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The relationship between a microfinance-based healthcare delivery platform, health insurance coverage, health screenings, and disease management in rural Western Kenya.

ABSTRACT: BACKGROUND:Structural barriers often prevent rural Kenyans from receiving healthcare and diagnostic testing. The Bridging Income Generation through grouP Integrated Care (BIGPIC) Family intervention facilitates microfinance groups, provides health screenings and treatment, and delivers education about health insurance coverage to address some of these barriers. This study evaluated the association between participation in BIGPIC microfinance groups and health screening/disease management outcomes. METHODS:From November 2018 to March 2019, we interviewed a sample of 300 members of two rural communities in Western Kenya, 100 of whom were BIGPIC microfinance members. We queried participants about their experiences with health screening and disease management for HIV, diabetes, hypertension, tuberculosis, and cervical cancer. We used log-binomial regression models to estimate the association between microfinance membership and each health outcome, adjusting for key covariates. RESULTS:Microfinance members were more likely to be screened for most of the health conditions we queried, including those provided by BIGPIC [e.g. diabetes: aPR (95% CI): 3.46 (2.60, 4.60)] and those not provided [e.g. cervical cancer: aPR (95% CI): 2.43 (1.21, 4.86)]. Microfinance membership was not significantly associated with health insurance uptake and disease management outcomes. CONCLUSIONS:In rural Kenya, a microfinance program integrated with healthcare delivery may be effective at increasing health screening. Interventions designed to thoughtfully and sustainably address structural barriers to healthcare will be critical to improving the health of those living in low-resource settings.

SUBMITTER: Rosenberg M

PROVIDER: S-EPMC7491169 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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The relationship between a microfinance-based healthcare delivery platform, health insurance coverage, health screenings, and disease management in rural Western Kenya.

Rosenberg Molly M Amisi James Akiruga JA Szkwarko Daria D Tran Dan N DN Genberg Becky B Luetke Maya M Kianersi Sina S Namae Jane J Laktabai Jeremiah J Pastakia Sonak S

BMC health services research 20200914 1

<h4>Background</h4>Structural barriers often prevent rural Kenyans from receiving healthcare and diagnostic testing. The Bridging Income Generation through grouP Integrated Care (BIGPIC) Family intervention facilitates microfinance groups, provides health screenings and treatment, and delivers education about health insurance coverage to address some of these barriers. This study evaluated the association between participation in BIGPIC microfinance groups and health screening/disease management ...[more]

PMID: 32928198

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Project description:BACKGROUND:Kenya has prioritized the attainment of universal health coverage (UHC) through the expansion of health insurance coverage by the National Hospital Insurance Fund (NHIF). In 2015, the NHIF introduced reforms in premium contribution rates, benefit packages, and provider payment methods. We examined the influence of these reforms on NHIF's purchasing practices and their implications for strategic purchasing and health system goals of equity, efficiency and quality. METHODS:We conducted an embedded case study with the NHIF as the case and the reforms as embedded units of analysis. We collected data at the national level and in two purposively selected counties through 41 in-depth interviews with health financing stakeholders, facility managers and frontline providers; 4 focus group discussions with 51 NHIF members; and, document reviews. We analysed the data using a Framework approach. RESULTS:The new NHIF reforms were characterized by weak purchasing actions. Firstly, the new premium contribution rates were inadequately communicated and unaffordable for certain citizen groups. Secondly, while the new benefit packages were reported to be based on service needs, preferences and values of the population, they were inadequately communicated and unequally distributed across different citizen groups. In addition, the presence of service delivery infrastructure gaps in public healthcare facilities and the pro-urban and pro-private distribution of contracted health facilities compromised delivery of, and access to, these new services. Lastly, the new provider payment methods and rates were considered inadequate, with delayed payments and weak links to financial accountability mechanisms which compromised their ability to incentivize equity, efficiency and quality of healthcare delivery. CONCLUSION:While NHIF sought to expand population and service coverage and reduce out-of-pocket payments with the new reforms, weaknesses in the reforms' design and implementation limited NHIF's purchasing actions with negative implications for the health system goals of equity, efficiency and quality. For the reforms to accelerate the country's progress towards UHC, policy makers at the NHIF and, national and county government should make deliberate efforts to align the design and implementation of such reforms with strategic purchasing actions that are aimed at improving health system goals.

Project description:BackgroundOver 150 million people, mostly from low and middle-income countries (LMICs) suffer from catastrophic health expenditure (CHE) every year because of high out-of-pocket (OOP) payments. In Tanzania, OOP payments account for about a quarter of the total health expenditure. This paper compares healthcare utilization and the incidence of CHE among improved Community Health Fund (iCHF) members and non-members in central Tanzania.MethodsA survey was conducted in 722 households in Bahi and Chamwino districts in Dodoma region. CHE was defined as a household health expenditure exceeding 40% of total non-food expenditure (capacity to pay). Concentration index (CI) and logistic regression were used to assess the socioeconomic inequalities in the distribution of healthcare utilization and the association between CHE and iCHF enrollment status, respectively.Results50% of the members and 29% of the non-members utilized outpatient care in the previous month, while 19% (members) and 15% (non-members) utilized inpatient care in the previous twelve months. The degree of inequality for utilization of inpatient care was higher (insured, CI = 0.38; noninsured CI = 0.29) than for outpatient care (insured, CI = 0.09; noninsured CI = 0.16). Overall, 15% of the households experienced CHE, however, when disaggregated by enrollment status, the incidence of CHE was 13% and 15% among members and non-members, respectively. The odds of iCHF-members incurring CHE were 0.4 times less compared to non-members (OR = 0.41, 95%CI: 0.27-0.63). The key determinants of CHE were iCHF enrollment status, health status, socioeconomic status, chronic illness, and the utilization of inpatient and outpatient care.ConclusionThe utilization of healthcare services was higher while the incidence of CHE was lower among households enrolled in the iCHF insurance scheme relative to those not enrolled. More studies are needed to establish the reasons for the relatively high incidence of CHE among iCHF members and the low degree of healthcare utilization among households with low socioeconomic status.

Project description:BACKGROUND:Elevated blood pressure is the leading risk for mortality in the world. Task redistribution has been shown to be efficacious for hypertension management in low- and middle-income countries. However, the workforce requirements for such a task redistribution strategy are largely unknown. Therefore, we developed a needs-based workforce estimation model for hypertension management in western Kenya, using need and capacity as inputs. METHODS:Key informant interviews, focus group discussions, a Delphi exercise, and time-motion studies were conducted among administrative leadership, clinicians, patients, community leaders, and experts in hypertension management. These results were triangulated to generate the best estimates for the inputs into the health workforce model. The local hypertension clinical protocol was used to derive a schedule of encounters with different levels of clinician and health facility staff. A Microsoft Excel-based spreadsheet was developed to enter the inputs and generate the full-time equivalent workforce requirement estimates over 3 years. RESULTS:Two different scenarios were modeled: (1) "ramp-up" (increasing growth of patients each year) and (2) "steady state" (constant rate of patient enrollment each month). The ramp-up scenario estimated cumulative enrollment of 7000 patients by year 3, and an average clinical encounter time of 8.9 min, yielding nurse full-time equivalent requirements of 4.8, 13.5, and 30.2 in years 1, 2, and 3, respectively. In contrast, the steady-state scenario assumed a constant monthly enrollment of 100 patients and yielded nurse full-time equivalent requirements of 5.8, 10.5, and 14.3 over the same time period. CONCLUSIONS:A needs-based workforce estimation model yielded health worker full-time equivalent estimates required for hypertension management in western Kenya. The model is able to provide workforce projections that are useful for program planning, human resource allocation, and policy formulation. This approach can serve as a benchmark for chronic disease management programs in low-resource settings worldwide.

Project description:ObjectiveTo improve understanding of the relationship between lack of insurance and risk of subsequent mortality.Data sourcesAdults who reported being uninsured or privately insured in the National Health Interview Survey from 1986 to 2000 were followed prospectively for mortality from initial interview through 2002. Baseline information was obtained on 672,526 respondents, age 18-64 at the time of the interview. Follow-up information on vital status was obtained for 643,001 (96 percent) of these respondents, with approximately 5.4 million person-years of follow-up.Study designRelationships between insurance status and subsequent mortality are examined using Cox proportional hazard survival analysis.Principal findingsAdjusted for demographic, health status, and health behavior characteristics, the risk of subsequent mortality is no different for uninsured respondents than for those covered by employer-sponsored group insurance at baseline (hazard ratio 1.03, 95 percent confidence interval [CI], 0.95-1.12). Omitting health status as a control variable increases the estimated hazard ratio to 1.10 (95 percent CI, 1.03-1.19). Also omitting smoking status and body mass index increases the hazard ratio to 1.20 (95 percent CI, 1.15-1.24). The estimated association between lack of insurance and mortality is not larger among disadvantaged subgroups; when the analysis is restricted to amenable causes of death; when the follow-up period is shortened (to increase the likelihood of comparing the continuously insured and continuously uninsured); and does not change after people turn 65 and gain Medicare coverage.ConclusionsThe Institute of Medicine's estimate that lack of insurance leads to 18,000 excess deaths each year is almost certainly incorrect. It is not possible to draw firm causal inferences from the results of observational analyses, but there is little evidence to suggest that extending insurance coverage to all adults would have a large effect on the number of deaths in the United States.

Project description:BackgroundChamas for Change (Chamas) is a group-based health education and microfinance program for pregnant and postpartum women that aims to address inequities contributing to high rates of maternal and infant mortality in rural western Kenya. In this prospective matched cohort study, we evaluated the association between Chamas participation and facility-based delivery. We additionally explored the effect of participation on promoting other positive maternal, newborn and child health (MNCH) behaviors.MethodsWe prospectively compared outcomes between a cohort of Chamas participants and controls matched for age, parity, and prenatal care location. Between October-December 2012, government-sponsored community health volunteers (CHV) recruited pregnant women attending their first antenatal care (ANC) visits at rural health facilities in Busia County to participate in Chamas. Women enrolled in Chamas agreed to attend group-based health education and microfinance sessions for one year; controls received the standard of care. We used descriptive analyses, multivariable logistic regression models, and random effect models to compare outcomes across cohorts 12 months following enrollment, with α set to 0.05.ResultsCompared to controls (n = 115), a significantly higher proportion of Chamas participants (n = 211) delivered in a health facility (84.4% vs. 50.4%, p < 0.001), attended at least four ANC visits (64.0% vs. 37.4%, p < 0·001), exclusively breastfed to six months (82.0% vs. 47.0%, p < 0·001), and received a CHV home visit within 48 h postpartum (75.8% vs. 38.3%, p < 0·001). In multivariable models, Chamas participants were over five times as likely as controls to deliver in a health facility (OR 5.49, 95% CI 3.12-9.64, p < 0.001). Though not significant, Chamas participants experienced a lower proportion of stillbirths (0.9% vs. 5.2%), miscarriages (5.2% vs. 7.8%), infant deaths (2.8% vs. 3.4%), and maternal deaths (0.9% vs. 1.7%) compared to controls.ConclusionsChamas participation was associated with increased odds of facility-based delivery compared to the standard of care in rural western Kenya. Larger proportions of program participants also practiced other positive MNCH behaviors. Our findings demonstrate Chamas' potential to achieve population-level MNCH benefits; however, a larger study is needed to validate this observed effect.Trial registrationClinicalTrials.gov, NCT03188250 (retrospectively registered 31 May 2017).

Dataset Information

The relationship between a microfinance-based healthcare delivery platform, health insurance coverage, health screenings, and disease management in rural Western Kenya.

Publications

The relationship between a microfinance-based healthcare delivery platform, health insurance coverage, health screenings, and disease management in rural Western Kenya.

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