Factors associated with inpatient medical record data quality in hospital settings: a systematic review

Abstract

Inpatient medical record data are an important source of information for clinical care, hospital management, clinical coding, and reimbursement. Poor-quality record data may lead to incomplete documentation, coding errors, inaccurate performance assessment, and distorted reimbursement. In this review, data quality mainly refers to the accuracy, completeness, consistency, timeliness, and validity of inpatient medical record data, including front-page or home-page information and diagnosis/procedure coding data. Evidence on factors associated with these dimensions is scattered across studies of clinical documentation, coding practice, information systems, quality-control, and payment reform. This systematic review aims to synthesise the key associated factors and provide evidence for quality improvement in healthcare organisations. This review followed the PRISMA 2020 reporting guideline and was registered in PROSPERO (CRD420251244232). PubMed, Scopus, CNKI, and Wanfang Data were searched for English and Chinese studies published from 1 January 2021 to 7 November 2025. Two reviewers independently screened records, extracted data, and appraised methodological quality using Joanna Briggs Institute tools. Because of heterogeneity in designs, outcomes, and measurements, findings were synthesised narratively. A total of 29 primary empirical studies were included in the narrative synthesis. Most studies were cross-sectional or retrospective hospital audits, and the overall methodological quality was mainly moderate. Six categories of factors associated with inpatient medical record data quality were identified: clinical documentation and physician-related factors (16 studies), coding staff capacity and professional competence (18 studies), institutional and quality-control mechanisms (19 studies), information-system support (14 studies), training and feedback (20 studies), and external policy or reimbursement pressure (7 studies). The evidence suggests that record quality is shaped by interactions between the data-generation process, coding transformation, organisational governance, technological support, and external incentives. The available evidence suggests that improving inpatient medical record data quality requires coordinated action across clinical documentation, coding capacity, quality-control mechanisms, information systems, training, and the external policy or reimbursement context. However, because much of the evidence comes from cross-sectional studies and is subject to language restrictions and search-field limitations, causal interpretation should remain cautious. This review provides a structured synthesis to inform future empirical studies and hospital quality-improvement work.