Ease of adoption of clinical natural language processing software: An evaluation of five systems

Journal of Biomedical Informatics

Volumn 58, Issue , 2015, Pages S189-S196

  Zheng, Kai ^a   Vydiswaran, V G Vinod ⁱ   Liu, Yang ^a   Wang, Yue ^a   Stubbs, Amber ^b   Uzuner, Özlem ^c   Gururaj, Anupama E ^d   Bayer, Samuel ^e   Aberdeen, John ^e   Rumshisky, Anna ^f   Pakhomov, Serguei ^g   Liu, Hongfang ^h   Xu, Hua ^d  

^a UNIVERSITY OF MICHIGAN   (United States)

^b SIMMONS COLLEGE   (United States)

^c STATE UNIVERSITY OF NEW YORK   (United States)

^d UNIVERSITY OF TEXAS   (United States)

^e MITRE CORPORATION   (United States)

^f University of Massachusetts Lowell   (United States)

^g UNIVERSITY OF MINNESOTA   (United States)

^h MAYO CLINIC   (United States)

ⁱ UNIVERSITY OF MICHIGAN MEDICAL SCHOOL   (United States)

Author keywords

Human computer interaction; Natural language processing L01.224.065.580 ; Software design L01.224.900.820 ; Software validation L01.224.900.868 ; Usability; User computer interface L01.224.900.910

Indexed keywords

COMPUTATIONAL LINGUISTICS; COMPUTER SOFTWARE; DIAGNOSIS; HUMAN COMPUTER INTERACTION; MEDICINE; PACKAGING MATERIALS; SOFTWARE DESIGN; SOFTWARE TESTING;

COMMUNICATION EFFECTIVENESS; NATURAL LANGUAGE PROCESSING; PARTICIPATING SYSTEMS; SOFTWARE DISTRIBUTIONS; SOFTWARE USABILITIES; SOFTWARE VALIDATION; USABILITY; USER-COMPUTER INTERFACES;

NATURAL LANGUAGE PROCESSING SYSTEMS;

ARTICLE; BIOMEDICAL INFORMATION COLLECTION AND UNDERSTANDING SYSTEM; CLINICAL NAMED ENTITY RECOGNITION SYSTEM; COMPUTER ANALYSIS; COMPUTER INTERFACE; COMPUTER PROGRAM; DATA ANALYSIS SOFTWARE; HUMAN COMPUTER INTERACTION; INFORMATION TECHNOLOGY; MEDICATION EXTRACTION AND NORMALIZATION; MEDICATION INFORMATION EXTRACTION SYSTEM; MITRE IDENTIFICATION SCRUBBER TOOLKIT; NATURAL LANGUAGE PROCESSING; PRACTICE GUIDELINE; PRIORITY JOURNAL; PROGRAM EFFECTIVENESS; QUALITATIVE ANALYSIS; ATTITUDE TO COMPUTERS; AUTOMATED PATTERN RECOGNITION; COMPARATIVE STUDY; DATA MINING; ELECTRONIC HEALTH RECORD; EVALUATION STUDY; HUMAN; MIDDLE AGED; PROCEDURES; SOFTWARE; STATISTICS AND NUMERICAL DATA; UTILIZATION;

ATTITUDE TO COMPUTERS; DATA MINING; ELECTRONIC HEALTH RECORDS; HUMANS; MIDDLE AGED; NATURAL LANGUAGE PROCESSING; PATTERN RECOGNITION, AUTOMATED; SOFTWARE; USER-COMPUTER INTERFACE;

EID: 84938262566     PISSN: 15320464     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jbi.2015.07.008     Document Type: Article

References (23)

1. Huang Y., Gottardo R. Comparability and reproducibility of biomedical data. Brief Bioinform. 2013, 14(4):391-401.
2. Boonstra A., Broekhuis M. Barriers to the acceptance of electronic medical records by physicians from systematic review to taxonomy and interventions. BMC Health Serv Res. 2010, 10:231.
3. Blumenthal D. Launching HITECH. N. Engl. J. Med. 2010, 362(5):382-385.
4. National Research Council. Computational Technology for Effective Health Care: Immediate Steps and Strategic Directions. Washington, DC, USA: National Academies Press; 2009.
5. Middleton B., Bloomrosen M., Dente M.A., Hashmat B., Koppel R., Overhage J.M., Payne T.H., Rosenbloom S.T., Weaver C., Zhang J. American Medical Informatics Association. Enhancing patient safety and quality of care by improving the usability of electronic health record systems: recommendations from AMIA. J. Am. Med. Inform. Assoc. 2013, 20(e1):e2-e8.
6. Campbell E.M., Sittig D.F., Ash J.S., Guappone K.P., Dykstra R.H. Types of unintended consequences related to computerized provider order entry. J. Am. Med. Inform. Assoc. 2006, 13(5):547-556.
7. Kohane I.S. Using electronic health records to drive discovery in disease genomics. Nat. Rev. Genet. 2011, 12(6):417-428.
8. Roden D.M., Xu H., Denny J.C., Wilke R.A. Electronic medical records as a tool in clinical pharmacology: opportunities and challenges. Clin. Pharmacol. Ther. 2012, 91(6):1083-1086.
9. Meystre S.M., Savova G.K., Kipper-Schuler K.C., Hurdle J.F. Extracting information from textual documents in the electronic health record: a review of recent research. Yearb Med. Inform. 2008, 128-144.
10. Haerian K., Varn D., Vaidya S., Ena L., Chase H.S., Friedman C. Detection of pharmacovigilance-related adverse events using electronic health records and automated methods. Clin. Pharmacol. Ther. 2012, 92(2):228-234.
11. Gottesman O., Kuivaniemi H., Tromp G., Faucett W.A., Li R., Manolio T.A., Sanderson S.C., Kannry J., Zinberg R., Basford M.A., Brilliant M., Carey D.J., Chisholm R.L., Chute C.G., Connolly J.J., Crosslin D., Denny J.C., Gallego C.J., Haines J.L., Hakonarson H., Harley J., Jarvik G.P., Kohane I., Kullo I.J., Larson E.B., McCarty C., Ritchie M.D., Roden D.M., Smith M.E., Böttinger E.P., Williams M.S. eMERGE Network. the electronic medical records and genomics (eMERGE) network: past, present, and future. Genet. Med. 2013, 15(10):761-771.
12. Wilke R.A., Xu H., Denny J.C., Roden D.M., Krauss R.M., McCarty C.A., Davis R.L., Skaar T., Lamba J., Savova G. The emerging role of electronic medical records in pharmacogenomics. Clin. Pharmacol. Ther. 2011, 89(3):379-386.
13. Ghassemi, M., Naumann, T., Doshi-Velez, F., Brimmer, N., Joshi, R., Rumshisky, A., Szolovits, P., 2014. Unfolding physiological state: mortality modelling in intensive care units. In: Proceedings of the 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '14), pp. 75-84.
14. Chapman W.W., Nadkarni P.M., Hirschman L., D'Avolio L.W., Savova G.K., Uzuner Ö. Overcoming barriers to NLP for clinical text: the role of shared tasks and the need for additional creative solutions. J. Am. Med. Inform. Assoc. 2011, 18(5):540-543.
15. Davis F.D. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quart. 1989, 13(3):319-340.
16. Venkatesh V., Morris M.G., Davis G.B., Davis F.D. User acceptance of information technology: toward a unified view. MIS Quart. 2003, 27(3):425-478.
17. Scott C.A. The effects of trial and incentives on repeat purchase behavior. J. Mark. Res. 1976, 13(3):263-269.
18. Rogers E.M. Diffusion of innovations 2003, Free Press, New York. fifth ed.
19. Liu Y., Bill R., Fiszman M., Rindflesch T., Pedersen T., Melton G.B., Pakhomov S.V. Using SemRep to label semantic relations extracted from clinical text. AMIA Annu. Symp. Proc. 2012, 587-595.
20. Boag W., Wacome K., Naumann T., Rumshisky A. CliNER: a lightweight tool for clinical concept extraction 2015, AMIA Joint Summits on Clinical Research Informatics, San Francisco, CA.
21. Xu H., Stenner S.P., Doan S., Johnson K.B., Waitman L.R., Denny J.C. MedEx: a medication information extraction system for clinical narratives. J. Am. Med. Inform. Assoc. 2010, 17(1):19-24.
22. Sohn S., Clark C., Halgrim S.R., Murphy S.P., Chute C.G., Liu H. MedXN: an open source medication extraction and normalization tool for clinical text. J. Am. Med. Inform. Assoc. 2014, 21(5):858-865.
23. Aberdeen J., Bayer S., Yeniterzi R., Wellner B., Clark C., Hanauer D., Malin B., Hirschman L. The MITRE identification scrubber toolkit: design, training, and assessment. Int. J. Med. Inform. 2010, 79(12):849-859.