Evidence map›Paper›PMID 42387544›Full record

ArticleBMC health services research2026

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

Mahtab Karami, Shokoofeh Afkhami, Yaser Ghelmani, Monireh Sadeqi Jabali

Abstract read
In one paragraph

Article in BMC health services research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Mahtab KaramiClinical Research Development Center of Shahid Sadoughi Hospital, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.ORCID http://orcid.org/0000-0003-2335-6627
Shokoofeh AfkhamiSchool of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.ORCID https://orcid.org/0000-0001-9305-7900
Yaser GhelmaniDepartment of Internal Medicine, School of Medicine, Shahid Sadoughi General Hospital, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.ORCID https://orcid.org/0000-0002-6905-0407
Monireh Sadeqi JabaliHealth Information Technology Research Center, Isfahan University of Medical Sciences, Isfahan, Iran. msadeqi2005@gmail.com.ORCID http://orcid.org/0000-0001-7520-0398

Funding

Shahid Sadoughi University of Medical Sciences 15577
6 · The paper itself

Abstract

backgroundHospital 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.

methodsThis 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.

resultsIn 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.

conclusionInappropriate 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. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Data AccuracyDocumentationInsurance Claim ReviewInsurance, Health, ReimbursementHumansDocumentationHealth insuranceHospitalInsurance deductions

Identifiers

PMID42387544
PMCPMC13599282

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.