Examining inequalities in spatial access to national health insurance fund contracted facilities in Kenya.

BACKGROUND: Kenya aims to achieve universal health coverage (UHC) by 2030 and has selected the National Health Insurance Fund (NHIF) as the 'vehicle' to drive the UHC agenda. While there is some progress in moving the country towards UHC, the availability and accessibility to NHIF-contracted facilities may be a barrier to equitable access to care. We estimated the spatial access to NHIF-contracted facilities in Kenya to provide information to advance the UHC agenda in Kenya. METHODS: We merged NHIF-contracted facility data to the geocoded inventory of health facilities in Kenya to assign facility geospatial locations. We combined this database with covariates data including road network, elevation, land use, and travel barriers. We estimated the proportion of the population living within 60- and 120-minute travel time to an NHIF-contracted facility at a 1-x1-kilometer spatial resolution nationally and at county levels using the WHO AccessMod tool. RESULTS: We included a total of 3,858 NHIF-contracted facilities. Nationally, 81.4% and 89.6% of the population lived within 60- and 120-minute travel time to an NHIF-contracted facility respectively. At the county level, the proportion of the population living within 1-hour of travel time to an NHIF-contracted facility ranged from as low as 28.1% in Wajir county to 100% in Nyamira and Kisii counties. Overall, only four counties (Kiambu, Kisii, Nairobi and Nyamira) had met the target of having 100% of their population living within 1-hour (60 min) travel time to an NHIF-contracted facility. On average, it takes 209, 210 and 216 min to travel to an NHIF-contracted facility, outpatient and inpatient facilities respectively. At the county level, travel time to an NHIF-contracted facility ranged from 10 min in Vihiga County to 333 min in Garissa. CONCLUSION: Our study offers evidence of the spatial access estimates to NHIF-contracted facilities in Kenya that can inform contracting decisions by the social health insurer, especially focussing on marginalised counties where more facilities need to be contracted. Besides, this evidence will be crucial as the country gears towards accelerating progress towards achieving UHC using social health insurance as the strategy to drive the UHC agenda in Kenya.

Assessing the choice of National Health Insurance Fund contracted outpatient facilities in Kenya: A qualitative study.

OBJECTIVE: To assess National Health Insurance Fund (NHIF) members' level of understanding, experiences, and factors influencing their choice of NHIF-contracted outpatient facilities in Kenya. METHODS: We conducted a cross-sectional qualitative study with NHIF members in two purposefully selected counties (Nyeri and Makueni counties) in Kenya. We collected data through 15 focus group discussions with NHIF members. Data were analysed using a framework analysis approach. RESULTS: Urban-based NHIF members had a good understanding of the NHIF-contracted outpatient facility selection process and the approaches for choosing and changing providers, unlike their rural counterparts. While NHIF members were required to choose a provider before accessing care, the number of available alternative facilities was perceived to be inadequate. Finally, NHIF members identified seven factors they considered important when choosing an NHIF-contracted outpatient provider. Of these factors, the availability of drugs, distance from the household to the facility and waiting time at the facility until consultation were considered the most important. CONCLUSION: There is a need for the NHIF to prioritise awareness-raising approaches tailored to rural settings. Further, there is a need for the NHIF to contract more providers to both spur competition among providers and provide alternatives for members to choose from. Besides, NHIF members revealed the important factors they consider when selecting outpatient facilities. Consequently, NHIF should leverage the preferred factors when contracting healthcare providers. Similarly, healthcare providers should enhance the availability of drugs, reduce waiting times whilst improving their staff's attitudes which would improve user satisfaction and the quality of care provided.

Modelling the economic burden of SARS-CoV-2 infection in health care workers in four countries.

Health care workers (HCWs) experienced greater risk of SARS-CoV-2 infection during the COVID-19 pandemic. This study applies a cost-of-illness (COI) approach to model the economic burden associated with SARS-CoV-2 infections among HCWs in five low- and middle-income sites (Kenya, Eswatini, Colombia, KwaZulu-Natal province, and Western Cape province of South Africa) during the first year of the pandemic. We find that not only did HCWs have a higher incidence of COVID-19 than the general population, but in all sites except Colombia, viral transmission from infected HCWs to close contacts resulted in substantial secondary SARS-CoV-2 infection and death. Disruption in health services as a result of HCW illness affected maternal and child deaths dramatically. Total economic losses attributable to SARS-CoV-2 infection among HCWs as a share of total health expenditure ranged from 1.51% in Colombia to 8.38% in Western Cape province, South Africa. This economic burden to society highlights the importance of adequate infection prevention and control measures to minimize the risk of SARS-CoV-2 infection in HCWs.

The Effects of Health Purchasing Reforms on Equity, Access, Quality of Care, and Financial Protection in Kenya: A Narrative Review.

Kenya has implemented several health purchasing reforms to facilitate progress toward universal health coverage. We conducted a narrative review of peer-reviewed and grey literature to examine how these reforms have affected health system outcomes in terms of equity, access, quality of care, and financial protection. We categorized the purchasing reforms we identified into the areas of benefits specification, provider payment, and performance monitoring. We found that the introduction and expansion of benefit packages for maternity, outpatient, and specialized services improved responsiveness to population needs and enhanced protection from financial hardship. However, access to service entitlements was limited by inadequate awareness of the covered services among providers and lack of service availability at contracted facilities. Provider payment reforms increased health facilities' access to funds, which enhanced service delivery, quality of care, and staff motivation. But delays and the perceived inadequacy of payment rates incentivized negative provider behavior, which limited access to care and exposed patients to out-of-pocket payments. We found that performance monitoring reforms improved the quality assurance capacity of the public insurer and enhanced patient safety, service utilization, and quality of care provided by facilities. Although health purchasing reforms have improved access, quality of care, and financial risk protection to some extent in Kenya, they should be aligned and implemented jointly rather than as individual interventions. Measures that policymakers might consider include strengthening communication of health benefits, timely and adequate payment of providers, and enhancing health facility autonomy over the revenues they generate.

The economics of sex work and major sporting events: Learning from the 2010 FIFA World Cup in South Africa.

Risk-taking in sex work is related to financial gains from condom-protected and condomless-acts alongside vulnerabilities, including socio-economic factors, which influence the safety of sex workers. Large international sporting events have been shown to significantly impact the economies of host countries, but there is a dearth of studies that examine how major sporting events may affect the economics of sex work and the risks taken by sex workers and clients. This study examines the determinants of the price of commercial sex alongside the price premium for and correlates of, condomless sex before, during and after the 2010 world cup in South Africa. We analysed data from three phases of repeated cross-sectional surveys with sex workers. Bivariate and multivariable logistic regression models were fitted to examine the predictors of condomless sex. We also fitted fixed-effect regression models to examine the determinants of the price of commercial sex across each survey phase. Findings suggest that the price of sex was higher during the world cup compared to before and after, whilst the price premium for condomless-sex increased from 36% before the world cup to 40% (p-value<0.001) and 57% (p-value<0.001) during and after the world cup, respectively. Across the survey phases, anal, oral or masturbation sex were more likely to be supplied without a condom compared to vaginal sex. The type of sex was the primary determinant of the price of sex across all phases. We show indicative evidence that the 2010 world cup was associated with an increase in the price of sex and supply of condomless-sex. Although these findings should be interpreted as associations rather than causal relationships, we recommend that countries with substantial sex-worker populations that host major events shouldexplicitly consider the context and structures of sex work, and promote client-focused safe-sex-interventions that explicitly consider the economic pressures faced by sexworkers to provide riskier acts, to minimise health impacts.

The burden of catastrophic and impoverishing health expenditure in Armenia: An analysis of Integrated Living Conditions Surveys, 2014-2018.

Armenia's health spending is characterized by low public spending and high out-of-pocket expenditure (OOP), which not only poses a financial barrier to accessing healthcare for Armenians but can also impoverish them. We analyzed Armenia's Integrated Living Conditions Surveys 2014-2018 data to assess the incidence and correlates of catastrophic health expenditure (CHE) and impoverishment. Households were considered to have incurred CHE if their annual OOP exceeded 40 percent of the per capita annual household non-food expenditure. We assessed impoverishment using the US$1.90 per person per-day international poverty line and the US$5.50 per person per-day upper-middle-income country poverty line. Logistic regression models were fitted to assess the correlates of CHE and impoverishment. We found that the incidence of CHE peaked in 2017 before declining in 2018. Impoverishment decreased until 2017 before rising in 2018. After adjusting for sociodemographic factors, households were more likely to incur CHE if the household head was older than 34 years, located in urban areas, had at least one disabled member, and had at least one member with hypertension. Households with at least one hypertensive member or who resided in urban areas were more likely to be impoverished due to OOP. Paid employment and high socioeconomic status were protective against both CHE and impoverishment from OOP. This detailed analysis offers a nuanced insight into the trends in Armenia's financial risk protection against catastrophic and impoverishing health expenditures, and the groups predominantly affected. The incidence of CHE and impoverishment in Armenia remains high with a higher incidence among vulnerable groups, including those living with chronic disease, disability, and the unemployed. Armenia should consider different mechanisms such as subsidizing medication and hospitalization costs for the poorest to alleviate the burden of OOP.

Examining the cost-effectiveness of personal protective equipment for formal healthcare workers in Kenya during the COVID-19 pandemic.

BACKGROUND: Healthcare workers are at a higher risk of COVID-19 infection during care encounters compared to the general population. Personal Protective Equipment (PPE) have been shown to protect COVID-19 among healthcare workers, however, Kenya has faced PPE shortages that can adequately protect all healthcare workers. We, therefore, examined the health and economic consequences of investing in PPE for healthcare workers in Kenya. METHODS: We conducted a cost-effectiveness and return on investment (ROI) analysis using a decision-analytic model following the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) guidelines. We examined two outcomes: 1) the incremental cost per healthcare worker death averted, and 2) the incremental cost per healthcare worker COVID-19 case averted. We performed a multivariate sensitivity analysis using 10,000 Monte Carlo simulations. RESULTS: Kenya would need to invest $3.12 million (95% CI: 2.65-3.59) to adequately protect healthcare workers against COVID-19. This investment would avert 416 (IQR: 330-517) and 30,041 (IQR: 7243 - 102,480) healthcare worker deaths and COVID-19 cases respectively. Additionally, such an investment would result in a healthcare system ROI of $170.64 million (IQR: 138-209) - equivalent to an 11.04 times return. CONCLUSION: Despite other nationwide COVID-19 prevention measures such as social distancing, over 70% of healthcare workers will still be infected if the availability of PPE remains scarce. As part of the COVID-19 response strategy, the government should consider adequate investment in PPE for all healthcare workers in the country as it provides a large return on investment and it is value for money.

Indirect health effects of the COVID-19 pandemic in Kenya: a mixed methods assessment.

BACKGROUND: The COVID-19 pandemic and country measures to control it can lead to negative indirect health effects. Understanding these indirect health effects is important in informing strategies to mitigate against them. This paper presents an analysis of the indirect health effects of the pandemic in Kenya. METHODS: We employed a mixed-methods approach, combining the analysis of secondary quantitative data obtained from the Kenya Health Information System database (from January 2019 to November 2020) and a qualitative inquiry involving key informant interviews (n = 12) and document reviews. Quantitative data were analysed using an interrupted time series analysis (using March 2020 as the intervention period). Thematic analysis approach was employed to analyse qualitative data. RESULTS: Quantitative findings show mixed findings, with statistically significant reduction in inpatient utilization, and increase in the number of sexual violence cases per OPD visit that could be attributed to COVID-19 and its mitigation measures. Key informants reported that while financing of essential health services and domestic supply chains were not affected, international supply chains, health workforce, health infrastructure, service provision, and patient access were disrupted. However, the negative effects were thought to be transient, with mitigation measures leading to a bounce back. CONCLUSION: Finding from this study provide some insights into the effects of the pandemic and its mitigation measures in Kenya. The analysis emphasizes the value of strategies to minimize these undesired effects, and the critical role that routine health system data can play in monitoring continuity of service delivery.

Examining the level and inequality in health insurance coverage in 36 sub-Saharan African countries.

INTRODUCTION: Low/middle-income countries (LMICs) in sub-Saharan Africa (SSA) are increasingly turning to public contributory health insurance as a mechanism for removing financial barriers to access and extending financial risk protection to the population. Against this backdrop, we assessed the level and inequality of population coverage of existing health insurance schemes in 36 SSA countries. METHODS: Using secondary data from the most recent Demographic and Health Surveys, we computed mean population coverage for any type of health insurance, and for specific forms of health insurance schemes, by country. We developed concentration curves, computed concentration indices, and rich-poor differences and ratios to examine inequality in health insurance coverage. We decomposed the concentration index using a generalised linear model to examine the contribution of household and individual-level factors to the inequality in health insurance coverage. RESULTS: Only four countries had coverage levels with any type of health insurance of above 20% (Rwanda-78.7% (95% CI 77.5% to 79.9%), Ghana-58.2% (95% CI 56.2% to 60.1%), Gabon-40.8% (95% CI 38.2% to 43.5%), and Burundi 22.0% (95% CI 20.7% to 23.2%)). Overall, health insurance coverage was low (7.9% (95% CI 7.8% to 7.9%)) and pro-rich; concentration index=0.4 (95% CI 0.3 to 0.4, p<0.001). Exposure to media made the greatest contribution to the pro-rich distribution of health insurance coverage (50.3%), followed by socioeconomic status (44.3%) and the level of education (41.6%). CONCLUSION: Coverage of health insurance in SSA is low and pro-rich. The four countries that had health insurance coverage levels greater than 20% were all characterised by substantial funding from tax revenues. The other study countries featured predominantly voluntary mechanisms. In a context of high informality of labour markets, SSA and other LMICs should rethink the role of voluntary contributory health insurance and instead embrace tax funding as a sustainable and feasible mechanism for mobilising resources for the health sector.

Preferences of healthcare providers for capitation payment in Kenya: a discrete choice experiment.

Provider payment mechanisms (PPMs) are important to the universal health coverage (UHC) agenda as they can influence healthcare provider behaviour and create incentives for health service delivery, quality and efficiency. Therefore, when designing PPMs, it is important to consider providers' preferences for PPM characteristics. We set out to uncover senior health facility managers' preferences for the attributes of a capitation payment mechanism in Kenya. We use a discrete choice experiment and focus on four capitation attributes, namely, payment schedule, timeliness of payments, capitation rate per individual per year and services to be paid by the capitation rate. Using a Bayesian efficient experimental design, choice data were collected from 233 senior health facility managers across 98 health facilities in seven Kenyan counties. Panel mixed multinomial logit and latent class models were used in the analysis. We found that capitation arrangements with frequent payment schedules, timelier disbursements, higher payment rates per individual per year and those that paid for a limited set of health services were preferred. The capitation rate per individual per year was the most important attribute. Respondents were willing to accept an increase in the capitation rate to compensate for bundling a broader set of health services under the capitation payment. In addition, we found preference heterogeneity across respondents and latent classes. In conclusion, these attributes can be used as potential targets for interventions aimed at configuring capitation to achieve UHC.

Health care purchasing in Kenya: Experiences of health care providers with capitation and fee-for-service provider payment mechanisms.

BACKGROUND: Provider payment mechanisms (PPMs) play a critical role in universal health coverage due to the incentives they create for health care providers to deliver needed services, quality, and efficiency. We set out to explore public, private, and faith-based providers' experiences with capitation and fee-for-service in Kenya and identified attributes of PPMs that providers considered important. METHODS: We conducted a qualitative study in two counties in Kenya. Data were collected using semistructured interviews with 29 management team members in six health providers accredited by the National Hospital Insurance Fund (NHIF). RESULTS: Capitation and fee-for-service payments from the NHIF and private insurers were reported as good revenue sources as they contributed to providers' overall income. The expected fee-for-service payment amounts from NHIF and private insurers were predictable while capitation funds from NHIF were not because providers did not have information on the number of enrolees in their capitation pool. Moreover, capitation payment rates were perceived as inadequate. Capitation and fee-for-service payments from NHIF and private insurers were disbursed late. Finally, public providers had lost their autonomy to access and utilise capitation and fee-for-service payments from the NHIF. CONCLUSION: Through their experiences, health care providers revealed characteristics of PPMs that they considered important.

What characteristics of provider payment mechanisms influence health care providers' behaviour? A literature review.

BACKGROUND: Provider payment mechanisms (PPMs) create incentives or signals that influence the behaviour of health care providers. Understanding the characteristics of PPMs that influence health care providers' behaviour is essential for aligning PPM reforms for improving access, quality, and efficiency of health care services. We reviewed empirical literature that examined the characteristics of PPMs that influence the behaviour of health care providers. METHODS: We systematically searched for empirical literature in PubMed, Web of Science, and Google Scholar databases and complemented these with physical searching of the references of selected papers for further relevant studies. A total of 16 studies that met our inclusion and exclusion criteria were identified. We analysed data using thematic review. RESULTS: We identified seven major characteristics of PPMs that influence health care providers' behaviour. Of these characteristics, payment rate, the sufficiency of payment rate to cover the cost of services, timeliness of payment, payment schedule, performance requirements, and accountability mechanisms were the most important. CONCLUSIONS: Our review found that health care providers' behaviour is influenced by the characteristics of PPMs. Provider payment mechanism reforms that optimally structure these characteristics can elicit required incentives for access, equity, quality, and efficiency in service delivery among health care providers towards achieving universal health coverage.

Examining levels, distribution and correlates of health insurance coverage in Kenya.

OBJECTIVE: To examine the levels, inequalities and factors associated with health insurance coverage in Kenya. METHODS: We analysed secondary data from the Kenya Demographic and Health Survey (KDHS) conducted in 2009 and 2014. We examined the level of health insurance coverage overall, and by type, using an asset index to categorise households into five socio-economic quintiles with quintile 5 (Q5) being the richest and quintile 1 (Q1) being the poorest. The high-low ratio (Q5/Q1 ratio), concentration curve and concentration index (CIX) were employed to assess inequalities in health insurance coverage, and logistic regression to examine correlates of health insurance coverage. RESULTS: Overall health insurance coverage increased from 8.17% to 19.59% between 2009 and 2014. There was high inequality in overall health insurance coverage, even though this inequality decreased between 2009 (Q5/Q1 ratio of 31.21, CIX = 0.61, 95% CI 0.52-0.0.71) and 2014 (Q5/Q1 ratio 12.34, CIX = 0.49, 95% CI 0.45-0.52). Individuals that were older, employed in the formal sector; married, exposed to media; and male, belonged to a small household, had a chronic disease and belonged to rich households, had increased odds of health insurance coverage. CONCLUSION: Health insurance coverage in Kenya remains low and is characterised by significant inequality. In a context where over 80% of the population is in the informal sector, and close to 50% live below the national poverty line, achieving high and equitable coverage levels with contributory and voluntary health insurance mechanism is problematic. Kenya should consider a universal, tax-funded mechanism that ensures revenues are equitably and efficiently collected, and everyone (including the poor and those in the informal sector) is covered.