2019
DOI: 10.1093/heapol/czz004
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Initiation and continuity of maternal healthcare: examining the role of vouchers and user-fee removal on maternal health service use in Kenya

Abstract: This study explores the relationship between two health financing initiatives on women’s progression through the maternal health continuum in Kenya: a subsidized reproductive health voucher programme (2006–16) and the introduction of free maternity services in all government facilities (2013). Using cross-sectional survey data, we ran three multivariable logistic regression models examining the effects of the voucher programme, free maternity policy, health insurance and other determinants on (1) early antenat… Show more

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Cited by 31 publications
(44 citation statements)
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“…In Kenya, we found that wealth index was the predominant determinant of hospital birth for those from low-and middle-SES households. The Kenyan governments has implemented various propoor interventions to support the use of maternal health services since the early 2000including childbirth fees abolishment in 2007 in government dispensaries and health centres (with the replacement of a registration fee of 10-20 Kenyan Shillings, ≈ 0.1-0.2 US dollars) [39,40], and from 2006 to 2016 a reproductive health voucher programme under which poor women could purchase subsidized vouchers for 200 Kenyan Shillings to cover the cost of antenatal care, facility childbirth and postnatal care [41,42]. In 2013, the government extended the abolishment of maternity services (including childbirth) fees in all levels of government health facilities under the Free Maternity Services (FMS) policy [43].…”
Section: Interpretation Of Resultsmentioning
confidence: 99%
“…In Kenya, we found that wealth index was the predominant determinant of hospital birth for those from low-and middle-SES households. The Kenyan governments has implemented various propoor interventions to support the use of maternal health services since the early 2000including childbirth fees abolishment in 2007 in government dispensaries and health centres (with the replacement of a registration fee of 10-20 Kenyan Shillings, ≈ 0.1-0.2 US dollars) [39,40], and from 2006 to 2016 a reproductive health voucher programme under which poor women could purchase subsidized vouchers for 200 Kenyan Shillings to cover the cost of antenatal care, facility childbirth and postnatal care [41,42]. In 2013, the government extended the abolishment of maternity services (including childbirth) fees in all levels of government health facilities under the Free Maternity Services (FMS) policy [43].…”
Section: Interpretation Of Resultsmentioning
confidence: 99%
“…Two (15.4%) studies each reported evidence from Burkina Faso and Tanzania, and one (7.7%) each reported from Niger, Sierra Leone, and Nigeria. Eight out of the 13 included studies were conducted in health facility-based settings [4,5,17,[50][51][52][53][54], two in a household-based based setting [11,55], two in community-based settings [56,57], and one was a national survey [58]. The majority (38%) of the included articles were cross-sectional studies [5,17,51,54,56], whilst the minority (8%) was quasi-experimental study design [52] (Fig.…”
Section: Characteristics Of Included Studiesmentioning
confidence: 99%
“…In the present SDG era, the world targets to reduce maternal deaths to less than 70 per 100,000 live births by 2030 (SDG 3.1) [9] and free maternal healthcare services remain vital to achieving this goal [10]. Free maternal healthcare is in line with the World Health Organization's (WHO) call for countries to eliminate financial barriers and improve access to healthcare for all who need it irrespective of where one lives, work, and income level [11,12]. Free maternal healthcare financing policy can help drive the achievement of the SDG 3.1 which stipulates the reduction of maternal mortality to less than 70 per 100,000 live births by 2030 [12].…”
Section: Introductionmentioning
confidence: 99%
“…Inequality can be further explained by decomposing the concentration index into its determining components, then horizontal inequity index (HI) can be computed by subtracting the contribution of need variables (such as women's age, health score and chronic disease) from the concentration index of CMHS utilisation; it is a summary measure of the magnitude of inequity in the dependent variable [35]. These determinants were selected according to previous research but constrained by the variables collected in the investigation [22,36]. A probit regression model was used to indirectly standardize the CMHS utilisation since the outcome variable is binary.…”
Section: Discussionmentioning
confidence: 99%