The Social Health Authority (SHA) has moved to defend its method of calculating health insurance contributions, following a hard-hitting investigation by Africa Uncensored that questioned the fairness and accuracy of the system.
At the centre of the debate is the Means Testing Instrument (MTI), a data-driven tool used to determine how much households contribute monthly to the Social Health Insurance Fund (SHIF), particularly those in the informal sector.
In a statement, SHA acknowledged the concerns raised by the exposé but maintained that the system is designed to promote equity.
“The Social Health Authority notes the concerns raised regarding the Means Testing Instrument utilised to determine SHIF contributions,” the agency said.
The MTI relies on Proxy Means Testing (PMT), which estimates household income based on various indicators, especially where formal income data is unavailable. This approach has, however, come under scrutiny after the investigation alleged significant inconsistencies in how contributions are calculated.
The authority defended the new model by contrasting it with the now-defunct National Health Insurance Fund (NHIF), arguing that the previous system disproportionately burdened low-income earners.
Under NHIF, SHA noted, a worker earning Ksh10,000 paid Ksh500 about 5 per cent of their income while someone earning Ksh1 million contributed just Ksh1,700, or roughly 0.17 per cent.
“This is where the system was punishing the poor for being poor,” SHA said.
Under the current framework, contributions are pegged at 2.75 per cent of household income, with a minimum monthly payment of Ksh300. According to SHA, more than half of formally employed contributors are now paying less than they did under NHIF.
However, the report from Africa Uncensored gives a different perspective. It reveals that the algorithm powering the tool might have some inherent problems, which will see poorer households overcharged while the income levels of richer people undercharged.
Furthermore, the report states that there is no proper income information on many people in Kenya, making it challenging for AI-powered assessments to accurately determine people’s economic standing. There is also a possibility of error margins of up to 80 to 90 percent, meaning a higher percentage of the poor and rich Kenyans will receive incorrect evaluations.
To counter the accusations, the authority cited its involvement in a collaborative effort among various organizations, such as research institutions, government agencies, development partners, and universities, to ensure that the errors were minimal.
On the other hand, it cited internal information that revealed that the system was helping poorer households more than anything else. As per the statement from the authority, 92 percent of the households in the informal sector using the model pay Ksh850 or less per month.
Within that group, 45 per cent contribute between Ksh300 and Ksh500, while 47 per cent fall within the Ksh501 to Ksh850 range.
The exposé also flagged concerns over approximately Ksh10.6 billion in questionable claims, including alleged payments to non-existent health facilities. SHA has dismissed the allegations, maintaining that its systems are robust and subject to ongoing oversight.
The exchange highlights growing scrutiny over Kenya’s transition to a new health financing model, with questions emerging about transparency, data accuracy and the role of technology in determining access to essential services.
