Financial Burden of Out-of-pocket Health Expenditure among Older Adults in Rural Kerala: A Mixed Methods Study

Abstract

Background:

The rising number of older adults in India has led to increased healthcare needs and financial challenges secondary to high out-of-pocket expenditure (OOPE). Understanding the extent and impact of OOPE among community-resident older adults is crucial for developing equitable health policies.

Methods:

A mixed methods study was conducted among 364 older adults in Arimbur Gramapanchayath, Kerala. Quantitative data on healthcare expenses were collected using a pretested proforma, and qualitative interviews were conducted with participants reporting higher OOPE. Descriptive and thematic analyses were performed.

Results:

The mean monthly OOPE for outpatient care was INR 1,379, while the average annual OOPE for hospitalization was INR 26,094. Many participants (59.4%) lacked health insurance, and 76.8% of them preferred private healthcare. Qualitative findings indicated the presence of issues related to accessibility and availability of specialist care when needed. Financial insecurity adversely impacted the healthcare of older adults and at times led to the neglect of healthcare.

Conclusion:

Older adults experience substantial financial strain due to healthcare costs, with inadequate insurance and reliance on private services. Strengthening of public healthcare services and efforts to reduce OOPE will help in scaling up senior care.

INTRODUCTION

India is home to more than 153 million people aged 60 years or older. This number is projected to reach 347 million by 2050.[1] The burden of chronic diseases and multimorbidity often leads to financial hardship from healthcare costs.[2] Older adults often require frequent outpatient clinic visits, long-term medication, and diagnostic services. The lack of a regular income, limited pension benefits, and insufficient social security benefits add to their financial strain. Data from the nationally representative National Sample Survey (75^th round) indicate that nearly 47% of households with older adults incur catastrophic health expenditures (CHEs), and more than 56% of these households could be pushed into poverty by healthcare costs.[3] Government initiatives such as Ayushman Bharat–Pradhan Mantri Jan Aarogya Yojna aim to reduce care costs, but evidence suggests they have not yet achieved the desired impact.[4]

Out-of-pocket expenditure (OOPE) refers to direct payments by individuals for healthcare services. This includes payments for consultations, diagnostic tests, medications, hospitalization costs, transport, and other expenses not reimbursed by health insurance or the government.[5] In India, OOPE accounts for a substantial share of total health expenditure. According to National Health Accounts estimates, the share of OOPE declined from 64.2% in 2013–14 to 39.4% in 2022; however, it remains a significant burden.[6] High OOPE can cause financial hardship, delay care-seeking, and increase the risk of poverty, especially among older adults from low-income families.[7] While high-income countries use government-funded insurance and social security to cover health-related expenses, low- and middle-income countries rely heavily on personal savings and family support, which often pushes low-income families into financial distress.[8] It is essential to understand the current financial arrangements for older adults’ healthcare expenses.

We aimed to estimate OOPE among a sample of older adults living in the community and to assess the level of financial strain and its effects.

METHODS

We chose Arimbur Gramapanchayath because of our involvement in social care programs there. Our study used an explanatory sequential mixed methods approach. The study protocol received approval from the University Ethics Committee of Kerala University of Health Sciences (KUHS AX04/SOP07A/V2 dated 14.03.2024). Permission to conduct the study was obtained from the Arimbur Panchayat president, including authorization for the involvement of accredited social health activists (ASHAs). Furthermore, permission for the support of ASHAs was secured from the medical officer of the Arimbur public health center.

For the quantitative part, we randomly selected older adults from each of the 17 wards in the panchayath, aiming for a sample size of 364, calculated using the formula Z2PQ/d2 at a 95% confidence level and 5% margin of error (P = 67.9%).[9] Names were taken from the panchayath’s register of older adults, maintained as part of ongoing social care activities. Older adult is operationally defined as an individual who is over 60 years of age. There were 5,468 older adults in the panchayath, and we randomly selected 364 older adults through a lottery method [Figure 1]. We consulted ASHAs, trained frontline health workers responsible for community outreach in each ward. The researcher contacted ASHAs across all 17 wards to identify the selected participants through the lottery method and to introduce themselves. If a person was unavailable or declined (only 3), the next eligible individual on the list was approached. All eligible participants were recruited after explaining the study aims and obtaining their written informed consent. The proforma was developed specifically for the study; it was based on existing literature and the study’s goals. Five older adults pretested it before finalization.

Figure 1.

Participant selection flow diagram

Direct costs—including consultation, medications, diagnosis, and hospitalization—were included. Indirect costs, such as transportation, caregiver expenses (e.g., loss of income during illness), and the cost of employing a formal caregiver to assist or look after the individual, were also considered. The reference period for outpatient treatment expenses was 3 months before the interview, while for hospitalization expenses, it was 12 months before the interview. This strategy has been used by many studies, stating that more frequent and smaller expenditure items are better captured in a shorter recall period, while infrequent, larger expenditure items are better captured in a longer recall period.[10] Written informed consent was obtained from all participants. Separate consent was obtained for audio-recording of qualitative interviews. Participants’ capacity to provide informed consent was ensured before enrollment. All transcripts were anonymized and stored securely.

The investigator conducted in-person interviews at the homes of older adults and collected sociodemographic data and details of OOPE using a proforma designed for the study. The data analysis was completed using Microsoft Excel and SPSS version 24.

Monthly outpatient OOPE included consultation fees, medicines, investigations, and transportation during the preceding 3 months. Hospitalization OOPE included admission charges, medicines, investigations, transportation, and caregiver-related costs incurred during the previous 12 months. All costs are reported in Indian rupees (INR).

For the qualitative phase, participants with relatively higher OOPE were purposively selected to gain in-depth understanding of financial burden and healthcare experiences. In-depth interviews were conducted using a semi-structured interview guide focusing on healthcare utilization, financial coping, and perceived barriers to care.

Interviews were audio-recorded, transcribed verbatim, and analyzed using an inductive thematic analysis approach. Initial coding was performed using open coding, followed by grouping of codes into categories and broader themes through constant comparison.

Data collection and analysis were conducted concurrently, and thematic saturation was considered achieved when no new themes emerged from successive interviews. A total of six interviews were conducted, and the sample size was guided by the concept of information power, as participants were selected based on their relevance to the research question and richness of data.

To enhance the rigor of the qualitative analysis, interviews were conducted by the first author, a public health researcher with prior experience in qualitative interviewing. Although the researcher had previous engagement with the study area through community programs, no prior personal relationship existed with participants. Reflexive notes were maintained after each interview to minimize researcher bias. An audit trail documenting coding decisions and theme development was maintained throughout the analysis. Owing to the advanced age of participants and logistical constraints, formal member checking was not undertaken. The reporting of the qualitative and quantitative components followed the STROKE and COREQ guidelines, respectively [Supplementary Tables S1 and S2].

Supplementary Table S1.

STROBE Checklist

Section/Item		Recommendation		Reported on page(s)		Status
Title/Abstract		Study design indicated; balanced summary		1		Yes
Introduction		Background and objectives		2		Yes
Methods		Design, setting, participants, variables, data sources, bias, study size, quantitative variables, statistics		2–5		Yes
Results		Participants, descriptive data, outcome data, main results		5–9		Yes
Discussion		Key results, limitations, interpretation, generalisability		10–13		Yes
Other information		Funding, conflicts, ethics		2,15		Yes

Supplementary Table S2.

COREQ Checklist (32-item)

Domain/Item		Description		Reported on page(s)		Status
Research team		Interviewer identified; experience described		4–5		Yes
Relationship		Prior relationship/reflexivity described		4–5		Yes
Study design		Sampling, setting, participants		3–5		Yes
Data collection		Interview guide, audio-recording, field notes, saturation		4–5		Yes
Analysis		Coding, thematic analysis, audit trail		4–5		Yes
Reporting		Illustrative quotations; consistency between data and findings		7–12		Yes
Member checking		Not undertaken; acknowledged		5		Reported

RESULTS

We conducted 364 interviews with older adults to collect quantitative information about OOPE. This was followed by in-depth interviews with six older adults who reported high OOPE. The interviews were conducted between April and July 2024. Of the participants, 50.3% were men and 49.7% were women. Less than one-third (30.8%) belonged to low-income families classified as “Below Poverty Line (BPL)” based on ration cards issued by the Civil Supply Department, Government of Kerala. Most of them (37.6%) were aged 60–65 years. Most participants (82.4%) reported taking regular medication.

Normality of OOPE was assessed using the Shapiro–Wilk test along with visual inspection of histograms and Q–Q plots. OOPE was found to be non-normally distributed. Despite this, an independent samples t-test was initially performed to compare mean OOPE between males and females, which showed no statistically significant difference (t = 0.33, P = 0.741). The effect size was negligible (Cohen’s d = 0.04). Given the skewed distribution of OOPE, a non-parametric Mann–Whitney U test was also conducted, which yielded consistent findings (P > 0.05).

No significant association was observed between age and OOPE. Linear regression analysis indicated that age was not a significant predictor of OOPE (β = −0.02 (95% confidence interval [CI]: −0.15 to 0.11), P > 0.05).

Because OOPE was highly positively skewed (Shapiro–Wilk test, P < 0.001), a logarithmic transformation [ln (OOPE + 1)] was applied before multivariable analysis. A multivariable linear regression analysis was performed using log-transformed OOPE as the dependent variable. The model explained 60.2% of the variance in OOPE (R² =0.602; adjusted R² =0.586). After adjustment for demographic, socioeconomic, and healthcare-related factors, hospitalization during the previous 12 months remained the strongest independent predictor of higher OOPE (B = 4.51, standard error [SE] = 0.33, P < 0.001). Regular medication use was also independently associated with higher OOPE (B = 5.26, SE = 0.34, P < 0.001). Among socioeconomic variables, participants with white ration cards had significantly higher OOPE than those with blue ration cards (B = 0.97, SE = 0.35, P = 0.007). Age, gender, education, and health insurance status were not independently associated with OOPE after adjustment.

OOPE and healthcare utilization

The mean monthly outpatient expenditure was INR 1,379 (95% CI: 1,210–1,548 with costs ranging from INR 0 to 8,000), while the median expenditure was INR 765 (IQR: INR 0–2,000), indicating a positively skewed distribution. Among the 364 participants, 69 (18.9%) required hospitalization in the previous year, with an average annual OOPE of INR 26,094 (95% CI: 21,870–30,318) [cost details in Table 1]. Household expenditure was collected in categorical bands. Midpoint values were used to estimate monthly household expenditure for the calculation of CHE. CHE was calculated as the proportion of monthly household expenditure spent on healthcare. Monthly household expenditure was estimated using the midpoint of the reported expenditure category. CHE was defined using two commonly adopted thresholds: healthcare expenditure exceeding 10% and 25% of total household expenditure. In accordance with WHO and previous literature, CHE was observed in 42.5% of households at the 10% threshold and in 28.1% at the 25% threshold.

Table 1.

Components of out-of-pocket expenditure among older adults

Cost component		Mean cost (INR)		Type of cost		Applicable population
Monthly outpatient treatment (consultation and routine medicines)		1,379		Direct		All participants (n=364)
Hospital care expenditure		26,094		Direct		Hospitalized participants (n=69)
Transportation		957		Indirect		All participants (n=364)
Cost of employing a caregiver after discharge		15,750		Indirect		Hospitalized participants (n=69)
Loss of income incurred to caregiver due to hospitalizations		5,757		Indirect		Hospitalized participants (n=69)

A majority of participants (76.8%) preferred private healthcare services despite higher costs. Qualitative findings provided insights into this preference, particularly highlighting challenges in public healthcare facilities, such as long waiting times and inconvenience.

These qualitative findings complement the quantitative observation that most participants preferred private facilities despite higher OOPE, demonstrating how perceived accessibility and quality drive expenditure.

“Long hours of waiting are stressful…food, travel, and we are aged people with frequent bathroom needs. It’s better to see a private doctor; money will go, but that is much easier.” (72-year-old female participant)

Concerns regarding the perceived effectiveness of treatment in public facilities also influenced healthcare choices:

“They give medicines without any effect. My blood sugar increased after getting treatment from a public hospital.” (65-year-old male participant)

These qualitative insights explain the higher utilization of private healthcare despite increased financial burden.

Financial burden and coping mechanisms

A considerable proportion of participants relied on personal financial resources to meet healthcare expenses. About 39% reported using savings, while 31% borrowed money from friends or family members.

Qualitative data revealed the financial strain experienced by older adults, particularly in the context of irregular income and delayed pension payments:

“It’s been 3–4 months since I got my pension. How am I supposed to buy medicine and seek treatment without money?” (69-year-old male participant)

Further analysis showed that BPL families incurred higher OOPE (INR 9095.09) than non-BPL families (INR 8304.86), and this difference was statistically significant (t = 2.31, P = 0.021). Male participants had higher OOPE than females, although this difference was not statistically significant. The mean OOPE among uninsured individuals (INR 8,721.6) was slightly higher than that among insured individuals (INR 7,942.8); however, this difference was not statistically significant (Welch’s t-test: t = 0.33, P = 0.741). A Mann–Whitney U test was also performed due to skewness of data and showed consistent results (P > 0.05). The effect size was negligible (Cohen’s d = 0.04).

These findings indicate limited financial protection and dependence on informal coping mechanisms among older adults.

Healthcare neglect

A substantial proportion of participants (62.9%) reported considering neglecting their healthcare needs, while 32.4% admitted to actually neglecting care.

Qualitative findings revealed that both financial constraints and family dynamics influenced this behavior. Some participants reported discontinuing treatment due to perceived financial burden on family members:

“My son spent a lot of money treating me. Now his wife is furious. She wants me to leave the house or die…I stopped medicines.” (72-year-old female participant)

These findings suggest that healthcare neglect is driven not only by economic hardship but also by social and familial pressures.

Access to healthcare and system-level barriers

Participants highlighted several barriers related to accessibility and quality of healthcare services. Transportation difficulties were commonly reported, particularly challenges in using public transport and poor road conditions.

“Bus people see us aged people as ghosts. They may not even stop the bus. If I don’t get on quickly, they use harsh words.” (72-year-old female participant)

Participants also emphasized the importance of provider behavior, communication, and availability of specialist services:

“I like when the doctor smiles, talks to me in a friendly manner, and asks me about my problems without hurry.” (81-year-old female participant)

“I had this tablet, and then at night I had severe pain…No one told me how to take it properly.” (67-year-old female participant)

These qualitative findings highlight that accessibility, provider interaction, and availability of specialized care significantly influence healthcare utilization among older adults [Table 2].

Table 2.

Joint display of quantitative and qualitative findings on out-of-pocket expenditure

Quantitative finding		Qualitative explanation		Supporting quote		Interpretation
76.8% prefer private care despite higher cost Mean outpatient OOPE: INR 1,379; inpatient OOPE: INR 26,094 42.5% (10%) and 28.1% (25%) households experienced CHE. 62.9% considered neglect 39% used savings Transport cost INR 957		Long waiting times, inconvenience in public hospitals Frequent healthcare needs and reliance on private services increase healthcare expenditure Lack of financial protection mechanisms and irregular income Financial strain and family pressure Lack of financial protection Travel difficulties		“Long hours of waiting…” “Money will go, but that is much easier.” “How am I supposed to buy medicine without money?” “My son spent a lot…I stopped medicines.” “How am I supposed to buy medicine…” “Bus people see us aged people…”		Preference for private care is driven by system-level inefficiencies in public healthcare, despite financial burden OOPE burden is sustained by repeated service use and preference for private healthcare High CHE reflects inadequate financial protection and unstable income sources among older adults Social and economic drivers of neglect Weak financial security Physical access barrier

CHE=catastrophic health expenditure, OOPE=out-of-pocket expenditure

DISCUSSION

This study investigated the OOPE among older adults in rural Kerala and its impact on healthcare utilization. The findings show a significant financial burden, with older adults spending a considerable amount on both outpatient and inpatient care.

The average monthly expenditure for outpatient care in this study was INR 1,379. The first wave of the longitudinal aging study in India (LASI) reported an average outpatient cost of INR 1,149 among individuals aged above 60 years, with variation across states. In Kerala, the reported cost was INR 847. The higher expenditure observed in the present study may reflect temporal changes, as the LASI data for Kerala were collected during 2017–18, whereas the present study was conducted in 2024.

The average annual hospitalization cost in this study was INR 26,094. According to LASI, the mean OOPE for inpatient care was INR 8,877 in public facilities and INR 52,022 in private facilities.[11] The relatively higher OOPE observed in this study may be explained by the high preference for private healthcare services (76.8%) among participants. Qualitative findings from this study suggest that this preference is influenced by perceived better accessibility, reduced waiting time, and ease of consultation in private facilities.

Accessibility and timeliness of healthcare emerged as important factors influencing healthcare utilization. Most participants preferred private facilities, and qualitative insights indicated that long waiting times and inconvenience in public healthcare settings were key reasons for this preference. Similar findings have been reported from other Indian settings, where inefficiencies in public healthcare systems drive patients toward private providers despite higher costs.[12] Addressing these issues through system-level improvements, such as dedicated outpatient services for older adults, may enhance utilization of public healthcare.

Quality and availability of healthcare professionals were also highlighted as important determinants of healthcare-seeking behavior. Participants emphasized the importance of effective communication, adequate consultation time, and availability of specialist services. These findings are consistent with previous studies indicating that inadequate communication and lack of specialist care in primary healthcare settings reduce patient satisfaction and trust.[13] Strengthening primary care services and improving provider–patient interaction can improve healthcare utilization among older adults.[14]

Financial insecurity was a major concern among participants. Many relied on savings (39%) or borrowing (31%) to meet healthcare expenses. High OOPE for inpatient care further adds to this burden, often pushing individuals into “hidden poverty.”[15] Hidden poverty refers to a condition in which households not classified as poor experience financial hardship due to healthcare spending, often resorting to coping strategies such as borrowing or asset depletion. Previous studies have similarly reported that hospitalization contributes substantially to OOPE among economically vulnerable populations.[16] The National Sample Survey 75^th round also reported high medical expenditure per hospitalization case in rural and urban India.[3] In the present study, irregular pension payments, inadequate insurance coverage, and lack of outpatient coverage further contributed to financial strain.

The higher OOPE observed among BPL households may reflect greater morbidity, delayed healthcare seeking, distress financing, and continued reliance on private healthcare despite socioeconomic disadvantage.

Healthcare neglect was another important finding. A significant proportion of participants reported considering or actually neglecting healthcare due to financial constraints. Qualitative insights suggest that, in addition to economic hardship, social factors such as family dynamics and perceived burden also influence such decisions. This reflects the complex interaction between financial and social determinants of healthcare utilization among older adults.

Infrastructure and accessibility challenges, particularly related to transportation, were also evident. Participants reported difficulties in using public transport and poor road conditions, which act as barriers to accessing healthcare services. These findings are consistent with existing evidence highlighting the importance of age-friendly infrastructure in improving healthcare access.[17]

Social support and access to accurate health information also play a crucial role in healthcare utilization. Participants reported instances of misinformation and mistrust in public healthcare, along with dependence on family support. Strengthening community-based awareness programs and improving trust in public healthcare systems may help reduce unnecessary OOPE and improve healthcare-seeking behavior.[18]

Overall, both quantitative and qualitative findings from this study indicate that the current healthcare financing mechanisms and service delivery systems seem to be inadequate to meet the needs of older adults in rural Kerala. Addressing financial, structural, and social barriers is essential to reducing OOPE and improving equitable access to healthcare.

The mixed method findings were integrated using a convergent interpretation. Quantitative results quantified the financial burden, whereas qualitative findings explained the contextual reasons underlying expenditure patterns, indicating strong complementarity between the two strands.

Enhancing public healthcare services and expanding insurance coverage to include clinic visits, hospital stays, medications, diagnostics, and transportation could be beneficial. Targeted financial support for low-income families can lessen financial burdens and promote fair access to healthcare in old age. There is a notable need to revisit and improve how healthcare for older adults is financed. Governments, including both local self-governments and state governments, should hold discussions with stakeholders on this issue. Both qualitative and quantitative parts of the study results indicate that the options for senior care in Kerala are insufficient and the OOPE burden is high.

New funding strategies for health and social care for older adults should be formulated to tackle high OOPE. For Kerala and India, increasing public funding and establishing affordable, effective services are crucial priorities. As Kerala faces rapid demographic aging, these insights offer valuable guidance. Ensuring the future of elder care involves adopting cost-efficient models and boosting public financial support.

Enhancing outreach services and making health and social care more accessible to those in need are crucial. Efforts should aim at reducing indirect costs such as travel, caregiver time, and work disruptions. Local authorities should be encouraged to develop and implement services tailored to the specific health and social needs of older adults within their communities. Community health workers, like ASHAs, can play a vital role in identifying unmet needs among older adults and connecting them with suitable services. It is evident that a care gap exists for older community members. Redefining senior care by lowering costs and improving outreach is essential for progress. Expanding specialized services like “Vayomithram” can also be considered an additional strategy.

Limitations of the study

• The study relied on self-reported data for healthcare expenditure and healthcare-seeking behavior, which are subject to recall bias. Participants, particularly older adults, may have had difficulty accurately recalling past expenses or events, leading to potential underestimation or overestimation of OOPE.

• The study was carried out in a single panchayat, which may not fully reflect the diversity in socioeconomic conditions, healthcare access, and expenditure patterns across other regions. This limits the external validity and broader applicability of the findings beyond similar local contexts.

• Only six in-depth interviews were conducted as part of the qualitative component. While these provided useful insights, the small number may have limited the range of perspectives captured.

• The study did not capture the co-morbidity burden or the number of medications.

• Household consumption expenditure data were unavailable; therefore, impoverishment analysis and concentration-index analysis could not be undertaken. Residual confounding due to unmeasured comorbidity burden and medication count is also possible.

Key messages

High healthcare costs and out-of-pocket expenses have a negative impact on the healthcare of older adults. Proactive policies and mechanisms to finance senior care are urgently needed.

Conflicts of interest

There are no conflicts of interest.

Funding Statement

This study was supported by C. Achutha Menon - TR Chandra Dutt Fellowship.