Factors associated with misreporting in performance-based financing in Burkina Faso: Implications for risk-based verification

What Factors Explain Low Adoption of Digital Technologies for Health Financing in an Insurance Setting? Novel Evidence From a Quantitative Panel Study on IMIS in Tanzania

BACKGROUND

Digital information management systems for health financing are implemented on the assumption thatdigitalization, among other things, enables strategic purchasing. However, little is known about the extent to which thesesystems are adopted as planned to achieve desired results. This study assesses the levels of, and the factors associated withthe adoption of the Insurance Management Information System (IMIS) by healthcare providers in Tanzania.

METHODS

Combining multiple data sources, we estimated IMIS adoption levels for 365 first-line health facilities in2017 by comparing IMIS claim data (verified claims) with the number of expected claims. We defined adoption as abinary outcome capturing underreporting (verified

RESULTS

We found a median (interquartile range [IQR]) difference of 77.8% (32.7-100) between expected and verifiedclaims, showing a consistent pattern of underreporting across districts, regions, and months. Levels of underreportingvaried across regions (ANOVA: F=7.24, P<.001) and districts (ANOVA: F=4.65, P<.001). Logistic regression resultsshowed that higher service volume, share of people insured, and greater distance to district headquarter were associatedwith a higher probability of underreporting.

CONCLUSION

Our study shows that the adoption of IMIS in Tanzania may be sub-optimal and far from policy-makers'expectations, limiting its capacity to provide the necessary information to enhance strategic purchasing in the healthsector. Countries and agencies adopting digital interventions such as openIMIS to foster health financing reform areadvised to closely track their implementation efforts to make sure the data they rely on is accurate. Further, our studysuggests organizational and infrastructural barriers beyond the software itself hamper effective adoption.

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Key Words

• Adoption
• Digital Health Intervention
• Health Financing
• Health Insurance
• Strategic Purchasing
• Tanzania

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MESH Headings

• Humans
• Tanzania
• Healthcare Financing
• Digital Technology
• Insurance, Health
• Universal Health Insurance

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Affiliation(s)

Leon Schuetze Heidelberg Institute of Global Health, Medical Faculty and University Hospital, University of Heidelberg, Heidelberg, Germany
Siddharth Srivastava Swiss Tropical and Public Health Institute (Swiss TPH), Basel, Switzerland University of Basel, Basel, Switzerland
Naasegnibe Kuunibe Heidelberg Institute of Global Health, Medical Faculty and University Hospital, University of Heidelberg, Heidelberg, Germany Faculty of Integrated Development Studies, University for Development Studies, Wa, Ghana
Elizeus Josephat Rwezaula Health Promotion and System Strengthening Project (HPSS), Dodoma, Tanzania
Abdallah Missenye Kongwa District Council, Dodoma, Tanzania
Manfred Stoermer Swiss Tropical and Public Health Institute (Swiss TPH), Basel, Switzerland University of Basel, Basel, Switzerland
Manuela De Allegri Heidelberg Institute of Global Health, Medical Faculty and University Hospital, University of Heidelberg, Heidelberg, Germany

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Do Targeted User Fee Exemptions Reach the Ultra-Poor and Increase their Healthcare Utilisation? A Panel Study from Burkina Faso

Background: A component of the performance-based financing intervention implemented in Burkina Faso was to provide free access to healthcare via the distribution of user fee exemption cards to previously identified ultra-poor. This study examines the factors that led to the receipt of user fee exemption cards, and the effect of card possession on the utilisation of healthcare services. Methods: A panel data set of 1652 randomly selected ultra-poor individuals was used. Logistic regression was applied on the end line data to identify factors associated with the receipt of user fee exemption cards. Random-effects modelling was applied to the panel data to determine the effect of the card possession on healthcare service utilisation among those who reported an illness six months before the surveys. Results: Out of the ultra-poor surveyed in 2017, 75.51% received exemption cards. Basic literacy (p = 0.03), living within 5 km from a healthcare centre (p = 0.02) and being resident in Diébougou or Gourcy (p = 0.00) were positively associated with card possession. Card possession did not increase health service utilisation (β = −0.07; 95% CI = −0.45; 0.32; p = 0.73). Conclusion: A better intervention design and implementation is required. Complementing demand-side strategies could guide the ultra-poor in overcoming all barriers to healthcare access.