Experiences and challenges in accessing hospitalization in a government-funded health insurance scheme: Evidence from early implementation of Pradhan Mantri Jan Aarogya Yojana (PM-JAY) in India.

INTRODUCTION: Government-sponsored health insurance schemes can play an important role in improving the reach of healthcare services. Launched in 2018 in India, Pradhan Mantri Jan Aarogya Yojana (PM-JAY) is one of the world's largest government-sponsored health insurance schemes. The objective of this study is to understand beneficiaries' experience of availing healthcare services at the empaneled hospitals in PM-JAY. This study examines the responsiveness of PM-JAY by measuring the prompt attention in service delivery, and access to information by the beneficiaries; financial burden experienced by the beneficiaries; and beneficiary's satisfaction with the experience of hospitalization under PMJAY and its determinants.
METHODS: The study was conducted during March-August 2019. Data were obtained through a survey conducted with 200 PM-JAY beneficiaries (or their caregivers) in the Indian states of Gujarat and Madhya Pradesh. The study population comprised of patients who received healthcare services at 14 study hospitals in April 2019. Prompt attention was measured in the form of a) effectiveness of helpdesk, and b) time taken at different stages of hospitalization and discharge events. Access to information by the beneficiaries was measured using the frequency and purpose of text messages and phone calls from the scheme authorities to the beneficiaries. The financial burden was measured in terms of the incidence and magnitude of out-of-pocket payments made by the beneficiaries separate from the cashless payment provided to hospitals by PMJAY. Beneficiaries' satisfaction was measured on a five-point Likert scale.
RESULTS: Socio-economically weaker sections of the society are availing healthcare services under PM-JAY. In Gujarat, the majority of the beneficiaries were made aware of the scheme by the government official channels. In Madhya Pradesh, the majority of the beneficiaries got to know about the scheme from informal sources. For most of the elements of prompt attention, access to information, and beneficiaries' satisfaction, hospitals in Gujarat performed significantly better than the hospitals in Madhya Pradesh. Similarly, for most of the elements of prompt attention, access to information, and beneficiaries' satisfaction, public hospitals performed significantly better than private hospitals. Incidence and magnitude of out-of-pocket payments were significantly higher in Madhya Pradesh as compared to Gujarat, and in private hospitals as compared to the public hospitals.
CONCLUSION: There is a need to focus on Information, Education, and Communication (IEC) activities for PM-JAY, especially in Madhya Pradesh. Capacity-building efforts need to be prioritized for private hospitals as compared to public hospitals, and for Madhya Pradesh as compared to Gujarat. There is a need to focus on enhancing the responsiveness of the scheme, and timely exchange of information with beneficiaries. There is also an urgent need for measures aimed at reducing the out-of-pocket payments made by the beneficiaries.

Introduction

An important goal of the health system of any country is to improve the health outcomes of its citizens. However, even a health system that successfully attains desired health outcomes can be deemed unsuccessful if it fails to satisfy its users. Users can disapprove of a health system if treatment costs are high or if the system does not provide a timely response to their felt needs. Hence, while working to preserve, promote, and improve the population’s health, health systems must also strive to provide financial protection and timely response to the expectations of the population [1].

Health system responsiveness is defined as "the ability of the health system to meet the population’s legitimate expectations regarding their interaction with the health system, apart from expectations for improvements in health or wealth" [2]. Responsiveness includes both physical and affective support during treatment. It incorporates elements of respect for and orientation to the rights of clients including confidentiality, prompt attention, choice of providers, and the quality of amenities. The flow and clarity of information between the health system and its patients also form an important element of responsiveness [3]. Information asymmetries between patients and providers are typical in healthcare—however, a responsive health system not only aims to keep patients informed about the course of treatment or other actions recommended by the healthcare providers but also has a mechanism to solicit patients’ feedback [4].

Government-sponsored health insurance schemes (GSHIS) can play an important role in developing countries. For developing countries, GSHISs have been advocated as a means for governments to fulfill their responsibilities to citizens, including their commitments to move towards the Universal Health Coverage (UHC) as envisioned under target 3.8 of the United Nation’s Sustainable Development Goals (SDGs) [5]. The element of responsiveness has been said to be especially essential for GSHIS that seeks to enhance the provision of services to the citizens through strategic purchasing of healthcare services [2, 6].

India is one of the countries that has been rapidly expanding health insurance coverage. In September 2018, the Government of India launched Pradhan Mantri Jan Aarogya Yojana (PM-JAY) to provide insurance coverage to approximately 500 million poor and vulnerable beneficiaries forming the bottom 40% of the Indian population [7]. The scheme provides coverage of up to INR 500,000 (USD 6800) per family per year for all secondary and most of the tertiary care procedures of surgery, medical, and daycare treatments at public and empaneled private hospitals [8]. The scheme is rolled out in active partnership with the state governments wherein state governments are implementing the scheme through a trust or an insurance company. This trust or an insurance company empanels the hospitals, approves the pre-authorization request, and makes payment to the hospitals.

To facilitate the implementation of PM-JAY, National Health Authority (central coordinating agency for PM-JAY) has provided guidelines for each step of the hospitalization process, namely, patient’s registration, selection of treatment package, preauthorization and hospitalization, discharge, claim reimbursement to the hospital, and exchange of information by the scheme authorities with the beneficiaries [9]. To support beneficiaries’ engagement with PM-JAY, the guidelines state that all empaneled hospitals must place a dedicated PM-JAY helpdesk at a prominent location in the hospital. The primary purpose of this helpdesk is to act as a ‘one-stop’ point for the information and help needed by the PM-JAY beneficiaries. This helpdesk is to be managed by an Ayushman Mitra (AM), a hospital representative who manages operations and liaises between patients, doctors, hospital administration, and the scheme managers. The guidelines state that the AM should be able to use a diagnosis sheet provided by the doctor to select and block the treatment package(s) in the PM-JAY IT (Information Technology) system. Once AM selects and blocks the package in the PM-JAY IT system, the request is submitted to the insurer for pre-authorization. According to guidelines, the insurer must either approve or reject this pre-authorization request within six hours of receiving the request. Once the pre-authorization request is approved by the insurer, patients are hospitalized and are provided the treatment. Being a cashless scheme, patients are not supposed to make any payments during any stage of hospitalization. PM-JAY guidelines also require scheme authorities to contact patients through text messages (Short Message Service) and telephonic calls to keep them informed and take their feedback on the hospitalization process [10]. As per the guidelines, some procedures, deemed prone to fraud and abuse, are reserved for public hospitals only. Beneficiaries must bear the expenses for these procedures if treatment is availed in a private hospital [11].

PM-JAY is one of the world’s largest government-sponsored health insurance schemes and is aimed at providing health insurance coverage to a large number of economically poor Indian citizens. This population, in India, has previously been considered a passive recipient of healthcare services, often has to bear catastrophic healthcare expenditure, and neither public nor private sector has been responsive to them. Within PM-JAY, though guidelines for the processes to be followed in the scheme are in place, however, there is a lack of information on beneficiaries’ experiences of navigating hospitalization processes, accessing information, and the financial burden incurred by them. In this context, this research aims to understand the experiences of beneficiaries who availed healthcare services under PM-JAY at the empaneled public and private hospitals. Specifically, this study aims to understand beneficiaries’ experiences of identification and registration in PM-JAY; navigating hospitalization processes related to medical package selection, preauthorization, discharge, and services received; information exchange during beneficiary verification, before hospitalization, during discharge, and after hospitalization; any additional payments made by the beneficiaries to the hospital separate from the cashless payments by PM-JAY, and beneficiaries’ satisfaction with the experience of hospitalization under PMJAY. The study is looking at the element of responsiveness in PM-JAY by measuring the prompt attention in service delivery by the providers/scheme authorities, and access to information by the beneficiaries. This study is looking at the financial burden in terms of incidence and magnitude of out-of-pocket payments made by the beneficiaries to the hospital. Along with it, this study also attempts to understand beneficiary’s satisfaction with the experience of hospitalization under PMJAY and its determinants.

Much of the published discourse around health system responsiveness on the experiences and expectations of patients is limited to developed country settings. Only a few studies have explored it in the context of developing countries [12-14]. PM-JAY is a recent initiative and there is limited literature on it. In the existing literature, a need to study beneficiaries’ perspectives on PM-JAY processes has also been stated [15]. By attempting to understand responsiveness, financial burden, and patient satisfaction and its determinants, this study seeks to enrich the existing literature and provides useful insights to the policymakers and program managers to strengthen the scheme.

Methodology

This study was conducted between March and August 2019. In consultation with the National Health Authority (NHA), Gujarat and Madhya Pradesh states in India were selected as the study locations. Gujarat is an economically developed state with a higher annual per capita Gross State Domestic Product, as compared to Madhya Pradesh. In the recent past, Gujarat had a high level of per capita health expenditure as compared to Madhya Pradesh, and the total and out-pocket expenditure per episode of hospitalization was higher in Madhya Pradesh. (S1 Table). Prior to PM-JAY, Gujarat has an experience of implementing state government funded GSHIS (Mukhyamantri Amrutam scheme) whereas Madhya Pradesh has no experience of implementing entitlement-based GSHIS. Study sites included seven hospitals in each state. These hospitals were selected by the respective State Health Agency (SHA) after ensuring representation of a) public and private hospitals, and b) multi-specialty and super-specialty hospitals (SHA is a state-level nodal agency for the implementation of PM-JAY). As shown in Table 1, the fourteen hospitals included in the study comprised nine multi-specialty and five super-specialty hospitals. Eight of the hospitals were private and the rest were public hospitals.

Table 1

Study hospitals and surveyed beneficiaries, by state.

Hospital type	Ownership type	Gujarat		Madhya Pradesh
		Number of hospitals	Sample of beneficiaries	Number of hospitals	Sample of beneficiaries
Multi-specialty	Private	2	35	2	29
	Public	2	21	3	57
Super-specialty	Private	2	21	2	14
	Public	1	23	-	-
Total		7	100	7	100

The study population was drawn from patients who were hospitalized in April 2019. Sample selection was done using the list of all claims from study hospitals, as provided by the SHAs in the two states. Each claims list was converted into a patient list by retaining one claim per beneficiary. Next, to ensure representation of most and least popular services at each hospital, the most and least popular specialties were selected. For each hospital, specialty clusters were arranged from those having the highest number of patients to those having the lowest. Those clusters that together contained the top 10% of patients were identified as the ‘most popular cluster’ for that hospital. Similarly, those clusters that together contained the bottom 10% of patients were identified as the ‘least popular cluster’ for that hospital. The resulting list of patients in the ‘top—bottom’ clusters was then used to generate a sample of 100 beneficiaries in each state through the probability proportional to size (PPS) method using the hospital as the sampling unit. Thus, a higher proportion of the sample was drawn from the hospital with the most claims and the smallest sample was derived from the hospital with the fewest claims. The use of a multi-stage sampling method with the use of PPS ensured that the selection of respondents was not biased either in favor or against any type of specialty and hospital [16]. The final distribution of patients included in the study across the different types of hospitals is shown in Table 1. The sampled patients were from six districts in Gujarat and five districts in Madhya Pradesh. Among the 100 patients in Gujarat, 39 were only enrolled in the Mukhyamantri Amrutam critical illness coverage scheme that existed at the time, not the full PM-JAY scheme (which has since subsumed Mukhyamantri Amrutam).

Data for this study were obtained through a household survey of the sampled beneficiaries. A structured questionnaire was developed to solicit details of the patient’s hospitalization experience keeping in consideration PM-JAY guidelines. The draft questionnaire was reviewed and approved by technical experts at the World Health Organization (WHO) and the NHA. Before data collection commenced, the revised instrument was piloted for accuracy and validation through a discussion with a panel of in-house experts and a field test. The survey questionnaire is available as supplementary material to this paper (S1 File). The data collection was done by a team of six investigators in May and June 2019. Before going to the field, these investigators underwent a one-day training specifically designed for the data collection targeted under this research. The questions were asked in the local language i.e. Gujarati for Gujarat and Hindi for Madhya Pradesh. Each survey administration lasted for 30–40 minutes.

The survey was administered to—either the patient or his/her primary caregiver—at their residences. They were contacted telephonically in advance to ascertain their availability for the survey. All participants were provided with a participant information sheet that described the ethical concerns and emphasized the rights of the respondents. After providing a brief description of the study and its objectives, surveyors requested the respondent’s participation in the survey, and verbal non-witnessed informed consent was taken. Nine of the initially contacted respondents refused to participate in the survey. These respondents were replaced by another nine participants from the patient list.

The consented respondents were asked to indicate the reasons for and duration of their hospitalization. They were asked in detail about their experiences and any challenges experienced during beneficiary identification and authentication, the experience of hospitalization, and the scope of services received (including medicines). The prompt attention element of responsiveness was measured in the form of a) extent to which help was provided at the helpdesk, b) time taken at different stages of hospitalization and discharge process, and c) information exchange between patient and scheme authorities. To ascertain the extent to which help was provided at the helpdesk, respondents were asked closed-ended questions about whether they had received three types of help from the registration desk: 1) information about PM-JAY; 2) help with documents and computerized registration; and, 3) guidance about treatment within the hospital. Respondents were also asked to report how long the pre-authorization request, admission, and discharge processes took. Respondents were also asked to provide details of any message and telephone calls received from the scheme authorities about registration, preauthorization, hospitalization, and discharge. Respondents were asked to rate their experiences of registration, and hospitalization on a five-point Likert scale that ranged from ‘highly dissatisfied’ to ‘highly satisfied’. The financial burden was measured in terms of OOP payment made by the patients to the hospitals. To ascertain the incidence and magnitude of OOP payments, respondents were asked to provide information on any additional payments made to the hospital separate from the cashless payment provided to hospitals by PMJAY. Respondents were also asked to indicate the reason for which the payment was made.

The questionnaire for the household survey was configured using Open Data Kit (ODK) software, a free and open-source tool developed by the University of Washington. The data was collected using hand-held electronic devices. On-site monitoring and cross-verification of data collection were carried out to ascertain the reliability of the data being collected. This was done by the research supervisors through observation and spot-checking.

The collected data was cleaned using MS-Excel software and descriptive statistics were generated. Data was statistically analyzed using SPSS version 20. Non-parametric test (Mann–Whitney U test) was used to compare beneficiaries’ responses across states (Gujarat and Madhya Pradesh), hospitals across states (public and private hospitals), and hospitals within a state (public and private hospital in Gujarat, public and private hospital in Madhya Pradesh). The non-parametric test (Mann–Whitney U test) was used due to the non-normal distribution of data (Kolmogorov-Smirnov and Shapiro-Wilks test, p < 0.05). A significance level of P < 0.05 was used for the Mann–Whitney U test. For each set of comparisons mean, standard deviation, and median of the studied variable was noted. Along with it, Mann–Whitney U test statistics and p-value were also noted. Before conducting the comparisons, extreme outliers were detected using a box-plot and removed from the dataset. Extreme outliers were defined as data points that were more than 3 box-lengths away from the edge of their box in the box-plot. These extreme outliers were less than five percent of the dataset under consideration.

A cumulative odds ordinal logistic regression with proportional odds was conducted to determine the effect of state, hospital type, OOP incidence, beneficiary’s caste, beneficiary’s location, beneficiary level of education, type of care/services received, help received at PM-JAY registration desk, and the number of days for which the beneficiary was admitted in a hospital (independent variables), on the beneficiary’s satisfaction with the experience of hospitalization under PMJAY (dependent variable). The dependent variable beneficiary’s satisfaction with the experience of hospitalization under PMJAY was an ordinal variable measured on a five-point scale that ranged from ‘highly dissatisfied’ to ‘highly satisfied’. The independent variables of

State refers to the state in which the respondent lives (Gujarat, MP)

Hospital type refers to the type of hospital in which respondent underwent hospitalization (Public, Private)

OOP made indicates whether respondent made OOP (Yes, No)

Beneficiary caste indicate the social caste to which respondent belongs (Marginalized and backward castes, General caste)

Beneficiary location refers to the geographical area where the respondent lives (urban, non-urban)

Beneficiary level of education indicate beneficiary’s level of schooling (illiterate, primary education, secondary education, and graduate and above)

Type of care/services received indicates the service that was availed by the beneficiary (hospitalization with surgery, hospitalization without surgery, Daycare procedure)

Help received at the PM-JAY registration desk indicates the extent of help received by the beneficiary at the registration desk (measured in terms of the help received, namely, information about PM-JAY, help with documents and computerized registration, and guidance about treatment within the hospital)

The number of days for which the beneficiary was admitted to a hospital indicates the beneficiary’s length of stay in the hospital

The study received ethical clearance from the institutional ethics committee of the Indian Institute of Public Health Gandhinagar (IIPHG) (TRC-IEC No: 14/2018-19).

Results

The results of the study are presented in five sections. The first section provides basic sociodemographic information of the survey respondents, as well as an overview of the healthcare services they received during their hospital visit. The remaining sections are organized based on the beneficiaries’ interactions with hospitals and scheme authorities during hospitalization process: identification and registration; treatment package selection before hospitalization; discharge and payments; and, information exchange. Results for prompt attention in service delivery, access to information by the beneficiaries, incidence and magnitude of OOP payment, and beneficiary’s satisfaction with the experience of hospitalization under PMJAY are discussed in the flow of beneficiaries’ interaction with the system.

Respondents’ characteristics and services received

Table 2 presents a summary of the socio-demographic profile of the survey respondents. The respondent’s profile highlight that there is a high proportion of respondents having a low level of education, belonging to socially marginalized and backward castes, and few have a salaried job. This indicates that the socio-economically poorer section of the society is availing healthcare services under PM-JAY.

Table 2

Profile of the surveyed beneficiaries.

Particulars	Details	Gujarat (n = 100)	Madhya Pradesh (n = 100)	Both states (%)
Type of hospital	Private	56	43	49.5
	Public	44	57	50.5
Gender	Female	38	53	45.5
	Male	62	47	54.5
Mean age (years)		49.1 (Range 6–79)	42.2 (Range 2–75)
Religion	Hindu	89	89	89
	Muslim	11	11	11
Caste	Marginalized and backward castes (Scheduled Tribe, Scheduled Caste, Other Backward Caste)	74	74	74
	Other (General caste)	26	25	25.5
	Refuse to answer	0	1	0.5
Highest level of education attained in the household	Illiterate or no formal education	39	15	27
	Primary education (1–8 standard)	35	50	42.5
	Secondary education (9–12 standard and diploma etc.)	23	26	24.5
	Graduate and above	3	9	6
Occupation	Farm Labor	18	4	11
	Other labor work in a rural area	8	7	7.5
	Labor work in an urban area	14	22	18
	Self-employment (agricultural)	20	7	13.5
	Self-employment (non-agricultural)	19	38	28.5
	Salaried job	19	22	20.5
	Other	2	0	1
Respondents who received benefits under state-sponsored health coverage before PMJAY		75	3	39

In terms of the services received by the beneficiaries, 39% had hospitalization with surgery, 37% reported hospitalization without surgery, and the remaining respondents received daycare treatment as an outpatient without having to remain overnight at the hospital. These proportions varied across states and types of hospitals. Among the patients who utilized services in public hospitals in Gujarat, 61% received day-care procedures. In Madhya Pradesh, 61% of respondents from public hospitals reported receiving hospitalization without surgery. In both states, around half of the respondents who received treatment in private hospitals had surgical procedures.

Beneficiary identification and registration

The patient’s first touchpoint with the PM-JAY scheme is the beneficiary identification and registration process. This involves beneficiaries’ awareness of the insurance scheme and experiences of using the e-card issued to them (PM-JAY e-card indicates beneficiaries’ registration in the scheme). The number of respondents from Gujarat in this section is 61, as at the time 39 were enrolled in the Mukhyamantri Amrutam scheme, which had not yet been subsumed under PMJAY; these patients did not have a comparable registration experience.

A large proportion (74%) of PM-JAY beneficiaries in Gujarat indicated that they were made aware of the scheme through a letter from the government. Another 11% indicated that they got to know about the scheme through village-level health workers and 7% got to know about the scheme only at the time of the hospitalization. The remaining respondents got to know about the scheme from friends and relatives or through newspapers. None of the respondents from Madhya Pradesh reported receiving a scheme-related letter from the government. Instead, nearly one-third of the beneficiaries (30%) learned about the scheme when they arrived at the hospital, while one-quarter of the respondents got to know about the scheme from their friends and relatives. The remaining sources included newspaper, Internet, etc.

Most (82%) beneficiaries from Gujarat mentioned that the letter from the government indicated their eligibility for entitlements in the scheme. In Madhya Pradesh, around half of the respondents indicated that they checked their eligibility at common service centers, government-authorized one-stop-facility for availing digital services on various public schemes and entitlements. (Fig 1). This proportion was 63% among those using private hospitals in Madhya Pradesh; around one-third of beneficiaries using public hospitals checked their eligibility at the time of admission in the hospital.

Fig 1

Proportion of beneficiaries by the source of eligibility checking: A comparison across states (In %).

As mentioned, survey respondents were asked about the extent of help they received at the PM-JAY helpdesks. Half of the beneficiaries (52%) reported receiving information about PM-JAY, help with documents and computerized registration, and guidance about treatment within the hospital. Respondents from Gujarat reported receiving relatively higher level of help (Mean = 2.1, Std. Deviation = 0.9, Median = 2) as compared to the respondents from MP (Mean = 2.1, Std. Deviation = 0.9, Median = 2)–no statistically significant difference U = 4793, z = -0.5, p = 0.59. Those who availed services from public hospital reported receiving higher level of help (Mean = 2.3, Std. Deviation = 0.8, Median = 3) as compared to those who availed services from private hospital (Mean = 1.9, Std. Deviation = 0.9, Median = 2)–statistically significant difference U = 6040.5, z = 2.7, p = 0.006. Within Gujarat, patients from public hospitals reported receiving higher level of help (Mean = 2.5, Std. Deviation = 0.8, Median = 3) as compared to the patients from private hospitals (Mean = 1.8, Std. Deviation = 0.9, Median = 1.5)–statistically significant difference U = 1692.5, z = 3.5, p = 0.001. In MP, there was little difference between private (Mean = 2, Std. Deviation = 0.8, Median = 2) and public hospitals (Mean = 2.1, Std. Deviation = 0.9, Median = 2)–no statistically significant difference, U = 1279, z = 0.4, p = 0.7. The proportion of respondents who received all three kinds of help was highest in the public hospitals of Gujarat (82%), and lowest in the private hospitals of Madhya Pradesh (35%). Only 7% of respondents indicated that they did not receive any help at the helpdesk—these were respondents who had been at a public hospital in Madhya Pradesh. Fewer than one in ten beneficiaries reported facing problems with registration in the form of long waiting time or payment before registration.

As shown in Fig 2, 81% of respondents felt either ‘satisfied’ or ‘highly satisfied’ with the registration process. This was higher in Gujarat (86%) than in Madhya Pradesh (77%), and among beneficiaries from public sector hospitals (83%) than their counterparts from the private sector (77%).

Fig 2

Proportion of beneficiaries by their level of satisfaction with registration: A comparison across states (In %).

Treatment package selection and blocking

PMJAY guidelines state that once the patient’ eligibility is ascertained, the AM should be able to block the benefit package(s) using PMJAY IT system. The mean waiting time reported by the patients for ‘admission and pre-authorization request’–i.e. the time that the AM took in preparing and submitting the request—was 32 minutes in Gujarat (Std Deviation = 25.7, Median = 30) and 75 minutes in Madhya Pradesh (Std Deviation = 104.1, Median = 30)–Statistically significant difference U = 4373.5, z = 4.1, p < 0.005. In Gujarat, the mean reported time for ‘admission and pre-authorization request’ for public hospitals was 29 minutes (Std Deviation = 25.5, Median = 30) and for private hospitals it was 34 minutes (Std Deviation = 25.9, Median = 30)–no statistically significant difference U = 639.5, z = -1.1, p = 0.3. In Madhya Pradesh, the mean reported time was 48 minutes for the patients at public hospitals (Std. Deviation = 51, Median = 30) and 120 minutes for those who were hospitalized in private hospitals (Std. Deviation = 145.6, Median = 50)—statistically significant difference U = 517.5, z = -2.9, p = 0.004. The self-reported mean time for ‘admission and pre-authorization request’ across the two states for public hospitals was 40 minutes (Std Deviation = 43, Median = 30) and for private hospitals it was 73 minutes (Std. Deviation = 107.5, Median = 30)—statistically significant difference U = 2599, z = -2, p = 0.048.

The average time reported by the beneficiaries for the ‘pre-authorization approval’ to be received from the scheme authorities was around 150 minutes in Gujarat (Std. Deviation = 625, Median = 30) and 480 minutes in MP (Std. Deviation = 899, Median = 55)–statistically significant difference U = 6123, z = 5, p < 0.005. Across the two states, for public hospitals it was 140 minutes (Std Deviation = 545, Median = 40) and for private hospitals it was 376 minutes (Std. Deviation = 939.4, Median = 60)—no statistically significant difference U = 3769.5, z = -1.5, p = 0.1. In Gujarat, those beneficiaries who availed the service from public hospital reported a mean time of 184 minutes (Std. Deviation = 680, Median = 30), and those who availed the service from private hospital reported a mean time of 136 minutes (Std. Deviation = 583.3, Median = 30)—no statistically significant difference U = 1313.5, z = 0.7, p = 0.5. In MP, beneficiaries reported a mean time of 104 minutes (Std Deviation = 397.3, Median = 40) for public hospitals and 743 minutes (Std. Deviation = 1230.6, Median = 60) for private hospitals—statistically significant difference U = 382.5, z = -4.664, p < 0.005.

Discharge and payments

Mean time reported by the beneficiaries to complete the discharge process by the hospitals was 63 minutes (Std. Deviation = 53, Median = 45) in Gujarat and 119 minutes (Std. Deviation = 85, Median = 120) in Madhya Pradesh—statistically significant difference U = 5330.5, z = 5.1, p < 0.005. For Gujarat, mean of the time taken to complete the discharge process was 75 minutes (Std. Deviation = 56.7, Median = 60) for public hospitals, and 52 minutes (Std. Deviation = 47, Median = 30) for private hospitals–statistically significant difference U = 905, z = 2.2, p = 0.03. For Madhya Pradesh, average time taken by public hospitals to complete the discharge process was 106 minutes (Std. Deviation = 76.5, Median = 90) and for private hospitals it was 137 minutes (Std. Deviation = 93.1, Median = 120)–no statistically significant difference U = 923, z = -1.8, p = 0.07. The mean reported time for completion of discharge process across the two states was 94 minutes (Std. Deviation = 71.1, Median = 60) in public hospitals and 96 minutes (Std. Deviation = 79, Median = 60) for private hospitals–no statistically significant difference U = 3950, z = 0.7, p = 0.5.

The average length of stay for hospitalizations, excluding day care procedures, was 4 days (Std. Deviation = 3.2, Median = 3.5 day) in Gujarat and 6 days (Std. Deviation = 2.6, Median = 5 day) in Madhya Pradesh—statistically significant difference, U = 2917.5, z = 2.7, p < 0.005. Average length of stay was 5 days for both surgical treatment (Std. Deviation = 3, Median = 5 days) and non-surgical treatment (Std. Deviation = 2.6, Median = 5 days)—no statistically significant difference, U = 2648, z = 0.7, p = 0.5. The average length of hospitalization was 5 days (Std Deviation = 4.2, Median = 5) in public hospitals and 3 days (Std Deviation = 3, Median = 3) in private hospitals—statistically significant difference, U = 5760.5, z = 2.6, p = 0.009). There was little difference between private (Mean = 5 days, Std. Deviation = 2.5, Median = 5) and public hospitals (Mean = 6 days, Std. Deviation = 2.4, Median = 6) in Madhya Pradesh—no statistically significant difference, U = 1141, z = 1.9, p = 0.05. Private hospitals in Gujarat, however, had noticeably shorter stays (Mean = 3 days, Std Deviation = 2.2, Median = 3) than public hospitals (Mean = 8 days, Std. Deviation = 3.7, Median = 7.5)—statistically significant difference, U = 445.5, z = 4, p < 0.005.

The possibility of having to make additional payments outside of insurance coverage at the time of discharge remained an important concern for the patients. As shown in Table 3, 26% of respondents reported that they made OOP payments either before, during, or after hospitalization. A lower proportion of respondents who reported making OOP payments were from Gujarat (10%) as compared to Madhya Pradesh (42%). A lower proportion (18%) of patients from public hospitals made OOP payments as compared to those from private hospitals (34%). The highest incidence of OOP was among patients of private hospitals in Madhya Pradesh.

Table 3

Incidence of OOP payments during hospitalization (%).

Hospital type	Gujarat	Madhya Pradesh	Total
Private	11 (n = 55)	63 (n = 43)	34 (n = 98)
Public	9 (n = 44)	25 (n = 55)	18 (n = 99)
Mean	10 (n = 99)	42 (n = 98)	26 (n = 197)

n = number of patients in a quadrant.

Most respondents who reported making OOP payments indicated that the payments were for either medicines or diagnostic tests. Patients reported making these payments directly to the pharmacies or laboratories outside the hospitals, as they were told that certain inputs were either not available or not covered under the PM-JAY. In addition, around one-fifth of respondents who made OOP payments, mostly from private hospitals in Madhya Pradesh, indicated that they were asked to make a lump-sum payment directly at the hospital billing counter. These patients reported that they were informed at the helpdesk that the actual costs of their treatments or procedures were higher than the amount the hospital would receive from claim reimbursements from PM-JAY; thus, patients needed to pay the balance.

In terms of the amounts of the OOP payments, there were notable differences between the two states and types of hospitals. The mean OOP payment made by patients in Gujarat was INR 1511 (Std. Deviation = 1620.2, Median = 1000) whereas for Madhya Pradesh it was INR 27,648 (Std. Deviation = 30692.4, Median = 15000)—statistically significant difference U = 359, z = 3.3, p = 0.001. Mean OOP payment made by patients in public hospitals across the two states was INR 1510 (Std. Deviation = 1308.9, Median = 1000) and for private hospitals it was INR 33700 (Std. Deviation = 31342.1, Median = 26000)—statistically significant difference U = 77, z = -4.4, p < 0.005. In Madhya Pradesh, average OOP payment made by patients in public hospitals was INR 1499 (Std. Deviation = 1358.4, Median = 1000) and in private hospitals the mean OOP payment was INR 40996 (Std. Deviation = 30834.8, Median = 34500)—statistically significant difference U = 10, z = -4.9, p < 0.005. In Gujarat, the average amount of OOP payment in public hospitals was INR 1550 and for private hospitals it was INR 1485. Across the two states, the average OOP payment made by the beneficiaries belonging to the marginalized and backward castes was INR 33339 (Std. Deviation = 32157, Median = 25000) and by those from general caste was INR 17608 (Std. Deviation = 26530, Median = 2750)—statistically significant difference U = 448.5, z = 2.3, p = 0.022. No statistically significant difference was found in the OOP payment with respect to the education and occupation of the beneficiaries.

Patients in Gujarat, as well as public hospital patients in Madhya Pradesh who reported lower OOP payments, had to purchase medicine and other supplies from outside the hospital. Most of the respondents from private hospitals of MP who made high OOP payments were hospitalized for either cancer-related procedures or cardiovascular procedures that involved the replacement of a valve or pacemaker. The average OOP payment was around three times higher for those patients who were asked by the hospitals to make a part-payment on top of their insurance coverage (mean: INR 47,840; median: INR. 42,500), when compared with those who reported making OOP for medicines, tests, blood, or other individual items (mean: INR 17,172; median expenses: INR 3,250).

Overall, a majority of survey respondents were either ‘satisfied’ or ‘highly satisfied’ with their hospitalization experience. This was higher in Gujarat (82%), compared with Madhya Pradesh (71%), and among public hospitals (82%), compared with private hospitals (66%). For cumulative odds ordinal logistic regression with proportional odds, having beneficiary’s overall satisfaction with the experience of hospitalization under PMJAY as the dependent variable, full likelihood ratio test indicated that the assumption of proportional odds was met, χ2(36) = 46.4, p = 0.11. Likelihood-ratio test indicated that the final model statistically significantly predicted the dependent variable over and above the intercept-only model, χ2(12) = 43.9, p < .001. Table 4 shows that OOP, beneficiary location, and help received at the PM-JAY registration desk have a statistically significant effect on the beneficiary’s overall satisfaction with the experience of hospitalization under PMJAY.

Table 4

Tests of model effects.

Independent variable	Wald Chi-Square	Degree of freedom	Level of significance (p-value)
State (Gujrat, MP)	.172	1	.678
Hospital type (Public, Private)	.554	1	.457
OOP made (Yes, No)	14.568	1	.000 *
Beneficiary caste (Marginalized and backward castes, General caste)	.007	1	.935
Beneficiary location (Urban, Non-urban)	8.251	1	.004 *
Beneficiary education (illiterate, primary education, secondary education, graduate and above)	1.134	3	.769
Type of care/service received (Hospitalization with surgery, Hospitalization without surgery, Daycare procedure)	1.860	2	.395
Help received at PM-JAY registration desk	14.110	1	.000 *
No of days admitted in hospital	1.193	1	.275

Dependent Variable: Beneficiary’s overall experience of hospitalization under PMJAY.

Table 5 shows the Odds ratio for the independent variables of cumulative odds ordinal logistic regression with proportional odds. The odds of beneficiaries who have made OOP having a higher level of satisfaction is 0.24 (95% CI, 0.1–0.5) times that of beneficiaries who have not made OOP, a statistically significant effect, χ2 (1) = 14.6, p < .0005. The odds of beneficiaries living in an urban area having a higher level of satisfaction is 2.6 (95% CI, 1.4–5.1) times that of beneficiaries living in a non-urban area, a statistically significant effect, χ2 (1) = 8.3, p = .004. An increase in help received at the PM-JAY registration desk is associated with an increase in the odds of beneficiaries having a higher level of satisfaction, with an odds ratio of 2 (95% CI, 1.4–2.9), χ2 (1) = 14.1, p < 0.0005.

Table 5

Odds ratio.

Independent variable		Odds ratio	95% Wald Confidence Interval for Odds ratio
			Lower	Upper
State	Gujrat	1.171	.556	2.463
	MP	1	.	.
Hospital type	Private	1.282	.666	2.469
	Public	1	.	.
OOP made	Yes	.241	.116	.500
	No	1	.	.
Beneficiary caste	Marginalized and backward castes	1.028	.536	1.970
	General caste	1	.	.
Beneficiary location	Urban	2.623	1.358	5.066
	Non-urban	1	.	.
Beneficiary education	Illiterate or no formal education	1.335	.348	5.121
	Primary education	1.740	.506	5.984
	Secondary education	1.403	.389	5.053
	Graduate and above	1	.	.
Type of care/service received	Hospitalization with surgery	1.100	.440	2.751
	Hospitalization without surgery	1.655	.673	4.068
	Day-care procedure	1	.	.
Help received at PM-JAY registration desk		2.004	1.394	2.880
No of days admitted in hospital		1.037	.971	1.108

Dependent Variable: Beneficiary’s overall experience of hospitalization under PMJAY.

Information exchange before, during, and after hospitalization

The PM-JAY guidelines indicate that patients should receive information about various processes concerning their hospitalization through calls and SMSs by the scheme authorities. Fig 3 shows that more than half of the patients in Gujarat reported receiving SMS during the verification step; lower proportions of patients reported receiving SMSs for preauthorization, admission, and discharge. In Madhya Pradesh, a significantly lower proportion of patients reported receiving SMSs across processes.

Fig 3

Proportions of beneficiaries who received SMS/call about specific processes (in %).

The most commonly reported information exchange was a call after a patient’s discharge soliciting their feedback. Nearly half of the beneficiaries in Madhya Pradesh and 60% in Gujarat reported having received a post-discharge feedback call. This proportion was 64% among public hospital beneficiaries of Gujarat and 40% among Madhya Pradesh beneficiaries who received services from public hospitals.

Discussion

This study aimed to understand beneficiaries’ experience of availing healthcare services at the empaneled public and private hospitals in PM-JAY. The results of this study highlight the time delays as experienced by the beneficiaries at different stages of hospitalization and discharge process, the help provided to them at the helpdesk, information exchanged with them by the scheme authorities, financial expense incurred by them, and their satisfaction with hospitalization experience under PM-JAY.

The results of this study highlight that in Gujarat more than 80% of the surveyed beneficiaries were made aware of the scheme and their eligibility for entitlement by the government’s official channel (letter from the government, and by the village-level health workers). As compared to it, in Madhya Pradesh most of the beneficiaries got to know about the scheme from informal sources (friends, relatives, newspaper) and on arrival for treatment at a hospital. In the context of Rashtriya Swasthya Bima Yojana (RSBY) an earlier GSHIS in India, only one in four of the beneficiaries knew about the scheme [17]. The extent of usage of GSHISs depends on beneficiaries’ level of awareness about the scheme and their entitlements. The absence of such knowledge before the onset of an illness can influence patients’ treatment-seeking behavior in terms of them choosing either to delay reaching out to hospitals or deciding not to seek care at all. The lack of targeted awareness generation work, in Madhya Pradesh, through the government’s official channels about the scheme and entitlement points to the need for focusing on Information, Education, and Communication (IEC) activities for PM-JAY in the state.

Once the PM-JAY beneficiary reaches a hospital, the PM-JAY helpdesk is supposed to act as a crucial source of information about the scheme, beneficiary’s registration and entitlement, and provide support to the beneficiaries in the hospitalization process. In terms of the information and support provided by the helpdesk to the beneficiaries, public hospitals performed much better than private hospitals. In the state of Gujarat, helpdesks in public hospitals were found to be more helpful as compared to that in private hospitals. Helpdesks in public and private hospitals in Madhya Pradesh were not significantly different in terms of providing information and support to the beneficiaries. The results of the regression model highlighted that the help received by the beneficiaries at the PM-JAY helpdesk desk (an indicator of prompt attention) has a significant impact on beneficiaries’ satisfaction. In the context of RSBY, an earlier GSHIS in India, the indifference of helpdesks in helping patients and a resultant poor satisfaction among beneficiaries have also been reported [18]. These findings indicate a need to strengthen the functioning of the helpdesk in PM-JAY. This needs to be prioritized for private hospitals as compared to the public hospitals, and for Madhya Pradesh as compared to Gujarat. Such an effort will help in increasing beneficiary’s satisfaction and will ultimately have a positive impact on the utilization of the scheme.

Beneficiaries in Gujarat experienced significantly lower waiting time as compared to those in Madhya Pradesh for ‘admission and pre-authorization request’–i.e. the time that the AM took in preparing and submitting the request using the PMJAY IT system. Within Gujarat, the waiting time experienced by the beneficiaries for ‘admission and pre-authorization request’ (an indicator of prompt attention) was not significantly different across public and private hospitals. In the case of Madhya Pradesh, the waiting time experienced by the beneficiaries for ‘admission and pre-authorization request’ was significantly lower in public hospitals as compared to that in private hospitals. On similar lines, the time taken for ‘pre-authorization approval’ (an indicator of prompt attention) by the insurer was found to be significantly lower in Gujarat as compared to Madhya Pradesh. The time taken for ‘pre-authorization approval’ was not significantly different between public and private hospitals in Gujarat. However, for Madhya Pradesh, the time taken for ‘pre-authorization approval’ was found to be significantly lower for public hospitals as compared to private hospitals. Time taken for ‘pre-authorization approval’ can be high if (a) at hospital level AM is submitting incomplete ‘admission and pre-authorization request’ resulting in repeated queries from the insurer, (b) the insurer lacks the capacity to process the received ‘admission and pre-authorization request’ on time. It has been suggested that the time required for completing hospital-based processes that involve AMs can be reduced by investing in capacity-building efforts for AMs [15]. The results of the present study highlight a need to focus on capacity-building initiatives for AMs in Madhya Pradesh as compared to Gujarat, and within Madhya Pradesh to prioritize such initiatives for AMs working in private hospitals. The results of this study also highlight a need to investigate insurers’ capacity for processing the ‘admission and pre-authorization request’ on time.

The results of this study highlight that the average length of stay in hospital was not significantly different for surgical and non-surgical treatment. The average length of stay in hospital was found to be significantly lower in Gujarat as compared to Madhya Pradesh. At an aggregate level, the average length of stay was found to be significantly lower in private hospitals as compared to that in public hospitals. Similarly, within Gujarat and Madhya Pradesh, the average length of stay was lower in private hospitals as compared to that in public hospitals. The lower average length of stay in private hospitals as compared to that in public hospitals may be leading to the higher efficiency of hospital bed use with or without having negative consequences on the outcomes of medical treatment. This needs to be investigated in future studies.

The results of this study highlight that around a quarter of the beneficiaries made OOP payments to the hospital. The incidence of OOP payment was high in Madhya Pradesh as compared to Gujarat, and in private hospitals as compared to the public hospitals. The magnitude of the OOP payment was significantly lower in Gujarat as compared to Madhya Pradesh and in public hospitals as compared to private hospitals. The magnitude of OOP payment made was significantly higher for beneficiaries belonging to the marginalized and backward castes as compared to those from general caste. The results of the regression model highlighted that making OOP payments while availing healthcare service under PM-JAY has a significant negative impact on beneficiaries’ satisfaction. The high incidence and extent of OOP payments, especially in Madhya Pradesh, is similar to that reported in the context of other GSHIS in India [19-21]. The magnitude of OOP across the two states and type of hospitals as reported in the present study are comparable to the similar estimates among non-insured patients from the recent National Sample Survey [22]. The findings of the present study are also similar to those reported for PM-JAY in the Chhattisgarh state of India. For the Chhattisgarh state of India, it has been reported that PM-JAY neither resulted in a reduction in OOP payment by beneficiaries nor incidences of catastrophic health expenditure, and the magnitude of OOP payment by PM-JAY beneficiaries was significantly higher in private hospitals as compared to that in the public hospitals [23]. The results on OOP of the present study are also consistent with findings from similar schemes in other low- and middle-income countries, where such payments have been stated as a result of moral hazards among poorly-regulated private providers [24].

The OOP payment in PM-JAY has been suggested to be an outcome of the design of the scheme in terms of process flows, poor package rates, and the policy of reserving some procedures for public hospitals. It has been reported that hospitals ask for payments from patients for pre-operative diagnostic procedures due to concern that they will not receive the payment if the patient is not ultimately hospitalized. It has also been reported that patients in private hospitals are asked to make payments for certain multimodal treatments that are reserved for public hospitals. This was found to be more relevant for patients with conditions, like cancer, that require treatment by a team of doctors using multiple treatment modalities. It has also been reported that the patients are asked to pay for the difference of costs between the treatment preferred by the healthcare providers (for example, medicine or an implant for treatment of a cardiovascular condition) and that covered under the scheme [15]. Irrespective of the reasons, OOP payments affect the financial and physical coverage of the GSHIS scheme and negatively affect user satisfaction. If not addressed optimally, such payments can lead to a paradoxical situation in which an overall increase in the utilization of services results in poor financial and physical coverage [25]. Hence, the results of this study highlight an urgent need for actions aimed at reducing the OOP payment by PM-JAY beneficiaries. The results of this study also highlight a need to understand the reasons for higher OOP payment made by the less-advantaged castes of the society.

In PM-JAY, information exchange with patients (an important element of responsiveness) is based on the timely provision of SMSs and telephone calls from scheme authorities. The results of this study found that this information exchange was better in Gujarat as compared to that in Madhya Pradesh. However, the results also suggest that in both the states this information exchange mechanism is performing sub-optimally as compared to that envisioned in the scheme. This weak information exchange mechanism may be making it easier for hospitals to ask for OOP payment from the beneficiaries, and at the same time making it difficult for beneficiaries to report their grievances to the scheme authorities. This finding, hence, suggests a need to strengthen the information exchange mechanism between patients and scheme authorities, and use of patients’ grievances to improve the scheme.

The results of the regression model highlight that beneficiaries’ location (rural, urban) has a significant impact on beneficiaries’ satisfaction with the experience of hospitalization under PM-JAY. The results highlight that chances of beneficiaries living in urban areas having a higher level of satisfaction were significantly higher than those living in rural areas. This can be because of the long distances that the beneficiaries from rural areas are generally required to travel for reaching hospitals of their choice or due to the issues in services received by them from the hospitals located nearby to them. Moving further, there is a need for PM-JAY scheme authorities to understand the challenges that are faced by the beneficiaries from rural areas and strengthen the scheme to meet their needs.

This study surveyed 200 beneficiaries across Gujarat and Madhya Pradesh. These beneficiaries were selected from the most popular and least popular clusters of each of the 14 hospitals covered in this study. This way of focusing on the most and least popular clusters for each hospital may have introduced some bias in sample selection. Also, for this study, the hospitals to shortlist PM-JAY beneficiaries were selected by the respective SHAs. This may also have unknowingly introduced some biases. In the future, studies may look at alternate ways of sampling the hospitals and patients. Also, the sample size of this study is small. In the future, studies may focus on larger sample size. This study looked at OOP payments made by the beneficiaries to the hospitals. In the future, studies may expand this to include direct and indirect OOP payments made by the beneficiaries in traveling to reach a hospital, making stay arrangements, and forgone wages. This will help in getting a holistic picture of the financial burden faced by the beneficiaries.

Conclusion

This research contributes to the existing literature by capturing beneficiaries’ experience of availing healthcare services at the public and private hospitals empaneled in PM-JAY. The results of this study provide insights into the a) responsiveness of PM-JAY in terms of prompt attention in service delivery, and access to information by the beneficiaries, b) financial burden faced by the beneficiaries in terms of incidence and magnitude of out-of-pocket payments made to the hospital, and c) beneficiary’s satisfaction with the experience of hospitalization under PMJAY and its determinants. These results provide insights to the policy-makers and program managers for strengthening the scheme.

In India, health is a state government subject. For implementing PM-JAY, states have the flexibility to implement the scheme as deemed suitable by them. Before PM-JAY, Gujarat had experience of implementing state-level GSHIS (Mukhyamantri Amrutam scheme) whereas Madhya Pradesh had no such experience. While implementing PM-JAY, Gujarat seems to be leveraging its experience, and in the absence of any such prior experience, Madhya Pradesh seems to be at an experimenting and learning stage. This difference in the capacities of these two governments to conceptualize and implement the PM-JAY scheme is resulting in a significant difference in the experiences of beneficiaries in the two states. To strengthen the implementation of PM-JAY, there is a need for a platform where states can share their experiences and learn from each other. This will help in improving the capacities of the state governments for better implementation of PM-JAY. Along with it, there is also a need for developing a quality assurance mechanism to ensure consistency of outcomes across states.

On the part of program managers, there is a need to look for ways to enhance the responsiveness of the scheme. Prompt attention in service delivery will improve beneficiaries’ satisfaction, and timely access to information will enable the beneficiaries to make informed choices and seek accountability from the healthcare providers. For policy-makers, there is an urgent need to focus on steps needed to reduce OOP payment.

Patient survey questionnaire.

(DOCX)

Click here for additional data file.

Comparison of study states across selected expenditure parameters.

(DOCX)

Click here for additional data file.

1 Apr 2021

PONE-D-21-06856

Improving Responsiveness and Financial Protection in Government-Funded Health Insurance Scheme in India: Evidence from Early Implementation of Pradhan Mantri Jan Aarogya Yojana (AB – PMJAY)

PLOS ONE

Dear Dr. Trivedi,

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The major comment from all the reviewers is requirement of a more succinct and structured presentation of the manuscript. It requires results and discussion to clearly follow from the objectives of the study. The variables/ indicators need to be clearly defined for responsiveness, quality and financial protection in the methodology section. My own specific comments are added below and also in the attached manuscript.

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Additional Editor Comments:

Studying responsiveness, quality and financial protection for the newly launched PMJAY scheme will add value to Indian policy and is useful for international literature to know factors that influence these attributes for government insurance schemes.

However, the paper needs to be better structured to follow it more clearly, especially for international audience.

There are several Grammatical issues and certain sections are really lengthy. The discussion and conclusion section needs to be better linked to results. The indicators under responsiveness, quality and financial protection must be explained upfront. The abstract needs to be rewritten with clear results and conclusions.

Abstract needs revision. Does not present any results from the text and conclusion does not follow from the result.

The title does not have quality, but you do mention about quality in results. if it is part of responsiveness, please say it clearly. Also AB in the title is not explained or used throughout the manuscript.

Very long introduction, needs to be structured with background linked to objectives studied.

In the methods section, clearly explain the variables/ indicators used for responsiveness, quality and financial protection used in your study. The indicators are mixed up under the procedures - from admission to discharge to follow up. EG. section c has a mix of responsiveness and financial protection in results. Use the same format then for results and discussion. These are given but the presentation needs to be clearer for the reader to follow.

There are several issues in the result section, which have been put as comments in the paper and need to be explained.

Discussion needs to be arranged in the context of major sections studied, what your research says and how does it corroborate with the research from other government health sponsored schemes from past in INDIA such as RSBY or state insurance schemes or other countries. In what ways PMJAY is better than existing insurance schemes and what needs to be improved.

Please see more specific comments in the attached document.

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Reviewer #1: Partly

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: No

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Reviewer #1: General comments:

The manuscript reviews major language editing and rewriting. There are far too many language errors across the manuscript, which makes it non readable.

All sections need major editing and shortening. The repetition should be eliminated. The discussion section needs to be improved with editing and in the quality of analysis.

Specific comments:

Abstract need to be completely re-written. It does not capture the essence of manuscript. There are 200 study participants from whom data was collected. Some quantitative analysis findings should be part of the abstract, which currently focuses upon qualitative aspects only. The conclusion in abstract is generic. Please re-write. The acronyms can be avoided.

Financial disclosure: Please confirm if this is full disclosure of grant or was there any other funding in addition to Health policy and system research at WHO HQ? Please also confirm if authors have acknowledged all the key people who contributed to this work?

Ethical statement: was there any specific reason that only verbal consent was sought and not the written consent?

Introduction / main text: The language need major re-writing for academic standards. The wordings such as ; line 3: ‘people may remain unhappy with the health systems” could be avoided. This section is a bit superfluous and verbose. It need to edited and shortened. There are total 108 lines, it is difficult to follow and read. The information about PM-AY can be moved into a box.

Methods section, there is duplication of information and repetitions.

Results section. One of the limitations is that the small sample size and then then findings have been used in both tables and text.

In discussion, the key actionable suggestions should be included. The limitations of this work need to be elaborated. More India specific literature review and citations should be used.

Conclusion: Should be succinct and single or maximum two paragraphs.

Figure 1- 4 are repetition and can be removed.

Reviewer #2: while the theme chosen is good, I have the following observations:

1. The paper may give some context of health care utilization and expenditure about the states chosen

2.Need to strengthen the discussion section with some comparison of the findings of PM-JAY with private health insurance schemes to judge the strengths and shortcomings of PM-JAY.

3. Quantitative analysis may be augmented by estimating odds-ratios for the chosen indicators.

4. The word "improving" may be dropped from the title.

5. There are many grammatical errors and many sentences need editing to have a more terse presentation.

6. in line 251, the figures in the Table and in the description do not match.

7. Line 274, and other lines, the style of writing figures is not uniform.

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Reviewer #1: Yes: Chandrakant Lahariya

Reviewer #2: No

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Submitted filename: PONE-D-21-06856- PMJAY scheme India - with comments.pdf

Click here for additional data file.

29 Jun 2021

Reviewers' #1 comments:

General comments: The manuscript reviews major language editing and rewriting. There are far too many language errors across the manuscript, which makes it non readable.

All sections need major editing and shortening. The repetition should be eliminated. The discussion section needs to be improved with editing and in the quality of analysis.

Response: We have revised the manuscript substantially with the help of a professional editor. This has reduced grammatical errors and improved the content.

Specific comment 1: Abstract need to be completely re-written. It does not capture the essence of manuscript. There are 200 study participants from whom data was collected. Some quantitative analysis findings should be part of the abstract, which currently focuses upon qualitative aspects only. The conclusion in abstract is generic. Please re-write. The acronyms can be avoided.

Response: We have revised the abstract to reflect these details.

Specific comment 2: Financial disclosure: Please confirm if this is full disclosure of grant or was there any other funding in addition to Health policy and system research at WHO HQ? Please also confirm if authors have acknowledged all the key people who contributed to this work?

Response: We have revised the financial disclosure statement. It now reads, “The research was made possible through the financial support provided by the World Health Organization. This included support from the Alliance for Health Policy and Systems Research, WHO Geneva as well as from the WHO Country Office, India under grant numbers 68345 (WHO, Geneva) and 67378 (WHO, India). Support was provided under the research programme titled- Health Systems Research for PM-JAY: Improving hospital-based processes for effective implementation. The grant was received by Prof. Dileep Mavalankar, Prof. Mayur Trivedi, and Prof. Anurag Saxena of the Indian Institute of Public Health Gandhinagar. The grant period was from 4 March to 3 September 2019. The URL of the funder is www.who.int. Dr Zubin Shroff of WHO provided guidance in strengthening the methodology and finalizing the instruments, and reviewed the manuscript critically.”

We have revised the acknowledgment statement. It now reads, “We are thankful to the National Health Authority, India, for the guidance and necessary approvals for the research. We acknowledge the inputs of WHO India team members Dr. Vinod Verma in conducting the research, and Dr. Grace Kabaniha in improving the manuscript. We would also like to thank Dr. Chandrakant Lahariya and Dr. Hilde De Graeve for their support and guidance. Please refer to line number 472-476.

Specific comment 3: Ethical statement: was there any specific reason that only verbal consent was sought and not the written consent?

Response: The respondents as poor beneficiaries of the PMJAY scheme were expected to have a low level of education to be poor and would be illiterate or semi-literate individuals from urban and rural areas. Since the data collection for the survey was done using handheld digital devices, the thumb impression was difficult to record. Therefore, informal verbal consent was obtained. However, the respondents were provided all details of the research, including their rights to refuse to participate and not answer any questions. We have provided these details in the manuscript. Please refer to line number 188-192.

Specific comment 4: Introduction / main text: The language need major re-writing for academic standards. The wordings such as; line 3: ‘people may remain unhappy with the health systems” could be avoided. This section is a bit superfluous and verbose. It need to edited and shortened. There are total 108 lines, it is difficult to follow and read. The information about PM-AY can be moved into a box.

Response: We have revised the introduction substantially. The introduction is also shortened by more than fifteen lines. The line “people may remain unhappy with the health systems” is also removed. The information on PMJAY Is now reduced and thus, not moved in a box.

Specific comment 5: Methods section, there is duplication of information and repetitions.

Response: We have revised the methodology section substantially to remove duplication of information and repetitions.

Specific comment 6: Results section. One of the limitations is that the small sample size and then then findings have been used in both tables and text.

Response: We have revised the results section to remove repetitions in the findings that have been used in both tables and text. We have acknowledged the small sample size as one of the limitations. Please refer to line number 438-443.

Specific comment 7: In discussion, the key actionable suggestions should be included. The limitations of this work need to be elaborated. More India specific literature review and citations should be used.

Response: We have revised the discussion section substantially. Certain key actionable suggestions were provided under the conclusion section. These are now shifted to the discussion section. Also, we have added India-specific literature while comparing our findings of awareness of schemes. Please refer to line number 379-381. We have also added literature on waiting time and satisfaction. Please refer to line number 397-398. Additionally, a comparison around OOP has already existed in the manuscript. Please refer to line number 404-406. The limitations of this work are added in the discussion section. Please refer to line number 438-443.

Specific comment 8: Conclusion: Should be succinct and single or maximum of two paragraphs.

Response: We have revised the conclusion section substantially. After shifting certain key actionable suggestions to the discussion section, the conclusion section is now of two paragraphs only.

Specific comment 9: Figure 1- 4 are repetition and can be removed.

Response: Agreeing to the suggestion, we have removed these figures, as the details are provided in the text. These are now provided as supplementary material.

Reviewer #2 comments:

Specific comment 1. The paper may give some context of health care utilization and expenditure about the states chosen

Response: We have now added this information, along with a Table. Please refer to line number 148-49 and Table 1 for these details.

Specific comment 2.Need to strengthen the discussion section with some comparison of the findings of PM-JAY with private health insurance schemes to judge the strengths and shortcomings of PM-JAY.

Response: We couldn’t find relevant research on responsiveness and financial protection from the perspective of beneficiaries of private health insurance schemes. Thus, we could not add such a comparison of PMJAY with private health insurance schemes. However, we have compared our findings with other GSHIS. Please refer to line number 406-420 for these details.

Specific comment 3. Quantitative analysis may be augmented by estimating odds-ratios for the chosen indicators.

Response: The study did not analyze the associations or determinants of responsiveness (measured in terms of patient satisfaction) and financial protection (measured in terms of incidence and magnitude of OOP). Estimation of odds ratio was therefore not attempted as it was not related to the study objectives. Additionally, small sample size was a limitation of the study restricting the scope of statistical analysis. We, however, explored the subgroup difference in responsiveness and financial protection across socio-economic categories of the respondents. These details are presented in Table 1 as supplementary material.

Specific comment 4. The word "improving" may be dropped from the title.

Response: Agreeing to the suggestion, we have removed the word ‘improving’ from the title.

Specific comment 5. There are many grammatical errors and many sentences need editing to have a more terse presentation.

Response: We have revised the manuscript substantially with the help of a professional editor. This has reduced grammatical errors and improved the content.

Specific comment 6. In line 251, the figures in the Table and in the description do not match.

Response: These were because the findings were presented to highlight the proportion of the respondents who did not make any OOP payments. We have now revised the language and figures to reflect the information in terms of those who made the OOP payment, as presented in the table

Specific comment 7. Line 274, and other lines, the style of writing figures is not uniform.

Response: We have corrected the style of writing figures to make them uniform at all places.

Specific comments in the attached document:

Comment 1: check grammar.

Response: We have revised the abstract and edited it for grammatical errors.

Comment 2: The abbreviation in title and text should be the same, otherwise need to repeat the full form here as well.

Response: We have revised the abbreviation in the title.

Comment 3: Indicate dollar values also

Response: We have revised the abstract and added dollar values.

Comment 4: delete. Repeated

Response: We have revised the abstract accordingly.

Comment 5: Avoid abbreviation

Response: We have revised the abstract accordingly.

Comment 6: The conclusion seems more like objective and does not follow from results.

Response: We have revised the conclusion part of the abstract accordingly.

Comment 7: Very long introduction. Clearly provide the background in the context of the objective of the study.

Response: We have revised the introduction substantially. The introduction is also shortened by more than fifteen lines.

Comment 8: Please place references as per the plos one style - different places before and after full stops.

Response: We have revised the references as per PLOS style. They are now after full stops at all places.

Comment 9: check grammar.

Response: We have revised the entire document for grammatical errors.

Comment 10: Major features to be more succinct and summarized in a box under headings

Response: We have revised the introduction of PM-JAY substantially and now it is shorter, and in the flow of the text. At this stage, it need not be in the box. However, if the reviewer feels appropriate, we would be happy to put the details in the box.

Comment 11: Please provide full references with links and dates accessed as per PLOS style.

Response: We have revised this reference. We have used the ‘PLOS’ style in the EndNote referencing software for generating full references for this manuscript.

Comment 12: what are autonomous hospitals

Response: These are publicly funded hospitals that have special status through legislation and thus, are governed independently. However, since this was not relevant for the objectives, we have removed this sentence.

Comment 13: what if the claim os from the same episode of ailment.

Response: All patients with single claims were retained in the population list. Few patients required multiple sessions of treatment like dialysis and chemotherapy. In such cases, each session was claimed separately, and thus, there were multiple claims of those patients. We retained all these patients.

Comment 14: Would this not add a bias for responsiveness, as the hospitals with least claims can also be the ones where people did not want to go.

Response: The hospitals for the study were selected by the state authorities. It was important to ensure the representation of patients across hospitals and specialties within the hospitals. The use of multi-stage sampling method with the use of Probability Proportional to Size ensured that the selection of respondents was not biased either in favour or against any type of specialty and hospital. This information is now explained in the manuscript. Please refer to line number 169-171.

Comment 14: They would already have better knowledge of the health scheme, so their responsiveness may be better.

Response: The selection of the state with previous experience of implementing a GSHIS was an element of study at the time of selection of the study location. The responsiveness in terms of their registration in the scheme was not analyzed and therefore, ‘n’ for the beneficiary registration did not include these patients. The responsiveness of their hospitalization experience was measured only for the particular episode during the study duration. Thus, such possibility of their experience influencing the knowledge and responsiveness of the scheme may be ruled out.

Comment 15: Can be added as supplementary material

Response: We have submitted a copy of the questionnaire as supplementary material.

Comment 15: Would this not create seasonal bias

Response: The study population includes patients who availed hospitalization under PMJAY during April 2019. This was given by the state authorities, and thus, was not under the control of the researchers. The data collection was done during May-June 2019. There could be seasonal effects on the type of illnesses, but the responsiveness and financial protection may not get affected by the time of the year.

Comment 16: Can say informed consent was taken

Response: We have revised the statement and provided more details in the manuscript. Please refer to line number 190-194.

Comment 17: These can be summarized under different headings in a box - in the same format as the results are presented. Some of it also repeated from above. Need to add them together.

Response: These are now well-defined and discussed in the methodology section between lines 196-211. We have removed the repetition. The results of this study were documented using the flow of processes in the standard official guideline as a template. The findings are therefore divided into subsections that correspond to the PM-JAY guidelines for hospital-based transactions. These sub-sections are beneficiary identification and registration, treatment package selection and blocking, discharge and payments, and information exchange.

Comment 18: Is anything covered before and after hospitalization. Was information collected on experience before and after hospitalization? If referral etc. had the influence on registration process. What about coverage after hospitalization.

Response: The study collected information on pre-and post-hospitalization expenses in detail. The analysis of OOP payment includes these details in light of the provision of such coverage under the scheme. The information exchange is an in-built element regarding a) registration done before or at the time of the hospitalization, b) package selection during hospitalization, and c) calls for feedback after the hospitalization. These were studied in detail.

Comment 19: why is education of beneficiary/ or highest education in HH not taken as indicator, as awareness and responsiveness depends quite a bit on that.

Response: We have now added this information in Table 3.

Comment 20: mismatch - 61 vs 74. Also if they were already enrolled in a scheme, one would expect better experience about the process. Could it be they did not want to switch.

Response: This is not a mismatch. 74% of the total 61 respondents (i.e. 45 respondents) indicated that they knew about the scheme from the letter. The remaining 39 participants at the time of the research were yet to be transferred from the MA scheme to PMJAY. For all practical purposes, all beneficiaries, irrespective of the scheme received the same coverage for their hospitalization. We did not include these 39 participants for their registration experience as they were not registered in PMJAY till April 2019. The participants did not have choice in switching as the existing scheme was getting subsumed under PMJAY over time.

Comment 21: what was the difference in public vs. private will be useful to know

Response: The satisfaction was higher among beneficiaries from public sector hospitals (83%) than their counterparts from the private sector (77%). This is now added in the result section. Please refer to line number 296 and 297.

Comment 22: You mention preauthorization above also. These are longer than for admission and preauthorization. Do you mean only admission above? Otherwise hours should be more above.

Response: The first mention of pre-authorization is in the context of ‘admission and pre-authorization request’ – i.e. time that the AM took in preparing and submitting the request. The second mention is about ‘pre-authorization approval’ to be received from the scheme authorities. The first one is the efficiency of the insurance processes at the level of healthcare providers, and the latter is about the efficiency of the scheme managers at the level of the insurance company / Trust. These details are clarified and streamlined in the subsection of ‘treatment package selection and blocking’ in the result section.

Comment 23: Why is the sum of total smaller than public plus private

Response: The total of ‘n’ is 100 (after adding 56 private and 44 public). The incidence of OOP is in proportion. So, the total need not be the summation of the two proportions. It is the mean of the two (i.e. 13 and 9).

Comment 24: Does PMJAY not cover the medicine bills for medicines not available. Also for a procedure, would everything not be covered?

Response: Ideally, all expenses should be covered. According to the guideline, the patient need not pay and the hospital must not do balance billing. However, the finding of this study, therefore, brings evidence on OOP and connects it to the reasons for such OOP in the discussion section. We, therefore, raise the need to address underlying supply-side reasons for OOP.

Comment 25: Are they informed and consulted about it before the registration.

Response: Yes. In most cases, the patients were informed beforehand about the possibility of such part payments. This was ascertained during the survey through informal discussions with the respondents.

Comment 26: Is insurance agency or the scheme informed about these payments charged to the patients?

Response: The survey respondents did not know of such communication. Therefore, this is not part of our analysis. However, since part payment is not allowed under the scheme, there is no mechanism/ mandate for the hospitals to make this information available to the insurer/scheme managers.

Comment 27: This is really high. Can this be compared with OOPS data from HH survey.

Response: This is high in the case of patients who availed of hospitalization in a private hospital in Madhya Pradesh, a state which saw such GSHIS with 5 lac coverage for the first time. Therefore, this needs to be seen contextually for the GSHISs covering secondary and tertiary hospitalization. We refrained from comparing the magnitude of OOP of this study (which was measured for those who made some payment) with similar data from the HH survey as the study population is not comparable. Our study population comprises those who exclusively opted for secondary and tertiary hospitalization, and thus are not comparable with households incurring expenses on a range of healthcare, including primary care and outpatient treatment. We have compared the incidence of OOP among the insured patients with similar research on beneficiaries of past GSHIS like RSBY that offered relatively low coverage. Please refer to line number 406-420 for these details.

Comment 28: This should and most of it is part of introduction. Not required here.

Response: We have revised this paragraph and removed irrelevant sentences from here.

Comment 29: What about the links to the socio economic conditions of the households. Also does education matter.

Response: The study did not analyze the determinants of responsiveness (measured in terms of patient satisfaction) and financial protection (measured in terms of incidence and magnitude of OOP). However, on comparing these parameters across the socio-economic subgroups of the respondents, it was found that the satisfaction for registration (91%) and hospitalization (82%) was highest among the illiterate respondents. This sub-group has the lowest incidence of OOP (15%), but reported the highest amount of OOP payment (Rs. 41075). We have provided this information with a table as supplementary material.

Comment 30: What about the links to the rights and information. Also not discussed clearly about the payments and links to Aarogya Mitra. Should AM not play a role in helping the patients to keep their payments low. Even if AM desk is not there in hospitals, should AM not visit the hospitalized patient under the scheme. That would improve the quality and financial protection.

Response: Aarogya Mitra is a staff of the hospital appointed to streamline the liaison between patients, doctors, and scheme authorities. As an employee of the hospital, the AM interacts with the patients on behalf of the hospitals – at the helpdesk or bedside. The AM’s interaction with the patient is limited to information and documentation for preauthorization and discharge. As for the payment, the AM merely conveys the decision of ‘balance payment’, if any, taken by the hospital authorities. Lastly, being a household survey of the patients, this research did not dwell deeper in the supply side issues of how AM can play an improved role at the provider level.

Comment 31: how do this and some other conclusions follow from your results. Please restrict discussion and conclusions to what your results show.

Response: This is connected to the reasons that patients indicated for their OOP, especially in the case of those who made a lump sum payment. These patients reported that they were informed at the helpdesk that the actual costs of their treatments or procedures were higher than the amount the hospital would receive from claim reimbursements from PM-JAY; thus, patients needed to pay the balance. This is indicated in the result section (Please refer to line number 32-335). We have revised the language and added corresponding arguments and evidence (Please refer to line number 414-416).

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4 Sep 2021

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Additional Editor Comments (if provided):

The title has responsiveness and financial protection. please discuss these clearly.

Abstract is still very vague. The introduction must have the objective linked to the title. Methods must state how are responsiveness and financial protection studied in the context of PMJAY scheme. Results should be linked clearly to the indicators measured and conclusion should be linked to the results.

Conclusion: there are unnecessary sentences in the conclusion. Eg. The statement “This study provides insights from its beneficiaries based on their experiences of hospitalization under PM-JAY”  —this is objective and not conclusion.

Need to clearly say what GSHIS did to improve responsiveness and what was the outcome or the result of that and what can India and other counties learn from the experience.

Please rewrite the abstract clearly

Introduction: Liner 95 – not clear - 500 million beneficiaries from the 100 million poor and vulnerable families

Last para of introduction could clearly state how responsiveness and financial protection would be studied. Especially there is nothing about financial protection in the introduction.

Table 1: the data should not be a part of the methodology. Even if is based on secondary sources, these are results. However not being a part of the main study, these could be supplementary material and the figures can be used in the context of responsiveness and financial protection in discussion. The hospital OOP data can be found in the latest version of the NSSO key indicators for 2017-18. Plus, the OOP differs when hospitalization is in public or private facilities and in rural and urban areas. The NHA data is also dated and available for more recent years

Methods: Still; very weak to compare the two states. No clear statistical analysis to understand the differences in the two states. Just presenting table 1 in methods does not show how the results are compared across two states and why the differences are observed. It’s just data presented from a survey with no good analysis. Can the results be compared with control population, those who had similar hospitalization episodes but were not a part of PMJAY scheme.

Results: Why are the n in tables 4 and 5 different. Tables 4 and 5 can be combined.

There are no control variables to say whether the PMJAY was more responsive or not.

Discussion: Lines 370-371 add OOPE also.

The discussion should be clearly organized first around the variables for responsiveness providing quantitative comparison with the studies from India and international. Why do you say PMJAY is more responsive – in comparison to what.

Also then compare financial protection the same way.

Lines 383, can you pls compare with the references mentioned in quantitative terms to provide a perspective of improvement. In providing the information to patients.

Lines 389-90: Do you mean overall in both states public sector hospitals performed better.

Discussions should clearly bring out reasons for differences in waiting times at the public and private sector and reasons for it. Also compare quantitatively with other studies to show whether the waiting time mentioned is responsive. Line 401- you mention short waiting time- but it was 3 hours in private sector in MP. That is not short.

Lines 406-420. OOP discussion should again be in perspective with non-insured patients and also insured in other programs. Why is PMJAY better. The para provides a weak discussion.

There are still a lot of repetition in conclusions and needs to be a para highlighting important points.

Is there a rural urban variation in responsiveness and financial protection? Why are there such varied results between two states. What is working in one state and not the other? The paper is important but still not convincing enough.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

Reviewer #3: (No Response)

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

Reviewer #3: Partly

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: No

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4. Have the authors made all data underlying the findings in their manuscript fully available?

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Reviewer #2: Yes

Reviewer #3: No

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

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Reviewer #2: Yes

Reviewer #3: No

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6. Review Comments to the Author

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Reviewer #2: The authors have addressed the comments raised in the review, revised the language and grammar and the paper may be accepted now.

Reviewer #3: Thanks for taking up an interesting topic on evaluation of delivery of Government Health Insurance Schemes to poor which was revised and re-launched in Sept 2018. I have reviewed the revised version of the paper and looking at previous reviewers comments I would like to state that all comments are not adequately addressed. My additional comments are as follows. 1. Abstract need a thorough revision which I agree with previous reviewers. 2. Neither objectives nor main outcome measurements were clearly defined in the paper as well as in the abstract. Conclusion seems don't appear from the findings of the survey. 3. No statistical tools were applied to explain differences in two states or controlling for hospital types. 4. It appears sample is biased when we talk about share of SC & ST patients in Madhya Pradesh. 5. The major flaw is in the sample selection procedure where the just did quota sampling from two tales of the patients hospitalised during April 2019 in 14 hospitals. One can't portray a robust picture using top 10% and bottom 10% of patients using services as "Highest"/ "Lowest" consumption of health care resources in the sampled hospitals. Instead of following a randomisation process they eliminated the middle 80% of cases. 6. I have mentioned comments on the body of paper and on tables; e.g. I can't understand they are using "Total" heading in both columns and rows even whilst presenting statistics on average for two states.

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Reviewer #2: No

Reviewer #3: Yes: Anil Gumber

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3 Mar 2022

• Comment: The title has responsiveness and financial protection. please discuss these clearly.

Response: The meaning of responsiveness and its dimensions are discussed on line number 72 – 82. The details of responsiveness and financial protection used in the study are discussed from line number 138-144, and indicators of responsiveness and financial protection are detailed in line number 211 – 227. We have revised the title to “Experiences and challenges in accessing hospitalization in a Government-Funded Health Insurance Scheme: Evidence from Early Implementation of Pradhan Mantri Jan Aarogya Yojana (PM-JAY) in India”.

• Comment: Abstract is still very vague. Please rewrite the abstract clearly

Response: We have revised the abstract to have objectives linked to the title of the study, methods stating the way indicators of responsiveness and financial protection were defined, and conclusion following from the results. Please refer line number 27 – 61.

• Comment: Introduction: Line 95 – not clear - 500 million beneficiaries from the 100 million poor and vulnerable families.

Response: We have revised this. Please refer line 90 – 96.

• Comment: Introduction could clearly state how responsiveness and financial protection would be studied.

Response: We have added the details. In line 72-82 the meaning of responsiveness and its dimensions are discussed. Towards the end of the Introduction section, in line 138 -144 further details of the way this study attempts to study responsiveness and financial protection have been specified. In the Methods section, the indicators of responsiveness and financial protection used in the study are discussed from line number 211 – 227.

• Comment: Table 1: the data should not be a part of the methodology. Even if is based on secondary sources, these are results. However not being a part of the main study, these could be supplementary material and the figures can be used in the context of responsiveness and financial protection in discussion. The hospital OOP data can be found in the latest version of the NSSO key indicators for 2017-18. Plus, the OOP differs when hospitalization is in public or private facilities and in rural and urban areas. The NHA data is also dated and available for more recent years

Response: We have updated the table with the latest data. We have also taken the table to supplementary material. Please refer to Supplementary Table 1.

• Comment: Was data collection completed within one month.

Response: No. The sample was derived from the patients who availed treatment during this one month. The study duration was March – August 2019. We have worded the description accordingly. Please refer line number 154, and 169.

• Comment: Methods- Still; very weak to compare the two states. No clear statistical analysis to understand the differences in the two states. Just presenting table 1 in methods does not show how the results are compared across two states and why the differences are observed. It’s just data presented from a survey with no good analysis. The paper lack rigorous statistical analysis. No statistical tools were applied to explain differences in two states or controlling for hospital types.

Response: We have revised the methods sections. We have used Non-parametric test (Mann–Whitney U test) to compare beneficiaries’ responses across states (Gujarat and Madhya Pradesh), hospitals across states (public and private hospitals), hospitals within a state (public and private hospital in Gujarat, public and private hospital in Madhya Pradesh), and across socio-economic categories. We have also carried out cumulative odds ordinal logistic regression with proportional odds to determine the effect of state, hospital type, OOP incidence, beneficiary’s caste, beneficiary’s location, beneficiary level of education, type of care/services received, help received at PM-JAY registration desk, and the number of days for which the beneficiary was admitted in a hospital (independent variables), on the beneficiary’s satisfaction with the experience of hospitalization under PMJAY (dependent variable). Please refer line numbers 233-272. Please refer to the results section for the results of the Non-parametric test (Mann–Whitney U test) and cumulative odds ordinal logistic regression with proportional odds. Please refer to the results section for the description of results obtained.

• Comment: Results- Why are the n in tables 4 and 5 different. Tables 4 and 5 can be combined.

Response: Table 4 was about the incidence of OOP and thus ‘n’ refers to those who made such expenses. Table 5 was about the magnitude of OOP payment for those who experienced OOP. We have combined Tables 4 and 5. Please refer to Table 3 on line number 422.

• Comment: No Differences between two states were tested by each socio-economic conditions

Response: We have used Non-parametric test (Mann–Whitney U test) to test the differences by each socio-economic condition. Please refer line number 445 – 450. We have also used caste, level of education, location of residence as independent variables in cumulative odds ordinal logistic regression with proportional odds. Please refer line 246-272, refer to table 4 and 5 at line 471 and 482.

• Comment: The discussion section is very weak and does not clearly discuss the results of the study. None of the points seem to cater to the international audience and are very broad even for Indian perspective

Response: We have revised the discussion section to highlight the significance of the results. We have also compared the findings of this study with other studies carried out in national and international contexts. We have also discussed reasons for difference in performance across states and types of hospitals. Please refer to line from 500 – 637.

• Comment: Lines 383, can you pls compare with the references mentioned in quantitative terms to provide a perspective of improvement in providing the information to patients.

Response: Information provided. Please refer to line 511 – 512.

• Comment: OOP discussion should be in perspective with non-insured patients and also insured in other programs.

Response: We have updated the discussion section. In the discussion section, results related to OOP payment are discussed in comparison with the OOP payment made by non-insured, those insured under PM-JAY in other states of India. Please refer line number 568 – 588.

• Comment: Neither objectives nor main outcome measurements were clearly defined in the paper. The conclusion seems don't appear from the findings of the survey.

Response: The objectives and aims of the study, outcome measures are outlined in the introduction section. Please refer line 130 – 144. The details of the way outcome measures were operationalized and data was collected are provided in line number 208-228. We have thoroughly revised the results, discussion, and conclusion sections of the paper.

• Comment: There is still a lot of repetition in conclusions and there needs to be a para highlighting important points.

Response: We have revised the conclusion part to highlight important takeaways. Please refer to lines 639-663.

• Comment: It appears sample is biased when we talk about the share of SC & ST patients in Madhya Pradesh.

Response: The profile of survey respondents as provided in table 2 on line 292 was a finding of the study. The sample of respondents for the study was drawn from the list of claims provided by the state health agency of the respective states. These were patients who received treatment from sample hospitals during April 2019. Scheduled Tribe, Scheduled Caste, Other Backward Caste represent the marginalized section of society in India. Taken together beneficiaries from these castes constitute 74% of the sample of beneficiaries from Madhya Pradesh.

• Comment: The major flaw is in the sample selection procedure where they just did quota sampling from two tales of the patients hospitalized during April 2019 in 14 hospitals. One can't portray a robust picture using the top 10% and bottom 10% of patients using services as "Highest"/ "Lowest" consumption of health care resources in the sampled hospitals. Instead of following a randomization process, they eliminated the middle 80% of cases.

Response: The sample of this study did not eliminate 80% of cases. We applied the ‘top-bottom’ rule` to the specialties, and not to patients, at each of the 14 sample hospitals for which we received the claims data from the insurance authorities. The hospitals included in this study were single- and multi-speciality in nature, and thus, we decided to include a representation of patients across a range of services, by selecting clusters having top 10% (most popular services) and bottom 10% loads of patients (Least popular services) from each hospital. These are not 10% patients, but clusters. By following this procedure, we had a pool of 57% of patients (67% in Gujarat and 53% in Madhya Pradesh) from which we randomly selected the respondents. There is a possibility that this way of selecting the respondents may have introduced some bias. We have acknowledged this a possibility in the discussion section of the paper. Please refer to lines 626-633.

• Comment: I have mentioned comments in the body of the paper and on tables; e.g. I can't understand they are using "Total" heading in both columns and rows even whilst presenting statistics on average for two states.

Response: We have revised the paper to take care of the comments received in the body of paper.

Submitted filename: Responses to comments.docx

Click here for additional data file.

29 Mar 2022

Experiences and challenges in accessing hospitalization in a Government-Funded Health Insurance Scheme: Evidence from Early Implementation of Pradhan Mantri Jan Aarogya Yojana (PM-JAY) in India

PONE-D-21-06856R2

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Reviewer #3: Yes: Anil Gumber

21 Apr 2022

PONE-D-21-06856R2

Experiences and challenges in accessing hospitalization in a Government-Funded Health Insurance Scheme: Evidence from Early Implementation of Pradhan Mantri Jan Aarogya Yojana (PM-JAY) in India

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