Dataset Information

Cost-related unmet need for healthcare services in Kenya.

ABSTRACT: BACKGROUND:The assessment of unmet need is one way to gauge inequities in access to healthcare services. While there are multiple reasons for unmet need, financial barriers are a major reason particularly in low- and middle-income countries where healthcare systems do not offer financial protection. Moreover, accessibility and affordability are paramount in achieving universal health coverage. This study examines the extent of unmet need in Kenya due to financial barriers, the associated determinants, and the influence of regional variations. METHODS:We use data from the 2013 Kenya household health expenditure and utilization (KHHEUS) cross sectional survey. Self-reported unmet need due to lack of money and high costs of care is used to compute the outcome of interest. A multilevel regression model is employed to assess the determinants of cost-related unmet need, confounding for the effect of variations at the regional level. RESULTS:Cost-related barriers are the main cause of unmet need for outpatient and inpatient services, with wide variations across the counties. A positive association between county poverty rates and cost-related unmet is noted. Results reveal a higher intraclass correlation coefficient (ICC) of 0.359(35.9%) for inpatient services relative to 0.091(9.1%) for outpatient services. Overall, differences between counties accounted for 9.4% (ICC?~?0.094) of the total variance in cost-related unmet need. Factors that positively influence cost-related unmet need include older household heads, inpatient services, and urban residence. Education of household head, good self-rated health, larger household size, insured households, and higher wealth quintiles are negatively associated with cost-related unmet need. CONCLUSION:The findings underscore the important role of cost in enabling access to healthcare services. The county level is seen to have a significant influence on cost-related unmet need. The variations noted in cost-related unmet need across the counties signify the existence of wide disparities within and between counties. Scaling up of health financing mechanisms would fundamentally require a multi-layered approach with a focus on the relatively poor counties to address the variations in access. Further segmentation of the population for better targeting of health financing policies is paramount, to address equity in access for the most vulnerable and marginalized populations.

SUBMITTER: Njagi P

PROVIDER: S-EPMC7164162 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Cost-related unmet need for healthcare services in Kenya.

Njagi Purity P Arsenijevic Jelena J Groot Wim W

BMC health services research 20200417 1

<h4>Background</h4>The assessment of unmet need is one way to gauge inequities in access to healthcare services. While there are multiple reasons for unmet need, financial barriers are a major reason particularly in low- and middle-income countries where healthcare systems do not offer financial protection. Moreover, accessibility and affordability are paramount in achieving universal health coverage. This study examines the extent of unmet need in Kenya due to financial barriers, the associated ...[more]

PMID: 32303244

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Project description:ImportanceImprovements in insurance coverage and access to care have resulted from the Affordable Care Act (ACA). However, a focus on short-term pre- to post-ACA changes may distract attention from longer-term trends in unmet health needs, and the problems that persist.ObjectiveTo identify changes from 1998 to 2017 in unmet need for physician services among insured and uninsured adults aged 18 to 64 years in the United States.Design, setting, and participantsSurvey study using 20 years of data, from January 1, 1998, to December 31, 2017, from the Centers for Disease Control and Prevention Behavioral Risk Factor Surveillance System to identify trends in unmet need for physician and preventive services.Main outcomes and measuresThe proportion of persons unable to see a physician when needed owing to cost (in the past year), having no routine checkup for those in whom a routine checkup was likely indicated (within 2 years), or failing to receive clinically indicated preventive services (in the recommended timeframe), overall and among subgroups defined by the presence of chronic illnesses and by self-reported health status. We estimated changes over time using logistic regression controlling for age, sex, race, Census region, employment status, and income.ResultsAmong the adults aged 18 to 64 years in 1998 (n = 117 392) and in 2017 (n = 282 378) who responded to the Centers for Disease Control and Prevention Behavioral Risk Factors Surveillance System (mean age was 39.2 [95% CI, 39.0-39.3]; 50.3% were female; 65.9% were white), uninsurance decreased by 2.1 (95% CI, 1.6-2.5) percentage points (from 16.9% to 14.8%). However, the adjusted proportion unable to see a physician owing to cost increased by 2.7 (95% CI, 2.2-3.8) percentage points overall (from 11.4% to 15.7%, unadjusted); by 5.9 (95% CI, 4.1-7.8) percentage points among the uninsured (32.9% to 39.6%, unadjusted) and 3.6 (95% CI, 3.2-4.0) percentage points among the insured (from 7.1% to 11.5%, unadjusted). The adjusted proportion of persons with chronic medical conditions who were unable to see a physician because of cost also increased for most conditions. For example, an increase in the inability to see a physician because of cost for patients with cardiovascular disease was 5.9% (95% CI, 1.7%-10.1%), for patients with elevated cholesterol was 3.5% (95% CI, 2.5%-4.5%), and for patients with binge drinking was 3.1% (95% CI, 2.3%-3.3%). The adjusted proportion of chronically ill adults receiving checkups did not change. While the adjusted share of people receiving guideline-recommended cholesterol tests (16.8% [95% CI, 16.1%-17.4%]) and flu shots (13.2% [95% CI, 12.7%-13.8%]) increased, the proportion of women receiving mammograms decreased (-6.7% [95% CI, -7.8 to -5.5]).Conclusions and relevanceDespite coverage gains since 1998, most measures of unmet need for physician services have shown no improvement, and financial access to physician services has decreased.

Project description:BackgroundThe elicitation of contact information, notification and testing of sex partners of HIV infected patients (aPS), is an effective HIV testing strategy in low-income settings but may not necessarily be affordable. We applied WHO guidelines and the International Society for Pharmaco-economics and Outcomes Research (ISPOR) guidelines to conduct cost and budget impact analyses, respectively, of aPS compared to current practice of HIV testing services (HTS) in Kisumu County, Kenya.MethodsUsing study data and time motion studies, we constructed an Excel-based tool to estimate costs and the budget impact of aPS. Cost data were collected from selected facilities in Kisumu County. We report the annual total and unit costs of HTS, incremental total and unit costs for aPS, and the budget impact of scaling up aPS over a 5-year horizon. We also considered a task-shifted scenario that used community health workers (CHWs) rather than facility based health workers and conducted sensitivity analyses assuming different rates of scale up of aPS.ResultsThe average unit costs for HIV testing among HIV-infected index clients was US$ 25.36 per client and US$ 17.86 per client using nurses and CHWs, respectively. The average incremental costs for providing enhanced aPS in Kisumu County were US$ 1,092,161 and US$ 753,547 per year, using nurses and CHWs, respectively. The average incremental cost of scaling up aPS over a five period was 45% higher when using nurses compared to using CHWs (US$ 5,460,837 and US$ 3,767,738 respectively). Over the five years, the upper-bound budget impact of nurse-model was US$ 1,767,863, 63% and 35% of which were accounted for by aPS costs and ART costs, respectively. The CHW model incurred an upper-bound incremental cost of US$ 1,258,854, which was 71.2% lower than the nurse-based model. The budget impact was sensitive to the level of aPS coverage and ranged from US$ 28,547 for 30% coverage using CHWs in 2014 to US$ 1,267,603 for 80% coverage using nurses in 2018.ConclusionScaling aPS using nurses has minimal budget impact but not cost-saving over a five-year period. Targeting aPS to newly-diagnosed index cases and task-shifting to community health workers is recommended.

Dataset Information

Cost-related unmet need for healthcare services in Kenya.

Publications

Cost-related unmet need for healthcare services in Kenya.

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