Development and evaluation of a crowdsourcing methodology for knowledge base construction: Identifying relationships between clinical problems and medications

Journal of the American Medical Informatics Association

Volumn 19, Issue 5, 2012, Pages 713-718

  McCoy, Allison B ^a   Wright, Adam ^b   Laxmisan, Archana ^c   Ottosen, Madelene J ^a   McCoy, Jacob A ^d   Butten, David ^c   Sittig, Dean F ^a  

^a UNIVERSITY OF TEXAS   (United States)

^b BRIGHAM AND WOMEN S HOSPITAL   (United States)

^c BAYLOR COLLEGE OF MEDICINE   (United States)

^d UNIVERSITY OF TEXAS MEDICAL SCHOOL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

PRESCRIPTION DRUG;

ACCURACY; ARTICLE; CROWDSOURCING METHODOLOGY; ELECTRONIC MEDICAL RECORD; EVALUATION; METHODOLOGY; METRIC SYSTEM; SENSITIVITY AND SPECIFICITY; ADOLESCENT; ADULT; CHILD; COMPUTER ASSISTED DRUG THERAPY; CROWDSOURCING; HUMAN; KNOWLEDGE BASE; MEDICAL RECORD; RETROSPECTIVE STUDY; UNITED STATES;

ADOLESCENT; ADULT; CHILD; CROWDSOURCING; DRUG THERAPY, COMPUTER-ASSISTED; ELECTRONIC HEALTH RECORDS; HUMANS; KNOWLEDGE BASES; MEDICAL RECORDS, PROBLEM-ORIENTED; RETROSPECTIVE STUDIES; SENSITIVITY AND SPECIFICITY; TEXAS;

EID: 84872222383     PISSN: 10675027     EISSN: 1527974X     Source Type: Journal    
DOI: 10.1136/amiajnl-2012-000852     Document Type: Article

References (33)

1. Laxmisan A, McCoy AB, Wright A, et al. Clinical Summarization Capabilities of Commercially-Available and Internally-developed Electronic Health Records. Appl Clin Inform 2012;3:80e93.
2. Health IT and Patient Safety: Building Safer systems for Better care - Institute of medicine [Internet]. http://iom.edu/Reports/2011/Health-IT-and-Patient-Safety- Building-Safer-Systems-for-Better-Care.aspx (accessed 9 Nov 2011).
3. Han YY, Carcillo JA, Venkataraman ST, et al. Unexpected increased mortality after implementation of a commercially sold computerized physician order entry system. Pediatrics 2005;116:1506e12.
4. Horsky J, Kuperman GJ, Patel VL. Comprehensive analysis of a medication dosing error related to CPOE. J Am Med Inform Assoc 2005;12:377e82.
5. Koppel R, Metlay JP, Cohen A, et al. Role of computerized physician order entry systems in facilitating medication errors. JAMA 2005;293:1197e203.
6. McCoy AB, Waitman LR, Lewis JB, et al. A framework for evaluating the appropriateness of clinical decision support alerts and responses. J Am Med Inform Assoc 2012;19:346e52. http://www.ncbi.nlm.nih.gov/pubmed/21849334 (accessed 29 Aug 2011).
7. Ash JS, Berg M, Coiera E. Some unintended consequences of information technology in health care: the nature of patient care information system-related errors. J Am Med Inform Assoc 2004;11:104e12.
8. Ash JS, Sittig DF, Poon EG, et al. The extent and importance of unintended consequences related to computerized provider order entry. J Am Med Inform Assoc 2007;14:415e23.
9. Sittig DF, Singh H. Legal, ethical, and financial dilemmas in electronic health record adoption and use. Pediatrics 2011;127:e1042e7.
10. Sittig DF, Teich JM, Osheroff JA, et al. Improving clinical quality indicators through electronic health records: it takes more than just a reminder. Pediatrics 2009;124:375e7.
11. Feblowitz JC, Wright A, Singh H, et al. Summarization of clinical information: a conceptual model. J Biomed Inform 2011;44:688e99.
12. Sittig DF, Singh H. Rights and responsibilities of EHR users. CMAJ. Published Online First: 13 February 2012. doi:10.1503/cmaj.111599
13. Carter JS, Brown SH, Erlbaum MS, et al. Initializing the VA medication reference terminology using UMLS metathesaurus co-occurrences. Proc AMIA Symp 2002:116e20.
14. Elkin PL, Carter JS, Nabar M, et al. Drug knowledge expressed as computable semantic triples. Stud Health Technol Inform 2011;166:38e47.
15. Wright A, Chen ES, Maloney FL. An automated technique for identifying associations between medications, laboratory results and problems. J Biomed Inform 2010;43:891e901.
16. Brown SH, Miller RA, Camp HN, et al. Empirical derivation of an electronic clinically useful problem statement system. Ann Intern Med 1999;131:117e26.
17. Zeng Q, Cimino JJ, Zou KH. Providing concept-oriented views for clinical data using a knowledge-based system: an evaluation. J Am Med Inform Assoc 2002;9:294e305.
18. Chen ES, Hripcsak G, Xu H, et al. Automated acquisition of disease drug knowledge from biomedical and clinical documents: an initial study. J Am Med Inform Assoc 2008;15:87e98.
19. Kilicoglu H, Fiszman M, Rodriguez A, et al. Semantic MEDLINE: A Web Application for Managing the Results of PubMed Searches. Turku, Finland: Proceedings of the Third International Symposium for Semantic Mining in Biomedicine (SMBM), 2008:69e76.
20. Duke JD, Friedlin J. ADESSA: a real-time decision support service for delivery of semantically coded adverse drug event data. AMIA Annu Symp Proc 2010;2010:177e81.
21. Sweidan M, Williamson M, Reeve JF, et al. Evaluation of features to support safety and quality in general practice clinical software. BMC Med Inform Decis Mak 2011;11:27.
22. Tapscott D. Wikinomics: How Mass Collaboration Changes Everything. New York: Portfolio, 2006.
23. Howe J. The rise of crowdsourcing. Wired magazine 2006;14:1e4.
24. Giles J. Internet encyclopaedias go head to head. Nature 2005;438:900e1.
25. Ekins S, Williams AJ. Reaching out to collaborators: crowdsourcing for pharmaceutical research. Pharm Res 2010;27:393e5.
26. Hughes S, Cohen D. Can online consumers contribute to drug knowledge? a mixedmethods comparison of consumer-generated and professionally controlled psychotropic medication information on the internet. J Med Internet Res 2011;13:e53.
27. Brownstein CA, Brownstein JS, Williams DS 3rd, et al. The power of social networking in medicine. Nat Biotechnol 2009;27:888e90.
28. Parry DT, Tsung-Chun T. Crowdsourcing Techniques to Create a Fuzzy Subset of SNOMED CT for Semantic Tagging of Medical Documents. 2010 IEEE International Conference on Fuzzy systems (FUZZ). Barcelona: IEEE, 2010:1e8. doi:10.1109/ FUZZY.2010.5584055
29. Blumenthal D, Tavenner M. The "meaningful use" regulation for electronic health records. N Engl J Med 2010;363:501e4.
30. Elkin PL, Brown SH, Husser CS, et al. Evaluation of the content coverage of SNOMED CT: ability of SNOMED clinical terms to represent clinical problem lists. Mayo Clin Proc 2006;81:741e8.
31. Burton MM, Simonaitis L, Schadow G. Medication and indication linkage: a practical therapy for the problem list? AMIA Annu Symp Proc 2008:86e90.
32. McCoy AB, Wright A, Laxmisan A, et al. A prototype knowledge base and SMART app to facilitate organization of patient medications by clinical problems. AMIA Annu Symp Proc 2011;2011:888e94.
33. Campbell EM, Sittig DF, Ash JS, et al. Types of unintended consequences related to computerized provider order entry. J Am Med Inform Assoc 2006;13:547e56.