Linking clinical documentation deficiencies to insurance reimbursement losses: a data quality perspective

Hospital claims deductions reduce revenue and quality of services. They are imposed for various reasons, including a lack of proper documentation. This study aimed to identify the extent and causes of the claims deductions in the ROSE (Review of Inpatient Services Evidence) system and the classification of the causes of claims deductions related to documentation deficiencies based on data quality dimensions.

This documentary analysis was conducted in the first half of 2024 at Shahid Sadoughi Hospital in Yazd in two phases. In the first phase, the extent and causes of claims deductions for all medical records with at least one documented deduction (n = 4,674) were identified and extracted directly from the ROSE system and exported to Excel 2016. Data cleaning was performed, including removal of duplicate and incomplete records, consistency checks, system cross-validation, and expert verification. In the second phase, the causes of deductions related to documentation deficiencies were classified based on AHIMA framework for data quality dimensions. Data were analyzed using Excel 2016 and IBM SPSS-21 software through descriptive and inferential statistics, including Chi-square and one-way ANOVA tests. Effect sizes for Chi-square analyses were estimated using Cramér's V.

In terms of locations of service provision, the emergency department had the highest number of deductions (n = 16,337; 28.5%) and largest deduction amount (amount = 6,834,923,119 Iranian Rials (IRR); 35.2%). Among service groups, medical diagnostic tests had the highest frequency of deductions (n = 40,012; 69.7%), while hospitalization services accounted for the largest deduction amount (amount = 5,924,801,117 IRR; 30.5%). These findings indicate that deductions frequency and financial burden were not uniformly distributed across clinical settings and service categories. The frequency of the deductions across locations of service provision and across service groups had a statistically significant difference (P < 0.001). Also, the difference of average amount of deduction between service groups and between locations of service provision was significant (P < 0.001). Inappropriate services were the most common cause of deductions (n = 31,502; 54.9%) and almost all (n = 25,714; 99.6%) the documentation-related deductions were assigned to violations of data accuracy.

Inappropriate services and documentation deficiencies, particularly data accuracy violations, were the major drivers of claims deductions in the ROSE system. By linking reimbursement-related deductions to structured data quality dimensions, this study provides a more nuanced understanding of documentation-related financial losses. Requesting services based on clinical guidelines, improving physician awareness of insurance reimbursement policies and service costs, and strengthening documentation accuracy may help reduce claims deductions. Integrated interventions combining health information technologies, audit-feedback mechanisms, and targeted educational strategies are recommended to improve documentation quality and reduce reimbursement-related financial losses.

Not applicable.