{"title":"Bias due to re-used databases: Coding in hospital for extremely vulnerable patients","authors":"Carine Milcent","doi":"10.1016/j.hlpt.2024.100851","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><p>This paper interrogates bias caused by heterogeneity in coding processes through an analysis of electronic medical records EMR databases in France. In general, researchers and professionals often apply data not only for its primary function but also for multiple alternative purposes. However, how they code information might be inconsistent with alternative purposes that exploit existing databases.</p></div><div><h3>Methods</h3><p>Using the EMR acute care and the EMR rehabilitation care databases, we select more than 800,000 patients coded as socially vulnerable during their rehabilitation stay. Statistical analysis was conducted to describe the types of heterogeneity and to compare the distribution of vulnerability coding processes across different hospital statuses and individual social vulnerability roles. Coding process rates were also analyzed.</p></div><div><h3>Results</h3><p>This paper shows the heterogeneity in this process of social vulnerability coding, exploiting acute care database and rehabilitation care database. For groups of patients with ICD-10 coded as socially vulnerable during their rehabilitation stays, the probability of being previously coded as such during their acute care stay is 11.4 % higher in the public sector than in the private one.</p></div><div><h3>Conclusion</h3><p>Implementing the EMR system leads to heterogeneity in the coding process. The paper concludes by arguing that heterogeneity in coding is not random but rather calculated. Applying this database in epidemiologic studies or health economics projects that factor in patients’ vulnerability information may lead to unintended biased results. These findings might also be useful for policymakers using EMR to plan for implementing new reforms in many healthcare settings.</p></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"13 2","pages":"Article 100851"},"PeriodicalIF":3.4000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Health Policy and Technology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2211883724000145","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEALTH POLICY & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Objective
This paper interrogates bias caused by heterogeneity in coding processes through an analysis of electronic medical records EMR databases in France. In general, researchers and professionals often apply data not only for its primary function but also for multiple alternative purposes. However, how they code information might be inconsistent with alternative purposes that exploit existing databases.
Methods
Using the EMR acute care and the EMR rehabilitation care databases, we select more than 800,000 patients coded as socially vulnerable during their rehabilitation stay. Statistical analysis was conducted to describe the types of heterogeneity and to compare the distribution of vulnerability coding processes across different hospital statuses and individual social vulnerability roles. Coding process rates were also analyzed.
Results
This paper shows the heterogeneity in this process of social vulnerability coding, exploiting acute care database and rehabilitation care database. For groups of patients with ICD-10 coded as socially vulnerable during their rehabilitation stays, the probability of being previously coded as such during their acute care stay is 11.4 % higher in the public sector than in the private one.
Conclusion
Implementing the EMR system leads to heterogeneity in the coding process. The paper concludes by arguing that heterogeneity in coding is not random but rather calculated. Applying this database in epidemiologic studies or health economics projects that factor in patients’ vulnerability information may lead to unintended biased results. These findings might also be useful for policymakers using EMR to plan for implementing new reforms in many healthcare settings.
期刊介绍:
Health Policy and Technology (HPT), is the official journal of the Fellowship of Postgraduate Medicine (FPM), a cross-disciplinary journal, which focuses on past, present and future health policy and the role of technology in clinical and non-clinical national and international health environments.
HPT provides a further excellent way for the FPM to continue to make important national and international contributions to development of policy and practice within medicine and related disciplines. The aim of HPT is to publish relevant, timely and accessible articles and commentaries to support policy-makers, health professionals, health technology providers, patient groups and academia interested in health policy and technology.
Topics covered by HPT will include:
- Health technology, including drug discovery, diagnostics, medicines, devices, therapeutic delivery and eHealth systems
- Cross-national comparisons on health policy using evidence-based approaches
- National studies on health policy to determine the outcomes of technology-driven initiatives
- Cross-border eHealth including health tourism
- The digital divide in mobility, access and affordability of healthcare
- Health technology assessment (HTA) methods and tools for evaluating the effectiveness of clinical and non-clinical health technologies
- Health and eHealth indicators and benchmarks (measure/metrics) for understanding the adoption and diffusion of health technologies
- Health and eHealth models and frameworks to support policy-makers and other stakeholders in decision-making
- Stakeholder engagement with health technologies (clinical and patient/citizen buy-in)
- Regulation and health economics