Busia ANC

BUSIA UHC/POPULATION HEALTH PROGRAM BASELINE SURVEY IN BUNYALA SUB-COUNTY, BUSIA

Contributors:

Jeremiah Laktabai, Co-Principal Investigator Associate Professor, Department of Family Medicine, School of Medicine, College of Health Sciences, Moi University

Laura Ruhl, Co-Principal Investigator Assistant Professor, Department of Medicine, Indiana University School of Medicine Benjamin Andama, Co-Investigator Health Financing Manager, Academic Model Providing Access to Healthcare (AMPATH)

Caitrin Kelly, Co-investigator Assistant Professor Department of Medicine Indiana University Department of Medicine

Matthew Turissini, Co-Investigator Assistant Professor, Department of Medicine, Indiana University School of Medicine Jamil Said, Co-Investigator Assistant Lecturer, Department of Human Anatomy and Department of Medicine, School of Medicine, College of Health Sciences, Moi University

Becky Genberg, Co-Investigator Assistant Professor, Department of Epidemiology, Johns Hopkins School of Public Health

Bishnu Thapa, PhD Student Department of Health Services, Policy and Practice, Brown University, School of Public Health

Beryl Maritim, Co-Investigator Program Manager, Population Health Initiative, Academic Model Providing Access to Healthcare (AMPATH)

Michael Scanlon, Co-Investigator Assistant Director of Research, Indiana University Center for Global Health

Cornelius Lagat, Co-Investigator M&E/Data Assistant, Population Health Initiative, Academic Model Providing Access to Healthcare (AMPATH)

Allan Kimaina, Co-Investigator Statistician, Population Health Initiative, Academic Model Providing Access to Healthcare (AMPATH)

Elvirah Riungu Population Health Initiative, Academic Model Providing Access to Healthcare (AMPATH)

Michael Kibiwott Population Health Initiative, Academic Model Providing Access to Healthcare (AMPATH)

1 Background

The Population Health Initiative is an AMPATH/MOH partnership initiated in 2016 working with county governments to develop a model for Universal Health Coverage (UHC) in Kenya. Its goal is to integrate siloed vertical services into a more comprehensive integrated system of providing care by focusing on three key strategies: (1) support economic empowerment by maximizing the power of community groups, (2) create a seamless public health care system, and (3) fully partner with NHIF to increase enrollment and retention in the insurance program. In 2019, AMPATH signed an MOU with Busia County government to design and implement the Busia UHC program. In order to provide household baseline data to inform the design and the monitoring and evaluation (M&E) of the program, we are conducting a cross-sectional mixed method baseline survey of households in Bunyala sub-County, Busia.

2 Objective

The objective of this study is to provide baseline data on UHC to inform the Busia UHC pilot. We plan to repeat this survey in future as funds become available in order to measure the impact of the UHC pilot in Bunyala sub-County on health service delivery, healthcare utilization, perceptions of healthcare quality in the public sector and household health spending.

Objective 1. To estimate UHC in Bunyala sub-County, Busia using an established UHC measurement framework

  • Objective 1.1. To estimate the health service coverage
  • Objective 1.2. To determine equity in access to preventative and curative health services
  • Objective 1.3. To estimate the prevalence of catastrophic health expenditure and the proportion of the population that is impoverished by out of pocket spending

Objective 2. To describe the correlates of NHIF health insurance enrolment among the informal sector

  • Objective 2.1. To evaluate the relationship between social solidarity, affordability of premiums, citizen awareness and empowerment and other factors and NHIF enrolment among the informal sector households.
  • Objective 2.2. To measure participation in economic empowerment interventions and its association with enrolment in NHIF

3 Population GIS

3.1 Location

drawing

3.2 Busia

drawing

4 % attending 4 ANC visits

5 Deliver in a health facility

6 Deliver in a health facility by a SBA

7 Receive a postnatal visit within 48 hours

  • Where can we find data to generate this ?

8 Exclusively breastfeed to 6 months

  • Where can we find data to generate this ?

9 Receive Full WHO Immunization series

Vaccines considered: “last born pentavalent vaccination” , “BCG at birth” ,“Polio at birth” , “OPV1” ,“OPV2” , “OPV3” ,“DPT_Hepatitis_HIB 1st dose” , “DPT_Hepatitis_HIB 2nd dose” , “DPT_Hepatitis_HIB 3rd dose” , “Pneumococcal vaccine 1” , “Pneumococcal vaccine 2” , “Pneumococcal vaccine 3” ,“Measles”

Responses considered: YES recorded on card and YES reported, but not on card /no card

10 Uptake of long-term FP

Only ‘Female Sterilization’, ‘Implant’, ‘Injectables’, ‘IUD’ were considered as “long-term”

11 Uptake of long-term FP XX months after delivery

  • Where can we find data to generate this ?

12 Appendix

12.1 Ordinal Data analisis

As we know that Wilcoxon Rank-Sum test can often be used provided the two independent samples are drawn from populations with an ordinal distribution.

For ordinal data, we are assuming a significance level of α = 0.05. We have a paired data over here.So,We can do hypothesis testing (two Tailed Test) to identify the given research proposition:

Hypothesis:

  • Null Hypothesis, Ho, MedianDifference = 0

  • Alternative Hypothesis, Ha, MedianDifference ≠ 0

  • Wilcoxon Rank-Sum Test For paired data set with ties,

  • WilcoxonRankSumtest was used for ordinal cohttps://rpubs.com/mominulislam2329/WilcoxonRankSumtest