Preference for Public versus Private Medical Services in Poorer Regions of India?

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Indrajeet Kumar This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4928901/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract This study examines preference for public versus private medical services in India’s poorest regions. Qualitative and quantitative insights from a primary survey highlight the substandard quality of public healthcare while private services are unaffordable so unreliable public services drive people to seek expensive private sector’s services. Multivariate analysis shows that the burden of medical expenses and regional disparities in access impact the choice of using public or private services. However, despite the challenges, solutions through conditional cash transfers or health insurance to offset out-of-pocket expenses in private facilities limits relief due to the inadequate medical services in rural and remote areas. Medical Service Preferences Public vs. Private Healthcare Health Service Quality Conditional Cash Transfers 1. Introduction The emergence of the COVID-19 pandemic reiterated the importance of a robust public healthcare infrastructure. In a middle-income country as India, providing this infrastructure becomes paramount to serve the poor (Slater, 2018). For instance, in healthcare personnel, the country has 6 physicians and 13 nurses (or midwives) to serve every 100,000 population. This number is significantly lower than the global average of 13 physicians and 28 nurses. The scenario becomes so alarming when compared to Europe, with 32 physicians and 79 nurses. In this regard, the World Health Organisation (WHO) recommends that having lesser than 23 healthcare personnel to serve every 100,000 population can hinder the primary healthcare interventions, which can affect the realization of the Millennium Development Goals (MDGs). 1 Thus, the scenario prompts- is India prepared to manage future pandemics and achieve health-related impending MDGs with this public healthcare infrastructure? India spends one of the lowest of its GDP on public health services- allocating only 3.53 % in 2017. 2 The need for responsive and effective health services intensified during the pandemic and later years. In the meantime, upsetting economic outlooks aggravated the scenario straining public investments in healthcare services from stressed government revenues. The increase in unemployment pushed millions of people into poverty giving limited scope for out-of-pocket expenditures. So, the COVID-19 pandemic weakened the public healthcare infrastructure and kicked off a cycle of increasing demand and decreasing the quality of services (Ray & Subramanian, 2020; Sengupta & Jha, 2020). During the pandemic, Indians had mixed experiences with using public medical services. 3 Kerala stood out with its robust public healthcare infrastructure and managed the pandemic better than other states in morbidity and mortality rates despite the first state to report COVID-19 in January 2020. Other Indian states such as Maharashtra, Madhya Pradesh, Delhi, and Uttar Pradesh recorded higher morbidity and mortality rates than Kerala. The scenario highlighted the role of public healthcare infrastructure in for pandemic management. The experience of using public or private medical services in times of need could influence people's preferences of the same. Understanding preferences for type of medical services in the pre-pandemic scenario can provide insights into its usage patterns. The prevailing narrative suggests that lack of quality care in public services delivery drives people to use private medical services (Das, Holla, Mohpal, & Muralidharan, 2016). So, a dilemma for public health policy and planning remains that are efforts of improving the quality of care in public service delivery encourage people to use the same? Or, is it effective to impart purchasing power through Conditional Cash Transfers (CCT) for those who cannot afford out-of-pocket private medical services? This study answers this dilemma by presenting evidence from a field survey in one of the most economically disadvantaged regions of India- Bihar. In particular, the study examines the factors inducing people’s preferences for public versus private medical services in the pre-pandemic context. 2. Medical Services in India In India, pricing of private medical services is contingent upon input market conditions and demand for it. Two crucial inputs are (i) the personnel- doctors, nurses, and paramedics, and (ii) the physical infrastructure- hospitals and clinics. The government's regulation conditions of the private sector and the performance of public healthcare services are the other considerations. The demand for private services depends on financing sources formal or informal as well. Thus, both the demand and the supply-side factors govern access and quality of care in medical services usage (Bhat, 1999). Index for Sustainable Development Goal (SDG) 2020 places Bihar, Jharkhand, Assam, Rajasthan, Uttar Pradesh, and Chhattisgarh at the bottom among the states. 4 One of the components contributing this ranking is health status of the people, which is ensured by access to public healthcare services. However, use of public versus private medical services follows a dichotomy. The National Family Health Survey (NFHS) 2015-16 suggest that during times of sickness, 51.4 % of Indian households opt for a private service provider, while 44.9 % choose a public sector. In private, private hospitals (18.6 %) and doctors or clinics (29.2 %) are the major providers of these services. While, in public sector, government or municipal hospitals (20.4 %) are the major, which is followed by CHC/rural hospital/block PHC (11 %) and PHC/additional PHC (8.9 %). 5 So, the numbers indicate that a major share of the households in India preferred to use private medical services. Top of FormBottom of Form The use of medical services also differs across Indian states. In times of need, 76.2 % households from Bihar, one of the poorest states in the country, had to use private medical services (Supplementary Table 1). 6 However, more than 50 % of households in Orissa, Himachal Pradesh, Jammu and Kashmir, Assam, Kerala, Rajasthan, and West Bengal used public medical services. The quality of care in government services deliver has been an issue in India (Mohanan, Hay, and Mor 2016). The problem is alarming in the low-income states. The lack of expected quality of care in public healthcare compel people with limited financial resources to use private medical services. Further, it involves debt financing sourced from informal sources, out-of-pocket expenditure, or dissaving. Thus, low-income people must spend a substantial share of their savings on healthcare expenses (Collins, Jonathan, Stuart, & Orlanda, 2009). The NFHS 2015-16 suggests that in 48 % of cases, the poor quality of care in government health facility compel people to avoid. Other reasons for avoiding such services include the absence of facilities (44.6 %), long waiting times (40.9 %), inconvenient facility timings (26.4 %), and absence of healthcare personnel (14.8 %). In addition, nearly half of India's people are either unsatisfied with the quality of care or travel distance. 7 The disparities in the quality of care are particularly evident in Bihar. The highest 60 % in Jharkhand and 50 % each in Chhattisgarh, Karnataka, and West Bengal, people grieve the absence of government facility in the neighbourhood; notwithstanding perceive medical service of better quality in these states than Bihar. Only 46 % in Jharkhand, 50 % in Chhattisgarh, 40 % in Karnataka, and 35 % in West Bengal are concerned about the quality of care in government services and this share is 70 % in Bihar. West Bengal (35 %) and Odhissa (34.6 %) stands out with one of the lowest shares of people concerned about the quality of care in government services. This share for Bihar (59.6 %) and Uttar Pradesh (61.1%) is quite high than the national average. Moreover, 42.6 % and 47.7 % of people in these respective states disuse government services given the absence of facilities in the neighbourhood. This share of people is comparable or higher in West Bengal (49.6 %) and Odhissa (48.4 %). Therefore, with same or better access to government facility in proximity, Bihar, and Uttar Pradesh faces problem of quality of care (NFHS-4, p. 377). Therefore, despite the inconvenience of facility timing, a reason for foregoing the government facility in Bihar, is comparable with Gujrat, Uttar Pradesh, Madhya Pradesh, and Maharashtra, people in these states perceive quality of care better than Bihar. Likewise, in absence of healthcare personnel, Jharkhand, Karnataka, Tamilnadu, and Telangana show similar pattern; however, these states ensure a better quality of care than Bihar. In other comparisons, long waiting times at medical facilities, Bihar with comparable problem than other states offer mediocre-quality care. For instance, 78 % of people in Chandigarh, 67 % in Delhi, 66 % in Punjab, and 59 % in Haryana are dissatisfied with the long waiting times, notwithstanding the perceived quality of care is better than in Bihar. 8 The reasons, three-fourths of the households (76 %) in Bihar rely on private medical services and a majority (60 %) using public facilities expresses dissatisfaction with the quality of care. Considering options improve the situation, two scenarios emerge. The first is to enhance the quality of care in government services delivery and encourage people to use them. The second scenario is to supplement the out-of-pocket expenditure with a 'CCT' for make private medical services to be affordable. The second scenario ensures people's preferences of using public or private medical services. This study aims to explore the ground realities for second scenario by analysing people’s preferences and the associated reasons through a field survey in Bihar. 3. The Field Survey Improved health endowments ensure increasing income and reducing poverty and so relationship of economic growth bringing human development is robust (Ranis, 2004). Bihar is the poorest in per capita income and the Human Development Indicators (HDI). 9 The state stands at the bottom in HDI (Planning Commission, 2011). 10 The Patna district in Bihar is better than other districts in per capita income and HDI. 11 In Bihar, 40.1 % of rural and 50.8 % of urban population are below the poverty line (Rangarajan et al., 2014). The state has about 37.7 million poor people, the second highest after Uttar Pradesh. The continuing poverty demands interventions in access to medical services to ensure a healthy workforce increasing households' income. Patna district comprises the capital region with the highest per capita income in the state. In 2011-12 (2004-05 prices), the district had a per capita income of ₹ 63,063 (Government of Bihar, 2019). The region is also the most urbanised place (43.07 %) in the least urbanised state (11.3 %) (Endow, 2017; Bhagat, 2011). The district also outperforms in educational attainment at a 70.68 % literacy rate for the state's literacy rate at 61.80 % (Census of India, 2011). The district is the best in a modest-performing state in urbanisation, per capita income, and literacy. Three motives the district as a survey site: (i) urbanisation determines the convenience of medical services, (ii) income influences the preference for using the medical services- public or private, and (iii) education helps in awareness of the use or convenience of medical services. So, the place qualifies as a survey site to study people's preferences of using public versus private medical services. Table 1 presents the survey description for selecting four Grama Panchayats (GP) based on two criteria. 12 The first is the share of the Scheduled Castes (SC) population in a GP. One of them is with the highest and the other is with the lowest SC population. 13 The rationale for selecting these two GPs is to study people's preference for public versus private medical services in a marginalised social and economic situations. 14 For this, we used stratified random sampling to select GPs using Population Census Abstract of the Census of India 2011. First, we selected two sets of five Blocks in the Patna district of the highest and the lowest SC populations. Then, we randomly selected one Block from each of these two sets. Later, we selected five GPs from each of these two Blocks- for one set of the highest SC population and the other of the lowest SC population. Finally, we randomly selected one GP from each of these two sets of GPs. Medical services are clustered in urban areas and people from far-off places incur extra costs to use them. 15 The urban settlements are a proxy for better access to medical services. So, the second criterion of GP selection is the remoteness or nearness of a GP from an urban place. Selecting two GPs based on urbanisation is to examine the preference given the health care infrastructure in the neighbourhood. The decision to select a GPs was based on visiting them by public transport. To better assess public transport facility and access to medical services at the places we used Google Maps. Hence, we interviewed 200 households from four GPs and ensured to visit each Ward in a GP. 16 Table 1: Selection of Grama Panchayats (GP) and households from Patna district in Bihar, India. Selection criterion of a GP Blocks Name GP Name Households’ Number Highest SC population Punpun Dumri 47 Least SC population Patna Sadar West Digha Mainpura 48 Near city Phulwari Kurthawal 55 Far from the city Mashaudhi Bara 50 Total 4 4 200 Source: authors' description based on the survey design; Scheduled Caste (SC). 4. Qualitative Insights This section discusses the preference for using public versus private medical services with the associated reasons for the same. 4.1 Preference for Public versus Private Medical Services We asked the respondents to choose between using public versus private medical services in times of need when the latter is financed through a conditional cash transfer. 17 Table 2 presents the preference and associated reasons (Supplementary Table 2). 18 The majority, two-thirds (60.54 %) of respondents, preferred using public medical services over private (29.73 %). In depth inquiry with the respondents suggested that the relying on preference alone was inadequate to understand the associated reasons. For, most people favoured using public services despite complaining about the quality of services at the nearby government hospital. Respondents stresses that public services often disserve them when it required the most. So, what encourages people to opt for such services when asked about the preference? The reason was- unaffordable private medical services compel people to use public services. Other reasons with associated preference for public and private services are (i) government services are satisfactory, (ii) using private services (though CCT) gives a choice of treatment, and (iii) both (government and private) services have one or the other issues. In-depth inquiry with respondents reveals that experiences of using medical services outlined the preferences. For instance, those saying public services are satisfactory (56 %) also had to use in times of need. 19 Similarly, those opting for private medical services (22 %) had to use the same given the unsatisfactory experience of public services. This group of people wanted to exercise their 'choice of treatment' through CCT. The group opting public services complained about the cost of medicines and diagnostic tests if purchased or done at private medicine shops or clinics. Households expecting conditional cash for spending on private medical services assume that it would complement their out-of-pocket expenses. Unaffordable medicines and diagnostic tests concerned both public and private medical care users (Wankhar, 2016). Table 2: Households’ preference for using type of medical services and associated reasons (in %). Preference Reasons Government services are satisfactory Using private services (through CCT) gives a choice Both (government & private) services have issues Other reasons Total Government services 56 6 34 4 100 94 17 66 21 61 Private services (though CCT) 5 56 33 5 100 4 76 31 16 30 Indifferent 6 17 11 67 100 1 7 3 63 10 Total 36 22 31 10 100 100 100 100 100 100 Source: author's calculation from field survey data. CCT: Conditional Cash Transfer. During the survey, people were unhappy with both category of medical services (Bennett, 1992; Bhat, 1993; Mathiyazhagan, 2003; Nagla, 2013). For, 34 % of households preferring public services and 33 % preferring private services also criticised the same for one or other reasons. Conversation with respondents suggest that- often, provision of public services failed people's expectations resulting in frustration and annoyance. People going to public services facilities, in want of unaffordable private services, appealed to improve the quality of care. The infrastructure inadequacy and lacking performance auditing were the major concerns in public medical service delivery. Lack of specialised services in geriatric, paediatric, and gynaecology concerned public services (Chatterjee et al., 2019). The respondents also whine about the unsuitable timing of service delivery and unfavourable attitude of personnel at government hospitals. People from lower social and economic groups mentioned the instances of subjective discrimination and corruption in government services delivery. Respondents share that people's social, economic, and political networks influence the quality-of-services received. For instance, lower social and economic groups people (SC- Dalits and Mahadalits) mentioned that medical personnel (doctors, nurses, and paramedical staffs) avoided touching the patients during the medical examination and make them sit-down or lie-down on the floor. The scenario suggested medical services, both at public or private, remained hostile for these groups. The reason available public services failed in quality, while the private were unaffordable. So, the frequent opinion of respondents was to improve the quality of public services. In this regard, one respondent said "money cannot buy doctors if doctors are unavailable in the neighbourhood, while CCTs would be insufficient to buy medical services at private ". 4.2 Rural-urban Divide The rural-urban dichotomy of access and quality of medical services remains a concern in India. In our survey too, households from rural and far-off areas preferred using public services: two-thirds of households from Bara Panchayat using government hospitals in times of need (Table 3). However, public medical services were unpopular in the urban and semi-urban areas. Half of the housheolds from W-D Mainpura (an urban place) and Dumri (a semi-urban) preferred using private hospitals. Inquiry with respondents suggested that rural and far-off places lacked private medical services; and if it was, insufficent cash hindered from using. In private medical services, quacks were rampant in villages, who were unqualified and ill-equipped to manage the mdical emergencies resulting people using government hospitals despite being unsatisfactory. 20 The private medical services in nearby cities were unaffordable due to transportation expenses. Medical ambulance was a luxury in rural areas and only well-off people can afford it through payments or social and political networks with government hospitals. The Block and District Hospitals, the nearby points of accessing public medical services disappointed patients requiring specialised care. The scenario was people suffering from chronic health conditions but travel and medical cost preventing them from going to nearest Block or District Hospital. Older people suffered the most and had postponed their treatment or routine visits and continue with the quacks in the neighbourhood. Survey reveal that private medical facilities in urban and semi-urban areas had problems. Households experiencing poverty accessed the services through debt financing or eroding their savings. Interaction with respondents suggested that it was also encouraging people to migrate to urban places. Besides education and livelihood opportunities, convenience of medical services was one of major attractions of urban places. Nevertheless, households across regions were unsatisfied citing the quality of care in government and the high cost in private medical services. We also asked respondents- why they choose certain services across the regions (Table 3). One respondent from a rural and far-off GP Bara said, "In medical emergencies, we have no option but to go to the nearby government hospitals". The preference for such services is 67 % in this GP. In contrast, one respondent from an urban Panchayat considered public medical services insufficient during emergencies, quoting, "it lacks quality of care". The private medical services, which are often absent in rural areas, were appreciated. In urban and semi-urban areas, where both the services were available, households criticised the both. For instance, 56 % households from Dumri (a semi-urban region) and 42 % from WD Mainpura (an urban region) complained using both facilities. Substandard public medical services compelled people to use private services. Households assert improving government services given the prohibitive cost in private. Table 3: Preference and reasons for using medical services across Grama Panchayats (in %). Grame Panchayats Preference Reasons Government Private Indifferent Total Government services are satisfactory Using private services (through CCT) gives a choice Both (government & private) services have issues Others Total Bara 69 10 20 100 67 10 4 18 100 30 9 56 26 49 12 3 47 26 Dumri 56 41 3 100 3 38 56 3 100 20 29 6 21 1 37 38 5 21 Kurthawal 58 35 7 100 40 20 29 11 100 29 35 22 30 33 27 28 32 30 W-D-Mainpura 57 36 7 100 26 24 43 7 100 21 27 17 23 16 24 31 16 23 Total 61 30 10 100 36 22 31 10 100 100 100 100 100 100 100 100 100 100 Source: Authors' calculation using field survey data. CCT: Conditional Cash Transfer. 5. Preference in a Multivariate Context The discussions until suggest that multiple factors affecting the preference for public versus private medical services by the surveyed households. This section analyses the preference in a multivariate context using logistic regression models aiming to identify the factors associated with the preferences. 21 The dependent variable is a respondent’s preference for public (= 1) versus private (= 0) medical services and if it is for private it to be financed by a CCT. The logistic regressions have the following functional form: Y i = α + β X i + µ. Where, Y i is the preference, and vector X i represent a set of explanatory variables. Thus, vector X i takes the possible factors explaining the preference for using public or private medical services. 5.1. Explanatory Variables Table 4 presents the summary statistics of the variables taken for the logistic regressions. Based on insights from the field survey, the explanatory variables are regional, household, and respondent characteristics. In regional, GPs are the proxies for distance from the city and so the convenience of medical services. In addition, we observe a village or hamlet in these GPs, which are in local parlance called Panchayat’s Main Village (PMV). Compared to other villages in a GP, residents from the PMV were well-off in social and economic status and had better transportation connectively. We also observed residential segregations of castes and classes in PMV. Panchayat Bhawan and Panchayat’s Head and Secretary are from here, while none of the SC households. Understanding the social hierarchy and reality, we have grouped surveyed households into General (GEN), Backward Classes (BC), Extremely Backward Classes (EBC), and Scheduled Castes (SC). 22 Similarly, health expenditure is infinitely non-increasing with increase in income (convexity of health expenditure), we have combined GEN and BC social groups. 23 EBCs and SCs are Bihar's most economically and socially marginalised groups. The Below Poverty Line (BPL) ration cards are a proxy for economic status. The homestead land ownership is an indicator of improved living space are grouped into owned land, government land, and rent. One related indicator is the housing type measured by an index based on the floor, wall, and roof structure and grouped into pucca, semi-pucca, and kaccha houses. The average years of male members' education in a household account for awareness of available medical services. The proportion of self-employed in agriculture or non-agriculture and regular wage or salary earners jobs in a household reflects the ability of out-of-pocket expenditure on health. Table 4 Summary statistics of variables used in the probit model. Variables N Mean SD min Max Preferences (Dependent Variable) 167 0.671 0.471 0 1 Grama Panchayats 167 2.305 1.447 0 4 Panchayat Main Village 167 0.335 0.474 0 1 Social Group 167 0.886 0.810 0 2 Below Poverty Line (BPL) Card 167 0.599 0.492 0 1 House Ownership 167 0.437 0.909 0 3 House Type 167 1.108 0.591 0 2 Proportion of Self-Employed or Regular Wage or Salary Earner (PSRWSE) 167 0.219 0.217 0 1 Proportion of Children (< 15 years) 167 0.281 0.216 0 0.714 Proportion of Old-age People (< 60 years) 167 0.113 0.201 0 1 JAM (bank account, Aadhaar Card, and Mobile Phone) 167 0.719 0.451 0 1 Medical Expenditure (in last year, in log) 167 9.270 2.203 0 13.59 Medical to Food Expenditure Share (in log) 167 2.239 1.802 0 6.399 Female Respondent 167 0.509 0.501 0 1 Respondents’ Education (in years of schooling) 167 4.320 5.009 0 15 Reasons for Preference 167 1.856 0.940 0 3 Rastriya Swasthya Bima Yojana 167 0.467 0.500 0 1 Janani Suraksha Yojana 167 0.0898 0.287 0 1 Average years of Male Education (AYME) 167 5.948 4.303 0 15.67 (PSRWSE) * (AYME) 167 1.599 2.100 0 15.67 (Grama Panchayats) * (Reasons for Preference) 167 4.665 3.821 0 12 Source: author's calculation using field survey data. Households' absolute and relative financial burden due to medical expenses (in the last year) is factored in by (i) total medical expenses, and (ii) a share of medical to food expenses. The increased proportion of children below 15 years and elderly of 60 years or above require increased medical attention and so medical expenditure. In addition, accessing CCT programmes requires an active bank account, an Aadhaar Number, and a mobile phone. So, we have introduced a variable JAM as an explanatory variable. 24 To account for households' experience in healthcare programmes, we have introduced participation in the Janani Suraksha Yojana (JSY) and possession of Rashtriya Swasth Bima Yojana (RSBY) cards. In addition, we also introduced reasons for preferring public versus private medical services narrated by respondents. There are two interaction terms. First, it is between the proportion of self-employed, regular wage, or salary earners and average years of male education since educated males often work in these jobs. Second, it is between GPs and reasons for preferring public versus private medical services. Field inquiry also suggests that reasons are often associated with the location of a GP. Moreover, gender and years of education are respondents' characteristics. 5.2. Results and Discussion Table 5 presents the results suggesting that urban and semi-urban places (Dumri & Kurthawal), as against rural and far-off (Bara), are more likely to prefer private medical services (Model 1). The reason is- urban and semi-urban places have access to private medical services. Similarly, increasing male members' education in a household is associated with using private services. These housheolds know the compromising quality of care at public facilities. Though, educated respondents do acknowledge the crucial role of public medical services and suggest that it is to be a prerequisite to ensure better public health services. The reason, increasing medical to food-expenditure share associating with preferring public services. Table 5 results of logit regressions models of preference for public medical service (= 1) versus private medical services through CCTs (= 0). Model 1 Model 2 Grama Panchayats (base: Bara, rural or far-flung) Dumri -1.153*** 0.147 (0.415) (0.641) Kurthawal -1.135*** -0.953 (0.407) (0.843) W-D Mainpura -0.753 -0.702 (0.494) (1.244) Panchayat Main Village (base: other villages) -0.351 -0.348 (0.261) (0.286) House Ownership (base: in own land) In government land -0.268 -0.443 (0.363) (0.528) In rented -0.442 -0.453 (0.427) (0.524) JAM (Bank Account, Aadhaar Card, and Mobile Phone) (base: missing at least one of the components of JAM in household) 0.133 -0.004 (0.266) (0.343) Social Group (base: General /Backward Classes) SC (Dalit/Mahadalit) 0.054 0.129 (0.347) (0.435) Extremely Backward Classes 0.060 0.340 (0.294) (0.329) BPL Card (base: non-BPL card) -0.341 -0.123 (0.268) (0.288) House Type (base: Kaccha) Semi-pucca 0.375 -0.673 (0.467) (0.810) Pucca -0.061 -0.729 (0.567) (0.926) Medical Expenditure (in last year, in the log) -0.029 -0.022 (0.056) (0.061) Proportion of Children ( 60 years) in a Household -0.803 -0.477 (0.641) (0.663) Medical to Food Expenditure Share (in log) 0.128* 0.131 (0.077) (0.086) Proportion of Self-Employed or Regular Wage or Salary Earners (PSERWSE) in a Household 1.158 1.355 (0.896) (0.935) (PSERWSE) * (AYME) 0.172 0.072 (0.170) (0.138) Female Respondent (base: male respondent) 0.276 0.521* (0.250) (0.287) Respondents’ Education (in years of schooling) 0.065** 0.054 (0.033) (0.037) Possession of RSBY Cards (base: No RSBY Card) -0.289 -0.508* (0.249) (0.287) Beneficiary oof JSY (base: Non-beneficiary of JSY) 0.462 0.846* (0.446) (0.478) Reasons for Preference (base: other reasons) Government Services are Satisfactory 1.468** (0.699) Using Private Services (through CCT) Gives a Choice -1.963* (1.060) Both (Government & Private) Services have Issues -0.789 (1.347) (Grama Panchayat) * (Reasons for Preference) 0.118 (0.142) Constant 1.359* 1.430 (0.779) (1.347) Observations 167 167 Source: author's calculation using field survey data. Robust standard errors in parentheses: *** p < 0.01, ** p < 0.05, * p < 0.1 The results get changed if reasons for preference is introduced (Table 5 , Model 2). Now, female respondents as opposed to males are more likely to prefer using public medical services supporting the insights by women during the field inquiry. The JSY, a CCT programme incentivising institutional delivery, were popular among women. The programme beneficiaries praised the initiative but not without complaining about the inconvenience of ambulance services required to transport expecting mothers to nearby government hospitals. That usually resulted in assocaited costs of escorting the expecting mothers to the government hospitals the requirement to claim the benefits (Carvalho & Rokicki, 2019 ; Ghosh, S., & Husain, 2019 ). The mothers also moan about the delays in cash receipt through DBT. Contrarily, households possessing RSBY cards, for a CCT programme, are more likely to prefer private hospitals, reflecting the programme's feature that a beneficiary can use public or private medical services and reimburse medical expenditure to a limit. However, talking with the respondents revealed lacking awareness most households with RSBY cards unused this service during the recent medical emergency. Lastly, respoendents who said that public services are satisfactory than those who highlighted reasons to avoid them are more likely to prefer public services as well. Conversely, people favouring private medical services through a CCT are more likely to prefer private services too. So, the reasons associated with the preferences are consistent in the multivariate preference model. 6. Conclusion This study investigates households' preferences for public versus private medical services examining qualitative and quantitative evidence from a field survey in Bihar, India. The results indicate that unreliable public medical services compel individuals to use private services. The delivery of medical services also varies across regions and for social groups. In remote and rural areas, underprivileged groups face an absence of dependable medical services. The substandard quality of care in public facilities and exorbitant costs is levied by private providers. Thus, using medical services in needed poses a dual challenge. The reason, private medical services is popular among those with financial means. While, those lacking must depend on unsatisfactory public services that are far-away and incurring travel expenses. The inconvenience of timing of services and the absence of quality of care due to understaffing and personnel absenteeism exacerbates the propblems in the public healthcare system. Embracing and implementing CCTs as a substitute for out-of-pocket expenditures on private medical services is unworkable given the absence of private services in rural and remote areas. In rural settings, inadequate public medical services and financially inaccessible private healthcare compounds the problem of medical care. Considering local-level factors, the households' inclination towards public or private in a multivariate scenario indicates a association between higher medical expenditure and a preference for public services. Similarly, a favourable experience with the Janani Suraksha Yojana correlates with simialr preference. The reason, female respondents exhibit more inclination towards public services. Likewise, an increase in respondents' education is linked to such preference too. The logistic regression results indicate that individuals in urban and semi-urban locations and better-educated males are more inclined towards using private medical services. Consequently, those using private services or expressing a preference for private over public services are more likely to choose private healthcare when presented with a choice between the two. In this regard, the COVID-19 pandemic highlight the need for a responsive and dependable public healthcare system. So, enhancing the public healthcare system without expanding coverage or providing financial means through CCTs to those unafford private services would be insufficient. The healthcare demand necessitates a synergy and complementarity between public and private capacities. The past years’ COVID-19 health policy, combining testing, treatment, and vaccination demonstrates the effectiveness of such synergy and complementarity in the two sectors. Relying on medical insurance- a panacea for the limited supply and compromised quality of public services, is also inadequate. The pandemic experience highlights the importance of a robust public healthcare infrastructure, when regulated and complemented, can address healthcare needs including those also met by private services. Finally, while the study employs a reasonable research design, it encounters two limitations. Firstly, differences exist in quality and extent of public health care provisioning among Indian states, exemplified by the disparity between Kerala and Bihar. Consequently, conducting a pan-India inquiry could unveil further nuances. Secondly, we relies on household information- the demand-side stakeholders, so, a similar study involving supply-side stakeholders- medical personnel, insurance companies, and policymakers- can complement this research by understanding input costs. Declarations Ethical Approval and Consent to Participate : This study was conducted in accordance with the ethical guidelines of Ethics Committee at the Centre for Development Studies, Thiruvananthapuram. Informed consents were obtained from all participants. The participants were fully informed about the purpose of the research, their right to withdraw at any time, and the measures taken to ensure confidentiality and anonymity. Clinical trial number not applicable Funding: This research was not supported by any funding. Author Contribution Indrajeet Kumar conducted the field survey, did data analysis by preparing tables and econometric models, wrote the manuscript, and reviewed the manuscript. Acknowledgement Acknowledgement: I am grateful to Dr Upasak Das, Presidential Fellow in Economics of Poverty Reduction at Global Development Institute, University of Manchester, United Kingdom for his help in survey design. In addition, I thank Professor Udaya S Mishra at International Institute for Population Sciences, Mumbai, India for guiding on analysis plan. I am also indebted to all the respondents who participated in this research. Availability of data and materials: The data and materials used in this study are available upon request to the author. References Bennett, S. (1992). Promoting the private sector: a review of developing country trends. Health Policy and Planning , 7 (2), 97-110. Bhagat, R. (2011). Emerging pattern of urbanisation in India. Economic and political weekly , 10-12. Census of India. (2011). District Census Handbook Patna, SERIES-11, PART XII-A. Directorate of Census Operations, Bihar. Endow, T. (July 2017). Urban development and rural-urban linkages in six towns in Bihar, C-89113-INB-1. Final report, International Growth Centre. Mohanan, M., Hay, K., & Mor, N. (2016). Quality of health care in India: challenges, priorities, and the road ahead. Health Affairs , 35(10), 1753-1758. Ranis, G. (2004). Human development and economic growth. Available at SSRN 551662 . Ray, D., & Subramanian, S. (2020). India's lockdown: an interim report. Indian economic review , 55 (1), 31-79. Sengupta, S., & Jha, M. K. (2020). Social policy, COVID-19 and impoverished migrants: challenges and prospects in locked down India. The International Journal of Community and Social Development , 2(2), 152-172. Slater, J. (2018). India is no longer home to the largest number of poor people in the world. Nigeria is. The Washington Post . Bhat, R. (1993). The private/public mix in health care in India. Health Policy and Planning, 8(1), 43–56. https://doi.org/10.1093/heapol/8.1.43 Bhat, R. (1999). Characteristics of Private Medical Practice in India: A Provider Perspective. Health Policy and Planning, 14(1), 26–37. https://doi.org/10.1093/heapol/14.1.26 Carvalho, N., & Rokicki, S. (2019). The Impact of India's Janani Suraksha Yojana Conditional Cash Transfer Programme: A Replication Study. The Journal of Development Studies, 55(5), 989–1006. https://doi.org/10.1080/00220388.2018.1506578 Chatterjee, C., Nayak, N. C., Mahakud, J., & Chatterjee, S. C. (2019). Factors affecting the choice of health care utilisation between private and public services among the elderly population in India. International Journal of Health Planning and Management, 34(1), e736–e751. https://doi.org/10.1002/hpm.2686 Das, J., Holla, A., Mohpal, A., & Muralidharan, K. (2016). Quality and accountability in health care delivery: Audit-study evidence from primary care in India. American Economic Review, 106(12), 3765–3799. https://doi.org/10.1257/aer.20151138 Ghosh, S., & Husain, Z. (2019). Has the National Health Mission Improved Utilisation of Maternal Healthcare Services in Bihar? Economic & Political Weekly, 54(31), 44–51. Retrieved from https://www.epw.in/journal/2019/31/special-articles/has-national-health-mission-improved-utilisation.html Government of Bihar. (2019). Bihar Economic Survey 2018-19. Patna: Finance Department. Retrieved from http://finance.bih.nic.in/Reports.htm Mathiyazhagan, M. K. (2003). People's Choice of Health Care Provider: Policy Options for Rural Karnataka in India. Journal of Health Management, 5(1), 111–137. https://doi.org/10.1177/097206340300500106 Nagla, M. (2013). Privatisation of health care in India: Emerging issues and concerns. Indian Journal of Public Health Research and Development, 4(4), 118–122. https://doi.org/10.5958/j.0976-5506.4.4.155 Planning Commission. (2011). India Human Development Report, Towards Social Inclusion. Retrieved from https://econpapers.repec.org/paper/esswpaper/id_3a6740.htm Rangarajan, C., Mahendra Dev, S., Sundaram, K., Vyas, M., & Datta, K. L. (2014). Report of the expert group to review the methodology for measurement of poverty. New Delhi: Planning Commission, Government of India. Retrieved from http://planningcommission.gov.in/reports/genrep/annrep.php?Repts=b_annrep.htm Wankhar, D. L. (2016). Affordability of Healthcare in the Eight North Eastern States of India. Indian Journal of Public Health Research & Development, 7(3), 165. https://doi.org/10.5958/0976-5506.2016.00150.9 Footnotes See: https://www.who.int/whosis/whostat/EN_WHS09_Table6.pdf See: https://apps.who.int/nha/database/country_profile/Index/en See: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7423401/ See: https://sdgindiaindex.niti.gov.in/#/ranking CHC and PHC are Community Health Centre and Primary Health Centre. The poorest states in per capita income (Rowan & Thirlwall, 2015). Punjab, as the second highest in using private services attributes to higher per capita income. For, as income increases, people tend to use high quality private medical services. The rural and remote regions suffer twin problems: poor quality of care and long distances of medical services. Though, urban areas are having access of medical services but at high costs. In Bihar, the scenario is: no nearby facility (43%), waiting time is too long (38%), services timing is inconvenient (33%), and medical personnel are often absent (18%). In quality-of-care too, the state is 10 percentage points below than national average. See: https://www.mitpressjournals.org/doi/abs/ 10.1162/153535102320893983 See: https://www.undp.org/content/dam/india/docs/inequality_adjusted_human_development_index_for_indias_state1.pdf See: http://finance.bih.nic.in/Reports/Economic-Survey-2019-EN.pdf & http://finance.bih.nic.in/Reports/Economic-Survey-2020-EN.pdf We conducted this field survey in the Patna district of Bihar from October through December 2015. The SC community suffers from social and economic marginalisation in Bihar and India. In India and Bihar, economic marginalization is an outcome of social marginalization. For, most of the SC households are the poorest or poorer in the Wealth Index of NFHS 2014-15. The distance estimate is from Patna Junction, Railway Station. The number of households (= 50) taken from a Grama Panchayat was divided by the number of Wards in a GP. For instance, if Dumri had 13 Wards, we interviewed 4 households from each Ward. However, on occasions, we had exceptions to accommodate social and economic realities of the place- for instance, caste and social groups. Throughout, a respondent’s preference represented a household’s preference and out of 200 households, 185 answered this question and 167 had marked public or private services and the rest were indifferent of using either. Supplementary Table 2, presents the grouping of reasons to prefer public or private medical services. In that, 9.73% of respondents were indifferent of using both services. During the interview, we observed that respondents, especially from the poor backgrounds, were reluctant to complain about the public medical services in the fear that even the existing services, though unsatisfactory, might be stopped. People hesitate to complain about the government medical personnel, who are from the nearby villages or neighbourhood and belonged to higher social and economic groups. During medical emergencies the poor must rely on them. So, the scope for complains was limited. Contrarily, private medical services were open for criticism. Hence, demand for medical services creates it supply than otherwise. In a mixed-method, we analyse the quantitative results considering qualitative insights. This survey had none Scheduled Tribe’s households. In social hierarchy, GENs are the most socially, economically, and politically well-off group, and it is followed by BC, EBC, and SC. Health expenditure by household is indefinitely non-increasing with increasing income rather it requires an optimum level of income to maintain a normal health unless or otherwise it is an emergency. JAM stands for (I) Jan Dhan Yojana, a scheme to open a zero-balance account, (ii) Aadhaar Card, a unique identification number, and (iii) a mobile phone. Additional Declarations No competing interests reported. Supplementary Files SupplementaryTables.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 26 Aug, 2024 Reviewers invited by journal 26 Aug, 2024 Editor invited by journal 22 Aug, 2024 Editor assigned by journal 19 Aug, 2024 Submission checks completed at journal 19 Aug, 2024 First submitted to journal 17 Aug, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4928901","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":351692688,"identity":"fb8a1d6c-06e9-49ba-849a-a67d8bfeb58a","order_by":0,"name":"Indrajeet Kumar","email":"data:image/png;base64,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","orcid":"","institution":"Centre For Development Studies","correspondingAuthor":true,"prefix":"","firstName":"Indrajeet","middleName":"","lastName":"Kumar","suffix":""}],"badges":[],"createdAt":"2024-08-17 09:01:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4928901/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4928901/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":64660802,"identity":"590d16ee-9f9f-44bd-a3a6-b0a52dbcf382","added_by":"auto","created_at":"2024-09-17 07:53:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":670880,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4928901/v1/37af4ce6-0335-4013-9525-2950dd786e2f.pdf"},{"id":64660798,"identity":"d2013863-e93a-45a7-a37b-f3b84daf6a33","added_by":"auto","created_at":"2024-09-17 07:53:07","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":20461,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-4928901/v1/c1ca088cdb4fc0103d64e7d4.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Preference for Public versus Private Medical Services in Poorer Regions of India?","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe emergence of the COVID-19 pandemic reiterated the importance of a robust public healthcare infrastructure. In a middle-income country as India, providing this infrastructure becomes paramount to serve the poor (Slater, 2018). For instance, in healthcare personnel, the country has 6 physicians and 13 nurses (or midwives) to serve every 100,000 population. This number is significantly lower than the global average of 13 physicians and 28 nurses. The scenario becomes so alarming when compared to Europe, with 32 physicians and 79 nurses. In this regard, the World Health Organisation (WHO) recommends that having lesser than 23 healthcare personnel to serve every 100,000 population can hinder the primary healthcare interventions, which can affect the realization of the Millennium Development Goals (MDGs).\u003ca href=\"#_ftn1\" name=\"_ftnref1\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e1\u003c/sup\u003e Thus, the scenario prompts- is India prepared to manage future pandemics and achieve health-related impending MDGs with this public healthcare infrastructure?\u003c/p\u003e\n\u003cp\u003eIndia spends one of the lowest of its GDP on public health services- allocating only 3.53 % in 2017.\u003ca href=\"#_ftn2\" name=\"_ftnref2\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e2\u003c/sup\u003e The need for responsive and effective health services intensified during the pandemic and later years. In the meantime, upsetting economic outlooks aggravated the scenario straining public investments in healthcare services from stressed government revenues. The increase in unemployment pushed millions of people into poverty giving limited scope for out-of-pocket expenditures. So, the COVID-19 pandemic weakened the public healthcare infrastructure and kicked off a cycle of increasing demand and decreasing the quality of services (Ray \u0026amp; Subramanian, 2020; Sengupta \u0026amp; Jha, 2020).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDuring the pandemic, Indians had mixed experiences with using public medical services.\u003ca href=\"#_ftn3\" name=\"_ftnref3\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e3\u003c/sup\u003e Kerala stood out with its robust public healthcare infrastructure and managed the pandemic better than other states in morbidity and mortality rates despite the first state to report COVID-19 in January 2020. Other Indian states such as Maharashtra, Madhya Pradesh, Delhi, and Uttar Pradesh recorded higher morbidity and mortality rates than Kerala. The scenario highlighted the role of public healthcare infrastructure in for pandemic management. The experience of using public or private medical services in times of need could influence people\u0026apos;s preferences of the same.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUnderstanding preferences for type of medical services in the pre-pandemic scenario can provide insights into its usage patterns. The prevailing narrative suggests that lack of quality care in public services delivery drives people to use private medical services (Das, Holla, Mohpal, \u0026amp; Muralidharan, 2016). So, a dilemma for public health policy and planning remains that are efforts of improving the quality of care in public service delivery encourage people to use the same? Or, is it effective to impart purchasing power through Conditional Cash Transfers (CCT) for those who cannot afford out-of-pocket private medical services? This study answers this dilemma by presenting evidence from a field survey in one of the most economically disadvantaged regions of India- Bihar. In particular, the study examines the factors inducing people\u0026rsquo;s preferences for public versus private medical services in the pre-pandemic context.\u0026nbsp;\u003c/p\u003e\n\u003cdiv id=\"ftn3\"\u003e\u003cbr\u003e\u003c/div\u003e"},{"header":"2. Medical Services in India","content":"\u003cp\u003eIn India, pricing of private medical services is contingent upon input market conditions and demand for it. Two crucial inputs are (i) the personnel- doctors, nurses, and paramedics, and (ii) the physical infrastructure- hospitals and clinics. The government\u0026apos;s regulation conditions of the private sector and the performance of public healthcare services are the other considerations. The demand for private services depends on financing sources formal or informal as well. Thus, both the demand and the supply-side factors govern access and quality of care in medical services usage (Bhat, 1999).\u003c/p\u003e\n\u003cp\u003eIndex for Sustainable Development Goal (SDG) 2020 places Bihar, Jharkhand, Assam, Rajasthan, Uttar Pradesh, and Chhattisgarh at the bottom among the states.\u003ca href=\"#_ftn1\" name=\"_ftnref1\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e4\u003c/sup\u003e One of the components contributing this ranking is health status of the people, which is ensured by access to public healthcare services. However, use of public versus private medical services follows a dichotomy. The National Family Health Survey (NFHS) 2015-16 suggest that during times of sickness, 51.4 % of Indian households opt for a private service provider, while 44.9 % choose a public sector. In private, private hospitals (18.6 %) and doctors or clinics (29.2 %) are the major providers of these services. While, in public sector, government or municipal hospitals (20.4 %) are the major, which is followed by CHC/rural hospital/block PHC (11 %) and PHC/additional PHC (8.9 %).\u003ca href=\"#_ftn2\" name=\"_ftnref2\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e5\u003c/sup\u003e So, the numbers indicate that a major share of the households in India preferred to use private medical services. Top of FormBottom of Form\u003c/p\u003e\n\u003cp\u003eThe use of medical services also differs across Indian states. In times of need, 76.2 % households from Bihar, one of the poorest states in the country, had to use private medical services (Supplementary Table 1).\u003ca href=\"#_ftn3\" name=\"_ftnref3\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e6\u003c/sup\u003e However, more than 50 % of households in Orissa, Himachal Pradesh, Jammu and Kashmir, Assam, Kerala, Rajasthan, and West Bengal used public medical services. The quality of care in government services deliver has been an issue in India (Mohanan, Hay, and Mor 2016). The problem is alarming in the low-income states. The lack of expected quality of care in public healthcare compel people with limited financial resources to use private medical services. Further, it involves debt financing sourced from informal sources, out-of-pocket expenditure, or dissaving. Thus, low-income people must spend a substantial share of their savings on healthcare expenses (Collins, Jonathan, Stuart, \u0026amp; Orlanda, 2009).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe NFHS 2015-16 suggests that in 48 % of cases, the poor quality of care in government health facility compel people to avoid. Other reasons for avoiding such services include the absence of facilities (44.6 %), long waiting times (40.9 %), inconvenient facility timings (26.4 %), and absence of healthcare personnel (14.8 %). In addition, nearly half of India\u0026apos;s people are either unsatisfied with the quality of care or travel distance.\u003ca href=\"#_ftn4\" name=\"_ftnref4\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e7\u003c/sup\u003e The disparities in the quality of care are particularly evident in Bihar. The highest 60 % in Jharkhand and 50 % each in Chhattisgarh, Karnataka, and West Bengal, people grieve the absence of government facility in the neighbourhood; notwithstanding perceive medical service of better quality in these states than Bihar. Only 46 % in Jharkhand, 50 % in Chhattisgarh, 40 % in Karnataka, and 35 % in West Bengal are concerned about the quality of care in government services and this share is 70 % in Bihar.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWest Bengal (35 %) and Odhissa (34.6 %) stands out with one of the lowest shares of people concerned about the quality of care in government services. This share for Bihar (59.6 %) and Uttar Pradesh (61.1%) is quite high than the national average. Moreover, 42.6 % and 47.7 % of people in these respective states disuse government services given the absence of facilities in the neighbourhood. This share of people is comparable or higher in West Bengal (49.6 %) and Odhissa (48.4 %). Therefore, with same or better access to government facility in proximity, Bihar, and Uttar Pradesh faces problem of quality of care (NFHS-4, p. 377).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTherefore, despite the inconvenience of facility timing, a reason for foregoing the government facility in Bihar, is comparable with Gujrat, Uttar Pradesh, Madhya Pradesh, and Maharashtra, people in these states perceive quality of care better than Bihar. Likewise, in absence of healthcare personnel, Jharkhand, Karnataka, Tamilnadu, and Telangana show similar pattern; however, these states ensure a better quality of care than Bihar. In other comparisons, long waiting times at medical facilities, Bihar with comparable problem than other states offer mediocre-quality care. For instance, 78 % of people in Chandigarh, 67 % in Delhi, 66 % in Punjab, and 59 % in Haryana are dissatisfied with the long waiting times, notwithstanding the perceived quality of care is better than in Bihar.\u003ca href=\"#_ftn5\" name=\"_ftnref5\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e8\u003c/sup\u003e\u0026nbsp; The reasons, three-fourths of the households (76 %) in Bihar rely on private medical services and a majority (60 %) using public facilities expresses dissatisfaction with the quality of care.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsidering options improve the situation, two scenarios emerge. The first is to enhance the quality of care in government services delivery and encourage people to use them. The second scenario is to supplement the out-of-pocket expenditure with a \u0026apos;CCT\u0026apos; for make private medical services to be affordable. The second scenario ensures people\u0026apos;s preferences of using public or private medical services. This study aims to explore the ground realities for second scenario by analysing people\u0026rsquo;s preferences and the associated reasons through a field survey in Bihar.\u0026nbsp;\u003c/p\u003e\n\u003cdiv id=\"ftn5\"\u003e\u003cbr\u003e\u003c/div\u003e"},{"header":"3. The Field Survey","content":"\u003cp\u003eImproved health endowments ensure increasing income and reducing poverty and so relationship of economic growth bringing human development is robust (Ranis, 2004). Bihar is the poorest in per capita income and the Human Development Indicators (HDI).\u003ca href=\"#_ftn1\" name=\"_ftnref1\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e9\u003c/sup\u003e The state stands at the bottom in HDI (Planning Commission, 2011).\u003ca href=\"#_ftn2\" name=\"_ftnref2\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e10\u003c/sup\u003e\u0026nbsp; The Patna district in Bihar is better than other districts in per capita income and HDI.\u003ca href=\"#_ftn3\" name=\"_ftnref3\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e11\u003c/sup\u003e In Bihar, 40.1 % of rural and 50.8 % of urban population are below the poverty line (Rangarajan et al., 2014). The state has about 37.7 million poor people, the second highest after Uttar Pradesh. The continuing poverty demands interventions in access to medical services to ensure a healthy workforce increasing households\u0026apos; income.\u003c/p\u003e\n\u003cp\u003ePatna district comprises the capital region with the highest per capita income in the state. In 2011-12 (2004-05 prices), the district had a per capita income of ₹ 63,063\u0026nbsp;(Government of Bihar, 2019). The region is also the most urbanised place (43.07 %) in the least urbanised state (11.3 %)\u0026nbsp;(Endow, 2017; Bhagat, 2011). The district also outperforms in educational attainment at a 70.68 % literacy rate for the state\u0026apos;s literacy rate at 61.80 %\u0026nbsp;(Census of India, 2011). The district is the best in a modest-performing state in urbanisation, per capita income, and literacy. Three motives the district as a survey site: (i) urbanisation determines the convenience of medical services, (ii) income influences the preference for using the medical services- public or private, and (iii) education helps in awareness of the use or convenience of medical services. So, the place qualifies as a survey site to study people\u0026apos;s preferences of using public versus private medical services.\u003c/p\u003e\n\u003cp\u003eTable 1 presents the survey description for selecting four Grama Panchayats (GP) based on two criteria.\u003ca href=\"#_ftn4\" name=\"_ftnref4\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e12\u003c/sup\u003e The first is the share of the Scheduled Castes (SC) population in a GP. One of them is with the highest and the other is with the lowest SC population.\u003ca href=\"#_ftn5\" name=\"_ftnref5\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e13\u003c/sup\u003e The rationale for selecting these two GPs is to study people\u0026apos;s preference for public versus private medical services in a marginalised social and economic situations.\u003ca href=\"#_ftn6\" name=\"_ftnref6\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e14\u003c/sup\u003e For this, we used stratified random sampling to select GPs using Population Census Abstract of the Census of India 2011. First, we selected two sets of five Blocks in the Patna district of the highest and the lowest SC populations. Then, we randomly selected one Block from each of these two sets. Later, we selected five GPs from each of these two Blocks- for one set of the highest SC population and the other of the lowest SC population. Finally, we randomly selected one GP from each of these two sets of GPs.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMedical services are clustered in urban areas and people from far-off places incur extra costs to use them.\u003ca href=\"#_ftn7\" name=\"_ftnref7\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e15\u003c/sup\u003e The urban settlements are a proxy for better access to medical services. So, the second criterion of GP selection is the remoteness or nearness of a GP from an urban place. Selecting two GPs based on urbanisation is to examine the preference given the health care infrastructure in the neighbourhood. The decision to select a GPs was based on visiting them by public transport. To better assess public transport facility and access to medical services at the places we used Google Maps. Hence, we interviewed 200 households from four GPs and ensured to visit each Ward in a GP.\u003ca href=\"#_ftn8\" name=\"_ftnref8\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e16\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1: Selection of Grama Panchayats (GP) and households from Patna district in Bihar, India.\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\" valign=\"top\"\u003e\n \u003cp\u003eSelection criterion of a GP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\" valign=\"top\"\u003e\n \u003cp\u003eBlocks Name\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003eGP Name\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.510204081632654%\" valign=\"top\"\u003e\n \u003cp\u003eHouseholds\u0026rsquo; Number\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\" valign=\"top\"\u003e\n \u003cp\u003eHighest SC population\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\" valign=\"top\"\u003e\n \u003cp\u003ePunpun\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003eDumri\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.510204081632654%\" valign=\"top\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\" valign=\"top\"\u003e\n \u003cp\u003eLeast SC population\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\" valign=\"top\"\u003e\n \u003cp\u003ePatna Sadar\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003eWest Digha Mainpura\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.510204081632654%\" valign=\"top\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\" valign=\"top\"\u003e\n \u003cp\u003eNear city\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\" valign=\"top\"\u003e\n \u003cp\u003ePhulwari\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003eKurthawal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.510204081632654%\" valign=\"top\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\" valign=\"top\"\u003e\n \u003cp\u003eFar from the city\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\" valign=\"top\"\u003e\n \u003cp\u003eMashaudhi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003eBara\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.510204081632654%\" valign=\"top\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\" valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.510204081632654%\" valign=\"top\"\u003e\n \u003cp\u003e200\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eSource: authors\u0026apos; description based on the survey design; Scheduled Caste (SC).\u003c/p\u003e"},{"header":"4. Qualitative Insights","content":"\u003cp\u003eThis section discusses the preference for using public versus private medical services with the associated reasons for the same.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003e4.1 Preference for Public versus Private Medical Services\u003c/h3\u003e\n\u003cp\u003eWe asked the respondents to choose between using public versus private medical services in times of need when the latter is financed through a conditional cash transfer.\u003ca href=\"#_ftn1\" name=\"_ftnref1\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e17\u003c/sup\u003e Table 2 presents the preference and associated reasons (Supplementary Table 2).\u003ca href=\"#_ftn2\" name=\"_ftnref2\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e18\u003c/sup\u003e\u0026nbsp; The majority, two-thirds (60.54 %) of respondents, preferred using public medical services over private (29.73 %). In depth inquiry with the respondents suggested that the relying on preference alone was inadequate to understand the associated reasons. For, most people favoured using public services despite complaining about the quality of services at the nearby government hospital. Respondents stresses that public services often disserve them when it required the most. So, what encourages people to opt for such services when asked about the preference? The reason was- unaffordable private medical services compel people to use public services. Other reasons with associated preference for public and private services are (i) government services are satisfactory, (ii) using private services (though CCT) gives a choice of treatment, and (iii) both (government and private) services have one or the other issues.\u003c/p\u003e\n\u003cp\u003eIn-depth inquiry with respondents reveals that experiences of using medical services outlined the preferences. For instance, those saying public services are satisfactory (56 %) also had to use in times of need.\u003ca href=\"#_ftn3\" name=\"_ftnref3\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e19\u003c/sup\u003e\u0026nbsp; Similarly, those opting for private medical services (22 %) had to use the same given the unsatisfactory experience of public services. This group of people wanted to exercise their \u0026apos;choice of treatment\u0026apos; through CCT. The group opting public services complained about the cost of medicines and diagnostic tests if purchased or done at private medicine shops or clinics. Households expecting conditional cash for spending on private medical services assume that it would complement their out-of-pocket expenses. Unaffordable medicines and diagnostic tests concerned both public and private medical care users (Wankhar, 2016). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2: Households\u0026rsquo; preference for using type of medical services and associated reasons (in %).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"629\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.793650793650794%\" valign=\"top\"\u003e\n \u003cp\u003ePreference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"79.2063492063492%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eReasons\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.82670906200318%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.488076311605724%\" valign=\"top\"\u003e\n \u003cp\u003eGovernment services are satisfactory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.488076311605724%\" valign=\"top\"\u003e\n \u003cp\u003eUsing private services (through CCT) gives\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ea choice\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.893481717011127%\" valign=\"top\"\u003e\n \u003cp\u003eBoth (government \u0026amp; private) services have issues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.9697933227345%\" valign=\"top\"\u003e\n \u003cp\u003eOther reasons\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.333863275039745%\" valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.82670906200318%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eGovernment services\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.488076311605724%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e56\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.488076311605724%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e6\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.893481717011127%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e34\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.9697933227345%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.333863275039745%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e100\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.08835341365462%\" valign=\"top\"\u003e\n \u003cp\u003e94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.08835341365462%\" valign=\"top\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.91566265060241%\" valign=\"top\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.855421686746988%\" valign=\"top\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.052208835341366%\" valign=\"top\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.82670906200318%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003ePrivate services\u003c/p\u003e\n \u003cp\u003e(though CCT)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.488076311605724%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e5\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.488076311605724%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e56\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.893481717011127%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e33\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.9697933227345%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e5\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.333863275039745%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e100\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.08835341365462%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.08835341365462%\" valign=\"top\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.91566265060241%\" valign=\"top\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.855421686746988%\" valign=\"top\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.052208835341366%\" valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.82670906200318%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eIndifferent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.488076311605724%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e6\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.488076311605724%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e17\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.893481717011127%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e11\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.9697933227345%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e67\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.333863275039745%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e100\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.08835341365462%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.08835341365462%\" valign=\"top\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.91566265060241%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.855421686746988%\" valign=\"top\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.052208835341366%\" valign=\"top\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.82670906200318%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.488076311605724%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e36\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.488076311605724%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e22\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.893481717011127%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e31\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.9697933227345%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e10\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.333863275039745%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e100\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.08835341365462%\" valign=\"top\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.08835341365462%\" valign=\"top\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.91566265060241%\" valign=\"top\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.855421686746988%\" valign=\"top\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.052208835341366%\" valign=\"top\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSource: author\u0026apos;s calculation from field survey data. CCT: Conditional Cash Transfer.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDuring the survey, people were unhappy with both category of medical services (Bennett, 1992; Bhat, 1993; Mathiyazhagan, 2003; Nagla, 2013). For, 34 % of households preferring public services and 33 % preferring private services also criticised the same for one or other reasons. Conversation with respondents suggest that- often, provision of public services failed people\u0026apos;s expectations resulting in frustration and annoyance. People going to public services facilities, in want of unaffordable private services, appealed to improve the quality of care. The infrastructure inadequacy and lacking performance auditing were the major concerns in public medical service delivery. Lack of specialised services in geriatric, paediatric, and gynaecology concerned public services (Chatterjee et al., 2019). The respondents also whine about the unsuitable timing of service delivery and unfavourable attitude of personnel at government hospitals.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePeople from lower social and economic groups mentioned the instances of subjective discrimination and corruption in government services delivery. Respondents share that people\u0026apos;s social, economic, and political networks influence the quality-of-services received. For instance, lower social and economic groups people (SC- Dalits and Mahadalits) mentioned that medical personnel (doctors, nurses, and paramedical staffs) avoided touching the patients during the medical examination and make them sit-down or lie-down on the floor. The scenario suggested medical services, both at public or private, remained hostile for these groups. The reason available public services failed in quality, while the private were unaffordable. So, the frequent opinion of respondents was to improve the quality of public services. In this regard, one respondent said \u0026quot;money cannot buy doctors if doctors are unavailable in the neighbourhood, while CCTs would be insufficient to buy medical services at private \u0026quot;.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003e4.2 Rural-urban Divide\u003c/h3\u003e\n\u003cp\u003eThe rural-urban dichotomy of access and quality of medical services remains a concern in India. In our survey too, households from rural and far-off areas preferred using public services: two-thirds of households from Bara Panchayat using government hospitals in times of need (Table 3). However, public medical services were unpopular in the urban and semi-urban areas. Half\u0026nbsp;of the housheolds from W-D Mainpura (an urban place) and Dumri (a semi-urban) preferred using private hospitals.\u003c/p\u003e\n\u003cp\u003eInquiry with respondents suggested that rural and far-off places lacked private medical services; and if \u0026nbsp;it was, insufficent cash hindered from using. In private medical services, quacks were rampant in villages, who were unqualified and ill-equipped to manage the mdical emergencies resulting people using government hospitals despite being unsatisfactory.\u003ca href=\"#_ftn4\" name=\"_ftnref4\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e20\u003c/sup\u003e The private medical services in nearby cities were unaffordable due to transportation expenses. Medical ambulance was a luxury in rural areas and only well-off people can afford it through payments or social and political networks with government hospitals. The Block and District Hospitals, the nearby points of accessing public medical services disappointed patients requiring specialised care. The scenario was people suffering from chronic health conditions but travel and medical cost preventing them from going to nearest Block or District Hospital. Older people suffered the most and had postponed their treatment or routine visits and continue with the quacks in the neighbourhood.\u003c/p\u003e\n\u003cp\u003eSurvey reveal that private medical facilities in urban and semi-urban areas had problems. Households experiencing poverty accessed the services through debt financing or eroding their savings.\u0026nbsp;Interaction\u0026nbsp;with respondents suggested that it was also encouraging people to migrate to urban places. Besides education and livelihood opportunities, convenience of medical services was one of major attractions of urban places. Nevertheless, households across regions were unsatisfied citing the quality of care in government and the high cost in private medical services.\u003c/p\u003e\n\u003cp\u003eWe also asked respondents- why they choose certain services across the regions (Table 3). One respondent from a rural and far-off GP Bara said, \u0026quot;In medical emergencies, we have no option but to go to the nearby government hospitals\u0026quot;. The preference for such services is 67 % in this GP. In contrast, one respondent from an urban Panchayat considered public medical services insufficient during emergencies, quoting, \u0026quot;it lacks quality of care\u0026quot;. The private medical services, which are often absent in rural areas, were appreciated. In urban and semi-urban areas, where both the services were available, households criticised the both. For instance, 56 % households from Dumri (a semi-urban region) and 42 % from WD Mainpura (an urban region) complained using both facilities. Substandard public medical services compelled people to use private services. Households assert improving government services given the prohibitive cost in private. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3: \u0026nbsp;Preference and reasons for using medical services across Grama Panchayats (in %).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"107%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.26530612244898%\" valign=\"top\"\u003e\n \u003cp\u003eGrame Panchayats\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.571428571428573%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003ePreference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"58.16326530612245%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eReasons\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.68421052631579%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.315789473684211%\" valign=\"top\"\u003e\n \u003cp\u003eGovernment\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.315789473684211%\" valign=\"top\"\u003e\n \u003cp\u003ePrivate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\"\u003e\n \u003cp\u003eIndifferent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.68421052631579%\" valign=\"top\"\u003e\n \u003cp\u003eGovernment services\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eare satisfactory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.894736842105264%\" valign=\"top\"\u003e\n \u003cp\u003eUsing private services (through CCT) gives\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ea choice\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.789473684210526%\" valign=\"top\"\u003e\n \u003cp\u003eBoth (government \u0026amp; private)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eservices have issues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.315789473684211%\" valign=\"top\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.68421052631579%\" rowspan=\"2\"\u003e\n \u003cp\u003eBara\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.315789473684211%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e69\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.315789473684211%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e10\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e20\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e100\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.68421052631579%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e67\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.894736842105264%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e10\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.789473684210526%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e4\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.315789473684211%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e18\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e100\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.317073170731708%\" valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.317073170731708%\" valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.975609756097562%\" valign=\"top\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.097560975609756%\" valign=\"top\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\" valign=\"top\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.73170731707317%\" valign=\"top\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.317073170731708%\" valign=\"top\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.097560975609756%\" valign=\"top\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.68421052631579%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eDumri\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.315789473684211%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e56\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.315789473684211%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e41\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e100\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.68421052631579%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.894736842105264%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e38\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.789473684210526%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e56\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.315789473684211%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e100\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.317073170731708%\" valign=\"top\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.317073170731708%\" valign=\"top\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.975609756097562%\" valign=\"top\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.097560975609756%\" valign=\"top\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.73170731707317%\" valign=\"top\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\" valign=\"top\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.317073170731708%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.097560975609756%\" valign=\"top\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.68421052631579%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eKurthawal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.315789473684211%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e58\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.315789473684211%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e35\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e7\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e100\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.68421052631579%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e40\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.894736842105264%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e20\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.789473684210526%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e29\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.315789473684211%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e11\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e100\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.317073170731708%\" valign=\"top\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.317073170731708%\" valign=\"top\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.975609756097562%\" valign=\"top\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.097560975609756%\" valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\" valign=\"top\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.73170731707317%\" valign=\"top\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\" valign=\"top\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.317073170731708%\" valign=\"top\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.097560975609756%\" valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.68421052631579%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eW-D-Mainpura\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.315789473684211%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e57\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.315789473684211%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e36\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e7\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e100\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.68421052631579%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e26\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.894736842105264%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e24\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.789473684210526%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e43\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.315789473684211%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e7\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e100\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.317073170731708%\" valign=\"top\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.317073170731708%\" valign=\"top\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.975609756097562%\" valign=\"top\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.097560975609756%\" valign=\"top\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\" valign=\"top\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.73170731707317%\" valign=\"top\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\" valign=\"top\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.317073170731708%\" valign=\"top\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.097560975609756%\" valign=\"top\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.68421052631579%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.315789473684211%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e61\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.315789473684211%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e30\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e10\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e100\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.68421052631579%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e36\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.894736842105264%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e22\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.789473684210526%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e31\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.315789473684211%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e10\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e100\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.317073170731708%\" valign=\"top\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.317073170731708%\" valign=\"top\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.975609756097562%\" valign=\"top\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.097560975609756%\" valign=\"top\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.853658536585366%\" valign=\"top\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.73170731707317%\" valign=\"top\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\" valign=\"top\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.317073170731708%\" valign=\"top\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.097560975609756%\" valign=\"top\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSource: Authors\u0026apos; calculation using field survey data. CCT: Conditional Cash Transfer.\u003c/p\u003e"},{"header":"5. Preference in a Multivariate Context","content":"\u003cp\u003eThe discussions until suggest that multiple factors affecting the preference for public versus private medical services by the surveyed households. This section analyses the preference in a multivariate context using logistic regression models aiming to identify the factors associated with the preferences.\u003csup\u003e21\u003c/sup\u003eThe dependent variable is a respondent\u0026rsquo;s preference for public (=\u0026thinsp;1) versus private (=\u0026thinsp;0) medical services and if it is for private it to be financed by a CCT. The logistic regressions have the following functional form:\u003c/p\u003e\n\u003cp\u003eY\u003csub\u003ei\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;\u0026alpha;\u0026thinsp;+\u0026thinsp;\u0026beta;\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003ei\u003c/strong\u003e\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u0026micro;.\u003c/p\u003e\n\u003cp\u003eWhere, Y\u003csub\u003ei\u003c/sub\u003e is the preference, and vector \u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003ei\u003c/strong\u003e\u003c/sub\u003e represent a set of explanatory variables. Thus, vector \u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003ei\u003c/sub\u003e takes the possible factors explaining the preference for using public or private medical services.\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e5.1. Explanatory Variables\u003c/h2\u003e\n \u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e presents the summary statistics of the variables taken for the logistic regressions. Based on insights from the field survey, the explanatory variables are regional, household, and respondent characteristics. In regional, GPs are the proxies for distance from the city and so the convenience of medical services. In addition, we observe a village or hamlet in these GPs, which are in local parlance called Panchayat\u0026rsquo;s Main Village (PMV). Compared to other villages in a GP, residents from the PMV were well-off in social and economic status and had better transportation connectively. We also observed residential segregations of castes and classes in PMV. Panchayat Bhawan and Panchayat\u0026rsquo;s Head and Secretary are from here, while none of the SC households.\u003c/p\u003e\n \u003cp\u003eUnderstanding the social hierarchy and reality, we have grouped surveyed households into General (GEN), Backward Classes (BC), Extremely Backward Classes (EBC), and Scheduled Castes (SC).\u003csup\u003e22\u003c/sup\u003e Similarly, health expenditure is infinitely non-increasing with increase in income (convexity of health expenditure), we have combined GEN and BC social groups.\u003csup\u003e23\u003c/sup\u003e EBCs and SCs are Bihar\u0026apos;s most economically and socially marginalised groups. The Below Poverty Line (BPL) ration cards are a proxy for economic status. The homestead land ownership is an indicator of improved living space are grouped into owned land, government land, and rent. One related indicator is the housing type measured by an index based on the floor, wall, and roof structure and grouped into pucca, semi-pucca, and kaccha houses. The average years of male members\u0026apos; education in a household account for awareness of available medical services. The proportion of self-employed in agriculture or non-agriculture and regular wage or salary earners jobs in a household reflects the ability of out-of-pocket expenditure on health.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSummary statistics of variables used in the probit model.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003emin\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMax\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreferences (Dependent Variable)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.671\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.471\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGrama Panchayats\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.447\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePanchayat Main Village\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.474\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.886\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.810\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBelow Poverty Line (BPL) Card\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.599\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.492\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHouse Ownership\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.437\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.909\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHouse Type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.591\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProportion of Self-Employed or Regular Wage or Salary Earner (PSRWSE)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProportion of Children (\u0026lt;\u0026thinsp;15 years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.714\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProportion of Old-age People (\u0026lt;\u0026thinsp;60 years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJAM (bank account, Aadhaar Card, and Mobile Phone)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.719\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.451\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedical Expenditure (in last year, in log)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.203\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedical to Food Expenditure Share (in log)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.802\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.399\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale Respondent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.509\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.501\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRespondents\u0026rsquo; Education (in years of schooling)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReasons for Preference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.856\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.940\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRastriya Swasthya Bima Yojana\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJanani Suraksha Yojana\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0898\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAverage years of Male Education (AYME)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.948\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.303\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(PSRWSE) * (AYME)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.599\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Grama Panchayats) * (Reasons for Preference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.665\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.821\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003eSource: author\u0026apos;s calculation using field survey data.\u003c/p\u003e\n \u003cp\u003eHouseholds\u0026apos; absolute and relative financial burden due to medical expenses (in the last year) is factored in by (i) total medical expenses, and (ii) a share of medical to food expenses. The increased proportion of children below 15 years and elderly of 60 years or above require increased medical attention and so medical expenditure. In addition, accessing CCT programmes requires an active bank account, an Aadhaar Number, and a mobile phone. So, we have introduced a variable JAM as an explanatory variable.\u003csup\u003e24\u003c/sup\u003e To account for households\u0026apos; experience in healthcare programmes, we have introduced participation in the Janani Suraksha Yojana (JSY) and possession of Rashtriya Swasth Bima Yojana (RSBY) cards. In addition, we also introduced reasons for preferring public versus private medical services narrated by respondents.\u003c/p\u003e\n \u003cp\u003eThere are two interaction terms. First, it is between the proportion of self-employed, regular wage, or salary earners and average years of male education since educated males often work in these jobs. Second, it is between GPs and reasons for preferring public versus private medical services. Field inquiry also suggests that reasons are often associated with the location of a GP. Moreover, gender and years of education are respondents\u0026apos; characteristics.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e5.2. Results and Discussion\u003c/h2\u003e\n \u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e presents the results suggesting that urban and semi-urban places (Dumri \u0026amp; Kurthawal), as against rural and far-off (Bara), are more likely to prefer private medical services (Model 1). The reason is- urban and semi-urban places have access to private medical services. Similarly, increasing male members\u0026apos; education in a household is associated with using private services. These housheolds know the compromising quality of care at public facilities. Though, educated respondents do acknowledge the crucial role of public medical services and suggest that it is to be a prerequisite to ensure better public health services. The reason, increasing medical to food-expenditure share associating with preferring public services.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eresults of logit regressions models of preference for public medical service (=\u0026thinsp;1) versus private medical services through CCTs (=\u0026thinsp;0).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eModel 1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eModel 2\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGrama Panchayats (base: Bara, rural or far-flung)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDumri\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.153***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.147\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.415)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.641)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKurthawal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.135***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.953\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.407)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.843)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eW-D Mainpura\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.753\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.702\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.494)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(1.244)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePanchayat Main Village (base: other villages)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.351\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.348\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.261)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.286)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHouse Ownership (base: in own land)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIn government land\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.268\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.443\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.363)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.528)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIn rented\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.442\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.453\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.427)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.524)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJAM (Bank Account, Aadhaar Card, and Mobile Phone) (base: missing at least one of the components of JAM in household)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.266)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.343)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial Group (base: General /Backward Classes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSC (Dalit/Mahadalit)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.129\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.347)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.435)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExtremely Backward Classes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.340\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.294)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.329)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBPL Card (base: non-BPL card)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.341\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.123\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.268)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.288)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHouse Type (base: Kaccha)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSemi-pucca\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.673\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.467)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.810)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePucca\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.729\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.567)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.926)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedical Expenditure (in last year, in the log)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.056)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.061)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProportion of Children (\u0026lt;\u0026thinsp;15 years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.443\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.058\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.671)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.774)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAverage years of Male Education (AYME) in a Household\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.102*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.057)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.055)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProportion of Old-age People (\u0026gt;\u0026thinsp;60 years) in a Household\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.803\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.477\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.641)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.663)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedical to Food Expenditure Share (in log)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.128*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.077)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.086)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProportion of Self-Employed or Regular Wage or Salary Earners (PSERWSE) in a Household\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.355\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.896)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.935)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(PSERWSE) * (AYME)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.170)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.138)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale Respondent (base: male respondent)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.521*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.250)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.287)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRespondents\u0026rsquo; Education (in years of schooling)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.065**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.033)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.037)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePossession of RSBY Cards (base: No RSBY Card)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.289\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.508*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.249)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.287)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBeneficiary oof JSY (base: Non-beneficiary of JSY)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.846*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.446)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.478)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReasons for Preference (base: other reasons)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGovernment Services are Satisfactory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.468**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.699)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUsing Private Services (through CCT) Gives a Choice\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.963*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(1.060)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBoth (Government \u0026amp; Private) Services have Issues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.789\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(1.347)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Grama Panchayat) * (Reasons for Preference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.118\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.142)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConstant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.359*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.430\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.779)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(1.347)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eObservations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003eSource: author\u0026apos;s calculation using field survey data.\u003c/p\u003e\n \u003cp\u003eRobust standard errors in parentheses: *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.1\u003c/p\u003e\n \u003cp\u003eThe results get changed if reasons for preference is introduced (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e, Model 2). Now, female respondents as opposed to males are more likely to prefer using public medical services supporting the insights by women during the field inquiry. The JSY, a CCT programme incentivising institutional delivery, were popular among women. The programme beneficiaries praised the initiative but not without complaining about the inconvenience of ambulance services required to transport expecting mothers to nearby government hospitals. That usually resulted in assocaited costs of escorting the expecting mothers to the government hospitals the requirement to claim the benefits (Carvalho \u0026amp; Rokicki, \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e; Ghosh, S., \u0026amp; Husain, \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). The mothers also moan about the delays in cash receipt through DBT.\u003c/p\u003e\n \u003cp\u003eContrarily, households possessing RSBY cards, for a CCT programme, are more likely to prefer private hospitals, reflecting the programme\u0026apos;s feature that a beneficiary can use public or private medical services and reimburse medical expenditure to a limit. However, talking with the respondents revealed lacking awareness most households with RSBY cards unused this service during the recent medical emergency. Lastly, respoendents who said that public services are satisfactory than those who highlighted reasons to avoid them are more likely to prefer public services as well. Conversely, people favouring private medical services through a CCT are more likely to prefer private services too. So, the reasons associated with the preferences are consistent in the multivariate preference model.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eThis study investigates households' preferences for public versus private medical services examining qualitative and quantitative evidence from a field survey in Bihar, India. The results indicate that unreliable public medical services compel individuals to use private services. The delivery of medical services also varies across regions and for social groups. In remote and rural areas, underprivileged groups face an absence of dependable medical services. The substandard quality of care in public facilities and exorbitant costs is levied by private providers. Thus, using medical services in needed poses a dual challenge. The reason, private medical services is popular among those with financial means. While, those lacking must depend on unsatisfactory public services that are far-away and incurring travel expenses. The inconvenience of timing of services and the absence of quality of care due to understaffing and personnel absenteeism exacerbates the propblems in the public healthcare system.\u003c/p\u003e \u003cp\u003eEmbracing and implementing CCTs as a substitute for out-of-pocket expenditures on private medical services is unworkable given the absence of private services in rural and remote areas. In rural settings, inadequate public medical services and financially inaccessible private healthcare compounds the problem of medical care. Considering local-level factors, the households' inclination towards public or private in a multivariate scenario indicates a association between higher medical expenditure and a preference for public services. Similarly, a favourable experience with the Janani Suraksha Yojana correlates with simialr preference. The reason, female respondents exhibit more inclination towards public services. Likewise, an increase in respondents' education is linked to such preference too.\u003c/p\u003e \u003cp\u003eThe logistic regression results indicate that individuals in urban and semi-urban locations and better-educated males are more inclined towards using private medical services. Consequently, those using private services or expressing a preference for private over public services are more likely to choose private healthcare when presented with a choice between the two. In this regard, the COVID-19 pandemic highlight the need for a responsive and dependable public healthcare system. So, enhancing the public healthcare system without expanding coverage or providing financial means through CCTs to those unafford private services would be insufficient. The healthcare demand necessitates a synergy and complementarity between public and private capacities. The past years\u0026rsquo; COVID-19 health policy, combining testing, treatment, and vaccination demonstrates the effectiveness of such synergy and complementarity in the two sectors. Relying on medical insurance- a panacea for the limited supply and compromised quality of public services, is also inadequate. The pandemic experience highlights the importance of a robust public healthcare infrastructure, when regulated and complemented, can address healthcare needs including those also met by private services.\u003c/p\u003e \u003cp\u003eFinally, while the study employs a reasonable research design, it encounters two limitations. Firstly, differences exist in quality and extent of public health care provisioning among Indian states, exemplified by the disparity between Kerala and Bihar. Consequently, conducting a pan-India inquiry could unveil further nuances. Secondly, we relies on household information- the demand-side stakeholders, so, a similar study involving supply-side stakeholders- medical personnel, insurance companies, and policymakers- can complement this research by understanding input costs.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003e\u003cstrong\u003e\u0026nbsp;\u003cstrong\u003eEthical Approval and Consent to Participate\u003c/strong\u003e:\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThis study was conducted in accordance with the ethical guidelines of Ethics Committee at the Centre for Development Studies, Thiruvananthapuram. Informed consents were obtained from all participants. The participants were fully informed about the purpose of the research, their right to withdraw at any time, and the measures taken to ensure confidentiality and anonymity.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003enot applicable\u003c/p\u003e\n\u003ch2\u003eFunding:\u003c/h2\u003e\n\u003cp\u003eThis research was not supported by any funding.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eIndrajeet Kumar conducted the field survey, did data analysis by preparing tables and econometric models, wrote the manuscript, and reviewed the manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eAcknowledgement: I am grateful to Dr Upasak Das, Presidential Fellow in Economics of Poverty Reduction at Global Development Institute, University of Manchester, United Kingdom for his help in survey design. In addition, I thank Professor Udaya S Mishra at International Institute for Population Sciences, Mumbai, India for guiding on analysis plan. I am also indebted to all the respondents who participated in this research.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials:\u003c/h2\u003e\n\u003cp\u003eThe data and materials used in this study are available upon request to the author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBennett, S. (1992). Promoting the private sector: a review of developing country trends. \u003cem\u003eHealth Policy and Planning\u003c/em\u003e, \u003cem\u003e7\u003c/em\u003e(2), 97-110.\u003c/li\u003e\n \u003cli\u003eBhagat, R. (2011). Emerging pattern of urbanisation in India. \u003cem\u003eEconomic and political weekly\u003c/em\u003e, 10-12.\u003c/li\u003e\n \u003cli\u003eCensus of India. (2011). \u003cem\u003eDistrict Census Handbook Patna, SERIES-11, PART XII-A.\u003c/em\u003e Directorate of Census Operations, Bihar.\u003c/li\u003e\n \u003cli\u003eEndow, T. (July 2017). \u003cem\u003eUrban development and rural-urban linkages in six towns in Bihar, C-89113-INB-1.\u003c/em\u003e Final report, International Growth Centre.\u003c/li\u003e\n \u003cli\u003eMohanan, M., Hay, K., \u0026amp; Mor, N. (2016). Quality of health care in India: challenges, priorities, and the road ahead. \u003cem\u003eHealth Affairs\u003c/em\u003e, 35(10), 1753-1758.\u003c/li\u003e\n \u003cli\u003eRanis, G. (2004). Human development and economic growth. \u003cem\u003eAvailable at SSRN 551662\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003eRay, D., \u0026amp; Subramanian, S. (2020). India\u0026apos;s lockdown: an interim report. \u003cem\u003eIndian economic review\u003c/em\u003e, \u003cem\u003e55\u003c/em\u003e(1), 31-79.\u003c/li\u003e\n \u003cli\u003eSengupta, S., \u0026amp; Jha, M. K. (2020). Social policy, COVID-19 and impoverished migrants: challenges and prospects in locked down India. \u003cem\u003eThe International Journal of Community and Social Development\u003c/em\u003e, 2(2), 152-172.\u003c/li\u003e\n \u003cli\u003eSlater, J. (2018). India is no longer home to the largest number of poor people in the world. Nigeria is. \u003cem\u003eThe Washington Post\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003eBhat, R. (1993). The private/public mix in health care in India. Health Policy and Planning, 8(1), 43\u0026ndash;56. https://doi.org/10.1093/heapol/8.1.43\u003c/li\u003e\n \u003cli\u003eBhat, R. (1999). Characteristics of Private Medical Practice in India: A Provider Perspective. Health Policy and Planning, 14(1), 26\u0026ndash;37. https://doi.org/10.1093/heapol/14.1.26\u003c/li\u003e\n \u003cli\u003eCarvalho, N., \u0026amp; Rokicki, S. (2019). The Impact of India\u0026apos;s Janani Suraksha Yojana Conditional Cash Transfer Programme: A Replication Study. The Journal of Development Studies, 55(5), 989\u0026ndash;1006. https://doi.org/10.1080/00220388.2018.1506578\u003c/li\u003e\n \u003cli\u003eChatterjee, C., Nayak, N. C., Mahakud, J., \u0026amp; Chatterjee, S. C. (2019). Factors affecting the choice of health care utilisation between private and public services among the elderly population in India. International Journal of Health Planning and Management, 34(1), e736\u0026ndash;e751. https://doi.org/10.1002/hpm.2686\u003c/li\u003e\n \u003cli\u003eDas, J., Holla, A., Mohpal, A., \u0026amp; Muralidharan, K. (2016). Quality and accountability in health care delivery: Audit-study evidence from primary care in India. American Economic Review, 106(12), 3765\u0026ndash;3799. https://doi.org/10.1257/aer.20151138\u003c/li\u003e\n \u003cli\u003eGhosh, S., \u0026amp; Husain, Z. (2019). Has the National Health Mission Improved Utilisation of Maternal Healthcare Services in Bihar? Economic \u0026amp; Political Weekly, 54(31), 44\u0026ndash;51. Retrieved from https://www.epw.in/journal/2019/31/special-articles/has-national-health-mission-improved-utilisation.html\u003c/li\u003e\n \u003cli\u003eGovernment of Bihar. (2019). Bihar Economic Survey 2018-19. Patna: Finance Department. Retrieved from http://finance.bih.nic.in/Reports.htm\u003c/li\u003e\n \u003cli\u003eMathiyazhagan, M. K. (2003). People\u0026apos;s Choice of Health Care Provider: Policy Options for Rural Karnataka in India. Journal of Health Management, 5(1), 111\u0026ndash;137. https://doi.org/10.1177/097206340300500106\u003c/li\u003e\n \u003cli\u003eNagla, M. (2013). Privatisation of health care in India: Emerging issues and concerns. Indian Journal of Public Health Research and Development, 4(4), 118\u0026ndash;122. https://doi.org/10.5958/j.0976-5506.4.4.155\u003c/li\u003e\n \u003cli\u003ePlanning Commission. (2011). India Human Development Report, Towards Social Inclusion. Retrieved from https://econpapers.repec.org/paper/esswpaper/id_3a6740.htm\u003c/li\u003e\n \u003cli\u003eRangarajan, C., Mahendra Dev, S., Sundaram, K., Vyas, M., \u0026amp; Datta, K. L. (2014). Report of the expert group to review the methodology for measurement of poverty. New Delhi: Planning Commission, Government of India. Retrieved from http://planningcommission.gov.in/reports/genrep/annrep.php?Repts=b_annrep.htm\u003c/li\u003e\n \u003cli\u003eWankhar, D. L. (2016). Affordability of Healthcare in the Eight North Eastern States of India. Indian Journal of Public Health Research \u0026amp; Development, 7(3), 165. https://doi.org/10.5958/0976-5506.2016.00150.9\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Footnotes","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e See: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/whosis/whostat/EN_WHS09_Table6.pdf\u003c/span\u003e\u003cspan address=\"https://www.who.int/whosis/whostat/EN_WHS09_Table6.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e See: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://apps.who.int/nha/database/country_profile/Index/en\u003c/span\u003e\u003cspan address=\"https://apps.who.int/nha/database/country_profile/Index/en\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e See: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7423401/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7423401/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e See: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://sdgindiaindex.niti.gov.in/#/ranking\u003c/span\u003e\u003cspan address=\"https://sdgindiaindex.niti.gov.in/#/ranking\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e CHC and PHC are Community Health Centre and Primary Health Centre.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e The poorest states in per capita income (Rowan \u0026amp; Thirlwall, 2015). Punjab, as the second highest in using private services attributes to higher per capita income. For, as income increases, people tend to use high quality private medical services.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e The rural and remote regions suffer twin problems: poor quality of care and long distances of medical services. Though, urban areas are having access of medical services but at high costs.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e In Bihar, the scenario is: no nearby facility (43%), waiting time is too long (38%), services timing is inconvenient (33%), and medical personnel are often absent (18%). In quality-of-care too, the state is 10 percentage points below than national average.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e See: https://www.mitpressjournals.org/doi/abs/\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1162/153535102320893983\u003c/span\u003e\u003cspan address=\"10.1162/153535102320893983\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e See: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.undp.org/content/dam/india/docs/inequality_adjusted_human_development_index_for_indias_state1.pdf\u003c/span\u003e\u003cspan address=\"https://www.undp.org/content/dam/india/docs/inequality_adjusted_human_development_index_for_indias_state1.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e See: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://finance.bih.nic.in/Reports/Economic-Survey-2019-EN.pdf\u003c/span\u003e\u003cspan address=\"http://finance.bih.nic.in/Reports/Economic-Survey-2019-EN.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003cdiv id=\"Par28\" class=\"Para\"\u003e\u0026amp; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://finance.bih.nic.in/Reports/Economic-Survey-2020-EN.pdf\u003c/span\u003e\u003cspan address=\"http://finance.bih.nic.in/Reports/Economic-Survey-2020-EN.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e We conducted this field survey in the Patna district of Bihar from October through December 2015.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e The SC community suffers from social and economic marginalisation in Bihar and India.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e In India and Bihar, economic marginalization is an outcome of social marginalization. For, most of the SC households are the poorest or poorer in the Wealth Index of NFHS 2014-15.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e The distance estimate is from Patna Junction, Railway Station.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e The number of households (=\u0026thinsp;50) taken from a Grama Panchayat was divided by the number of Wards in a GP. For instance, if Dumri had 13 Wards, we interviewed 4 households from each Ward. However, on occasions, we had exceptions to accommodate social and economic realities of the place- for instance, caste and social groups.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Throughout, a respondent\u0026rsquo;s preference represented a household\u0026rsquo;s preference and out of 200 households, 185 answered this question and 167 had marked public or private services and the rest were indifferent of using either.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Supplementary Table\u0026nbsp;2, presents the grouping of reasons to prefer public or private medical services. In that, 9.73% of respondents were indifferent of using both services.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e During the interview, we observed that respondents, especially from the poor backgrounds, were reluctant to complain about the public medical services in the fear that even the existing services, though unsatisfactory, might be stopped. People hesitate to complain about the government medical personnel, who are from the nearby villages or neighbourhood and belonged to higher social and economic groups. During medical emergencies the poor must rely on them. So, the scope for complains was limited. Contrarily, private medical services were open for criticism.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Hence, demand for medical services creates it supply than otherwise.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e In a mixed-method, we analyse the quantitative results considering qualitative insights.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e This survey had none Scheduled Tribe\u0026rsquo;s households. In social hierarchy, GENs are the most socially, economically, and politically well-off group, and it is followed by BC, EBC, and SC.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Health expenditure by household is indefinitely non-increasing with increasing income rather it requires an optimum level of income to maintain a normal health unless or otherwise it is an emergency.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e JAM stands for (I) Jan Dhan Yojana, a scheme to open a zero-balance account, (ii) Aadhaar Card, a unique identification number, and (iii) a mobile phone.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Medical Service Preferences, Public vs. Private Healthcare, Health Service Quality, Conditional Cash Transfers","lastPublishedDoi":"10.21203/rs.3.rs-4928901/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4928901/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study examines preference for public versus private medical services in India\u0026rsquo;s poorest regions. Qualitative and quantitative insights from a primary survey highlight the substandard quality of public healthcare while private services are unaffordable so unreliable public services drive people to seek expensive private sector\u0026rsquo;s services. Multivariate analysis shows that the burden of medical expenses and regional disparities in access impact the choice of using public or private services. However, despite the challenges, solutions through conditional cash transfers or health insurance to offset out-of-pocket expenses in private facilities limits relief due to the inadequate medical services in rural and remote areas.\u003c/p\u003e","manuscriptTitle":"Preference for Public versus Private Medical Services in Poorer Regions of India?","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-17 07:53:02","doi":"10.21203/rs.3.rs-4928901/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"132887472298134155804856159965008534735","date":"2024-08-26T18:50:59+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-26T10:03:20+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-08-22T09:50:25+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-20T00:04:13+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-20T00:03:34+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2024-08-17T08:59:54+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dcd635ba-c205-4362-89a2-0830f1888be8","owner":[],"postedDate":"September 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-28T14:53:46+00:00","versionOfRecord":[],"versionCreatedAt":"2024-09-17 07:53:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4928901","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4928901","identity":"rs-4928901","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}