Building a hospital referral expert system with a Prediction and Optimization-Based Decision Support System algorithm

Journal of Biomedical Informatics

Volumn 41, Issue 2, 2008, Pages 371-386

  Chi, Chih Lin ^a   Street, W Nick ^b   Ward, Marcia M ^b  

^a University of Iowa Libraries   (United States)

^b UNIVERSITY OF IOWA   (United States)

Author keywords

Artificial intelligence; Data mining; Decision support systems; Expert systems; Hospital quality; Hospital referral; Machine learning; Optimization; Support vector machines

Indexed keywords

DATA MINING; EXPERT SYSTEMS; HEALTH RISKS; HOSPITALS; LEARNING ALGORITHMS; PATIENT MONITORING; SUPPORT VECTOR MACHINES;

HOSPITAL FEATURES; HOSPITAL QUALITY; HOSPITAL REFERRAL; TRAVELING DISTANCE;

DECISION SUPPORT SYSTEMS;

ALGORITHM; ARTICLE; CLASSIFICATION ALGORITHM; DECISION SUPPORT SYSTEM; EXPERT SYSTEM; HOSPITAL INFORMATION SYSTEM; MACHINE LEARNING; PATIENT REFERRAL; PATIENT TRANSPORT; PREDICTION; PRIORITY JOURNAL; RISK FACTOR; SURVIVAL; TRAVEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DECISION SUPPORT SYSTEMS, CLINICAL; EXPERT SYSTEMS; HOSPITALIZATION; REFERRAL AND CONSULTATION;

EID: 40049102115     PISSN: 15320464     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jbi.2007.10.002     Document Type: Article

References (44)

1. Abidi S.S.R., Cheah Y.-N., and Curran J. A knowledge creation info-structure to acquire and crystallize the tacit knowledge of health-care experts. IEEE Trans Inform Technol Biomed 9 2 (2005) 193-204
2. Allison J.J., Kiefe C.I., Weissman N.W., Person S.D., Rousculp M., Canto J.G., et al. Relationship of hospital teaching status with quality of care and mortality for medicare patients with acute MI. J Am Med Assoc 284 10 (2000) 1256-1262
3. The American Hospital Association. Data source, [Accessed in April 2007].
4. Ayanian J.Z., and Weissman J.S. Teaching hospitals and quality of care: a review of the literature. Milbank Q 80 3 (2002) 569-593
5. Bali R.K., Feng D.D., Burstein F., and Dwivedi A.N. Introduction to the special issue on advances in clinical and health-care knowledge management. IEEE Trans Inform Technol Biomed 9 2 (2005) 157-161
6. Birkmeyer J.D., Dimick J.B., and Staiger D.O. Operative mortality and procedure volume as predictors of subsequent hospital performance. Ann Surg 243 3 (2006) 411-417
7. Birkmeyer J.D., Finlayson E.V., and Birkmeyer C.M. Volume standards for high-risk surgical procedures: potential benefits of the Leapfrog initiative. Surgery 130 3 (2001) 415-422
8. Birkmeyer J.D., Siewers A.E., Finlayson E.V.A., Stukel T.A., Lucas F.L., Batista I., et al. Hospital volume and surgical mortality in the United States. New Engl J Med 346 15 (2002) 1128-1137
9. Birkmeyer J.D., Siewers A.E., Marth N.J., and Goodman D.C. Regionalization of high-risk surgery and implications for patient travel times. J Am Med Assoc 290 20 (2003) 2703-2708
10. Brohman, MK. Knowledge creation opportunities in the data mining process. In: HICSS'06: Proceedings of the 39th annual hawaii international conference on system sciences, Washington, DC: IEE Computer Society; 2006, p. 170.3.
11. Chen J., Rathore S.S., Radford M.J., and Krumholz H.M. JCAHO accreditation and quality of care for acute myocardial infarction. Health Aff 22 2 (2003) 243-254
12. Clancey W.J. Heuristic classification. Artif Intell 27 3 (1985) 289-350
13. Coenen F., and Bench-Capon T.J.M. Maintenance and maintainability in regulation based systems. ICL Tech J (1992) 76-84
14. Deyo R.A., Cherkin D.C., and Ciol M.A. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 45 6 (1992) 613-619
15. Dimick J.B., and Ailawadi G. The volume-outcome effect for abdominal aortic surgery. Arch Surg 137 7 (2002) 828-832
16. Dimick JB, Finlayson SRG, Birkmeyer JD. Regional availability of high-volume hospitals for major surgery. Health Aff, Web Exclusive: VAR45-VAR53, 2004.
17. Elixhauser A., Steiner C., and Fraser I. Volume thresholds and hospital characteristics in the United States. Health Aff 22 2 (2003) 167-177
18. Elixhauser A., Steiner C., Harris D.R., and Coffey R.M. Comorbidity measures for use with administrative data. Med Care 36 1 (1998) 8-27
19. Feigenbaum EA. The art of artificial intelligence: 1. Themes and case studies of knowledge engineering. Technical report, Stanford, CA, USA; 1977.
20. Gandjour A., Bannenberg A., and Lauterbach K.W. Threshold volumes associated with higher survival in health care: a systematic review. Med Care 41 10 (2003) 1129-1141
21. Glance L.G., Dick A.W., Mukamel D.B., and Osler T.M. Is the hospital volume-mortality relationship in coronary artery bypass surgery the same for low-risk versus high-risk patients?. Ann Thorac Surg 76 (2003) 1155-1162
22. The Leapfrog Group, 2004. Evidence-Based Hospital Referral, ; 2004 [Accessed in March 2006].
23. Halm E.A., Lee C., and Chassin M.R. Is volume related to outcome in health care? a systematic review and methodologic critique of the literature. Ann Int Med 137 6 (2002) 511-520
24. Healthcare Cost and Utilization Project (HCUP). The project description and data, [Accessed in April 2007].
25. Hillner B.E., Smith T.J., and Desch C.E. Hospital and physician volume or specialization and outcomes in cancer treatment: importance in quality of cancer care. J Clin Oncol 18 11 (2000) 2327-2340
26. Ihse I. The volume-outcome relationship in cancer surgery: a hard sell. Ann Surg 238 6 (2003) 777-781
27. Jaana M, Wakefield D, Rosenthal G. Access to healthcare services within the VA system: comparison of two methods for computing travel distances for CABG patients. Poster presented at the COM/CPH Research Week; 2003.
28. Jeffrey L.R. Multiobjective optimization: behavioral and computational considerations (1992), Kluwer Academic Publishers, Norwell, Massachusetts
29. In: Kohn L.T., Corrigan J.M., and Donaldson M.S. (Eds). To err is human: building a safer health system (2000), National Academy Press, Washington, DC
30. Kupersmith J. Quality of care in teaching hospitals: a literature review. Acad Med 80 5 (2005) 458-466
31. Ling CX, Li C. Data mining for direct marketing: problems and solutions. In: Proceedings of the forth ACM SIGKDD international conference on knowledge discovery and data mining, AAAI Press: New York, NY; 1998, p. 73-79.
32. Lin H-T, Lin C-J, Weng C-H. A note on Platt's probabilistic outputs for support vector machines, ; 2003 [Accessed in February 2006].
33. Nallamothu B.K., Saint S., and Hofer T.P. Impact of patient risk on the hospital volume-outcome relationship in coronary artery bypass grafting. Arch Int Med 165 3 (2005) 333-337
34. Nemati H.R., Steiger D.M., Iyer L.S., and Herschel R.T. Knowledge warehouse: an architectural integration of knowledge management, decision support, artificial intelligence and data warehousing. Decision Support Syst 33 2 (2002) 143-161
35. Niculescu-Mizil A, Caruana R. Predicting good probabilities with supervised learning. In: Proceedings 22th international conference on machine learning, New York, NY: ACM Press; 2005, p. 625-632.
36. Platt J. Probabilistic outputs for support vector machines and comparison to regularized likelihood methods. Advances in large margin classifiers (1999), MIT Press 61-74
37. Quinlan J.R. C4.5: programs for machine learning (1993), Morgan Kaufman, San Mateo, CA
38. Shortliffe E.H., Davis R., Axline S.G., Buchanan B.G., Green C.C., and Cohen S.N. Computer-based consultations in clinical therapeutics: explanation and rule acquisition capabilities of the MYCIN system. Comput Biomed Res 8 4 (1975) 303-320
39. Thompson TG, Brailer DJ, 2004. The decade of health information technology: delivering consumer-centric and information-rich health care: Framework for strategic action. Washington, DC: Department of Health and Human Services, National Coordinator for Health Information Technology, [Accessed in March 2007].
40. Vapnik V. The nature of statistical learning theory (1995), Springer, NY
41. Ward M.W., Jaana M., Wakefield D.S., and Ohsfeldt R.L. What would be the effect of referral to high-volume hospitals in a largely rural state?. J Rural Health 20 4 (2004) 344-354
42. Watson I.D., Basden A., and Brandon P.S. The client centered approach: expert system maintenance. Expert Syst 9 4 (1992) 189-196
43. Watson I., and Marir F. Case-based reasoning: a review. Knowledge Eng Rev 9 4 (1994) 355-381
44. Zadrozny B, Elkan C. Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers. In: Proceedings of the eighteenth international conference on machine learning, San Francisco, CA: Morgan Kaufman; 2001, p. 609-616.