Open AccessA Smart Audit Teaching Case Using CAATs for Medicare
Author(s) -
Shi-Ming Huang Shi-Ming Huang,
heng-HanTsai Shi-Ming Huang
Publication year - 2021
Publication title -
international journal of computer auditing
Language(s) - English
Resource type - Journals
eISSN - 2562-9999
pISSN - 2562-9980
DOI - 10.53106/256299802021120301002
Subject(s) - audit , clinical governance , audit plan , declaration , information technology audit , business , medicine , health care , operations management , process management , joint audit , medical emergency , internal audit , computer science , accounting , engineering , economics , programming language , economic growth
Risk is inherent at all levels of hospital management such as determining healthcare service priorities, purchasing new medical equipment, patient safety, clinical governance, etc. The effectiveness of an audit process in reducing risk is a critical success factor in hospital management. Since hospital data is becoming increasingly larger, the data may be too large for auditors to handle. Consequently, they need to learn a new skill and knowledge to face the digital transformation era. The era of intelligent audit technology has arrived. In the future, auditors can use big data analysis and technology to get the assistance of advanced audit analysis tools. This paper introduces a smart audit case using diagnosis-related group (DRG) data. It explains how to use computer-assisted audit techniques (CAATs) to develop the predictions of DRGs as a starting point, triggering students to analyze the editing of DRG codes in depth by using a machine-learning model to pre-audit the accuracy of inpatient DRGs’ drop point in Health Insurance Declaration forms.