Impact of NHIS on Antenatal Care Attendance among Pregnant Women in Ghana: Research Methodology
RESEARCH METHODOLOGY
3.1 Introduction
This section provides a brief overview of the dataset employed for the study. The independent, dependent and intermediate variables were also treated. This chapter also layouts the proposed strategy to be utilized for the examination of the secondary information as contained in the dataset preselected for this study.
3.2 Sources of data
The information for this investigation was drawn from the 2013 Ghana Living Standard Survey Round 6 (GLSS6). The goal of the GLSS is to provide a more comprehensive, reliable and up-to-date statistics and indicators to monitor and evaluate the impact of development policies and programmes on the living conditions of their citizens. This information was gathered from all the ten regions of Ghana to guarantee an across the country representativeness. The review is completed at regular intervals. The first Ghana Living Standards Survey was conducted in 1987, the second, third, fourth and fifth rounds were conducted in 1988, 1991/92, 1998/99 and 2005/06 in that order.
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3.3 The Ghana Living Standard Survey Study Design
The Ghana Living Standard Survey is a household based survey which uses a two-stage stratified sampling design. At the first stage, enumeration areas (EAs) from the Ghana Population and Housing Census 2010 were selected to form the primary sampling units (PSUs). At the second stage, households from each PSU were selected systematically to get the total sample size of households nationwide.
The Survey collects data through a questionnaire-based interview. The questionnaires are structured as follows: Household Questionnaires, Non-farms Household Questionnaires, Community Questionnaires, Governance, Peace and Security Questionnaire and Price of Food and Non –food Items Questionnaires. The household Questionnaire is made up of two parts A and B. Part A and has seven sections namely: demographic characteristics of respondents; education and skills training; health and fertility behavior; employment and time use; migration and tourism; household agriculture; housing and housing conditions. All men 15-59 and women 15-59 were eligible to be interviewed from each household selected. Since this study focuses on the impact of National Health Insurance Scheme on Antenatal care attendance among pregnant women, responses from the Household Questionnaire Part A was utilized.
3.4 Data
The data used for this analysis is based on the responses from women who has been pregnant in the five years preceding the survey and pregnant during the survey with antenatal care and national health insurance histories.
Inclusion Criteria: All women of reproductive age (15-49) who have been pregnant during the last 12months.
Exclusion Criteria: Women who were in the reproductive age but are infecund and those who have ever been pregnant more than 12months.
The variable age was treated as continuous variable. Parity was analyzed as a continuous variable. Income was also analyzed as a continuous variable.
Education was measured as a categorical variable of the highest level of education attained (none, primary, secondary and tertiary).
Marital status was categorized as married, consensual union, separated, Divorced, widowed and never married.
Ethnicity was categorized as Akan, Ga-Dangbe, Ewe, Guan, Gurnia, Mole-Dagani, Grusi. and others. This was based on the major tribes in Ghana.
Religion was treated as a categorical variable of five categories, namely no religion, catholic, protestant, Islam and traditional.
Employment status was categorized as employed and unemployed.
Area of residence was also categorized as urban and rural.
Region was categorized based on the ten regions of Ghana namely: Western, Central, Greater Accra, Volta, Brong Ahafo, Ashanti, Northern, Upper West and Upper East.
3. Sample Size
Taking all things together, 2,587 ladies inside the ages 15-49 were utilized as the example estimate which was drawn from the women's record. The sample was directed on the information balanced by test weight to represent the stratified inspecting outline for representativeness. This was then sifted to get the appropriate sample for this examination which incorporates every single missing value and ladies who did not attend ANC and did not have valid NHIS card. This is on the grounds that the fundamental objective of this investigation is to assess the effect of National Health Insurance on antenatal care participation among pregnant women in Ghana.
3.4 Measurement of variables
3.3.1 Primary Outcome Measure
The primary outcome measure for this study was antenatal care attendance measured as 4 or more visits to a recommended health facility during pregnancy. The antenatal care attendance acts as the dependent variable. The World Health Organization (WHO) prescribes that for the lion's share of typical pregnancies, ANC should comprise of no less than four visits over the span of the pregnancy, the first ought to happen inside the first trimester. Timing of first ANC visit was in this way recoded as "none" for ladies who did not start ANC by any stretch of the imagination, "early" when it happened amid the primary trimester and "late" when the visit occurred amid the second or third trimester.
3.3.2 Secondary Outcome Measure
For specific objective 3, valid NHIS membership will be an outcome variable although it serves as the main independent variable for specific objective 4. The estimation of a dependent factor is subject to other independent factors and its value will alter as the autonomous variable or mediation changes (Mathers, Fox, & Hunn, 2010). Statistical approaches can be utilized to forecast the value of the dependent factor.
3.3.3 Independent Variables
The independent variable is autonomous in nature and appears as the mediation or treatment in an investigation and is controlled to show change in the dependent factor (Mathers et al., 2010). For the purpose of this study, Socio-demographic/economic factors such as age, parity, marital status, religious belief, ethnicity, area of residence, region, formal educational status and Income level, employment status as well as NHIS membership.
3.5 Power analysis
Since this study is using a secondary data, power analysis was conducted to determine whether the sample size from the complex survey is enough to detect the impact of NHIS on antenatal care attendance via matching procedures.
3.6 Statistical Methods
The baseline socio-demographic characteristics of pregnant women who have valid NHIS to non-NHIS pregnant women was compared using the chi-square test of independence and Cochran Armitage trend test where appropriate. Continuous covariates were compared among pregnant women with and without valid NHIS using t-test or Wilcoxon rank sum test. Multivariable logistic regression analysis was used to assess relationship between covariates and NHIS enrolment.
To evaluate the impact of NHIS on ANC attendance, the propensity score for the pregnant women was defined as the probability of enrolling in NHIS given the observed covariates based on the logistic regression model. Thus the probability to enroll in NHIS given the observed covariates will be given by where is the estimated propensity score, where represent individual sociodemographic/economic characteristics and other observed factors.
3.6.1 Assessing Common Support/ Diagnosing Matches from NHIS
This study used numerical and graphical diagnosis to evaluate and observe the common support of the distribution of propensity score between subjects with and without valid NHIS. The multidimensional histograms and Kernel density plots of the covariates in the matched NHIS and non-ART groups was compared.
In this study the standardized differences greater than 10% in absolute value will be assumed to indicate serious imbalance in the covariate of interest between the two groups. The standardized difference d is given as follows for continuous and binary indicator variables:
3.6.2 Sensitivity Analysis of matching procedures
Analysis of sensitivity to the ignorability assumption under propensity score matching was performed. This assumption states that there may be other unobserved factors that influence NHIS enrollment, ANC attendance or both. The Rosenbaum bounds for average NHIS effects on the treated in the presence of unobserved heterogeneity (hidden bias) between pregnant women with and without NHIS were also calculated.
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