Determinants of Access to Health Services Research Example

Introduction

The intercontinental improvement plan places the improvement of health position as one of its most crucial agendas. Improvement of health status is an important element to them since it results in social and economic benefits The theoretical assertions that on the advantages of improved health status are backed by evidence provided by scholars. For instance, one of the evidence is that healthier individuals tend to be more productive and efficient since they are less absent from their occupational duties. If a country has many of individuals who are healthy, their productivity will have a ripple effect and possibly increase economic growth. In essence, better health status in the population is associated with the reduction of rates of poverty.

Is your time best spent reading someone else’s essay? Get a 100% original essay FROM A CERTIFIED WRITER!

Save 25%

However, despite there being a proved association between improved health status and beneficial outcomes, health status remains to be poor particularly in developed countries. In the African continent, people a have a low life expectancy and as a result, experience an estimate of a third of the deaths in the world. It is saddening that 60.7% of these deaths are caused by ailments that can either be prevented or treated. It is further saddening that health facilities in African countries are underutilized. The occurrence has prompted interest among many researchers in the assessment of demand-side factors in the admittance to medical amenities.

The focus of this paper is to provide a comprehensive summary to the article by Kabongo and Mbonigaba (2018). It will summarize the ideas and concepts the authors presented when identifying the factors of accessing medical amenities in the African continent. This paper will detail the methodology used in the study, the results and a discussion of the author's findings.

Methods

The research concentrated on the demand-side conception of accessing medical services. The paper's theoretical framework conceived access to health services being preceded by financial stability of the patients, which include used the cost of the health services and the income of the service recipients. It also conceived access to health care services as geographical accessibility, which was the distance to the health facilities. Based on the theoretical framework, an index of health care access was constructed which was then used as the dependent framework. In their research, Kabongo and Mbonigaba (2018) collected data from 37 countries in Africa. Data that was collected was obtained from databases of the World Development Indicator and the World Health Organization. From these databases, the research was able to access data from 1995 to 2012.

The research also employed descriptive statistics to present its findings. The study also used dynamic panel data modeling since its panel data was large. Other than descriptive statistics, the research also presented data using graphs. The study conducted preliminary diagnostics of its data in the determination of whether variables used in the study had a unit root. These tests included unit root tests, cross-section dependence test, and the cointegration test. Based on the diagnostics of the information, the researchers utilized the dynamic ARDL panel model, which was obtained from the general model on access to health care services. The occurrence allowed modeling for both the long run and short run effect on access to health care by the variables. The research, therefore, used other variables such as out of pocket payment for health services, GDP of a country and the cost of fuel.

The research also used three estimators, which included the dynamic fixed effect, the mean group, and the pooled mean in the evaluation of the error connection model of the study. The mean group was an estimator used when resolving subjectivity in the research that occurred due to heterogeneous slopes. The dynamic effect estimator was used to speed the adjustments of the short run coefficients. It was also used to restrict the coefficient of the cointegrating vector. Lastly, the pooled mean was aimed at detecting then short run and the long run association in the research variables.

Results

The results section presented both long run and short run elasticities. The results of the regression analysis showed that that long run elasticity was vital for the variables of interest in the PMG model. However, the elasticities were found to be only significant in the in the pooled mean model and not on the dynamic effect estimator. Within countries in Africa, the pooled model is deemed sustainable and justified if the countries engaged in initiatives aimed at combating health issues. In this case, the element was referred to as the long run effect. Since these initiatives might witness different rates of success and would be achieved at different times, it would be referred to as the long run effect (Kabongo and Mbonigaba, 2018).

In the long run estimates, the research found that an increase in a country's GDP by 1% results in the increase of access to health care by citizens by 0.11%. The study also found that a 1% increase in usage of fuel increased health care access by 0.06%. In the short run estimates, the research found that income was a significant determinant of whether people access health care services or not. The research, however, found unexpected negative results on the association of income and health care access in countries such as Burundi, Mozambique, and Ghana. The results also found an unexpected negative result in fuel consumption on access to health care in four countries (Kabongo and Mbonigaba, 2018).

Discussion

There was scarce evidence on demand factors that influence access to health care in African countries which therefore attracted the interest of scholars. The study by Kabongo and Mbonigaba (2018) was motivated by underutilization of health care facilities and the need for health services. Based on the theoretical framework and previously published literature, the study determined that income and the geographical distance to clinics or hospitals were the main determinants on access to health services. The researchers argued that distance to health facilities was an added cost to the access to health care services. The study thus analyzed the long run and short-run determinants of access to health care services.

As the research's results, in Africa, income was the biggest determining factor to access to health care. The authors also discovered that geographical length of way to medical facilities, which was assessed by the amount of fuel consumed, had a positive correlation with access to health care services. The results of the study have fundamental implications for policy formulation. One of the implications is that policymakers from both the international and national levels should prioritize policies that are related to income so as to increase access to health care services in the long run. The other policy implication of this study is that countries do have different responses to recommended policies and that focusing on income-related policies may not yield positive results in all countries.

The authors of the study revealed that the study was limited since the study variable was used based on availability. The authors give an example of a theoretically critical variable that was not available was the cost of healthcare services which was inaccessible. The reason is that price could not be factors in as an element that affects patients when accessing health care services since some health services in Africa are provided at no cost. Hence patients are on some occasions required to pay transport cost and other costs that are not related to accessing medical care.

Conclusion

The research was successful in identifying the determinants of access to health care by assessing short run and long-run estimates. Using the theoretical framework of financial stability and geographical accessibility, the paper collected data from 37 countries in Africa from the WHO and WDI databases. The paper analyzed its data using regression analysis and presented results using descriptive statistics. The paper found that availability of finances was a significant elements of accessing to health care facilities in Africa. It also found that accessing medical services was a critical necessity in the continent. The study has significant implications for policy formulation as its recommended that policymakers should focus on income factors when targeting to improve health care access in the long run. It also recommended that policies on improving health care, in the long run, may have limited effects on the short run.

References

Kabongo, W. N. S., & Mbonigaba, J. (2018). Demand-side determinants of access to healthcare services: Empirical evidence from Africa. SPOUDAI-Journal of Economics and Business, 67(4), 3-22.