Does mobile renewal make health insurance more responsive to clients? A case study of the National Health Insurance Scheme in Ghana.

BACKGROUND: In 2018, Ghana's National Health Insurance Authority (NHIA) introduced a mobile strategy to enhance re-enrolment and improve client knowledge of their entitlements. This study investigated how Ghana's mobile strategy has influenced the NHIA's responsiveness to clients in terms of patient rights and entitlements, equity and satisfaction with health services. METHODS: We surveyed people (n=1700) in 6 districts who had renewed their insurance in the previous 12 months, using any strategy (mobile or manual). Multiple regression analysis examined correlation between individual characteristics and renewal modality. Policy documents on the mobile programme's design and focus group discussions (n=12) on people's experiences renewing their insurance were analysed thematically. RESULTS: While the mobile platform was designed for mobile National Health Insurance Scheme (NHIS) renewal and to provide information about insurance entitlements, few people surveyed (20%) knew about these informational features. Among those who renewed their NHIS coverage, 58% did so on the mobile renewal platform. Mobile renewal was high among those with tertiary education and those in the higher wealth quintiles. Mobile renewal was considered convenient, but required literacy in English, a phone and a mobile money wallet. For those who lacked some or all of these prerequisites but wanted to use mobile renewal, mobile vendors emerged as valued facilitators. CONCLUSION: The mobile platform has increased the responsiveness of Ghana's NHIS through offering clients a more convenient mechanism to renew their insurance policies. It does not, however, eliminate the one month waiting period for activating the card, does not provide prompts to reassure clients of their renewal and does not empower most clients with information on entitlements. To improve the adoption and use of the mobile renewal strategy, the NHIA should publicise the platform's information-sharing functions and explore formally engaging mobile vendors.

Challenges and experiences in linking community level reported out-of-pocket health expenditures to health provider recorded health expenditures: Experience from the iHOPE project in Northern Ghana.

Out of pocket health payment (OOPs) has been identified by the System of Health Accounts (SHA) as the largest source of health care financing in most low and middle-income countries. This means that most low and middle-income countries will rely on user fees and co-payments to generate revenue, rationalize the use of services, contain health systems costs or improve health system efficiency and service quality. However, the accurate measurement of OOPs has been challenged by several limitations which are attributed to both sampling and non-sampling errors when OOPs are estimated from household surveys, the primary source of information in LICs and LMICs. The incorrect measurement of OOP health payments can undermine the credibility of current health spending estimates, an otherwise important indicator for tracking UHC, hence there is the need to address these limitations and improve the measurement of OOPs. In an attempt to improve the measurement of OOPs in surveys, the INDEPTH-Network Household out-of-pocket expenditure project (iHOPE) developed new modules on household health utilization and expenditure by repurposing the existing Ghana Living Standards Survey instrument and validating these new tools with a 'gold standard' (provider data) with the aim of proposing alternative approaches capable of producing reliable data for estimating OOPs in the context of National Health Accounts and for the purpose of monitoring financial protection in health. This paper reports on the challenges and opportunities in using and linking household reported out-of-pocket health expenditures to their corresponding provider records for the purpose of validating household reported out-of-pocket health expenditure in the iHOPE project.

Effect of specificity of health expenditure questions in the measurement of out-of-pocket health expenditure: evidence from field experimental study in Ghana.

BACKGROUND: The effect of number of health items on out-of-pockets (OOPs) has been identified as a source of bias in measuring OOPs. Evidence comes mostly from cross-sectional comparison of different survey instruments to collect data on OOPs. Very few studies have attempted to validate these questionnaires, or distinguish bias arising from the comprehensiveness of the OOPs list versus specificity of OOPs questions. OBJECTIVES: This study aims to estimate biases arising from the specificity of OOPs questions by comparing provider and household's information. METHODS: A generic questionnaire to collect data on household's OOPs was developed following the nomenclature proposed in division 6 of the classification of household final consumption 2018. The four categories within such division are used to set the comprehensiveness of the OOPs list, the specificity within each category was tailored to the design of the nationally representative living standard survey in Ghana where a field experiment was conducted to test the validity of different versions. Households were randomised to 11, 44 or 56 health items. Using data from provider records as the gold standard, we compared the mean positive OOPs, and estimated the mean ratio and variability in the ratio of household expenditures to provider data for the individual households using the Bland-Altman method of assessing agreement. FINDINGS: We found evidence of a difference in the overall mean ratio in the specificity for OOPs in inpatient care and medications. Within each of these two categories, a more detailed disaggregation yielded lower OOPs estimates than less detailed ones. The level of agreement between household and provider OOPs also decreased with increasing specificity of health items. CONCLUSION: Our findings suggest that, for inpatient care and medications, systematically decomposing OOPs categories into finer subclasses tend to produce lower OOPs estimates. Less detailed items produced more accurate and reliable OOPs estimates in the context of a rural setting.