurance scheme, coupled with patient volume data stratified by distinct diseases across different specialties. For estimation of revenue generated from providing inpatient care, the case- based bundled payments were determined using the provider payment rates of health benefit packages (version 2.0) as defined under India’s national insurance program- Ayushman Bharat Pradhan Mantri-Jan Arogya Yojana (AB PM-JAY) [25]. We used the annual (2019) data on health insurance claims for various health benefit packages at the district hospital level under AB PM-JAY to obtain a distribution of services by the type of morbidity [26].

For estimation of revenue generated from providing inpatient care, considering an average allocation of beds to the different specialties in the district hospitals, and the average length of stay of the patients admitted in each of the different specialties, we estimated the expected number of admissions that are likely to take place in each of the specialties. The revenue generated from providing inpatient care was assessed at the specialty level and computed as a product of the provider payment rate of delivering the services under health benefit packages (HBPs) as defined under PM-JAY and the number of cases corresponding to each of the HBP in the preceding year [11]. However, the hospitals are also assumed to provide inpatient care for procedures that may not be part of the PM-JAY health benefit package. For diseases/procedures that are not covered under PM-JAY, the revenue generated from providing inpatient care was assessed using the specialty-specific weighted average price and volume of non-PM-JAY admissions, as explained in the equation below:

$$\text{Estimated inpatient care revenue}=\left\{\begin{array}{c}{I}_1={\sum }_{i=1}^n{\sum }_{j=1}^{\text{i}}{c}_{\text{ij}}{a}_{\text{ij}},ifpackageisincludedinPMJAY\hfill \\ I_2={\sum }_{i=1}^n\left(\frac{{\sum }_{j=1}^{\text{i}}{c}_{\text{ij}}{a}_{\text{ij}}}{{\sum }_{j=1}^{\text{i}}{a}_{\text{ij}}}\right)\times t_{\text{i}},other\hfill \end{array},,\right)$$

where n is total number of specialties, $m_{\text{i}}$ is number of PM-JAY packages in $i^{\text{th}}$ speciality, $c_{\text{ij}}$ is the $j^{\text{th}}$ package price in $i^{\text{th}}$ specialty, $a_{\text{ij}}$ is number of $j^{\text{th}}$ package claims in $i^{\text{th}}$ speciality, $t_{\text{i}}$ is number of non-PMJAY packages in $i^{\text{th}}$ speciality,

$$\text{IPD revenue}=I_1+I_2.$$

Revenue projections factored in an estimated 10% annual increase, reflective of health inflation trends and data from private hospital annual reports [40, 41]. Furthermore, outpatient department (OPD) revenue was modeled as a proportion of inpatient department (IPD) revenue, set at 15%, in line with data extracted from private hospital annual reports [40, 41].

Sensitivity Analysis

We conducted three sensitivity analyses to demonstrate the impact of potential changes in key inputs and outputs of a private hospital on its financial performance. The first sensitivity analysis aimed to quantify the effects of changing bed occupancy levels on hospital revenue. Bed occupancy rates were systematically reduced, and the resulting decrease in hospital revenue was assessed. It is noteworthy that alterations in bed occupancy rates not only directly affect revenue generated from inpatient services but also influence outpatient revenue, which is linked to the volume of inpatient services and thereby estimated as a proportion of inpatient revenue in our analysis.

The second sensitivity analysis focused on investigating the effect of changing the bed-to-doctor ratio on hospital expenditure. In our base-case analysis, the bed-to-doctor ratio was set at 8.13, meaning one doctor attends to 8.13 beds. This consideration was aligned with observed staffing patterns across the 27 district hospitals, which were surveyed as a part of CHSI study. However, for this sensitivity analysis, we varied this ratio from 4 to 16. This broad range was chosen in consultation with subject experts and key informants. In consultations, it emerged that the government staffing norms, which are typically followed in public sector district hospitals, tend to allocate relatively higher human resources compared with their private counterparts. Therefore, we explored the variations in hospital expenditure resulting from different levels of relaxation in the bed-to-doctor ratio.

In the third sensitivity analysis, we explored a scenario where the government offers free land for hospital construction. This scenario was selected owing to the government’s proactive measures aimed at encouraging the establishment of private hospitals, particularly in tier-2 and tier-3 cities. Recognizing the significance of private healthcare infrastructure in these areas, the government has introduced a range of incentives to facilitate their development [2, 42]. Therefore, this analysis examines the potential impact of such a policy on the financial landscape of individual hospitals.

Results

For a model 100-bed private hospital situated in a district level, projected financial data indicate an average annual expenditure of ₹85.27 million (US $1.03 million) and revenue of ₹104.36 million (US $1.26 million) over the initial 10-year period (Fig. 1). Specifically, within this timeframe, the estimated mean annual expenditure on human resources amounts to ₹34.42 million, while expenses on drugs and consumables and on land and construction (inclusive of building maintenance) stand at ₹17.22 million (US $0.21 million) and ₹20.3 million (US $0.24), respectively. A breakdown of annual expenditure across various resources is detailed in Table 2.

Fig. 1.

Input-wise expenditure on establishing and operating a hospital across different years (estimates for a 100-bed hospital)

Table 2.

Details of annual revenue and expenditure (in million ₹) for a model 100-bed hospital

Year since commencement of construction (in parentheses: year since operationalization)	Expenditure								Revenue
	Human resource	Land cost (down payment and EMIs)	Construction and maintenance of building (down payment and EMIs)	Equipment (inclusive of operating and maintenance cost)	Drugs and consumables	Furniture (inclusive of maintenance cost)	Overheads and utilities	Total
First year	0	27.1	21.7	0	0	0	4.6	53.3	0
Second year	0	7.3	9.8	20.3	0	7.9	4.9	50.3	0
Third year (first operational year)	32.4	7.3	9.8	2.1	16.8	0.8	5.2	74.4	91.3
Fourth year (second operational year)	35	7.3	9.8	2.4	18	1	5.6	79	100.4
Fifth year (third operational year)	37.8	7.3	9.8	2.7	19.2	1.2	6	83.9	110.4
Sixth year (fourth operational year)	40.8	7.3	9.8	3.1	20.6	1.1	6.4	89	121.5
Seventh year (fifth operational year)	44	7.3	9.8	6.1	22	2.8	6.8	98.9	133.6
Eighth year (sixth operational year)	47.6	7.3	9.8	4.5	23.5	2.1	7.3	102.2	147
Ninth year (Seventh operational year)	51.4	7.3	9.8	4.7	25.2	1.5	7.8	107.7	161.7
Tenth year (Eighth operational year)	55.5	7.3	9.8	3.9	27	2.1	8.4	114	177.8

As illustrated in Fig. 2, human resource costs constitute the largest portion (40%) of total expenditure, followed by spending on drugs and consumables (20%). This breakdown underscores the significance of human capital and resource allocation in shaping the financial trajectory of hospital operations. Analysis of yearly revenue and expenditure indicates that hospitals achieve breakeven by their fourth operational year (or the sixth-year post-construction commencement), thereafter transitioning into profitability (Fig. 3). This transition marks a significant turning point, signaling the hospital’s ability to generate sufficient revenue to offset initial startup expenditure and subsequent operational expenses. The model hospital’s annual revenue generation across an analytical horizon of 10 years is also presented in Table 2.

Fig. 2.

Proportion of different input resources in the overall expenditure of establishing and operating a hospital

Fig. 3.

Financial trajectory of attaining breakeven by a newly established hospital

The findings of the sensitivity analysis, which explores varying levels of hospital revenue corresponding to different bed occupancy levels (Fig. 4a), illustrate that higher bed occupancy rates accelerate breakeven attainment. Operating at a 95% bed occupancy rate leads to breakeven at the onset of the fifth operational year (seventh year post-construction). Thus, as the bed occupancy rate decreases, the break-even point shifts further ahead by a few months. If the bed occupancy rate decreases to 75%, the break-even point will be reached by the end of the eighth year of operation (tenth year from the start of construction). This sensitivity analysis also highlights that as bed occupancy drops below 80%, the break-even point is pushed farther into the future at an accelerated rate. This occurs because, while variable costs decrease steadily with declining occupancy, the proportion of fixed costs in the total expenses begins to rise, as it remains constant across all occupancy levels.

Fig. 4.

Cumulative revenue and expenditure at varying levels of a bed occupancy and b bed-to-doctor ratio

Another sensitivity analysis, depicted in Fig. 4b, explored various levels of hospital expenditure corresponding to different bed-to-doctor ratios. It was found that increasing this ratio to 10 (meaning one doctor attending to 10 beds, as opposed to the current ratio of 8.13 beds per doctor in the hospitals surveyed) results in achieving break-even several months earlier, specifically in the beginning of the fourth operational year (or in the beginning of the sixth year since construction began). Moreover, the analysis indicates that further relaxation of the bed-to-doctor ratio to 12 leads to an even earlier break-even, but still within the fourth operational year. However, with a more relaxed ratio of 14 or 16, break-even is attained in the third operational year (or in the fifth year since construction commenced). Conversely, when bed-to-doctor ratio is decreased, the break-even is pushed farther into the future.

We additionally simulated a scenario wherein the government provides free land for hospital construction. In the scenario, break-even occurs by the conclusion of the second operational year. This highlights that the government subsidy has the strongest effect on making private provisioning of healthcare financially viable.

Discussion

The findings of this study provide insights into the financial viability of private hospitals operating under the AB PM-JAY model, an area often overshadowed by concerns about the adequacy of provider payment rates. It is well-documented that, at the inception of the scheme, a significant proportion of health benefit packages were priced well below the actual cost of care, with 42% being reimbursed at rates that covered only half the cost [11, 18]. While subsequent revisions have addressed these gaps to some extent, with the first revision alone halving the number of significantly underpriced packages, the decentralized nature of healthcare governance in India has limited the uniform application of these revisions across states [43]. Consequently, the perceived inadequacy of provider payments persists, leading to dissatisfaction among private hospitals. These systemic challenges underscore the need for continued efforts to ensure the financial sustainability of healthcare institutions serving AB PM-JAY beneficiaries, a concern that this study sought to address.

While our analysis demonstrates that private district hospitals financed solely through AB PM-JAY can achieve financial viability, we acknowledge the concerns around potential disincentives and tiered treatment protocols if hospitals cater to both insured and private-paying patients. To address this, our study focused specifically on hospitals financed entirely by the PM-JAY model, thereby eliminating the possibility of preferential treatment based on payment type. Furthermore, we recognize that the modeled hospital’s financial performance is contingent upon achieving operational efficiencies and addressing initial capital expenditures. The projected annual revenue exceeding expenditure in the first 10 years and the potential for higher profitability in subsequent years highlight the importance of strategic investments in private healthcare infrastructure. These findings emphasize the need for robust policy measures, such as timely revisions in reimbursement rates and incentivization schemes such as land subsidies to ensure that private hospitals remain active contributors to achieving universal health coverage in India.

By utilizing the data on the actual costs incurred in delivering healthcare services, our research has highlighted the financial viability of hospitals operating within the framework of the AB PM-JAY model. Our findings reveal that despite criticisms, hospitals can indeed operate sustainably under the AB PM-JAY reimbursement rates. As such, our study suggests that the private healthcare sector in India should consider the AB PM-JAY scheme as a financially viable payer. This recommendation is grounded in our robust analysis, which underscores the feasibility of hospitals effectively managing their finances while participating in the AB PM-JAY scheme. By embracing AB PM-JAY as a financially sustainable option, the private healthcare sector can contribute significantly to the broader goals of enhancing healthcare accessibility and affordability for the masses in India.

It is also worthwhile to note that the demand for health services is rising in tier-2 and tier-3 locations at a greater pace across the country [44, 45]. This is because the per capita income in these locations has increased rapidly over the past few years [46]. An added factor is that these locations also cater to the health needs of the population in nearby villages and towns, as well as serve as referral centers for surrounding regions [47]. According to Invest India’s Investment Grid, there exist investment opportunities worth ₹2.3 lac crores (US $32 billion) in the country’s hospital/medical infrastructure sector currently [2]. Therefore, the establishment of private hospitals at the district level has emerged as a strategic investment opportunity. However, the decision to establish private hospitals in these locations necessitates careful consideration of their financial viability to ensure sustainable healthcare delivery. The findings of this research furnish the pertinent information necessary for such deliberation.

By exploring variables such as bed occupancy rates and bed-to-doctor ratios, we identify opportunities for enhancing efficiency and accelerating breakeven attainment. These insights are particularly relevant in addressing India’s healthcare challenges, including the shortage of hospital beds and the need for optimized resource allocation. Furthermore, our research highlights the importance of supportive government policies in fostering private sector participation in healthcare delivery. Our analysis underscores the transformative potential of government subsidies in catalyzing the financial viability of private healthcare provision. We demonstrated that the provision of land subsidy for hospital construction by the government resulted in a significantly accelerated breakeven point, occurring by the conclusion of the second operational year. These insights have the potential to inform the development of a novel model of healthcare delivery, wherein the government subsidizes the establishment of private hospitals by providing them with free land and mandating such hospitals to provide care to patients at rates aligned with the AB PM-JAY. Given the profound financial impact of government subsidies, it is imperative to ensure stringent enforcement of the provision of free care by hospitals. By leveraging government subsidies and aligning reimbursement rates with AB PM-JAY, this model not only ensures financial sustainability for private hospitals but also enhances healthcare accessibility and affordability for patients. Such innovative approaches hold immense potential in advancing the goals of universal healthcare coverage and fostering collaborative partnerships between the public and private sectors.

The recent directive from the Supreme Court of India urging the government to standardize charges levied by private hospitals in alignment with the rates set under publicly funded health insurance schemes underscores the importance of ensuring equitable and transparent healthcare pricing [22]. In this context, the estimates derived from our study hold significant relevance in guiding policy decisions. This is because our findings suggest that despite providing treatment on the rates of publicly funded health insurance schemes, investing in the private hospital industry remains a reasonably sustainable financial opportunity. Thus, our study serves as a timely resource to inform ongoing discussions surrounding healthcare pricing reforms and to promote a more equitable healthcare system for all.

Amidst the exploration of financial viability in private healthcare settings, it is worthwhile to underscore the importance of upholding standards and ensuring the delivery of quality care [48]. Striking a delicate balance between financial sustainability and quality of care is essential for safeguarding patient safety, fostering trust in healthcare services, and ultimately, achieving sustainable healthcare outcomes [49]. Therefore, the investment decisions and policy initiatives should emphasize the integration of robust quality assurance mechanisms alongside strategies aimed at enhancing financial viability within the private healthcare sector.

Although the findings of this study demonstrate the financial viability of private hospitals under the AB PM-JAY scheme, they also underscore the inherent challenges in reconciling the profit-driven objectives of private providers with the regulated pricing structure of a publicly financed health insurance program. While our analysis demonstrates that private hospitals can achieve breakeven within 4 years and sustain profitability thereafter, we recognize that the profit margins in the initial years may not meet the expectations of all private sector stakeholders. This dynamic is particularly relevant for hospitals that make significant upfront investments in infrastructure and operations while adhering to the scheme’s fixed reimbursement rates. However, it is worth emphasizing that once the initial capital costs are amortized, the projected revenues in subsequent years are likely to generate substantial profit margins, especially as operational efficiencies improve and patient volumes grow.

We also acknowledge that the PM-JAY scheme limits the pricing flexibility traditionally exercised by private hospitals, a practice that has historically allowed them to adjust tariffs on the basis of market demand. While this constraint may appear to reduce the scheme’s attractiveness, it simultaneously provides a stable and predictable revenue stream, which can mitigate the uncertainties associated with fluctuating patient demand in purely private markets. In addition, the scheme’s emphasis on high patient volumes, driven by a large insured population, can offset the lower per-patient margins by ensuring steady utilization rates. As highlighted in our sensitivity analysis, achieving and maintaining optimal bed occupancy is an important determinant of the financial sustainability of hospitals under the PM-JAY model, underscoring the need for demand-side interventions to maximize service utilization.

We recognize the broader implications of these findings for the private healthcare sector in India, particularly in the context of an unregulated market where providers often prioritize profit maximization. While the PM-JAY scheme may not align with the immediate financial objectives of all private hospitals, it offers a viable model for sustainable participation in the scheme. Moreover, it is imperative to recognize that the financial viability of private hospitals extends beyond mere profitability and delves into more comprehensive implications for healthcare accessibility, affordability, and quality. While profitability serves as a critical aspect, it is equally essential to assess how private hospitals contribute to these broader healthcare goals. To enhance the scheme’s appeal, policymakers should consider additional financial incentives, such as land subsidies and periodic revisions to reimbursement rates to address concerns about pricing adequacy. Furthermore, fostering dialogue between private sector stakeholders and government agencies is important to ensure that the scheme meets the dual objectives of financial sustainability for providers and equitable access to care for beneficiaries, thereby advancing the broader goals of universal health coverage in India.

While this study provides valuable insights into the potential dynamics influencing private hospital investment, certain limitations must be acknowledged. Beyond the cost and revenue inputs considered in our analysis, some other factors may impact the financial viability of hospitals. One such factor is the demographic and morbidity profile of the catchment population, as differences in age distribution, disease burden, and healthcare-seeking behavior can affect hospital service utilization and revenue generation [50]. Secondly, the presence or absence of competing healthcare facilities (both public and private) within a given district plays a role in shaping market dynamics. The current analysis does not account for these competitive market influences. Thirdly, our analysis does not consider the potential impact of future technological advancements, which can alter healthcare delivery models over time. For instance, the newer digital health technologies, telemedicine, and automation may reduce operational costs and expand access to care in future, potentially influencing the financial outlook for hospitals. Similarly, unforeseen health crises, such as the coronavirus disease-2019 (COVID-19) pandemic, have demonstrated the profound effects on hospital revenues and costs, which were beyond the scope of the current analysis. Lastly, we have not considered the impact of quality-of-care in our financial assessment. The reputation and perceived quality of a hospital influence overall service demand [51]. Facilities delivering good quality care often experience increased patient inflow and greater revenue stability and vice versa.

Looking ahead, our research sets the stage for future investigations into the dynamics of private hospital investment, exploring these additional factors influencing hospital financial performance. Longitudinal studies exploring the impact of these factors on private hospital investments represent a promising avenue for future research.

It is worthwhile to mention that the financial viability metrics are highly context-specific, as both the cost of delivering healthcare services and the provider payment rates used to estimate hospital revenues vary significantly across countries owing to differences in healthcare financing models, reimbursement mechanisms, and local economic conditions. Given these variations, the financial estimates derived from our study may not be directly extrapolated to other countries. However, the methodological framework employed in our analysis can serve as a valuable reference for similar evaluations in other low- and middle-income country settings where private sector involvement in healthcare is expanding.

Conclusions

This study contributes to the understanding of private hospital investment in India and its implications for financial sustainability. By demonstrating the financial viability of establishing private hospitals at district level, our findings inform strategic purchasing-related decisions for investors, policymakers, and other healthcare stakeholders. Our findings also highlight the substantial influence of government subsidies on the financial viability of private healthcare provision. This recognition underscores the importance of fostering synergistic partnerships between the government and private investors to foster a conducive environment for healthcare infrastructure development and service delivery.

Declarations

Ethical Considerations

The study was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki. The ethical approval to conduct the study was obtained from the Institutional Ethics Committee of Postgraduate Institute of Medical Education and Research, Chandigarh, India, vide reference no. PGI/IEC/2018/00125A.

Authorship Contributions

Concept and design—Shankar Prinja; acquisition of data—Shankar Prinja; analysis and interpretation of data—Gaurav Jyani, Praveen Gedam, Sameer Sharma, Jyoti Dixit, and Shankar Prinja; drafting of the manuscript—Gaurav Jyani and Shankar Prinja; critical revision of the paper for important intellectual content—Gaurav Jyani, Praveen Gedam, Sameer Sharma, Jyoti Dixit, and Shankar Prinja; obtaining funding—Shankar Prinja; administrative, technical, or logistic support—Gaurav Jyani, Praveen Gedam, Sameer Sharma, Jyoti Dixit, and Shankar Prinja; supervision—Shankar Prinja; all the authors have reviewed and approved the final version of the manuscript.

Conflict of Interests

The authors have no relevant financial or nonfinancial interests to disclose.

Consent to Participate

Not applicable.

Consent for Publication (from Patients/Participants)

Not applicable.

Availability of Data and Material

All the original data and materials used for the analysis presented in the study will be made available by the corresponding author upon request.

Code Availability

Not applicable.