ArticleBMC medical informatics and decision making2022
Study of patients' attitude to automatic interpretation of laboratory test results and its influence on follow-up rate.
Article in BMC medical informatics and decision making, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Potential and pitfalls of personal reference intervals in general practice: A focus group and case vignette study among Dutch general practitioners.The European journal of general practice · 2026Article
- The application and challenges of ChatGPT in laboratory medicine.Advances in laboratory medicine · 2025Review
- Article
- Enhancing patient engagement and understanding: is providing direct access to laboratory results through patient portals adequate?JAMIA open · 2025Article
- Increasing the Impact and Value of Laboratory Medicine Through Effective and AI-Assisted Communication.EJIFCC · 2025Review
- Quality of Answers of Generative Large Language Models Versus Peer Users for Interpreting Laboratory Test Results for Lay Patients: Evaluation Study.Journal of medical Internet research · 2024Article
- Article
- Annotation and Information Extraction of Consumer-Friendly Health Articles for Enhancing Laboratory Test Reporting.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2023Article
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Abstract
backgroundOne of the current major factors of not following up on the abnormal test results is the lack of information about the test results and missing interpretations. Clinical decision support systems (CDSS) can become a solution to this problem. However, little is known how patients react to the automatically generated interpretations of the test results, and how this can affect a decision to follow up. In this research, we study how patients perceive the interpretations of the laboratory tests automatically generated by a clinical decision support system depending on how they receive these recommendations and how this affects the follow-up rate.
methodsA study of 3200 patients was done querying the regional patient registry. The patients were divided into 4 groups who received: 1. Recommendations automatically generated by a CDSS with a clear indication of their automatic nature. 2. Recommendations received personally from a doctor with a clear indication of their automatic nature. 3. Recommendations from a doctor with no indication of their automated generation. 4. No recommendations, only the test results. A follow-up rate was calculated as the proportion of patients referred to a laboratory service for a follow-up investigation after receiving a recommendation within two weeks after the first test with abnormal test results had been completed and the interpretation was delivered to the patient. The second phase of the study was a research of the patients' motivation. It was performed with a group of 789 patients.
resultsAll the patients who received interpretations on the abnormal test results demonstrated a significantly higher rate of follow-up (71%) in comparison to the patients who received only test results without interpretations (49%). Patients mention a time factor as a significant benefit of the automatically generated interpretations in comparison to the interpretations they can receive from a doctor.
conclusionThe results of the study show that delivering automatically generated interpretations of test results can support patients in making a decision to follow up. They are trusted by patients and raise their motivations and engagement.
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