Gender-specific inequalities in coverage of Publicly Funded Health Insurance Schemes in Southern States of India: evidence from National Family Health Surveys.

BACKGROUND: Publicly Funded Health Insurance Schemes (PFHIS) are intended to play a role in achieving Universal Health Coverage (UHC). In countries like India, PFHISs have low penetrance and provide limited coverage of services and of family members within households, which can mean that women lose out. Gender inequities in relation to financial risk protection are understudied. Given the emphasis being placed on achieving UHC for all in India, this paper examined intersecting gender inequalities and changes in PFHIS coverage in southern India, where its penetrance is greater and of longer duration. DATA AND METHODS: This study used the fourth (NFHS-4, 2015-16) and fifth (NFHS-5, 2019-21) rounds of India's National Family Health Survey for five southern states: namely, Andhra Pradesh, Karnataka, Kerala, Tamil Nadu, and Telangana. The World Health Organization's Health Equity Assessment Toolkit (HEAT) Plus and Stata were used to analyse PFHIS coverage disaggregated by seven dimensions of inequality. Ratios and differences for binary dimensions; Between Group Variance and Theil Index for unordered dimensions; Absolute and Relative Concentration Index (RCI) for ordered dimensions were computed separately for women and men. RESULTS: Overall, PFHIS coverage increased significantly (p < 0.001) among women and men in Andhra Pradesh, and Kerala from NFHS-4 to NFHS-5. Overall, men had higher PFHIS coverage than women, especially in Andhra Pradesh, Tamil Nadu, and Telangana in both surveys. In both absolute and relative terms, PFHIS coverage was concentrated among older women and men across all states; age-related inequalities were higher among women than men in both surveys in Andhra Pradesh, Kerala, and Telengana. The magnitude of education-related inequalities was twice as high as among women in Telangana (RCINFHS-4: -12.23; RCINFHS-5: -9.98) and Andhra Pradesh (RCINFHS-4: -8.05; RCINFHS-5: -7.84) as compared to men in Telangana (RCINFHS-4: -5.58; RCINFHS-5: -2.30) and Andhra Pradesh (RCINFHS-4: -4.40; RCINFHS-5: -3.12) and these inequalities remained in NFHS-5, suggesting that lower education level women had greater coverage. In the latter survey, a high magnitude of wealth-related inequality was observed in women (RCINFHS-4: -15.78; RCINFHS-5: -14.36) and men (RCINFHS-4: -20.42; RCINFHS-5: -13.84) belonging to Kerala, whereas this inequality has decreased from NFHS-4 to NFHS-5., again suggestive of greater coverage among poorer populations. Caste-related inequalities were higher in women than men in both surveys, the magnitude of inequalities decreased between 2015-16 and 2019-20. CONCLUSIONS: We found gender inequalities in self-reported enrolment in southern states with long-standing PFHIS. Inequalities favoured the poor, uneducated and elderly, which is to some extend desirable when rolling out a PFHIS intended for harder to reach populations. However, religion and caste-based inequalities, while reducing, were still prevalent among women. If PFHIS are to truly offer financial risk protection, they must address the intersecting marginalization faced by women and men, while meeting eventual goals of risk pooling, indicated by high coverage and low inequality across population sub-groups.

Who are the vulnerable, and how do we reach them? Perspectives of health system actors and community leaders in Kerala, India.

BACKGROUND: Among the core principles of the 2030 agenda of Sustainable Development Goals (SDGs) is the call to Leave no One behind (LNOB), a principle that gained resonance as the world contended with the COVID-19 pandemic. The south Indian state of Kerala received acclaim globally for its efforts in managing COVID-19 pandemic. Less attention has been paid, however, to how inclusive this management was, as well as if and how those "left behind" in testing, care, treatment, and vaccination efforts were identified and catered to. Filling this gap was the aim of our study. METHODS: We conducted In-depth interviews with 80 participants from four districts of Kerala from July to October 2021. Participants included elected local self-government members, medical and public health staff, as well as community leaders. Following written informed consent procedures, each interviewee was asked questions about whom they considered the most "vulnerable" in their areas. They were also asked if there were any special programmes/schemes to support the access of "vulnerable" groups to general and COVID related health services, as well as other needs. Recordings were transliterated into English and analysed thematically by a team of researchers using ATLAS.ti 9.1 software. RESULTS: The age range of participants was between 35 and 60 years. Vulnerability was described differentially by geography and economic context; for e.g., fisherfolk were identified in coastal areas while migrant labourers were considered as vulnerable in semi-urban areas. In the context of COVID-19, some participants reflected that everyone was vulnerable. In most cases, vulnerable groups were already beneficiaries of various government schemes within and beyond the health sector. During COVID, the government prioritized access to COVID-19 testing and vaccination among marginalized population groups like palliative care patients, the elderly, migrant labourers, as well as Scheduled Caste and Scheduled Tribes communities. Livelihood support like food kits, community kitchen, and patient transportation were provided by the LSGs to support these groups. This involved coordination between health and other departments, which may be formalised, streamlined and optimised in the future. CONCLUSION: Health system actors and local self-government members were aware of vulnerable populations prioritized under various schemes but did not describe vulnerable groups beyond this. Emphasis was placed on the broad range of services made available to these "left behind" groups through interdepartmental and multi-stakeholder collaboration. Further study (currently underway) may offer insights into how these communities - identified as vulnerable - perceive themselves, and whether/how they receive, and experience schemes designed for them. At the program level, inclusive and innovative identification and recruitment mechanisms need to be devised to identify populations who are currently left behind but may still be invisible to system actors and leaders.

Monitoring the Family Health Centres in Kerala, India: Findings from a facility survey.

Introduction: Kerala, a south Indian state, has often been cited globally as a model for better health outcomes at low cost but faces unique challenges in achieving Universal Health Coverage (UHC). To propel the efforts in achieving UHC, the Government of Kerala announced the "Aardram" health reform initiative, emphasising improving the quality of primary care service delivery. The reforms started in 2017, and in the first stage, 170 of 848 Primary Health Centres (PHCs) were upgraded to Family Health Centres (FHCs). The facilities were provided with additional doctors, nurses, and paramedical staff; the working hours were extended, and the range of services offered increased. In support of these processes, we carried out a facility assessment to assess differences between upgraded FHCs and existing PHCs. Materials and Methods: We conducted a facility-based cross-sectional assessment in eight primary care facilities of Kerala, FHC (N=4) and PHCs (N=4) from June to October 2019. A structured questionnaire covering utilisation and coverage of selected priority services for various populations and health outcome data was filled out by health staff to report data for the financial year 2018-19. Data were analysed in Microsoft Excel spreadsheets for easy analysis and replication by state stakeholders. Results: Coverage indicators such as full antenatal care and full immunization coverage were not appreciably different in FHCs as compared to PHCs. However, key reform-related differences were observed. On average, FHCs had 0.8 medical officers and one staff nurse per 10,000 population, whereas PHCs had 0.7 medical officers and less than 0.4 staff nurses per 10,000 population, even as the size of populations served by these human resources varied greatly across both types of facilities. The number of outpatient department visits per 10,000 population annually was 11,343 persons in FHCs and 9,580 persons in PHCs. FHCs also provided additional services such as screening for depression and chronic obstructive pulmonary disorders. Conclusion: Aardram primary healthcare reforms are still in their early days and appear to be associated with improved service coverage at the institutional level. However, some patterns are uneven: reforms should be carefully documented, and population-level impacts monitored over time.

Decomposing socioeconomic inequality in blood pressure and blood glucose testing: evidence from four districts in Kerala, India.

BACKGROUND: Non-Communicable Diseases (NCDs) constitute a significant danger to the nation's public health system, both in terms of morbidity and mortality, as well as the financial burden they inflict. Kerala is undergoing an epidemiologic transition, which has significantly impacted the state's morbidity and mortality figures. For decades, the state has been putting in place myriad programs to reduce the burden of NCDs across population groups. Socioeconomic inequalities in NCD testing have been documented in India, although they are understudied in Kerala. The study aimed to estimate and characterize districtwise socioeconomic inequality in Blood Pressure (BP) and Blood Glucose (BG) testing. METHODS: A cross-sectional household survey was conducted between July-October 2019 in Kasaragod, Alappuzha, Kollam and Thiruvananthapuram districts of Kerala, India. A total of 6383 participants aged 30 years and above were interviewed using multistage random sampling. Descriptive statistics were derived district-wise. We computed ratios, differences, equiplots, and Erreygers concentration indices for each district to measure socioeconomic inequality in BP and BG testing. Erreygers decomposition techniques were used to estimate the relative contribution of covariates to socioeconomic inequality. RESULTS: There was a significant concentration of BP and BG testing favouring wealthier quintiles in Alappuzha, Kollam, and Thiruvananthapuram districts. The inequality in BP and BG testing was highest in Thiruvananthapuram (0.087 and 0.110), followed by Kollam (0.077 and 0.090), Alappuzha (0.083 and 0.073) and Kasaragod (0.026 and 0.056). Decomposition analysis revealed that wealth quintile and education contributed substantially to socioeconomic inequality in BP and BG testing in all four districts. It was also found that family history of NCDs significantly contributed to observed socioeconomic inequality in BP testing (29, 11, 16, and 27% in Kasaragod, Alappuzha, Kollam, and Thiruvananthapuram, respectively). Similarly, in BG testing, family history of NCDs substantially contributed to observed socioeconomic inequality, explaining 16-17% in Kasaragod, Alappuzha, Kollam, and Thiruvananthapuram respectively of the total inequality. CONCLUSION: While the magnitude of socioeconomic inequality in NCD risk factor testing did not appear to be very high in four Kerala districts, although levels were statistically significant in three of them. Greater exploration is needed on how education and caste contribute to these inequalities and their relationship to NCD risk factors such as family history. From such analyses, we may be able to identify entry points to mitigate inequalities in testing access, as well as burden.

Field-testing of primary health-care indicators, India.

OBJECTIVE: To develop a primary health-care monitoring framework and health outcome indicator list, and field-test and triangulate indicators designed to assess health reforms in Kerala, India, 2018-2019. METHODS: We used a modified Delphi technique to develop a 23-item indicator list to monitor primary health care. We used a multistage cluster random sampling technique to select one district from each of four district clusters, and then select both a family and a primary health centre from each of the four districts. We field-tested and triangulated the indicators using facility data and a population-based household survey. FINDINGS: Our data revealed similarities between facility and survey data for some indicators (e.g. low birth weight and pre-check services), but differences for others (e.g. acute diarrhoeal diseases in children younger than 5 years and blood pressure screening). We made four critical observations: (i) data are available at the facility level but in varying formats; (ii) established global indicators may not always be useful in local monitoring; (iii) operational definitions must be refined; and (iv) triangulation and feedback from the field is vital. CONCLUSION: We observe that, while data can be used to develop indices of progress, interpretation of these indicators requires great care. In the attainment of universal health coverage, we consider that our observations of the utility of certain health indicators will provide valuable insights for practitioners and supervisors in the development of a primary health-care monitoring mechanism.

A simple colorimetric method for estimation of tramadol hydrochloride in pure and tablet dosage forms.

OBJECTIVE: The objective of this study was to develop and validate a simple method for estimation of tramadol hydrochloride (TH) in pure and pharmaceutical dosage forms using a colorimeter. MATERIALS AND METHODS: TH on reaction with Eriochrome Black T in the presence of acetate buffer at pH 3.5 forms a colored complex. This complex was extracted with a fixed volume of chloroform. The optical density of this colored complex was measured against reagent blank using a colorimeter at 520 nm. RESULTS: Beer's law was obeyed with a good correlation coefficient (0.999) in the concentration range of 2.5 µg/ml to 10 µg/ml. Drug content estimation and recovery studies carried out on commercial tablet dosage forms demonstrated the accuracy of the method and that excipients do not cause interference. Precision and robustness were measured and found to be acceptable (% relative standard deviation <2%). CONCLUSION: The proposed method can be used for the rapid determination of TH content in tablets at a health-care provider level using already available staff and equipment.

Investigating a community-wide outbreak of hepatitis a in India.

BACKGROUND: There was an outbreak of acute hepatitis in Mylapore village, Kollam district, Kerala, southern India during February to June 2013. An outbreak investigation was initiated with the objective of describing the epidemiological features of the hepatitis outbreak. MATERIALS AND METHODS: House-to-house visits were undertaken to identify symptomatic cases. The outbreak was described in terms of person, place and time. Hypothesis was generated based on findings from descriptive study, laboratory investigation of water samples, and environmental observations. A case-control study was designed to test the hypothesis. Chi-square test, univariate analysis, and logistic regression to identify the risk factors associated with hepatitis A infection were done. RESULTS: Line list generated consisted of 45 cases. Attack rate was the highest among the age group 15-24 years (4.6%) followed by 5-14 years (3.1%). The geographical distribution of the cases suggested a clustering around the water supply through the pipeline and epidemic curve showed a sharp rise in cases suggestive of a common source outbreak. Water samples collected form pipeline showed evidence of fecal contamination and absence of residual chlorine. In the case-control study, having consumed water from the pipeline (odds ratio: 9.01 [95% confidence interval: 2.16-37.61]) was associated with the hepatitis A cases. CONCLUSION: The time frame of disease occurrence, environmental observations, anecdotal evidences, laboratory results and results of the analytical study indicated the possibility of occurrence of hepatitis A outbreak as a result of pipe water contamination supplied from a bore well. The study warrants establishment of an efficient water quality surveillance system.