Abstract

Legislation by government has changed the playing fields in the medical scheme industry in South Africa. Medical schemes can no longer choose their members or discriminate against members who claim more than projected amounts. Only those medical schemes that are able to manage their risk optimally, will ultimately survive.In the research it was established that the number of chronic beneficiaries in a family is an important risk factor if a member is classified into a normal claim category or an above-normal claim category. The medical schemes should make sure that they have systems in place to manage the health of such beneficiaries holistically. This group of individuals is ideally suited for a preventative healthcare programme.

Highlights

  • Healthcare costs continue to rise and this means that employees belonging to medical schemes are likely to suffer the consequences (Business Day, 1999b)

  • In order to identify the high-risk combinations of members it is possible to calculate the claim premium ratio for different demographic groupings of members, for example, the claim premium ratio according to an age distribution, member type, number of dependants, etcetera. This was all done, but for this paper a logistic regression model was fitted to the data in an attempt to identify the most important risk factor and to calculate the probability that a member would fall into a certain claim premium ratio category

  • In the study it was established that the number of chronic beneficiaries in a family is an important risk factor if a member is classified into a normal claim category or abovenormal claim category

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Summary

Classification of a member in terms of healthcare risk

Legislation by government has changed the playing fields in the medical scheme industry in South Africa. Medical schemes can no longer choose their members or discriminate against members who claim more than projected amounts. Those medical schemes that are able to manage their risk optimally, will survive. The medical schemes should make sure that they have systems in place to manage the health of such beneficiaries holistically. This group of individuals is ideally suited for a preventative healthcare programme

Introduction
The data used in the analysis
Diagnosis code
Manipulation of the data
Analysis of the data
Logistic regression
Xn εi
Independent variables
The equation that results from the analysis is
Number of beneficiaries on the chronic programme
Mean benefit amount per member
Findings
Conclusion
Full Text
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