Health insurance claims management systems: Potential factors affecting their decisions

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Type of the article: Research Article

Abstract
This study examines how patients’ health insurance claims were denied by different insurance providers at a Saudi Academic Medical Center (AMC), exploring the reasons for these rejections, their relationship to claim characteristics, and the factors that predict health insurance claim rejections. A descriptive study design was employed, involving a retrospective review of all insurance claims submitted by both inpatients and outpatients between January and December 2023 at a tertiary care AMC in Saudi Arabia. Following data screening using the UCAF 2.0 form, all denied insurance claims cases (n = 1,117) were subjected to qualitative analysis. The majority of rejected health insurance claims were submitted by female patients (56.9%) and outpatients (93.6%). Among the insurance companies studied, “Tawuniya” rejects the most insurance claims (n = 730). Variables such as age, gender, and insurance company were significantly associated with the reasons for denying claims (p < 0.05). Furthermore, variables such as age, cost, department type (inpatient/outpatient), and the month of claims are significant predictors of claim rejections (p < 0.05). However, gender, insurance companies, and clinical diagnosis were not significant (p > 0.05). The primary reasons for insurance claim denials in Saudi Arabia are missing medical data, system errors, and non-coverage of specific conditions. This study will help insurance companies and patients identify trends and reasons for claim rejections, enabling them to implement more effective preventive and corrective measures.

Acknowledgments
The authors expressed their gratitude to Imam Abdulrahman Bin Faisal University for granting permission [IRB-2024-03-188] to conduct this study.

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    • Table 1. Demographic profile
    • Table 2. Chi-square statistic showing the association between insurance claim rejection reasons and the gender of patients
    • Table 3. Chi-square statistic showing the association between insurance claim rejection reasons and the age group of patients
    • Table A1. Chi-square statistic showing the association between insurance claim rejection reasons concerning different insurance companies
    • Table B1. Linear regression showing those independent variables predicting insurance rejection claims
    • Conceptualization
      Nouf Khalid Al-Kahtani, Mariam AL-Abdulwahab, Zahra Aljafar, Vinoth Raman
    • Investigation
      Nouf Khalid Al-Kahtani, Manal Alshakhs, Naof Faiz Saleem Al-Ansary, Mariam AL-Abdulwahab, Zahra Aljafar
    • Project administration
      Nouf Khalid Al-Kahtani, Arun Vijay Subbarayalu
    • Resources
      Nouf Khalid Al-Kahtani, Naof Faiz Saleem Al-Ansary
    • Supervision
      Nouf Khalid Al-Kahtani, Manal Alshakhs
    • Writing – original draft
      Nouf Khalid Al-Kahtani, Arun Vijay Subbarayalu, Manal Alshakhs, Naof Faiz Saleem Al-Ansary
    • Writing – review & editing
      Nouf Khalid Al-Kahtani, Arun Vijay Subbarayalu, Naof Faiz Saleem Al-Ansary
    • Data curation
      Arun Vijay Subbarayalu, Mariam AL-Abdulwahab, Zahra Aljafar, Vinoth Raman
    • Methodology
      Arun Vijay Subbarayalu, Mariam AL-Abdulwahab, Zahra Aljafar
    • Validation
      Manal Alshakhs
    • Formal Analysis
      Vinoth Raman
    • Visualization
      Vinoth Raman