Probability and amount of medicines expenditure according to health insurance status in Kenya: A household survey in eight counties

Willingness to pay brand premiums for generic medicines in Kenya: A bidding game experiment

BACKGROUND

Recent growth in the market share of higher priced branded generic medicines in low- and middle-income countries (LMICs) has raised concerns around affordability and access. We examined consumer willingness to pay (WTP) for branded versus unbranded generic non-communicable disease (NCD) medicines in Kenya.

METHODS

We randomly assigned NCD patients to receive a hypothetical offer for either a Novartis Access-branded medicine or for an unbranded generic equivalent. We then analysed WTP data captured using a bidding game methodology.

RESULTS

We found that WTP for Novartis Access medicines was on average 23% higher than for unbranded generic equivalents (p = 0.009). The WTP brand premium was driven almost entirely by wealthier patients.

CONCLUSIONS

Our findings suggest that the dominance of branded generics in LMICs like Kenya reflect in part consumer preferences for these medicines. Governments and other health sector actors may be justified in intervening to improve access to these medicines and equivalent non-branded generics, particularly for the poorest patients who appear to have no preference for branded medicines.

Factors related to women's use of health insurance cover in Navakholo, Kakamega County, Kenya: sub-county level results based on community household register

BACKGROUND

In concert with international commitments, the Government of Kenya identified Universal Health Coverage (UHC), mainly through the National Health Insurance Fund (NHIF), as one of its four priority agenda to enable its populations access health care without financial duress. Nevertheless, only about 19.5% of the Kenyan population is enrolled in any insurance health cover. Since 2016, Amref Health Africa and PharmAccess Foundation have been implementing the Innovative Partnership for Universal and Sustainable Healthcare (iPUSH) programme in Navakholo sub-county of Kakamega County. The main objective of this study is to examine use of health insurance cover among Women of Reproductive Age (WRA) in Navakholo sub-county, Kakamega County.

METHODS

We analysed data captured during household registration conducted in February 2021 which embraced a question on use of health insurance cover including NHIF. The dataset consisted 148,957 household members within 32,262 households, 310 villages, and 32 community health units. The data had been collected using mobile phones by trained Community Health Volunteers (CHVs) and transmitted using the Amref electronic data management platform and reposited in a server. Data were analysed through frequency distributions and logistic regression (descriptive and causal methods) using STATA software.

RESULTS

Insurance coverage, all providers included, in Navakholo sub-county stood at 11% among women aged 15-49 years. This is much lower than the national aggregate reported from sample surveys, but higher than the 7% found in the same survey for the region where Navakholo is situated. Social determinant variables - age, perceived condition of the household, and wealth ranking - are highly significant in the relationship with use of health insurance cover while measures of reproductive health and health vulnerability are not.

CONCLUSION

In Navakholo sub-county of Western Kenya, all-health-insurance coverage is lower than the national aggregate estimated from sample surveys. Age, perception of household condition, and wealth ranking are very significantly related to use of a health insurance cover. Frequent household registrations should be conducted to help monitor the trends and impact of health insurance campaigns. Training - upstream and downstream - on community household registration and data processing should be conducted to arrive at better quality data.

A public-private partnership based model for regulating out-of-pocket expenditures to strengthen primary care system

In developing countries like India, the cost of health care is largely borne by patient out-of-pocket payments. Recent studies have reported that patients skip public-funded clinics providing free consultation for distant private care providers. Some of the reasons identified for such behaviour include longer waiting times, perception regarding quality of care, etc. Therefore, optimal allocation of existing and new capacity is critical for a greater public interest. This article presents a decision-making framework towards this intent for strengthening the existing government primary healthcare network. In this article, a mixed-integer linear programing (MILP) model is developed for optimal reconfiguration of the existing government primary healthcare network to minimise patient out-of-pocket expenditures (OOPE). The model involves three types of facilities: Primary Health Centre (PHC), Community Health Centre (CHC), and Private OPD (outpatient department). Implementation of the proposed model can help in reducing out-of-pocket expenditures. The optimization model proposed in the article is unique as it incorporates for the first time, patient out-of-pocket expenditure, capacity reconfiguration, and public-private partnership decisions in the primary healthcare system. A solution algorithm is also proposed for the optimization model. The model would be useful for theory development and also in policy-making.