Determining the amount and causes of insurance deficits in selected Teaching and non-Teaching hospitals affiliated to Iran University of Medical Sciences

• Main Authors: mohammadreza maleki, samira bolghadr, asgar aghaeihashjin
• Format: Article
• Language: fas
• Published: Iran University of Medical Sciences 2021-01-01
• Series: مدیریت سلامت
• Subjects: hospital deduction; insurance; teaching hospitals; non-teaching hospitals
• Online Access: http://jha.iums.ac.ir/article-1-3334-en.html

Introduction: Some of the significant and irreparable financial losses in hospitals are Insurance deficits which for various reasons are not fully reimbursed by the insurance companies. Therefore, the present study was an attempt to determine the amount and causes of insurance deficits in selected Teaching  and non-Teaching hospitals affiliated to Iran University of Medical Sciences. Methods: This cross-sectional descriptive study was performed in six selected hospitals of Iran University of Medical Sciences. The research population included patients’records during the first six months of 2020 for inpatient and outpatient wards. Reports of deficits for Health Care and Social Security Insurance were collected by referring to the revenue units of the hospitals. The data collection tool was a researcher-made form. The deficit amount of each hospital was collected separately for the type of file and teaching and non-teaching hospitals. Data were analyzed by descriptive statistics using Excel software. Results: The findings showed that the most deductions applied in inpatient records are related to surgery and hospitalization fees, respectively, and in outpatient documents are related to visits, laboratory services, diagnostic and counseling services. Conclusion: According to the type and causes of deficits identified based on research findings, policy makers and planners in the field of healthcare system are advised to hold workshops for staff in the process of treating patients with insurance rules, using hospital information systems, using relevant graduates, and analyzing files before sending them to insurance companies in order to prevent insurance deficits.