2018
DOI: 10.7196/samj.2018.v108i4.12758
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Understanding the types of fraud in claims to South African medical schemes

Abstract: Background. Medical schemes play a significant role in funding private healthcare in South Africa (SA). However, the sector is negatively affected by the high rate of fraudulent claims. Objectives. To identify the types of fraudulent activities committed in SA medical scheme claims. Methods. A cross-sectional qualitative study was conducted, adopting a case study strategy. A sample of 15 employees was purposively selected from a single medical scheme administration company in SA. Semi-structured interviews wer… Show more

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Cited by 7 publications
(5 citation statements)
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“…This view is validated by a study that found that most of the fraudulent claims are perpetrated through the submission of false claims, irregular billing of codes, duplicate claims, claiming for services that were not rendered and card farming, which refers to members utilising medical aid benefits for a person not covered on the medical aid. 37 Nortjé and Hoffmann 38 also had similar findings and further noted that optometry recorded the third-most transgressions within the HPCSA, second to psychology and the medical professions, respectively. The negative impact of fraud on healthcare and healthcare financing is that it threatens sustainability and security of providing healthcare by driving up the cost of healthcare, impeding the provision of universal access to quality, affordable and timely healthcare.…”
Section: Discussionmentioning
confidence: 69%
“…This view is validated by a study that found that most of the fraudulent claims are perpetrated through the submission of false claims, irregular billing of codes, duplicate claims, claiming for services that were not rendered and card farming, which refers to members utilising medical aid benefits for a person not covered on the medical aid. 37 Nortjé and Hoffmann 38 also had similar findings and further noted that optometry recorded the third-most transgressions within the HPCSA, second to psychology and the medical professions, respectively. The negative impact of fraud on healthcare and healthcare financing is that it threatens sustainability and security of providing healthcare by driving up the cost of healthcare, impeding the provision of universal access to quality, affordable and timely healthcare.…”
Section: Discussionmentioning
confidence: 69%
“…Overall, moral hazard affects the normal operation of medical insurance funds. Identification of moral hazard behaviors and their occurrence mechanism is the first step in risk management ( 12 ). Therefore, the study aims to visualize the relationship of stakeholders and their moral hazard actions through social network analysis (SNA), and further explore the combination of conditions leading to funding loss by using crisp-set qualitative comparative analysis (cs/QCA) based on diamond fraud theory, to help Chinese governance to efficiently predict and investigate immoral behaviors in medical insurance and propose specific strategies to reduce moral hazards in the operation of medical insurance funds.…”
Section: Research Status Of Moral Hazards In China's Medical Insuranc...mentioning
confidence: 99%
“…The NHS Fraud Authority (NHS CFA) predicted that in the UK the NHS costs around £1.27 billion due to moral hazards such as fraud annually ( 11 ). According to the cases of sanctioning healthcare professionals in South Africa, 51.7% of ethical transgressions were for insurance fraud, and the amount lost per year is about ZAR 13 billion in private healthcare sectors ( 12 , 13 ). Statistics for some Asian countries are also appalling.…”
Section: Introductionmentioning
confidence: 99%
“…In particular, in some high-income countries, 3–10% of annual healthcare expenditures are lost as a result of health insurance fraud, amounting to billions of dollars [ 6 – 9 ]. However, due to the unique characteristics of the health insurance industry and the complex and insidious of health insurance fraud, the supervision of health insurance funds is very difficult [ 10 , 11 ].…”
Section: Introductionmentioning
confidence: 99%