LabQAR: A Manually Curated Dataset for Question Answering on Laboratory Test Reference Ranges and Interpretation

Abstract Laboratory tests are crucial for diagnosing and managing health conditions, providing essential reference ranges for result interpretation. The diversity of lab tests, influenced by variables like the specimen type (e.g., blood, urine), gender, age-specific, and other influencing factors such as pregnancy, makes automated interpretation challenging. Automated clinical decision support systems attempting to interpret these values must account for such nuances to avoid misdiagnoses or incorrect clinical decisions. In this regard, we present LabQAR (Laboratory Question Answering with Reference Ranges), a manually curated dataset comprising 550 lab test reference ranges derived from authoritative medical sources, encompassing 363 unique lab tests and including multiple-choice questions with annotations on reference ranges, specimen types, and other factors impacting interpretation. We also assess the performance of several large language models (LLMs), including LLaMA 3.1, GatorTronGPT, GPT-3.5, GPT-4, and GPT-4o, in predicting reference ranges and classifying results as normal, low, or high. The findings indicate that GPT-4o outperforms other models, showcasing the potential of LLMs in clinical decision support. Competing Interest Statement The authors have declared no competing interest. Funding Statement This work was supported by the Agency for Healthcare Research and Quality grant R21HS029969 (PI: ZH). This project was also partially supported by the University of Florida-Florida State University Clinical and Translational Science Award, which is supported in part by the National Center for Advancing Translational Sciences under award UL1TR001427. QJ and ZL were supported by the NIH Intramural Research Program, National Library of Medicine. Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The source data is publicly available. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data Availability All data produced in the present study are available upon reasonable request to the authors.