Research

I have made many contributions to science, which are listed below with some representative publications (modeled on the NIH Biosketch).

1. My initial research focused on the development and implementation of information retrieval (IR, also called search) systems in biomedicine and health. I experimented with concept-based approaches to indexing and retrieval of knowledge-based information. Subsequently, I found that methods for evaluation systems were inadequate and developed an interest in new approaches to evaluation. My interests in search have also evolved with the emergence of new content for retrieval, such as medical images and electronic health record data. My recent work focuses on IR needs in the setting of pandemics with rapidly emerging publications and evolving information needs. I am also the author of a textbook in the field.

• Hersh WR, Greenes RA, SAPHIRE: an information retrieval system featuring concept matching, automatic indexing, probabilistic retrieval, and hierarchical relationships, Computers and Biomedical Research, 1990, 23: 410-425.

• Hersh WR, Crabtree MK, Hickam DH, Sacherek L, Friedman CP, Tidmarsh P, Moesbaek C, Kraemer D, Factors associated with success for searching MEDLINE and applying evidence to answer clinical questions, Journal of the American Medical Informatics Association, 2002, 9: 283-293. PMC344588.

• Hersh W, Information Retrieval: A Biomedical and Health Perspective, 4th Edition, New York: Springer, 2020.

• Gupta D, Demner-Fushman D, Hersh W, Bedrick S, Roberts K, Overview of TREC 2024 Biomedical Generative Retrieval (BioGen) Track. arXiv, 2024, doi: 10.48550/arXiv.2411.18069.

2. My work in IR has converged with additional interest in the re-use (or secondary use) of clinical (especially electronic health record) data. The focus of this work has been on the use cases of cohort retrieval and identification of patients with possible rare disease diagnoses.

• Voorhees E, Hersh W, Overview of the TREC 2012 Medical Records Track, The 21st Text Retrieval Conference - TREC 2012.

• Chamberlin SR, Bedrick SD, Cohen AM, Wang Y, Wen A, Liu S, Liu H, Hersh WR, Evaluation of patient-level retrieval from electronic health record data for a cohort discovery task, JAMIA Open, 2020, 3: 395-404, PMC7660955.

• Cohen A, Chamberlin S, Deloughery T, Nguyen M, Bedrick S, Ko JJ, Amin J, Wei A, Hersh W, Detecting rare diseases in electronic health records using machine learning and knowledge engineering: case study of acute hepatic porphyria, PLoS ONE, 2020, 15: e0235574, PMC7331997.

• Hersh W, Cohen A, Nguyen M, Bensching K, Deloughery T, Clinical study applying machine learning to detect a rare disease: results and lessons learned, JAMIA Open, 2022, 5(2):ooac053, PMC9243401.

3. I have also made contributions in conducting systematic reviews of evaluative research of informatics technologies. These reviews can be challenging because many evaluations use weak evaluation methodologies, in part because these technologies are tools rather than typical medical tests or treatments.

• Hersh WR, Hickam DH, How well do physicians use electronic information retrieval systems? A framework for investigation and systematic review, Journal of the American Medical Association, 1998, 280: 1347-1352.

• Hersh WR, Hickam DH, Severance SM, Dana TL, Krages KP, Helfand M, Diagnosis, access, and outcomes: update of a systematic review on telemedicine services, Journal of Telemedicine and Telecare, 2006, 12(Supp 2): 3-31.

• Stanfill MH, Williams M, Fenton SH, Jenders R, Hersh W, A systematic review of automated clinical coding and classification systems, Journal of the American Medical Informatics Association, 2010, 17: 646-651, PMC3000748.

• Hersh W, Totten A, Eden K, Devine B, Gorman P, Kassakian S, Woods SS, Daeges M, Pappas M, McDonagh MS, Outcomes from health information exchange: systematic review and future research needs, JMIR Medical Informatics, 2015, 3(4): e39, PMC4704923.

4. I have also carried out research characterizing the informatics professional workforce. My study on the need for health IT professionals played a role in workforce development being a component of the Health Information Technology for Clinical and Economic Health (HITECH) Act of the American Recovery and Reinvestment Act (ARRA).

• Hersh W, Who are the informaticians? What we know and should know, Journal of the American Medical Informatics Association, 2006, 13: 166-170. PMC1447543.

• Hersh W, Wright A, What workforce is needed to implement the health information technology agenda? Analysis from the HIMSS Analytics™ Database, Proceedings of the AMIA 2008 Annual Symposium, 2008, 303-307. PMC2656033.

• Hersh WR, Margolis A, Quirós F, Otero P, Building a health informatics workforce in developing countries, Health Affairs, 2010, 29: 274-277.

• Hersh W, Boone KW, Totten AM, Characteristics of the healthcare information technology workforce in the HITECH era: underestimated in size, still growing, and adapting to advanced uses, JAMIA Open, 2018, 1: 188-194, PMC6952018.

5. Also, as a result of being an educational leader, I have carried out evaluation of educational programs in informatics, including those using distance learning technologies and artificial intelligence techniques.

• Hersh W, Williamson J, Educating 10,000 informaticians by 2010: the AMIA 10x10 program, International Journal of Medical Informatics, 2007, 76: 377-382.

• Bichel-Findlay J, Koch S, Mantas J, Abdul SS, Al-Shorbaji N, Ammenwerth E, Baum A, Borycki EM, Demiris G, Hasman A, Hersh W, Hovenga E, Huebner UH, Huesing ES, Kushniruk A, Lee KH, Lehmann CU, Lillehaug SI, Marin HF, Marschollek M, Martin-Sanchez F, Merolli M, Nishimwe A, Saranto K, Sent D, Shachak A, Udayasankaran JG, Were MC, Wright G, Recommendations of the International Medical Informatics Association (IMIA) on education in biomedical and health informatics: second revision, International Journal of Medical Informatics, 2023, 170: 104908.

• Hersh W, Fultz Hollis K, Results and implications for generative AI in a large introductory biomedical and health informatics course, npj Digital Medicine, 2024, 7: 247.

• Hersh W, Generative artificial intelligence: implications for biomedical and health professions education. Annual Review of Biomedical Data Science, 2025, 8: 355-380.

Complete List of Published Works in NIH MyBibliography.