{"title":"Factors affecting clinicians' adherence to principles of diagnosis documentation: A concept mapping approach for improved decision-making.","authors":"Nafiseh Hosseini, Sayyed Mostafa Mostafavi, Kazem Zendehdel, Saeid Eslami","doi":"10.1177/1833358321991362","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The quality of data in electronic health records (EHRs) depends on adherence of clinicians to principles of diagnosis documentation.</p><p><strong>Objective: </strong>A concept mapping (CM) approach was used to extract factors related to quality of clinicians' documentation that govern EHR data quality.</p><p><strong>Method: </strong>Influential factors extracted from brainstorming sessions were sorted by individual participants, followed by a quantitative analysis using multidimensional scaling and cluster analysis to categorise sorted factors. Finally, a questionnaire was used to elicit the importance-feasibility of the extracted factors. Results were visualised by cluster maps and Go-Zone plots.</p><p><strong>Result: </strong>Factors were classified into seven clusters: \"knowledge about International Classification of Diseases and clinical coding,\" \"need for facilitators and guidelines,\" \"explaining the importance of the issue and defining responsibilities,\" \"cooperation of other personnel,\" \"codify legal requirements,\" \"workload\" and \"clinical obstacles,\" as ranked by importance.</p><p><strong>Conclusion: </strong>To enhance the quality of EHR data, a collaboration between physicians, nurses, managers and EHR developers is required. CM is an acceptable approach to meet this objective. Our findings highlight the significance of clinical coding knowledge, awareness about its importance and applicability and use of well-structured information systems. In combination, these three factors can have a strong positive impact on the quality of EHR data.</p><p><strong>Implications: </strong>A list of solutions is provided for policymakers, and two interventions suggested, based on the findings of this study, including the adoption of EHRs that incorporate documentation guidelines. We further propose updated clinical training programs and a monitoring and feedback mechanism to facilitate the EHR documentation process.</p>","PeriodicalId":73210,"journal":{"name":"Health information management : journal of the Health Information Management Association of Australia","volume":"51 3","pages":"149-158"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1833358321991362","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Health information management : journal of the Health Information Management Association of Australia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/1833358321991362","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/4/12 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Background: The quality of data in electronic health records (EHRs) depends on adherence of clinicians to principles of diagnosis documentation.
Objective: A concept mapping (CM) approach was used to extract factors related to quality of clinicians' documentation that govern EHR data quality.
Method: Influential factors extracted from brainstorming sessions were sorted by individual participants, followed by a quantitative analysis using multidimensional scaling and cluster analysis to categorise sorted factors. Finally, a questionnaire was used to elicit the importance-feasibility of the extracted factors. Results were visualised by cluster maps and Go-Zone plots.
Result: Factors were classified into seven clusters: "knowledge about International Classification of Diseases and clinical coding," "need for facilitators and guidelines," "explaining the importance of the issue and defining responsibilities," "cooperation of other personnel," "codify legal requirements," "workload" and "clinical obstacles," as ranked by importance.
Conclusion: To enhance the quality of EHR data, a collaboration between physicians, nurses, managers and EHR developers is required. CM is an acceptable approach to meet this objective. Our findings highlight the significance of clinical coding knowledge, awareness about its importance and applicability and use of well-structured information systems. In combination, these three factors can have a strong positive impact on the quality of EHR data.
Implications: A list of solutions is provided for policymakers, and two interventions suggested, based on the findings of this study, including the adoption of EHRs that incorporate documentation guidelines. We further propose updated clinical training programs and a monitoring and feedback mechanism to facilitate the EHR documentation process.