Determinants of Out-of-Pocket Health Payments (Research Paper Sample)

DETERMINANTS OF OUT OF POCKET HEALTH PAYMENTS AMONG THE ELDERLY IN KENYA
EMMANUEL MULAA OPONDO
X53/87759/2016
SUPERVISOR
DR. MARTINE OLECHE
A Research Paper Submitted in Partial Fulfillment of the Requirements for the Award of the Degree of Master of Science, Health Economics and Policy in the School of Economics, The University of Nairobi.
NOVEMBER 2018
DECLARATION
I hereby declare that this is my original work and that to the best of my knowledge it has not been presented for the award of a degree at any university.
Signed…………………………………Date……………………………………
Emmanuel Mulaa Opondo
X53/87759/2016
Approval
This paper has been submitted for examination with my approval as the university supervisor.
Signed………………………………….Date…………………………………….
Dr. Martine Oleche
DEDICATION
I dedicate this paper to my beloved family, which has always been my source of great inspiration.
ACKNOWLEDGEMENT
This paper is as a result of effort from various quarters. Without them, it would not have been successful.
First and foremost is my supervisor, Dr. Martine Oleche. You incessantly guided, directed and positively criticized the work making it better with each passing day. Your insights greatly improved the quality of the paper and my understanding of project writing.
Second is the faculty, school of economics, who taught me the various theoretical courses of this program. Your knowledge impacted on me positively and gave me a solid foundation in health economics. It is this knowledge upon which this paper is based.
Finally I thank my close friends Mercy and Isaac. Your words of encouragement made sure this paper remained a priority until it was done and dusted. To all others not mentioned, know that you have my eternal gratitude from the bottom of my heart. Thank you.
TABLE OF CONTENTS TOC \o "1-3" \h \z \u DECLARATION PAGEREF _Toc530031623 \h iiDEDICATION PAGEREF _Toc530031624 \h iiiACKNOWLEDGEMENT PAGEREF _Toc530031625 \h ivLIST OF TABLES PAGEREF _Toc530031626 \h viiLIST OF FIGURES PAGEREF _Toc530031627 \h viiiABSTRACT PAGEREF _Toc530031628 \h ixACRONYMS/ABBREVIATIONS PAGEREF _Toc530031629 \h xCHAPTER ONE: INTRODUCTION PAGEREF _Toc530031630 \h 11.1 Background PAGEREF _Toc530031631 \h 11.2 Health expenditure PAGEREF _Toc530031632 \h 21.3 Highlights of public health financing in Kenya PAGEREF _Toc530031633 \h 51.4 Problem Statement PAGEREF _Toc530031634 \h 81.5 Objectives of the study PAGEREF _Toc530031635 \h 101.6 Justification of the study PAGEREF _Toc530031636 \h 10CHAPTER TWO: LITERATURE REVIEW PAGEREF _Toc530031637 \h 122.1 Theoretical literature review PAGEREF _Toc530031638 \h 122.2 Empirical literature review PAGEREF _Toc530031639 \h 152.3 Overview of literature review PAGEREF _Toc530031640 \h 20CHAPTER THREE: RESEARCH METHODOLOGY PAGEREF _Toc530031641 \h 223.1 Introduction PAGEREF _Toc530031642 \h 223.2 Theoretical framework PAGEREF _Toc530031643 \h 22Source: Authors PAGEREF _Toc530031644 \h 233.3 Econometric model specification PAGEREF _Toc530031645 \h 233.4 Operationalization of variables PAGEREF _Toc530031646 \h 253.5 Data and Data Sources PAGEREF _Toc530031647 \h 273.6 Diagnostic tests PAGEREF _Toc530031648 \h 273.6.1 Endogeneity test PAGEREF _Toc530031649 \h 273.6.2 Correlation test PAGEREF _Toc530031650 \h 273.6.3 Multicollinearity PAGEREF _Toc530031651 \h 283.6.4 Heteroscedasticity test PAGEREF _Toc530031652 \h 283.7 Multivariate Regression PAGEREF _Toc530031653 \h 28CHAPTER FOUR: DATA ANALYSIS, INTERPRETATION AND DISCUSSION PAGEREF _Toc530031654 \h 294.1 Introduction PAGEREF _Toc530031655 \h 294.2 Descriptive Summary dataset PAGEREF _Toc530031656 \h 294.3 Descriptive Summary statistics PAGEREF _Toc530031657 \h 304.4 Correlation Analysis PAGEREF _Toc530031658 \h 334.5 Endogeneity test PAGEREF _Toc530031659 \h 334.6 Regression model PAGEREF _Toc530031660 \h 354.7 Diagnostic tests PAGEREF _Toc530031661 \h 384.7.1: Multicollinearity test PAGEREF _Toc530031662 \h 384.7.2: Test for heteroscedasticity PAGEREF _Toc530031663 \h 394.8 Distribution of OOPHE with wealth PAGEREF _Toc530031664 \h 41CHAPTER FIVE: SUMMARY, CONCLUSIONS AND POLICY IMPLICATIONS PAGEREF _Toc530031665 \h 425.1 Introduction PAGEREF _Toc530031666 \h 425.2 Summary of the findings PAGEREF _Toc530031667 \h 425.3 Conclusions PAGEREF _Toc530031668 \h 445.4 Policy implications PAGEREF _Toc530031669 \h 465.5 Areas of further research PAGEREF _Toc530031670 \h 47REFERENCES PAGEREF _Toc530031671 \h 48
LIST OF TABLES
TOC \h \z \c "Table 1." Table 1.1: National Government Recurrent and Development Expenditures on health services, 2013/14-2016/17 PAGEREF _Toc526841053 \h 7
TOC \h \z \c "Table 3." Table 3.1: Definition, Measurement and Expected Outcomes of Study Variables. PAGEREF _Toc526841063 \h 26
TOC \h \z \c "Table 4."
Table 4.1: Summary of the Database PAGEREF _Toc526841091 \h 30
Table 4.2: Descriptive Statistics PAGEREF _Toc526841092 \h 32
Table 4.3: Correlation Analysis Matrix PAGEREF _Toc526841093 \h 33
Table 4.4: Two-Stage Least Square Regression and Test for Endogeneity PAGEREF _Toc526841094 \h 34
Table 4.5: Regression Model Results PAGEREF _Toc526841095 \h 36
Table 4.6: Multicollinearity Test PAGEREF _Toc526841096 \h 39
Table 4.7: Heteroscedasticity Test PAGEREF _Toc526841097 \h 39
Table 4.8: Regression Results Based on the Robust Standard Errors PAGEREF _Toc526841098 \h 40
LIST OF FIGURES
TOC \h \z \c "Figure 3." Figure 3. 1: Framework for viewing health services utilization by Andersen and Newman PAGEREF _Toc526148078 \h 23
TOC \h \z \c "Figure 4."
Figure 4.1: Concentration curves showing OOPHE distribution in the different wealth quintiles PAGEREF _Toc526147981 \h 41
ABSTRACT
Universal Health Coverage (UHC) ensures that everyone uses promotive, preventive, curative, rehabilitative and palliative health services they need, of sufficient quality to be effective, while also ensuring that the use of these services does not expose the user to financial hardship CITATION WHO10 \l 1033 (WHO, 2010). This however remains a major bottleneck facing health systems globally. Kenya is no exception. The struggle to finance for health care remains a pipedream for a big proportion of the citizenry. One of the most vulnerable demographic is the elderly.This study sought to analyze determinants of out of pocket (OOP) health payments among the elderly in Kenya. It was also to determine the distribution of these payments in the various wealth quintiles. It applied a multivariate regression model and concentration curves to achieve this. The data used was sourced from the Kenya Household Health Expenditure and Utilization Survey (KHHEUS) done in 2013. This data was analyzed using STATA version 14.1.The regression results showed that increasing age, presence of chronic illnesses in a household, being male, higher education level, having more wealth, possessing a health insurance cover, increased distance and number of visits to the health facility positively affected OOP health payments among the elderly in Kenya. They further revealed that these results were significant for presence of chronic illnesses, increasing age, possessing a health insurance cover and belonging to the richest wealth quintile and insignificant for the rest. The concentration curves revealed OOP health payments were concentrated in the richest households. From the study, it was possible to make recommendations to further strengthen Kenya’s health system. They include reforms in NHIF insurance to increase the benefit package for the elderly and giving exemptions to ensure every person over 60 years has health insurance cover. Others include shift in policy from curative to preventive for chronic illnesses such as cancers, diabetes and hypertension. These illnesses were noted to contribute significantly to the OOP health payments.
KEY WORDS: Universal Health Coverage, Out-of-Pocket, Out-of-Pocket Health Expenditure.
ACRONYMS/ABBREVIATIONS
KESKenya Shillings
KHHEUSKenya Household Health Expenditure and Utilization Survey
KNBSKenya National Bureau of Statistics
MoHMinistry of Health
NHIFNational Hospital Insurance Fund
OOPOut-of-pocket
OOPHEOut-of-pocket health expenditure
STATA Software for Statistics and Data Science
THETotal Health Expenditure
UHCUniversal Health Coverage
WHO World Health Organization
CHAPTER ONE: INTRODUCTION
1.1 Background
The chronological figure that demarcates the elderly from non-elderly varies from place to place. While in America and Europe it is taken as 65 years, in Africa it's the age at which an individual is eligible for pension usually 60 years CITATION Wor18 \l 1033 (World Health Organization, 2018). For ease in collecting, analyzing and comparing data from different countries across the world, World Health Organization (WHO) uses a working age of 60 years to mark a person(s) as elderly.
In 1950 the life expectancy worldwide was 46 years and by 2010 it was 68 years. The number of people in the world over 60 years is approximately 700 million CITATION Uni18 \l 1033 ...