Sex differences in disease burden, utilization, and expenditure on primary health care services in Kerala, India

Abstract

Sex and gender are important determinants of health, conditioning health exposures and needs, health seeking behavior, health outcomes, and subsequent consequences. We aim to explore the nature and magnitude of sex differences in disease burden, service awareness, utilization, expenditure and satisfaction while accessing primary health care services in the light of recent primary care reforms implemented in the southern Indian state of Kerala. We conducted a cross-sectional study to explore the nature and magnitude of sex differences in disease burden, service awareness, utilization, expenditure and satisfaction in the public sector of Kerala, India. A household survey using multistage random sampling design was conducted to collect information from 3234 households in the selected eight PHC catchment areas of four districts in the state. Descriptive data analysis was carried out with a focus on disease burdens, place of care seeking, cost of care and patient satisfaction, using STATA 12. More males reported fever as their primary ailment compared to females (67.7% vs. 58.6%). A greater proportion of males as compared to females knew about the recently implemented reforms (43% vs 36%; p = 0.01). Allopathic (modern medicine) care was the most sought-after system of medicine across the sample. A higher proportion of females visited government primary health centres for outpatient care (34.7% vs. 27.5%; p = 0.00).Our analysis found statistically significant differences in the self reported cost of care in the private sector: 20 times greater than in public sector for males, whereas the difference was roughly five fold among females (Private: ₹650, $8.5 (95% CI ₹524, ₹776) vs. Public: ₹120, $1.58 (95%CI ₹17, ₹223, p < 0.001)). Males showed greater awareness of state health reforms than females, and high patient satisfaction existed for both private and public outpatient care across sex groups. We found significant sex differences in health system utilization and expenditure in Kerala, although our present analysis lacks data on trans, intersex and other sexual and gender minority groups. Further research on intersectionalities, such as care-seeking experiences across genders and socioeconomic groups, could enhance our understanding the role of sex in care seeking.

Introduction

Biological, or sex differences as well as norm-based or gender differences affect health status, health seeking behavior and access to health care services^1–3. The southern Indian state of Kerala has historically been recognized for placing attention on health and development, including the empowerment of women⁴. With a view to attaining the third Sustainable Development Goal pertaining to “Good Health and Well Being” (SDG 3), the Government of Kerala rolled out Aardram Mission (2017) as part of which Primary Health Centres (PHCs) were re-engineered into Family Health Centres (FHCs) to provide people-friendly, high quality outpatient services. In this process, sex differentials in disease burden, population level awareness of the health sector, service utilization, expenditure and satisfaction with services emerge as important monitoring considerations.

Overall, Kerala is at an advanced stage of the epidemiological transition compared to other Indian states⁵, with increasing burden of non-communicable diseases arising out of rapid urbanization, increasing affluence, international migration, changing age structure and changing lifestyle^6,7. Some sex-disaggregated data in most cases is available; however, data on intersex or trans populations is neither readily available, nor routinely reported. A state level analysis of the National Sample Survey Office (NSSO) 2014 data indicated that women and men had similar prevalence levels of heart disease (seven per 1,000 persons); the study also showed that women were more inclined to receive care from primary care settings⁸. In the 75th round of the National Sample Survey, Kerala females reported greater prevalence of ailments in a 15-day period as compared to males⁹. The Kerala Economic Review (2020) has reported that the state in recent years has witnessed a rise in communicable diseases like chikungunya, leptospirosis, dengue, and malaria¹⁰,; official data is available on this growing burden, but is not sex disaggregated¹¹.

Whatever existing and emerging burdens may be, effective interaction with health system and use of health services is contingent in part upon population level awareness of these services and of their rights and entitlement¹², alongside the social determinants of health¹³. There are limited studies reporting evidence on user awareness in India¹². Recent data suggest that even as the number of in-patients in Kerala was four times higher than the national average (admitted most commonly for infections, metabolic disorders, cardiovascular and respiratory ailments), no significant sex difference were reported⁹. However, given the aforementioned sex difference in ailments, it is possible that something may be getting lost here along the patient care continuum. Indeed, studies have shown that utilization of healthcare services is influenced by the cost of service, distance to health facilities, cultural beliefs, and level of education, among other factors^14–17. These factors vary by gender, intersecting with class, ethnicity, education, occupation, and income levels: understanding and addressing these forms of social stratification can reduce the inequalities in health¹⁸. Multiple studies have reported gender discrimination during healthcare-seeking among females (in both younger and older age-groups), and also among persons living far from facilities^19,20. Elsewhere in the world, sex differences in service utilization have been found^21–23,; evidence for Kerala is scant.

There is growing literature from India on the growing cost of healthcare due to lack of benefit package coverage under publicly funded health insurance schemes for outpatient care²⁴. A 2021 study from northern India found that a mean of Rs.400 (USD 5.27) per episode of outpatient care in India was spent for public providers, Rs.586 (USD 7.72) for informal private providers and Rs. 2643 (USD 34.81) for formal private providers²⁵. Health care expenditure for men and women also differs drastically, with lower health care expenditure for women than for men across all socio-economic subgroups, despite women suffering from higher prevalence of morbidity than men^26,27. Given these constraints, there are nonetheless very few studies on patient satisfaction in India²⁸. Studies have reported lower satisfaction with overall quality of care among females as compared males^29,30.

Focusing on the Kerala context, where primary health care reforms have spanned Universal Health Coverage (UHC) dimensions of increasing population and service coverage as well as financial risk protection^31,32, the aim of our study is to explore the nature and magnitude of sex differences in disease burden, service awareness, utilization, expenditure and satisfaction while accessing primary health care services in the light of recent primary care reforms implemented in the state.

Materials and methods

Setting

We undertook a cross-sectional household survey in four districts of Kerala as part of a larger health systems mixed method research study from July–October 2019. The study used multistage random sampling. The fourteen districts of the state were grouped into clusters based on an index generated using selected health indicators and data on determinants of health sourced from the National Family Health Survey (2015–16) using principal component analysis. Further the 14 districts of the state were grouped into four groups based on the Composite factor scores and One district per group was randomly chosen, and one FHC and PHC in that district were randomly selected. Household level data collection was conducted in the institutional catchment areas following multi-stage random sampling. Information on data collection, household survey methods and sampling size calculation is reported elsewhere^33,34.

Study tool

A household survey using multistage random sampling design was conducted to collect information from 3234 households in the selected eight PHC catchment areas of four districts in Kerala.

The questionnaire designed for the study had multiple blocks which include individual demographics, health information, outpatient care, inpatient care, communicable and non-communicable diseases, patient satisfaction scores on FHC/PHC visits and on awareness of services under Aardram Mission. For this paper we have used data from various blocks to present the findings on (i) participants characteristics (ii) disease burden (iii) awareness on PHC outreach services, (iv) utilization and expenditure on outpatient care services, and (v) patient satisfaction scores. We gathered information on individual demographics and visits to FHCs/PHCs from 3234 households covering 13,064 individuals.

Data analysis

For assessing the disease burden and cost of outpatient care the participants were asked to self-report the nature of most recent ailment in the past 15 days prior to survey excluding childbirth. This included care seeking for outpatient care through public and private sector primary healthcare facilities. 1,848 individuals reported that they suffered from ailments during this period along with cost for incurred if any. Self-reported disease categories were adopted from NSSO’s social consumption on health survey and divided into broad categories: Infectious diseases, Non-Communicable Diseases (NCDs), disability and other diseases. These categories were further divided into subcategories such as fever, hearth stroke, diabetes, cancer etc. Sex-disaggregated frequency distribution of self-reported morbidities were obtained and then ranked from the most common to least common and the top ten most common ailments. Using this information, we analyzed the disease burden of top 10 ailments disaggregated by sex with 95% confidence intervals. Chi-Square and Fisher’s exact tests were performed to test the significance of sex differences.

For understanding the awareness of the participants on PHC outreach services, one member from each household surveyed were asked questions on their awareness regarding the new features introduced through Aardaram primary care reform, house visits by the health human resource, and about the pension scheme for tuberculosis patients. We have analyzed the response from 3,222 individuals to present the findings for this study. Proportions and 95% confidence intervals were estimated for awareness of outreach services disaggregated by sex and Chi-Square and Fisher-exact tests were performed to test the significance of sex differences.

Further to assess the utilization pattern for outpatient care services through FHCs/PHCs participants were asked to respond about his/her most recent visit to an FHC/PHC for outpatient care in the last 15 days prior to the survey. 2,717 individuals reported to have visited an FHC/PHC during this period and from them we collected information on (i) nature of ailment, (ii) type of care and (iii) medical and non-medical expenditures incurred for outpatient visits. For gathering information on the utilization of primary health services, in the context of recent primary health care reforms³¹, we enquired about time of their outpatient visit, pre-check facility by a staff nurse and availability of prescribed medicines and lab tests from the visited facility. Proportions and 95% confidence intervals were also calculated for utilization pattern for outpatient care services disaggregated by sex, Further, Chi-Square and Fisher-exact tests were performed to test the significance of sex differences in the utilization pattern for outpatient care services.

Finally, to analyze data on the patient perspective and satisfaction level, indicators from Service Provision Assessment were used³⁵. A total of 1546 respondents rated their experience of their most recent outpatient care visit to a PHC or FHC on a scale of one to ten (where 1 meant the experience was bad and ten meant the experience surpassed expectations).

Medical expenditure incurred by the respondent in the last 15 days before the survey for the most recent ailment was calculated by adding expenditure on doctor’s fee, medicines, diagnostics, and other medical expenditures. Similarly, non-medical expenditure included expenditure on transport, and any other non-medical expenditure incurred by the respondent. Those who did not report any expenditure were represented as having zero expenditure. Mean and median expenditures were computed. Additionally, mean patient satisfaction scores for the most recent visit at PHC and FHC were also calculated, with significances by sex computed using Chi square tests. All data analysis was carried out using survey weights in STATA 12³⁶.

Ethics approval

Ethical approval for the study was granted by the Institutional Ethics Committee of the George Institute for Global Health (Project Number 05/2019). Additional permissions were obtained from Department of Health and Family Welfare (DHFW) Kerala. While conducting the study, each health facility and concerned local self-government body was appraised about the purpose of the study. All participants gave written informed consent before taking part in the study including Illiterate participants in the survey who were read out and explained the consent form in the local language. Thereafter, they were able to sign their names. The ethics committee that approved the study also approved this procedure of obtaining written informed consent from these participants. All methods were carried out in accordance with relevant guidelines and regulations. The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees in human experimentation and with the Helsinki Declaration of 1978, as revised in 2008.

Results

Participant characteristics

Data for a total of 13,064 individuals was covered in the survey, of which more than half (52.5%) interviewed were women 47.4% males and 0.1% (13) transgender population (see Table 1). We have excluded transgender population from the analysis as we were not powered to carry analysis for this sub-group. Sampled households reported a high literacy rate (96%) and 64.7% of the participants were married. Most of the households belonged to Hindu religion (66.8%). Households reporting themselves as Scheduled Caste and Scheduled Tribe were 7.1% and 2% respectively. About 38.8% of the households in the sample reported having a Below Poverty Line card.

Table 1.

Overall socio-demographic characteristics of the selected sample.

Total individuals sampled	13,064
Individual characteristics	n (%)
Male	6191 (47.4%)
Female	6861 (52.5%)
Other#	13 (0.1%)
Illiterate population *	384 (3.2%)
Married population *	7,254 (64.7%)
Total Households Surveyed	3234
Household Characteristics	n (%)
Households by Religion
Hindu	2162 (66.8%)
Muslim	535 (16.6%)
Christian/Others	537 (16.6%)
Households by caste and tribal status
Schedule Caste (SC)	230 (7.1%)
Tribal Status (ST)	64 (2.0%)
Other Backward Classes (OBC)	2027 (62.7%)
Other (General)/Others	913 (28.2%)
Households Below Poverty Line (BPL)	1255 (38.8%)

*Excluding individuals aged below 10, #excluded from the analysis.

n’s are rounded to zero digits and percentages are rounded to one digit. We also calculated frequency distribution of subsamples in the study, these distributions were similar to the overall distribution presented here.

Disease burden: similar burdens by sex with some key differences

While the overall pattern of disease burden did not differ by sex, some distinct burdens were seen (see Fig. 1). Among the top 10 conditions for non-hospitalization, a higher proportion of males (67.7%) reported fever than females (58.6%) for which they sought outpatient treatment in past 15 days. Acute Upper Respiratory Infection (AURI) was reported to be higher among female participants (15.7%) than males (10.2%). Our study found that accidental injuries and road traffic accidents (RTA), though relatively a small share of ailments, were slightly more common among males (3.6% of the sample, ranking third) as compared to females (2.2%, ranking sixth). Musculo-skeletal disorders (back or body aches) were the third most common ailment reported by females (by 3.7%) and fourth most common for males (3.1%).

Fig. 1.

Sex Disaggregated Top 10 Disease Burdens (recent ailment in the past 15 days not requiring hospitalization, excluding childbirth (%) (N = 1848).

Awareness of PHC outreach services: new scheme (Aardram) awareness greater among males, no differences for ongoing vertical programs

While looking at the sex differences in population-level awareness of primary health care outreach services (see Table 2), we found that 43.6% of male and 36.6% of females reported knowledge of ongoing reforms, a statistically significant difference (p = 0.01). Awareness about palliative care visits and field visits by health care workers was high among both males and females, which speaks to the high penetration of these programs (p = 0.81). This was not the case with a specific component of the TB program (the pension scheme): awareness was low among both males and females with no sex differences (p = 0.16).

Table 2.

Awareness of PHC outreach services by Sex (%) (N = 3222).

Indicators (N)	Male	Female	Chi2 /Fisher Value	P value
Proportion of persons who reported hearing of recently launched government program for improving health called “Aardram mission “(%) (M: 2439; F: 783)	43.6(95% CI 41.2, 45.9)	36.6(95% CI 31.5, 42.0)	11.9	0.01
Proportion of persons who reported knowing about visits by workers to the bed-ridden or those who are dying (palliative care) (%)(M: 2439; F: 783)	77.1(95%CI 73.6, 80.2)	77.6(95% CI 71.8, 82.6)	0.09	0.81
Proportion of persons reporting visit of someone to check water sources/source reduction (%)(M: 2439; F: 783)	81.2(95%CI 78.1, 84.0)	83.1(95% CI 78.2, 87.0)	1.3	0.32
Proportion of persons reporting awareness of the TB pension scheme (%)(M: 2438; F: 783)	15.6(95%CI 13.6, 17.7)	12.5(95% CI 9.2, 16.8)	4.3	0.16

*excluding other sex.

Outpatient service utilization

We found that the proportion of females who visited the PHC/FHC (34.7%) was higher than males (27.5%); this difference was statistically significant (p = 0.00). A marginally greater proportion of females (35%) as compared to males (33.5%) received pre-check services administered by a staff nurse. Approximately 8% of the population reported visiting facilities during extended service delivery hours: no sex differences were observed (p = 0.47)). More than 86% of participants who visited PHCs received medicines free of cost and lab tests at discounted rates, differences here were not significantly different by sex (p = 0.08). However, there was a significantly greater proportion of females (82.4%) as compared to males (77.9%, Chi² = 4.1, p = 0.03) who were able to get all their prescribed test done within the FHC premises (see Table 3).

Table 3.

Utilization of Primary Healthcare outpatient services by Sex.

Indicators (N)	Male	Female	Chi2/Fisher value	P value
Proportion of all persons who visited FHC/PHC last year (M: 4513, F: 5315)	27.5%(95%CI 24.1, 31.3)	34.7%(95%CI 30.9, 38.7)	58.4	0.00
Of those who visited an FHC/PHC in the last year, proportion who received pre-check service by Staff Nurse (M: 1159; F: 1554)	33.5%(95%CI 25.3, 41.6)	35.0%(95%CI 26.9, 43.1)	0.69	0.37
Of those who visited an FHC/PHC in the last year, proportion who visited during extended outpatient hours (i.e., after 2 pm) (M: 1160; F: 1557)	7.8%(95% CI 5.7, 10.4)	8.6%(95% CI 6.8, 10.7)	0.56	0.47
Of those who visited FHC/PHC last year, proportion of persons who were able to get all medicines prescribed by the doctor from the adjoining pharmacy free of cost (%) (M: 1043; F: 1375)	86.0%(95% CI 82.5, 88.8)	88.1%(95%CI 84.9, 90.7)	2.4	0.08
Of those who visited FHC/PHC last year, proportion of persons who were able to do all the tests prescribed by the doctor from the adjoining lab with discounted rates displayed (%)(M: 543; F: 741)	77.9%(95% CI 71.4, 83.3)	82.4%(95%CI 78.1, 86.1)	4.1	0.03

“n” denotes numerator and “N” denotes denominator.

For those seeking treatment, (Overall, we found no sex differences in foregone care: nearly 14.6% of males and 15% of females opted not to take any treatment) we found that allopathic (modern) medicine in the public sector and in private sector was the most sought-after option for outpatient care across sex (see Fig. 2). Males reported slightly higher utilization than females from public and private allopathic (modern medicine) facilities, although the difference was not statistically significant (Design based F = 0.62, p = 0.66). Utilization of services from the Ayurveda, Unani, Siddha/Sowa Rigpa and Homeopathy (AYUSH) systems of medicine was low among both males (2.1%) and females (3%).

Fig. 2.

Care-seeking by sex (%) for ailments experienced in the past 15 days not requiring hospitalization, (N = 1848).

Treatment expenditure for outpatient care: statistically significant sex differences, but spending in private sector substantially higher than public sector

While measuring the sex difference for mean medical and non-medical costs incurred for allopathic (modern medicine) outpatient care seeking among the participants (see Table 4), we found that the cost of OP care was more than 20 times greater in the private sector as compared to the public sector for males (Private: INR 809 (95% CI 629,989) (USD (INR was converted to USD on 15th March 2022, figures may vary based on the value of USD)10.80) versus Public: INR 39 (95% CI 10,68) (USD 0.52); the difference was roughly fivefold among females (Private: INR 650 (95% CI 524,776) (USD 8.59) vs. Public: INR 120 (CI 17,223) (USD 1.59)); statistically significant sex differences (p < 0.001) were seen in expenditure by sector. We used two sample t-test for sex differences in expenditure. We also found that mean medical expenditures for males (INR 809, USD 10.69) was higher than females (INR 650, USD 8.59) while accessing private OP care.The cost incurred in public sector was considerably lower for males (INR 39, USD 0.52) than females (INR 120, USD 1.59). Mean non-medical expenditure was also higher in private for males (INR 118, USD 1.56) and females (INR 101, USD 1.33) when compared to the public sector OP care which was found to be statistically significant (p < 0.001) (We also computed median medical and non-medical expenditure by sex. For both males and females in public sector the value for medical and non-medical expenditure was zero, whereas in the private sector, the median medical expenditure for males (INR 500) was higher than that of females (INR 430).)

Table 4.

Mean medical and non-medical costs incurred for care-seeking (across sectors) for most recent ailment in the last 15 days by Sex (amount in INR.)

		Male (N = 718)		Female (N = 828)		Total
		Private (N = 331) (46.1%)	Public (N = 387)(53.9%)	Private (N = 384)(46.4%)	Pubic (N = 444)(53.6%)	Public (N = 715)(46.2%)	Private(N = 831)(831)
Medical expenditure	Mean (95%CI)	809 (95%CI 629, 989)	39 (95%CI 10, 68)	650(95%CI 524, 776)	120(95% CI 17, 223)	82(95%CI 30, 135)	724(95%CI 591, 856)
	Median (Interquartile range)	500 (275, 750)	0 (0, 0)	432 (275, 750)	0 (0, 0)	0 (0, 0)	450 (275, 750)
Non- medical expenditure	Mean (95%CI)	118(95% CI 91, 144)	22(95%CI 6, 39)	101(95%CI 69, 133)	15(95%CI 7, 22)	18(95%CI 11, 26)	109(95%CI 86, 131)
	Median (Interquartile range)	50 (0, 100)	0 (0, 0)	50 (0, 100)	0 (0, 0)	0 (0, 0)	50 (0, 100)
Total	Mean (95%CI)	927 (95% CI 727, 112)	61(95% CI:18, 105)	751 (95% CI 609, 893)	135 (95% CI 28, 242)	101 (95% CI 45, 156)	832 (95% CI 686, 979)
	Median (Interquartile range)	550 (350, 900)	0 (0, 0)	500 (325, 870)	0 (0, 0)	0 (0, 0)	500 (340, 900)

1. Medical expenditure includes expenses on Doctor’s/ consultation fee, diagnostics, medicines, and other medical expenditure (attendant charges, physiotherapy, personal medical appliances, blood, oxygen, etc. excluding reimbursements (if any). Non-medical expenses include transportation expenses and informal payments.

2. Those who reported no treatment were excluded from the sample to calculate expenditure estimates. Further, any missing values were replaced by zero. Its denoted cases where expenses were zero because either the patient incurred no expenses due to either visiting a public facility or covered under insurance, CHIS, RSBY etc.

3. The total number of female cases was 828 out of which 53.6% visited public facilities and the total number of male cases was 718, out of which 53.9% visited public facilities.

Patient satisfaction: high ratings for Public and Private OP care, no sex differences

From our study population of 1546 individuals who sought outpatient care visits to primary care facilities, 828 were females and 718 were males. Out of these 828 females, 384 went to private and 444 went to public. Of 718 males, 331 went to private and 387 went public. We did not observe sex differences in patient satisfaction scores reported by the participants in public and private sector and among both sexes. (See Fig. 3), nor were scores significantly different across public and private sector PHC outpatient services.

Fig. 3.

Average rating of services received (scale of 1–10), across sectors, by sex, (N = 1558).

Discussion

The study done in Kerala looked at sex differences in disease burden, utilization and expenditure of primary healthcare services and found distinct sex-based differences in disease burden and healthcare utilization. Fever was more commonly reported by males, while Acute Upper Respiratory Infection was more prevalent among females. Accidental injuries were slightly higher among males, whereas musculoskeletal disorders were more frequently reported by females. Awareness of primary health care outreach was significantly higher among males, yet females had higher visitation rates to Primary Health Centers (PHCs) and received more comprehensive services. Both sexes showed high awareness of palliative care, but low awareness of a TB program. Allopathic medicine (modern medicine) was the predominant choice for outpatient care, with higher costs in the private sector compared to the public sector for both sexes. Despite these variations, no significant sex differences were noted in patient satisfaction scores across public and private healthcare services.

In our study, we found that PHC services were frequently utilized by both male and female members of the population for the treatment of fever, followed by AURI and Musculo-skeletal disorders. Karan et al. (2014) reports, in the public sector, outpatient care primarily addresses cardiovascular ailments, followed by fever, musculoskeletal diseases, and respiratory disorders. Similarly, in the private sector, cardiovascular ailments are the most treated condition, with diabetes, fever, and respiratory disorders also being significant³⁷. We also noted that the proportion of males who received outpatient care for fever was higher, which is consistent with other recent studies^38,39. Among female participants, AURTI, general back and body ache, as well as bronchial asthma were among the top five conditions for seeking outpatient care. A study conducted in FHCs of Kerala found high prevalence of multimorbidity among the primary care patients with higher females compared to males having both hypertension and diabetes⁴⁰. Malla et.al (2024) reported higher burden of multi-morbidity among pregnant women in Kerala, which ranked 7th position compared to other Indian states⁴¹.

Road traffic accidents and falls were among the top five conditions among males for availing outpatient services. This aligns with a previous study that underscores the high incidence of RTAs and falls as significant causes of morbidity and healthcare utilization among males by Shibu et al. in 2018⁴². Another study by WHO (2018) reported that RTAs are a leading cause of injury-related deaths worldwide, particularly affecting young adult males in low- and middle-income countries⁴³. Similarly, falls are recognized as a major source of non-fatal injuries, arising from occupational hazards, especially in construction and manual labor sectors where males are overrepresented, contribute to a higher incidence of falls⁴⁴. Given the high utilization PHC services for trauma and injury, this study underscores the importance of integrating trauma and injury prevention strategies into primary healthcare services including community outreach strategies. Kerala has already initiated decentralization of trauma care training and equipping all medical personnel with advanced emergency care skills⁴⁵. The bedrock of most PHC systems is community outreach⁴⁶. The results of our study indicate relatively high levels of awareness and utilization of primary healthcare (PHC) components among the population, which reflect the robustness and effectiveness of Kerala's PHC network. This finding is consistent with previous studies highlighting Kerala's exemplary model of healthcare delivery, characterized by widespread accessibility and strong community health initiatives^47,48. The high awareness and utilization rates observed in our study can be attributed to several factors like the comprehensive health education programs that emphasize the importance of primary care services and the state’s robust network of PHC centers that ensures essential services to the most remote communities, reducing barriers to care⁴⁹. While awareness of these “staples” of PHC was high; newly introduced health reforms as part the larger primary care reform Aardram, like extended OP hours, and the TB pension scheme were not widely known or utilized by communities. Facility based infrastructural upgrades in diagnostics and medicine supply appear to be reaching those who can reach centres. This is critical as spending on drugs and diagnostics constitutes the bulk of out-of- pocket expenditure in India and globally⁵⁰. Prioritizing public health services, population interventions, maintaining political commitment, and rigorous monitoring are also key to strengthen primary healthcare on the road to universal health coverage⁵¹.

We observed that PHC services were utilized by the population for treatment of fever. This concords with the finding of a 2019 report of the Kerala Department of Health and Family Welfare, which observed that nearly 28 lakh outpatient visits in public facilities were made across the state for treatment of fever, indicative of a generally high level of utilisation of public health facilities for this purpose⁵². Kerala has an extensive public and private network of allopathic (modern medicine) health facilities³⁹. Our study suggests that the allopathic (modern medicine) system of medicine as the most preferred system for outpatient care (public or private sectors). This is consistent with the findings of National Sample Survey (NSS) 75th round⁹ and similar studies in the state^37,39,53,54. Results from a study examining gender differentials in health care utilization in India found that both sexes preferred private hospitals over public hospitals for OP and IP care, and also that males travelled greater distance to reach hospital than women⁵⁵. However nearly 15% of both males and females reported not taking any type of treatment for an ailment–a matter of concern for both sexes- which is consistent with similar studies in India⁵³. Beyond this, Kerala matches the national trend of greater reliance on allopathic (modern medicine) systems of medicine although almost 1 in 10 females relied on non-allopathic (modern medicine) systems in both urban and rural areas⁹

We found high of Out-of-Pocket-Expenditure (OOPE) for outpatient care in the private sector among both males and females, starkly divergent from the zero-median cost of care for PHC services from the public sector. This is consistent with findings of study which reported no cost for consultation, medicines and diagnostics for all beneficiaries who accessed the Mohalla Community Clinics in Delhi⁵⁶. On the one hand, the advanced economic status of Kerala is reported to be the reason for higher purchasing of outpatient among the population of Kerala⁵⁷. Yet, spending per capita on the whole is lower in Kerala as compared to the national average: the NSS 75th round reported an average outpatient expenditure for treating a spell of ailment in Kerala has been estimated at Rs.480 (USD 6.3) against Rs.636, (USD 8.4) at the national level⁹. This is consistent with our finding of Rs. 450 (USD 5.9) as median cost of care overall. Health equity, remains challenging due to socio-economic disparities and barriers faced by marginalized communities. Effective monitoring, data-driven approaches, and community engagement are essential to address these inequities and promote a more equitable health system⁵⁸.

Patient satisfaction scores are a reliable instrument to measure quality of service delivery globally^28,59. Our study found high patient satisfaction with OP services across sectors among both male and female respondents (see Limitations). This is consistent with the findings of study which assessed the access, utilization, perceived quality, and satisfaction with health services at Mohalla Clinics which reported higher satisfaction rate with overall services, doctor patient interaction time⁵⁶. The consistency of satisfaction across genders suggests that OP services are equitably meeting the needs of both men and women, which is an important indicator of gender-inclusive healthcare practices. Contrary to this a study by Saxena et.al (2024) found that Health and Wellness Centres (HWCs) under the Ayushman Bharat program had a low level of appropriateness and a medium level of acceptability for managing depression and suggested enhancing trained human resources, improving infrastructure and drug availability, and enhancing integration and coordination with other programs and higher centres⁶⁰. The Kerala public health system has demonstrated a commitment to improving the quality of its health institutions, introducing as far back as 2013, a dedicated program called Kerala Accreditation Standards for Hospitals (KASH)⁶¹. Aardram health reforms have sought to further improve the infrastructure of primary care facilities: many institutions have either already been accredited or are seeking accreditation under the National Quality Assurance Standards (NQAS)⁶². The high patient satisfaction scores for outpatient care in public and private sector suggest that quality reforms across the health system in Kerala may be delivering results; however further qualitative analysis is required to understand the reasons behind these scores.

Limitations

Our sampling included primary health centre areas which are in grama panchayat area and excluded population living in municipality and corporation areas. The self -reported disease burden and treatment expenditures were used in this study, though we tried to crossmatch this information with bills and hospital records which was not possible with all the participants. Social desirability bias may have influenced the response of the participants on awareness of PHC outreach services as well as ranking of services. In the latter case, we also noted that only 84% of those surveyed provided patient satisfaction data–we cannot speak to the ranking preferences of those who did not respond to this set of questions). We had small sample of other gender, so we have focused only on male and female in our analysis.

Conclusion

Our study, drawing on a population-based survey, found that patterns of disease burden did not differed somewhat by sex. Males were more aware of newer health service reforms in the state and patient satisfaction with OP care in private and public appear to be high among both sexes. Care seeking was higher among females, and they were able to get most of the prescribed test done in the facility itself. The wide disparity in cost of care for outpatient services between public and private sector in the state is a matter that requires immediate policy attention as majority of the health insurance schemes do not cover OP care. Further research which examines intersectionalities (e.g. experiences for care seeking among males and females, across socio-economic groups or place of residence) may help in better understanding role of sex in care seeking.

Notes

• Survey weights were used to cater for different selection probabilities in different blocks of the survey and to adjust for household non-response and individual non-response. Survey weights were calculated based on sampling probabilities separately for each sampling stage. The final sampling weights were normalized to give a total number of weighted cases that equals the total number of unweighted cases. Normalization was done by multiplying the sampling weight by the estimated total sampling fraction obtained from the survey for household weights and individual weights.

• For caste and religion groups, we carried out a separate analysis by grouping ‘general’ caste category with prefer not to say/don’t know as well as by grouping ‘other religious group’ with prefer not to say/don’t know. In all analyses, results were similar to those presented here.

Abbreviations

AURI

Acute upper respiratory infection

FHC

Family health centre

INR

Indian rupee

NCDs

Non-communicable diseases

NSSO

National sample survey office

OOPE

Out-of-pocket expenditure

OP

Out-patient care

PHC

Primary health centre

RTA

Road traffic accidents

SDG

Sustainable development goals

TB

Tuberculosis

USD

United States dollar

Author contributions

Jaison Joseph: conceptualization, methodology, formal analysis, writing original draft, review, and editing; Hari Sankar: methodology, writing, reviewing, and editing original draft; Santosh Kumar Sharma: conceptualization, data analysis, writing, reviewing and editing original draft; Devaki Nambiar: conceptualization, methodology, writing, reviewing and editing original draft fund acquisition, monitoring, and supervision. All authors read and approved the manuscript.

Funding

We wish to indicate that this work was supported by the Wellcome Trust/DBT India Alliance Fellowship(https://www.indiaalliance.org) Grant number IA/CPHI/16/1/502653) awarded to Dr. Devaki Nambiar. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The funder provided support in the form of salaries and research materials and field work support for authors DN, HS, JN and JJ but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.

Data availability

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

Competing interest

The authors of this paper do not have any conflicts of interest.