Formal representation of eligibility criteria: A literature review

Journal of Biomedical Informatics

Volumn 43, Issue 3, 2010, Pages 451-467

  Weng, Chunhua ^a   Tu, Samson W ^b   Sim, Ida ^c   Richesson, Rachel ^d  

^a Och Spine at New York Presbyterian Hospitals   (United States)

^b STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

^d UNIVERSITY OF SOUTH FLORIDA   (United States)

Author keywords

Clinical decision support systems; Clinical research; Electronic health records; Eligibility criteria; Knowledge representation

Indexed keywords

CLINICAL APPLICATION; CLINICAL DECISION SUPPORT SYSTEMS; CLINICAL RESEARCH; DECISION SUPPORTS; ELECTRONIC HEALTH RECORD; ELECTRONIC HEALTH RECORDS; EXPRESSION LANGUAGES; FORMAL KNOWLEDGE; FORMAL REPRESENTATIONS; LITERATURE REVIEWS; PATIENT DATA;

ARTIFICIAL INTELLIGENCE; DECISION MAKING; DECISION SUPPORT SYSTEMS; DECISION THEORY; HOSPITAL DATA PROCESSING; KNOWLEDGE MANAGEMENT; LINGUISTICS; OBJECT ORIENTED PROGRAMMING; RECORDS MANAGEMENT; RESEARCH;

KNOWLEDGE REPRESENTATION;

BIOINFORMATICS; CLASSIFICATION; CLINICAL RESEARCH; COST EFFECTIVENESS ANALYSIS; DECISION SUPPORT SYSTEM; LANGUAGE; MEDICAL LITERATURE; PATIENT CODING; PRIORITY JOURNAL; REVIEW; SAMPLING; STANDARDIZATION; CLINICAL TRIAL (TOPIC); CONTROLLED VOCABULARY; HUMAN; INFORMATION RETRIEVAL; NATURAL LANGUAGE PROCESSING; PATIENT SELECTION; PROCEDURES;

CLINICAL TRIALS AS TOPIC; HUMANS; INFORMATION STORAGE AND RETRIEVAL; NATURAL LANGUAGE PROCESSING; PATIENT SELECTION; VOCABULARY, CONTROLLED;

EID: 77952742925     PISSN: 15320464     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jbi.2009.12.004     Document Type: Review

References (92)

1. Wang D., Peleg M., Tu S.W., Boxwala A.A., Greenes R.A., et al. Representation primitives, process models and patient data in computer-interpretable clinical practice guidelines: a literature review of guideline representation models. Int J Med Inform 68 (2002) 59-70
2. Newell A. The knowledge level. AI Mag 2 (1981) 1-33
3. Klausner R.D., Silva J.S., Ball M.J., Chute C.G., Douglas J.V., et al. Cancer informatics. 1st ed. (2002), Springer
4. Olasav B, Sim I. RuleEd, a web-based semantic network interface for constructing and revising computable eligibility rules. In: American medical informatics annual symposium, November 11-15, 2006, Washington, DC; 2006. p. 1051.
5. Niland J, Dorr D, El Saadawi G, Embi P, Richesson RL, et al. Knowledge representation of eligibility criteria in clinical trials. In: American medical informatics association annual symposium, Chicago; 2007.
6. ERGO: a template-based expression language for encoding eligibility criteria, ; 2009 [accessed 24.11.09].
7. Clinical research filtered query. ; 2008 [accessed 23.04.08].
8. Niland J. ASPIRE: agreement on standardized protocol inclusion requirements for eligibility. In: An unpublished web resource; 2007.
9. Papaconstantinou C., Theocharous G., and Mahadevan S. An expert system for assigning patients into clinical trials based on Bayesian networks. J Med Syst 22 (1998) 189-202
10. Séroussi J.B., Bouaud J., Antoine E.-C., Zelek L., and Spielmann M. Using OncoDoc as a computer-based eligibility screening system to improve accrual onto breast cancer clinical trials. Artif Intell Med 29 (2001) 153-167
11. Ohno-Machado L, Wang S, Mar P, Boxwala A. Decision support for clinical trial eligibility determination in breast cancer. In: Proceedings of the AMIA symposium; 1999. p. 340-4.
12. Wang SJ, Ohno-Machado L, Mar P, Boxwala AA, Greenes RA. Enhancing Arden syntax for clinical trial eligibility criteria. In: Proceedings of the AMIA symposium; 1999. p. 1188.
13. Séroussi B., Bouaud J., and Antoine E.-C. OncoDoc: a successful experiment of computer-supported guideline development and implementation in the treatment of breast cancer. Artif Intell Med 22 (2001) 43-64
14. Fink E, Hall LO, Goldgof DB, Goswami BD, Boonstra M, Krischer JP. Experiments on the automated selection of patients for clinical trials. In: Proceedings of the IEEE international conference on systems, man, and cybernetics; 2003. p. 4541-5.
15. Fink E., Kokku P.K., Nikiforou S., Hall L.O., Goldgof D.B., and Krischer J.P. Selection of patients for clinical trials: an interactive web-based system. Artif Intell Med 31 (2004) 241-254
16. Nikiforou S, Fink E, Hall LO, Goldgof DB, Krischer JP. Knowledge acquisition for clinical-trial selection. In: Proceedings of the IEEE international conference on systems, man, and cybernetics; 2002. p. 66-71.
17. Metz M.J., Coyle C., Hudson C., and Hampshire M. An internet-based cancer clinical trials matching resource. J Med Internet Res 7 3 (2005) e24
18. Cohen Eea. caMATCH: a patient matching tool for clinical trials. In: caBIG annual meeting; 2005.
19. Gennari J, Sklar D, Silva J. Cross-tool communication: from protocol authoring to eligibility determination. In: Proceedings of the AMIA symposium; 2001. p. 199-203.
20. Ohno-Machado L, Parra E, Henry S, Tu S, Musen M. AIDS2: a decision-support tool for decreasing physicians' uncertainty regarding patient eligibility for HIV treatment protocols. In: Proceedings of the annual symposium on computer application in medical care; 1993. p. 429-33.
21. Lonsdale D.W., Tustison C., Parker C.G., and Embley D.W. Assessing clinical trial eligibility with logic expression queries. Data Knowl Eng 66 1 (2007) 3-17
22. Butte A, Weinstein D, Kohane I. Enrolling patients into clinical trials faster using RealTime recruiting. In: Proceedings of the AMIA symposium; 2000. p. 111-5.
23. Patel C, Cimino J, Dolby J, Fokoue A, Kalyanpur A, Kershenbaum A, et al. Matching patient records to clinical trials using ontologies. IBM Thomas J. Watson Research Center; 2007.
24. Patel C, Cimino J, Dolby J, Fokoue A, Kalyanpur A, Kershenbaum A, et al. Matching patient records to clinical trials using ontologies. In: Proceedings of international semantic web conference; 2007. p. 816-29.
25. Patel C, Cimino J. Semantic query generation from eligibility criteria in clinical trials. In: Proceedings of the AMIA annual symposium; 2007. p. 1070.
26. Musen M, Carlson R, Fagan L, Deresinski S, Shortliffe E. T-HELPER: automated support for community-based clinical research. In: Proceedings of the annual symposium on computer application in medical care; 1992. p. 719-23.
27. Rubin D, Gennari J, Srinivas S, Yuen A, Kaizer H, Musen M, et al. Tool support for authoring eligibility criteria for cancer trials. In: Proceedings of the AMIA symposium; 1999. p. 369-73.
28. Patel C, Cimino J. Using ontology reasoning to match electronic patient records to clinical trials. In: Proceedings of the AMIA'06, Washington, DC; 2006.
29. Musen M.A., Tu S.W., Das A.K., and Shahar Y. EON: a component-based approach to automation of protocol-directed therapy. J Am Med Inform Assoc 3 (1996) 367-388
30. Hammond P., and Sergot M. Computer support for protocol-based treatment of cancer. J Logic Programm 26 (1996) 93-111
31. Sutton D.R., and Fox J. The syntax and semantics of the PROforma guideline modeling language. J Am Med Inform Assoc 10 (2003) 433-443
32. Fox J., Johns N., Lyons C., Rahmanzadeh A., Thomson R., and Wilson P. PROforma: a general technology for clinical decision support systems. Comput Meth Program Biomed 54 (1997) 59-67
33. Shahar Y., Miksch S., and Johnson P. The Asgaard project: a task-specific framework for the application and critiquing of time-oriented clinical guidelines. Artif Intell Med 14 (1998) 29-51
34. Miksch S, Shahar Y, Johnson. P. Asbru: a task-specific, intention-based, and time-oriented language for representing skeletal plans. In: Proceedings of the 7th workshop on knowledge engineering methods and languages (KEML-97), Milton Keynes, UK; 1997. p. 1-20.
35. Boxwala A. GLIF3: a representation format for sharable computer-interpretable clinical practice guidelines. J Biomed Inform 37 (2004) 147-161
36. Tu S.W., Campbell J.R., Glasgow J., Nyman M.A., McClure R., McClay J., et al. The SAGE guideline model: achievements and overview. J Am Med Inform Assoc 14 (2007) 589-598
37. Quaglini S., Stefanelli M., Cavallini A., Micieli G., Fassino C., and Mossa C. Guideline-based careflow systems. Artif Intell Med 20 (2000) 5-22
38. Quaglini S., Stefanelli M., Lanzola G., Caporusso V., and Panzarasa S. Flexible guideline-based patient careflow systems. Artif Intell Med 22 (2001) 65-80
39. Johnson P, Tu S, Booth N, Sugden B, Purves I. Using scenarios in chronic disease management guidelines for primary care. In: Proceedings of the AMIA symposium; 2000. p. 389-93.
40. Shortliffe EH, Scott AC, Bischoff MB, Campbell AB, Melle Wv, Jacobs CD. ONCOCIN: an expert system for oncology protocol management. In: Seventh international joint conference on artificial intelligence, Vancouver, BC; 1981.
41. Sim I., Olasov B., and Carini S. An ontology of randomized controlled trials for evidence-based practice: content specification and evaluation using the competency decomposition method. J Biomed Inform 37 (2004) 108-119
42. Nammuni K., Pickering C., Modgil S., Montgomery A., Hammond P., Wyatt J.C., et al. Design-a-trial: a rule-based decision support system for clinical trial design. Knowl-Based Syst 17 (2004) 121-129
43. Chute C. Medical concept representation. In: Medical informatics: knowledge management and data mining in biomedicine. US: Springer; 2005 [chapter 6].
44. Li L, Chase H, Patel C, Friedman C, Weng C. Comparing ICD9-encoded diagnoses and NLP-processed discharge summaries for clinical trials pre-screening: a case study. In: Proceedings of 2008 AMIA fall symposium; 2008. p. 404-8.
45. CancerGrid, ; 2008 [accessed 02.08.08].
46. Van Spall H.G.C., Toren A., Kiss A., and Fowler R.A. Review: eligibility criteria of randomized controlled trials published in high-impact general medical journals. A systematic sampling review. JAMA 297 (2007) 1233-1240
47. PDQ, ; 2008 [accessed 04.08.08].
48. Tu S.W. A methodology for determining patients' eligibility for clinical trials. Meth Inf Med 32 (1993) 317-325
49. Peleg M., Tu S., Bury J., Ciccarese P., Fox J., et al. Comparing computer-interpretable guideline models: a case-study approach. J Am Med Inform Assoc 10 (2003) 52-68
50. Protege, ; 2000 [accessed 24.11.09].
51. Chamberlin DD, Boyce RF. SEQUEL: a structured english query language. In: Proceedings of the 1974 ACM SIGFIDET workshop on data description, access and control: association for computing machinery; 1974. p. 249-64.
52. Baader F., Calvanese D., McGuinness D.L., Nardi D., and Patel-Schneider P.F. The description logic handbook: theory, implementation, applications (2003), Cambridge University Press, Cambridge, UK ISBN: 0-521-78176-0
53. Sordo M., Boxwala A., Ogunyemi O., and Greenes R. Description and status update on GELLO: a proposed standardized object-oriented expression language for clinical decision support. Stud Health Technol Inform 107 (2004) 164-168
54. O'Connor MJ, Tu SW, Musen MA. The Chronus II temporal database mediator. In: AMIA annual symposium, San Antonio, TX; 2002.
55. Richters M. A precise approach to validating UML models and OCL constraints (2001), Logos Verlag, Berlin
56. Current procedural terminology, ; 2009 [accessed 24.11.09].
57. Hulse R., Clark S., Jackson J., Warner H., and Gardner R. Computerized medication monitoring system. Am J Hosp Pharm 33 (1976) 1061-1064
58. McDonald C.J., Murray R., Jeris D., Bhargava B., Seeger J., et al. A computer-based record and clinical monitoring system for ambulatory care. Am J Public Health 67 (1977) 240-245
59. The knowledge interchange format (KIF), ; 2009 [accessed 24.11.09].
60. Tu S, Musen M. Modeling data and knowledge in the EON guideline architecture. In: MedInfo; 2001. p. 280-4.
61. GELLO at OpenClinical, ; 2009 [accessed 18.05.09].
62. Medical objects, ; 2008 [accessed 03.08.08].
63. InferMed, ; 2008 [accessed 03.08.08].
64. Weng C, Kahn M, Gennari J. Temporal knowledge representation for scheduling tasks in clinical trial protocols. In: American medical informatics association annual symposium, San Antonio; 2002. p. 879-83.
65. Carlson R, Tu S, Lane N, Lai T, Kemper C, Musen M, Shortliffe E. Computer-based screening of patients with HIV/AIDS for clinical-trial eligibility. Online J Curr Clin Trials 1995. Doc. No. 179.
66. Das A.K., and Musen M.A. A temporal query system for protocol-directed decision support. Meth Inf Med 33 (1994) 358-370
67. Ahn I., Ariav G., Batory D., Clifford J., Dyreson C., et al. The temporal query language TSQL2. In: Snodgrass R.T.E. (Ed). Health telematics for clinical guidelines and protocols (1995), Kluwer Academic Press 3-15
68. Lin RS, Rhee S, Shafer RW, Das AK. A combined data mining approach for infrequent events: analyzing HIV mutation changes based on treatment history. In: Computational systems bioinformatics, Stanford; 2006.
69. Cooper G, Buchanan B, Kayaalp M, Saul M, Vries J. Using computer modeling to help identify patient subgroups in clinical data repositories. In: Proceedings of AMIA symposium; 1998. p. 180-4.
70. Hampton T. Rare disease research gets boost. JAMA 295 (2006) 2836-2838
71. SAGE guideline model technical specification, [accessed 20.12.09].
72. Lindberg D., Humphreys B., and McCray A. The unified medical language system. Meth Inf Med 32 (1993) 281-291
73. Friedman C. Towards a comprehensive medical language processing system: methods and issues. In: Proceedings of the AMIA annual fall symposium; 1997. p. 595-9.
74. Huff S.M., Rocha R.A., McDonald C.J., De Moor G.J.E., Fiers T., et al. Development of the logical observation identifier names and codes (LOINC) vocabulary. J Am Med Inform Assoc 5 (1998) 276-292
75. Jenders RA, Corman R, Dasgupta B. Making the standard more standard: a data and query model for knowledge representation in the Arden syntax. In: Proceedings of the AMIA annual symposium; 2003. p. 323-30.
76. Trialx, ; 2009 [accessed 12.12.09].
77. SNOMED-CT, ; 2009 [accessed 24.11.09].
78. Chisholm J. The read clinical classification. BMJ (1990) 300
79. Medical subject headings (MeSH), ; 2009 [accessed 26.05.09].
80. Carter J, Brown S, Erlbaum M, Gregg W, Elkin P, et al. Initializing the VA medication reference terminology using UMLS metathesaurus co-occurrences. In: Proceedings of the AMIA symposium; 2002. p. 116-20.
81. Johnson P, Tu S, Musen M. A virtual medical record for guideline-based decision support. In: Proceedings of the AMIA annual fall symposium; 2001. p. 294-8.
82. Jenders R, Sujansky W, Broverman C, Chadwick M. Towards improved knowledge sharing: assessment of the HL7 reference information model to support medical logic module queries. In: Proceedings of the AMIA annual fall symposium; 1997. p. 308-12.
83. Richesson R.L., and Krischer J. Data standards in clinical research: gaps, overlaps, challenges and future directions. J Am Med Inform Assoc 14 (2007) 687-696
84. Richesson R., Andrews J., and Krischer J. Use of SNOMED CT to represent clinical research data: a semantic characterization of data items on case report forms in vasculitis research. J Am Med Inform Assoc 13 (2006) 536-546
85. CHI (Consolidated Health Informatics). Standards adoption recommendation. Functioning and disability: consolidated health informatics, 12/12/2006. Report No.: Disability Public Full.doc; 2006.
86. Making the "Minimum Data Set" compliant with health information technology standards, ; 2009 [accessed 24.11.09].
87. Nadkarni P., and Brandt C. The common data elements for cancer research: remarks on functions and structure. Meth Inf Med 45 (2006) 594-601
88. Covitz P.A., et al. CaCORE: a common infrastructure for cancer informatics. Bioinformatics 19 (2003) 2404-2412
89. Warzel DB. Common data element (CDE) management and deployment in clinical trials. In: Proceedings of the AMIA fall symposium; 2003. p. 1048.
90. Kahn M.G., Fagan L.M., and Tu S.W. Extensions to the time-oriented database model to support temporal reasoning in medical expert systems. Meth Inf Med 30 (1989) 4-14
91. Modgil S., and Hammond P. Decision support tools for clinical trial design. Artif Intell Med 27 (2003) 181-200
92. Tu S, Musen M. A flexible approach to guideline modeling. In: Proceedings of the AMIA symposium; 1999. p. 420-4.