Exploring fraud and abuse in National Health Insurance Scheme (NHIS) using data mining technique as a statistical model
This study explored patterns of fraud and abuse that exist in the National Health Insurance Scheme (NHIS) claims in the Awutu-Effutu-Senya District using data mining techniques, with a specific focus on malaria-related claims. The study employed quantitative research approach with survey design as a strategy of enquiry. This survey explores the utility of various data mining techniques such as data collection, data cleaning/extraction, data integration, data selection, data transformation and pattern evaluation in the health domain. Samples of 720 clients diagnosed with malaria in the years 2013, 2014 and 2015 from 4 NHIS service providers in the districts were randomly selected for this study. Results from two-way between-subjects Analysis of Variance (ANOVA) revealed that Hospital B Private and Hospital A Private recorded the highest and lowest mean cost of malaria treatment respectively. The study further revealed that repetition of NHIS registration number, overbilling of drugs, drug mismatch, excessive prescription of drugs for malaria treatment and duplication of clients records were some of the fraud and abuse at the facility.
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