Does Moral Hazard Occour in the Implementation of Social Health Insurance? Evidence From Public Hospitals in a Rural Province of Indonesia

Abstract

Indonesia is now encountering moral hazard problems in the implementation of social health insurance. BPJS, as the administrator of Indonesia’s National Health Insurance, reported that there was an increase in deficit in the 4 years of the implementation of National Health Insurance from US$ 228 million in 2014 to US$ 470 million in 2016. Despite efforts conducted to overcome the problem, no evidence-based predictor that might be significantly associated with moral hazard in a rural province hospital in Indonesia. The purpose of this research is to identify the incidence of moral hazard in the implementation of National Health Insurance in Indonesia. Data consisting of 180 medical records obtained from three public hospitals in rural province of Indonesia were selected as samples in this study. These medical records were reviewed by Independent Senior Coder (ISC) who had more than 5 years experiences as a coder. The indicators of moral hazard in this study were upcoding, readmission, and possible unnecessary admission. Logistic regression was used to explore determinant of moral hazard from patient, coder, and physician side. The results show that rate of moral hazard cases for upcoding is 10%, readmission is 2.8%, and possible unnecessary admission is 18.9%. It can be seen from multivariate analysis that discharge status, severity level and LOS have a significant relationship with moral hazard. Illness severity level, Discharge against Medical Advice, and higher Length of Stay are risk factors for moral hazard incidence.

Fraud in healthcare facilities: A Narrative Review

“…The percentage of readmission is 37.9%. This result is greater than the Niu et al (2013) study results, which only stated that almost 20% of readmissions occurred in Medicare patients (Machmud et al, 2020). The percentage of keystroke mistakes is 7.1%.…”

“…Fraud in health care facilities can occur due to several things, including incomplete medical record files (Yuniati, 2017;Zafirah et al, 2017;Zafirah et al, 2018;Bastani et al, 2019;Suryandari, 2019;Kusumawati & Pujiyanto, 2020;Machmud et al, 2020). Then, doctors' writings that are difficult to read also make it difficult for a coder to code for a disease (Yuniati, 2017;Kusumawati & Pujiyanto, 2020;Syafrawati et al, 2020;Taslim et al, 2020).…”

“…Coders who have never received coding training and lack coder work experience (Yuniati, 2017;Bastani et al, 2019;Machmud et al, 2020) and lack knowledge about disease diagnosis codes and procedures (Kusumawati & Pujiyanto, 2020;Syafrawati et al, 2020;Taslim et al, 2020) affect the occurrence of fraud, according to Clark et al (2009) experience is an important factor for the coder in determining the diagnostic code in the medical record (Yuniati, 2017).…”

Analysis of the Impact of Corruption in the Health System and Some Recommendations Concepts

“…Besides, the longer care system is also a burden on patients and has the potential to become fraud in the health sector. (Machmud et al 2020) The study found that the appointment of non-medical doctors as internal veri ers, lack of clarity in guidelines for doctors and coding, and poor coordination between hospitals and health insurance are the causes of upcoding in the hospital (Syafrawati et al, 2020).…”

“…EducationApart from the above factors, there has also been a delay in receiving health care, including slow processing times and gaps in the number of claims and the amount paid(Panda et al, 2016).Indonesia is now facing several problems in implementing BPJS health insurance because it has experienced a de cit from 2014-2018(Machmud et al, 2020) …”