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Clinical Information Retrieval: A Literature Review

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Abstract

Clinical information retrieval (IR) plays a vital role in modern healthcare by facilitating efficient access and analysis of medical literature for clinicians and researchers. This scoping review aims to offer a comprehensive overview of the current state of clinical IR research and identify gaps and potential opportunities for future studies in this field. The main objective was to assess and analyze the existing literature on clinical IR, focusing on the methods, techniques, and tools employed for effective retrieval and analysis of medical information. Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we conducted an extensive search across databases such as Ovid Embase, Ovid Medline, Scopus, ACM Digital Library, IEEE Xplore, and Web of Science, covering publications from January 1, 2010, to January 4, 2023. The rigorous screening process led to the inclusion of 184 papers in our review. Our findings provide a detailed analysis of the clinical IR research landscape, covering aspects like publication trends, data sources, methodologies, evaluation metrics, and applications. The review identifies key research gaps in clinical IR methods such as indexing, ranking, and query expansion, offering insights and opportunities for future studies in clinical IR, thus serving as a guiding framework for upcoming research efforts in this rapidly evolving field. The study also underscores an imperative for innovative research on advanced clinical IR systems capable of fast semantic vector search and adoption of neural IR techniques for effective retrieval of information from unstructured electronic health records (EHRs).

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Data and materials are available in the supplemental files.

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Acknowledgements

The authors would like to acknowledge the support from the National Center for Advancing Translational Sciences (NCATS) U24TR004111, the National Library of Medicine (NLM) R01LM014306, the University of Pittsburgh Clinical and Translational Science Institute (CTSI) Pilot Award, the University of Pittsburgh Momentum Funds, and the School of Health and Rehabilitation Sciences Dean’s Research and Development Award. Authors KR, WH, and HL would like to acknowledge the support from the NLM R01LM011934.

Funding

National Center for Advancing Translational Sciences (NCATS) U24TR004111.

University of Pittsburgh Clinical and Translational Science Institute (CTSI) Pilot Award.

University of Pittsburgh Momentum Funds.

School of Health and Rehabilitation Sciences Dean’s Research and Development Award.

National Library of Medicine R01LM014306, R01LM011934.

Author information

Authors and Affiliations

  1. Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA, USA

    Sonish Sivarajkumar, Shyam Visweswaran & Yanshan Wang

  2. Department of Information Science, University of Pittsburgh, Pittsburgh, PA, USA

    Haneef Ahamed Mohammad & Daqing He

  3. Department of Health Information Management, University of Pittsburgh, Pittsburgh, PA, USA

    David Oniani & Yanshan Wang

  4. School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA

    Kirk Roberts & Hongfang Liu

  5. Department of Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA

    William Hersh

  6. Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA

    Shyam Visweswaran & Yanshan Wang

  7. Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, PA, USA

    Shyam Visweswaran & Yanshan Wang

Authors
  1. Sonish Sivarajkumar
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  2. Haneef Ahamed Mohammad
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  3. David Oniani
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  4. Kirk Roberts
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  5. William Hersh
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  6. Hongfang Liu
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  7. Daqing He
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  8. Shyam Visweswaran
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  9. Yanshan Wang
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Contributions

SS: conceptualized the study, wrote the manuscript; HAM: conducted data analysis; DO: conducted data analysis, edited the manuscript; KR: edited the manuscript; WH: edited the manuscript; HL: edited the manuscript; DH: edited the manuscript; SV: edited the manuscript; YW: conceptualized the study, wrote the manuscript.

Corresponding author

Correspondence to Yanshan Wang.

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Sivarajkumar, S., Mohammad, H.A., Oniani, D. et al. Clinical Information Retrieval: A Literature Review. J Healthc Inform Res 8, 313–352 (2024). https://doi.org/10.1007/s41666-024-00159-4

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  • DOI: https://doi.org/10.1007/s41666-024-00159-4

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