Computational protocol: Impact of free delivery policy on utilization of maternal health services in county referral hospitals in Kenya

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Protocol publication

[…] The study analyzed data on antenatal attendance and facility based deliveries. These were extracted from the Kenya Health Information System website (https://hiskenya.org). This is based on the free and open- source web-based District Health Information Software (DHIS2) []. This is run by the division of health information, Ministry of Health Kenya. The division has health information and records officers working in health facilities. They get various reports generated by health facilities, collate and upload them into this website. We looked at data for one year pre-intervention and one year post-intervention for the 47 county referral hospitals and compared them to that of 30 not-for profit private hospitals not participating in the free maternity program. The pre-intervention period was from June 2012 to May 2013 while the post intervention period was from June 2013 to May 2014. Majority of these private hospitals are run by religious organizations under the auspices of the Kenya Episcopal Conference-Catholic Secretariat and Christian Health Association of Kenya respectively.The study utilized the integrated reproductive health, HIV/AIDS, malaria, tuberculosis and nutrition report commonly called MOH 711. Data were extracted from the safe delivery section. This section has the number of maternal deaths and births. Total births were derived by adding the number of normal deliveries, caesarian section, breech delivery and assisted vaginal delivery. Antenatal attendance is listed as new attendance and re-attendance. These two were added to give total antenatal attendance. Standard multiple regression was used to assess the ability of poverty, total fertility rate, population and type of county referral hospital to predict the increase in number of deliveries in 2014 among county referral hospitals. Data on poverty levels per county were extracted from the Kenya Economic Report, 2013 []. Data on population per county were extracted from the national census reports []. Data on total fertility rate per county were extracted from the Kenya Demography and Health Survey 2014 []. Preliminary analyses were conducted to ensure no violations of the assumptions of normality, linearity, multicollinearity and homoscedasticity. Analysis was done using Ms. Excel and SPSS version 16.This study was not reviewed and approved by an institutional review board. Ethical approval was not necessary as the study utilized data sets available in a public website. The data on the Kenya health information system is normally de-identified to protect patient confidentiality and privacy. […]

Pipeline specifications

Software tools SAMtools, SPSS
Application Miscellaneous