Developing and evaluating an automated appendicitis risk stratification algorithm for pediatric patients in the emergency department

Journal of the American Medical Informatics Association

Volumn 20, Issue E2, 2013, Pages

  Deleger, Louise ^a   Brodzinski, Holly ^a   Zhai, Haijun ^a   Li, Qi ^a   Lingren, Todd ^a   Kirkendall, Eric S ^a   Alessandrini, Evaline ^a   Solti, Imre ^a  

^a CINCINNATI CHILDREN'S HOSPITAL MEDICAL CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ABDOMINAL PAIN; ACUTE APPENDICITIS; ALGORITHM; ARTICLE; AUTOMATION; CHILD; CLINICAL EVALUATION; DATA EXTRACTION; DECISION SUPPORT SYSTEM; DEVICE RECALL; DIAGNOSTIC ACCURACY; ELECTRONIC MEDICAL RECORD; EMERGENCY WARD; EQUIVOCAL RISK PATIENT; GOLD STANDARD; HIGH RISK PATIENT; HUMAN; LOW RISK PATIENT; MACHINE LEARNING; MAJOR CLINICAL STUDY; NATURAL LANGUAGE PROCESSING; PEDIATRIC APPENDICITIS SCORE; RANDOM SAMPLE; RISK; RISK ASSESSMENT; SCORING SYSTEM; SENSITIVITY AND SPECIFICITY;

ELECTRONIC HEALTH RECORD; INFORMATION EXTRACTION; NATURAL LANGUAGE PROCESSING; PEDIATRIC APPENDICITIS SCORE; RISK STRATIFICATION;

ABDOMINAL PAIN; ALGORITHMS; APPENDICITIS; ARTIFICIAL INTELLIGENCE; CHILD; ELECTRONIC HEALTH RECORDS; EMERGENCY SERVICE, HOSPITAL; HUMANS; NATURAL LANGUAGE PROCESSING; RISK ASSESSMENT;

EID: 84890524813     PISSN: 10675027     EISSN: 1527974X     Source Type: Journal    
DOI: 10.1136/amiajnl-2013-001962     Document Type: Article

References (31)

1. Bhuiya FA, Pitts SR, McCaig LF. Emergency department visits for chest pain and abdominal pain: United States, 1999-2008. NCHS Data Brief 2010;43:1-8.
2. Buckius MT, McGrath B, Monk J, et al. Changing epidemiology of acute appendicitis in the United States: study period 1993-2008. J Surg Res 2012;175:185-90.
3. Fahimi J, Herring A, Harries A, et al. Computed tomography use among children presenting to emergency departments with abdominal pain. Pediatrics 2012;130: e1069-75.
4. Brenner D, Elliston C, Hall E, et al. Estimated risks of radiation-induced fatal cancer from pediatric CT. Am J Roentgenol 2001;176:289-96.
5. Pierce DA, Shimizu Y, Preston DL, et al. Studies of the mortality of atomic bomb survivors. Report 12, Part I. Cancer: 1950-1990. Radiat Res 1996;146:1-27.
6. Pines JM. Trends in the rates of radiography use and important diagnoses in emergency department patients with abdominal pain. Med Care 2009;47:782-6.
7. Samuel M. Pediatric Appendicitis Score. J Pediatr Surg 2002;37:877-81.
8. Zuniga RV, Arribas JL, Montes SP, et al. Application of Pediatric Appendicitis Score on the emergency department of a secondary level hospital. Pediatr Emerg Care 2012;28:489-92.
9. Goldman RD, Carter S, Stephens D, et al. Prospective validation of the pediatric appendicitis score. J Pediatr 2008;153:278-82.
10. Bhatt M, Joseph L, Ducharme FM, et al. Prospective validation of the pediatric appendicitis score in a Canadian pediatric emergency department. Acad Emerg Med 2009;16:591-6.
11. Escriba A, Gamell AM, Fernandez Y, et al. Prospective validation of two systems of classification for the diagnosis of acute appendicitis. Pediatr Emerg Care 2011;27:165-9.
12. Kulik DM, Uleryk EM, Maguire JL. Does this child have appendicitis? A systematic review of clinical prediction rules for children with acute abdominal pain. J Clin Epidemiol 2013;66:95-104.
13. Chaudhry B, Wang J, Wu S, et al. Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med. 2006;144:742-52.
14. Friedman C, Knirsch C, Shagina L, et al. Automating a severity score guideline for community-acquired pneumonia employing medical language processing of discharge summaries. AMIA Annu Symp Proc 1999:256-60.
15. Aronsky D, Fiszman M, Chapman WW, et al. Combining decision support methodologies to diagnose pneumonia. AMIA Annu Symp Proc 2001:12-16.
16. Pakhomov SV, Buntrock J, Chute CG. Prospective recruitment of patients with congestive heart failure using an ad-hoc binary classifier. J Biomed Inform 2005;38:145-53.
17. Cheng LT, Zheng J, Savova GK, et al. Discerning tumor status from unstructured MRI reports-completeness of information in existing reports and utility of automated natural language processing. J Digit Imaging 2010;23:119-32.
18. Wagholikar KB, MacLaughlin KL, Henry MR, et al. Clinical decision support with automated text processing for cervical cancer screening. J Am Med Inform Assoc 2012;19:833-9.
19. Chapman WW, Dowling JN, Wagner MM. Classification of emergency department chief complaints into 7 syndromes: a retrospective analysis of 527,228 patients. Ann Emerg Med 2005;46:445-55.
20. Grouin C, Deléger L, Rosier A, et al. Automatic computation of CHA2DS2-VASc score: information extraction from clinical texts for thromboembolism risk assessment. AMIA Annu Symp Proc 2011;2011:501-10.
21. Synnergren J, Olsson B, Gamalielsson J. Classification of information fusion methods in systems biology. In Silico Biol 2009;9:65-76.
22. Boström H, Andler SF, Brohede M, et al. On the definition of information fusion as a field of research. Technical report at the University of Skövde, HS-IKI-TR-07-006. 2007.
23. Lafferty J, McCallum A, Pereira F. Conditional random fields: Probabilistic models for segmenting and labeling sequence data. Proceedings of the 18th International Conference on Machine Learning. Morgan Kaufmann. 2001:282-9.
24. McCallum A. MALLET: a machine learning for language toolkit. 2002. http://mallet.cs.umass.edu/ (last accessed on 10/10/2013)
25. Savova GK, Masanz JJ, Ogren PV, et al. Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications. J Am Med Inform Assoc 2010;17:507-13.
26. UMLS. http://www.nlm.nih.gov/research/umls/knowledge_sources/metathesaurus/ index.html
27. Friedman C, Hripcsak G. Evaluating natural language processors in the clinical domain. Methods Inf Med. 1998;37:334-44.
28. Hripcsak G, Rothschild AS. Agreement, the F-measure, and reliability in information retrieval. J Am Med Inform Assoc. 2005;12:296-8.
29. Noreen EW. Computer-intensive methods for testing hypotheses: an introduction. New-York: Wiley, 1989.
30. Kharbanda AB, Stevenson MD, Macias CG, et al Interrater reliability of clinical findings in children with possible appendicitis. Pediatrics. 2012;129:695-700.
31. Kharbanda AB, Fishman SJ, Bachur RG. Comparison of pediatric emergency physicians' and surgeons' evaluation and diagnosis of appendicitis. Acad Emerg Med 2008;15:119-25.