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.

Intersecting sex-related inequalities in self-reported testing for and prevalence of Non-Communicable Disease (NCD) risk factors in Kerala.

BACKGROUND: Non-Communicable Diseases (NCDs) are among India's top burdens, particularly in states like Kerala, which is at an advanced stage of the epidemiological transition. Evidence in India points towards intersectional inequalities in risk factors of NCDs and testing, both of which are understudied in Kerala. We estimated the self-reported testing and prevalence of key NCD risk factors-blood pressure (BP) and blood glucose (BG) comparing Kerala men and women across educational, wealth, religion, as well as caste and tribal status subgroups. METHOD: A multistage random sample survey of 3398 women and 2982 men aged 30 years and over was administered in 4 districts of Kerala from July to October 2019. Descriptive analysis for men and women was undertaken using survey weights. Slope index of Inequality and Relative Concentration Index for wealth and education related inequalities, and, Weighted Mean Difference from Mean and Index of Disparity for caste and tribal status, as well as religion related inequalities were calculated using World Health Organisation's Health Equity Assessment Toolkit Plus and Stata 12. RESULTS: A significantly higher proportion of women reported BP and BG testing by medical personnel in the previous year than men (BP Testing among Women (BPTw): 90.3% vs BP Testing among Men (BPTM):80.8%, BG Testing among Women (BGTw): 86.2% vs BG Testing among Women (BGTM):78.3%). Among those tested, more women (11.2%) than men (7.9%) reported High Blood Pressure (HBP) but not High Blood Glucose (HBG). Testing for BP was concentrated among less-educated women while BG testing was concentrated among both less educated women and men. HBP and HBG were concentrated among less educated and wealthier groups. Although sex differences were insignificant across caste and tribal status and religion subgroups, magnitude of inequalities was high for HBP and HBG. CONCLUSION: Distinct patterns of sex inequalities were present in self-reported testing and prevalence of NCD risk factors in Kerala. Education and wealth seem to be associated with testing while prevalence appeared to vary by religious groups. Given the low rates of illiteracy, it is encouraging but maybe a data artefact that a small population of less-educated persons was getting tested; however, exclusion of poor groups and inequalities by other dimensions raise concerns. Further exploration is needed to understand underlying mechanisms of these inequalities to ensure we leave no one behind.

Intersectional social-economic inequalities in breast cancer screening in India: analysis of the National Family Health Survey.

BACKGROUND: Breast cancer incidence rates are increasing in developing countries including India. With 1.3 million new cases of cancer been diagnosed annually, breast cancer is the most common women's cancer in India. India's National Family Health Survey (NFHS-4) data 2015-2016 shows that only 9.8% of women between the ages of 15 and 49 had ever undergone breast examination (BE). Further, access to screening and treatment is unequally distributed, with inequalities by socio-economic status. It is unclear, however, if socio-economic inequalities in breast examination are similar across population subgroups. METHODS: We compared BE coverage in population sub-groups categorised by place of residence, religion, caste/tribal groups, education levels, age, marital status, and employment status in their intersection with economic status in India. We analysed data for 699,686 women aged 15-49 using the NFHS-4 data set conducted during 2015-2016. Descriptive (mean, standard errors, and confidence intervals) of women undergoing BE disaggregated by dimensions of inequality (education, caste/tribal groups, religion, place of residence) and their intersections with wealth were computed with national weights using STATA 12. Chi-square tests were performed to assess the association between socio-demographic factors and breast screening. Additionally, the World Health Organisation's Health Equity Assessment Toolkit Plus was used to compute summary measures of inequality: Slope index for inequality (SII) and Relative Concentration Indices (RCI) for each intersecting dimension. RESULTS: BE coverage was concentrated among wealthier groups regardless of other intersecting population subgroups. Wealth-related inequalities in BE coverage were most pronounced among Christians (SII; 20.6, 95% CI: 18.5-22.7), married (SII; 14.1, 95% CI: 13.8-14.4), employed (SII: 14.6, 95%CI: 13.9, 15.3), and rural women (SII; 10.8, 95% CI: 10.5-11.1). Overall, relative summary measures (RCI) were consistent with our absolute summary measures (SII). CONCLUSIONS: Breast examination coverage in India is concentrated among wealthier populations across population groups defined by place of residence, religion, age, employment, and marital status. Apart from this national analysis, subnational analyses may also help identify strategies for programme rollout and ensure equity in women's cancer screening.

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.

Monitoring Universal Health Coverage reforms in primary health care facilities: Creating a framework, selecting and field-testing indicators in Kerala, India.

In line with the Sustainable Development Goals (SDGs) and the target for achieving Universal Health Coverage (UHC), state level initiatives to promote health with "no-one left behind" are underway in India. In Kerala, reforms under the flagship Aardram mission include upgradation of Primary Health Centres (PHCs) to Family Health Centres (FHCs, similar to the national model of health and wellness centres (HWCs)), with the proactive provision of a package of primary care services for the population in an administrative area. We report on a component of Aardram's monitoring and evaluation framework for primary health care, where tracer input, output, and outcome indicators were selected using a modified Delphi process and field tested. A conceptual framework and indicator inventory were developed drawing upon literature review and stakeholder consultations, followed by mapping of manual registers currently used in PHCs to identify sources of data and processes of monitoring. The indicator inventory was reduced to a list using a modified Delphi method, followed by facility-level field testing across three districts. The modified Delphi comprised 25 participants in two rounds, who brought the list down to 23 approved and 12 recommended indicators. Three types of challenges in monitoring indicators were identified: appropriateness of indicators relative to local use, lack of clarity or procedural differences among those doing the reporting, and validity of data. Further field-testing of indicators, as well as the revision or removal of some may be required to support ongoing health systems reform, learning, monitoring and evaluation.