Improving case definition of Crohn's disease and ulcerative colitis in electronic medical records using natural language processing: A novel informatics approach

Inflammatory Bowel Diseases

Volumn 19, Issue 7, 2013, Pages 1411-1420

  Ananthakrishnan, Ashwin N ^a,b   Cai, Tianxi ^c   Savova, Guergana ^d   Cheng, Su Chun ^b   Chen, Pei ^d   Perez, Raul Guzman ^e   Gainer, Vivian S ^e   Murphy, Shawn N ^a,e   Szolovits, Peter ^f   Xia, Zongqi ^a,b   Shaw, Stanley ^a,b   Churchill, Susanne ^g   Karlson, Elizabeth W ^b,g   Kohane, Isaac ^b,d,g   Plenge, Robert M ^b,g   Liao, Katherine P ^b,g  

^a MASSACHUSETTS GENERAL HOSPITAL   (United States)

^b HARVARD MEDICAL SCHOOL   (United States)

^c HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

^d BOSTON CHILDREN S HOSPITAL   (United States)

^e PARTNERS HEALTHCARE   (United States)

^f MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^g BRIGHAM AND WOMEN S HOSPITAL   (United States)

Author keywords

Crohn's disease; Disease cohort; Informatics; Natural language processing; Ulcerative colitis

Indexed keywords

ACCURACY; ADULT; CLASSIFICATION ALGORITHM; CROHN DISEASE; DISEASE CLASSIFICATION; ELECTRONIC MEDICAL RECORD; FEMALE; HUMAN; MAJOR CLINICAL STUDY; MALE; NATURAL LANGUAGE PROCESSING; PRIORITY JOURNAL; REVIEW; SENSITIVITY ANALYSIS; ULCERATIVE COLITIS;

ADULT; ALGORITHMS; COLITIS, ULCERATIVE; CROHN DISEASE; ELECTRONIC HEALTH RECORDS; FEMALE; FOLLOW-UP STUDIES; HUMANS; MALE; MEDICAL INFORMATICS; NATURAL LANGUAGE PROCESSING; PROGNOSIS; TERTIARY CARE CENTERS;

EID: 84875917060     PISSN: 10780998     EISSN: 15364844     Source Type: Journal    
DOI: 10.1097/MIB.0b013e31828133fd     Document Type: Review

References (34)

1. Carroll RJ, Thompson WK, Eyler AE, et al. Portability of an algorithm to identify rheumatoid arthritis in electronic health records. J Am Med Inform Assoc. 2012;19:e162-e169.
2. Denny JC, Crawford DC, Ritchie MD, et al. Variants near FOXE1 are associated with hypothyroidism and other thyroid conditions: using electronic medical records for genome-and phenome-wide studies. Am J Hum Genet. 2011;89:529-542.
3. Jha AK. The promise of electronic records: around the corner or down the road? JAMA. 2011;306:880-881.
4. Kurreeman F, Liao K, Chibnik L, et al. Genetic basis of autoantibody positive and negative rheumatoid arthritis risk in a multi-ethnic cohort derived from electronic health records. Am J Hum Genet. 2011;88:57-69.
5. Love TJ, Cai T, Karlson EW. Validation of psoriatic arthritis diagnoses in electronic medical records using natural language processing. Semin Arthritis Rheum. 2011;40:413-420.
6. Murff HJ, Fitz Henry F, Matheny ME, et al. Automated identification of postoperative complications within an electronic medical record using natural language processing. JAMA. 2011;306:848-855.
7. Liao KP, Cai T, Gainer V, et al. Electronic medical records for discovery research in rheumatoid arthritis. Arthritis Care Res (Hoboken). 2010;62:1120-1127.
8. Kohane IS. Using electronic health records to drive discovery in disease genomics. Nat Rev Genet. 2011;12:417-428.
9. Benchimol EI, Guttmann A, Griffiths AM, et al. Increasing incidence of paediatric inflammatory bowel disease in Ontario, Canada: evidence from health administrative data. Gut. 2009;58:1490-1497.
10. Bernstein CN, Blanchard JF, Rawsthorne P, et al. Epidemiology of Crohn's disease and ulcerative colitis in a central Canadian province: a population-based study. Am J Epidemiol. 1999;149:916-924.
11. Herrinton LJ, Liu L, Lafata JE, et al. Estimation of the period prevalence of inflammatory bowel disease among nine health plans using computerized diagnoses and outpatient pharmacy dispensings. Inflamm Bowel Dis. 2007;13:451-461.
12. Liu L, Allison JE, Herrinton LJ. Validity of computerized diagnoses, procedures, and drugs for inflammatory bowel disease in a northern California managed care organization. Pharmacoepidemiol Drug Saf. 2009;18:1086-1093.
13. Liddy ED, Turner AM, Bradley J. Modeling interventions to improve access to public health information. AMIA Annu Symp Proc. 2003:909.
14. Hripcsak G, Kuperman GJ, Friedman C. Extracting findings from narrative reports: software transferability and sources of physician disagreement. Methods Inf Med. 1998;37:1-7.
15. Melton GB, Hripcsak G. Automated detection of adverse events using natural language processing of discharge summaries. J Am Med Inform Assoc. 2005;12:448-457.
16. Meystre S, Haug PJ. Evaluation of medical problem extraction from electronic clinical documents using MetaMap Transfer (MMTx). Stud Health Technol Inform. 2005;116:823-828.
17. Savova GK, Olson JE, Murphy SP, et al. Automated discovery of drug treatment patterns for endocrine therapy of breast cancer within an electronic medical record. J Am Med Inform Assoc. 2012;19:e83-e89.
18. Sohn S, Kocher JP, Chute CG, et al. Drug side effect extraction from clinical narratives of psychiatry and psychology patients. J Am Med Inform Assoc. 2011;18(suppl 1):i144-i149.
19. Xu H, Stenner SP, Doan S, et al. MedEx: a medication information extraction system for clinical narratives. J Am Med Inform Assoc. 2010;17:19-24.
20. Zeng QT, Goryachev S, Weiss S, et al. Extracting principal diagnosis, co-morbidity and smoking status for asthma research: evaluation of a natural language processing system. BMC Med Inform Decis Mak. 2006;6:30.
21. 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;17:507-513.
22. Fonager K, Sorensen HT, Rasmussen SN, et al. Assessment of the diagnoses of Crohn's disease and ulcerative colitis in a Danish hospital information system. Scand J Gastroenterol. 1996;31:154-159.
23. Loftus EV Jr, Silverstein MD, Sandborn WJ, et al. Ulcerative colitis in Olmsted County, Minnesota, 1940-1993: incidence, prevalence, and survival. Gut. 2000;46:336-343.
24. Loftus EV Jr, Silverstein MD, Sandborn WJ, et al. Crohn's disease in Olmsted County, Minnesota, 1940-1993: incidence, prevalence, and survival. Gastroenterology. 1998;114:1161-1168.
25. Zou H. The adaptive lasso and its oracle properties. J Am Stat Assoc. 2006;101:1418-1429.
26. Friedman J, Hastie T, Tibshirani R. The Elements of Statistical Learning. New York: Springer; 2001.
27. Pepe MS. The Statistical Evaluation of Medical Tests for Classification and Prediction. Oxford, United Kingdom: Oxford University Press; 2004.
28. Efron B, Tibshirani R. An Introduction to the Bootstrap. London: Chapman & Hall/CRC; 1993.
29. Ananthakrishnan AN, McGinley EL, Binion DG, et al. A nationwide analysis of changes in severity and outcomes of inflammatory bowel disease hospitalizations. J Gastrointest Surg. 2011;15:267-276.
30. Bernstein CN, Nabalamba A. Hospitalization, surgery, and readmission rates of IBD in Canada: a population-based study. Am J Gastroenterol. 2006;101:110-118.
31. Molodecky NA, Myers RP, Barkema HW, et al. Validity of administrative data for the diagnosis of primary sclerosing cholangitis: a populationbased study. Liver Int. 2011;31:712-720.
32. Riley SA, Mani V, Goodman MJ, et al. Microscopic activity in ulcerative colitis: what does it mean? Gut. 1991;32:174-178.
33. Kho AN, Pacheco JA, Peissig PL, et al. Electronic medical records for genetic research: results of the eMERGE consortium. Sci Transl Med. 2011;3:79re1.
34. Schildcrout JS, Basford MA, Pulley JM, et al. An analytical approach to characterize morbidity profile dissimilarity between distinct cohorts using electronic medical records. J Biomed Inform. 2010;43:914-923.