Using Regular Expressions to Abstract Blood Pressure and Treatment Intensification Information from the Text of Physician Notes

Journal of the American Medical Informatics Association

Volumn 13, Issue 6, 2006, Pages 691-695

  Turchin, Alexander ^a,c,d   Kolatkar, Nikheel S ^a,c   Grant, Richard W ^b,c   Makhni, Eric C ^c   Pendergrass, Merri L ^a,c   Einbinder, Jonathan S ^a,c,d  

^a BRIGHAM AND WOMEN S HOSPITAL   (United States)

^b MASSACHUSETTS GENERAL HOSPITAL   (United States)

^c HARVARD MEDICAL SCHOOL   (United States)

^d PARTNERS HEALTHCARE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANTIHYPERTENSIVE AGENT; CAPTOPRIL; CLONIDINE; GLIBENCLAMIDE; LISINOPRIL; LOSARTAN; VALSARTAN;

ACCURACY; ANTIHYPERTENSIVE THERAPY; ARTICLE; BLOOD PRESSURE; BLOOD PRESSURE MEASUREMENT; BLOOD PRESSURE MONITORING; COMPUTER PROGRAM; HEALTH CARE ORGANIZATION; HUMAN; HYPERTENSION; LABORATORY DIAGNOSIS; MEDICAL INFORMATICS; MEDICAL INFORMATION; MEDICAL RECORD; SENSITIVITY AND SPECIFICITY;

BLOOD PRESSURE; HUMANS; HYPERTENSION; MEDICAL RECORDS; NATURAL LANGUAGE PROCESSING; PHYSICIANS; SOFTWARE; TERMINOLOGY;

EID: 33750432529     PISSN: 10675027     EISSN: None     Source Type: Journal    
DOI: 10.1197/jamia.M2078     Document Type: Article

References (25)

1. Hicks J. The potential of claims data to support the measurement of health care quality (2003), RAND, San Diego, CA [PhD]
2. de Lusignan S., Teasdale S., Little D., et al. Comprehensive computerised primary care records are an essential component of any national health information strategy: report from an international consensus conference. Inform Prim Care 12 4 (2004) 255-264
3. de Lusignan S., and van Weel C. The use of routinely collected computer data for research in primary care: opportunities and challenges. Fam Pract 23 2 (2006) 253-263
4. Meystre S., and Haug P.J. Natural language processing to extract medical problems from electronic clinical documents: Performance evaluation. J Biomed Inform (2005) [Epub ahead of print.] Dec 5
5. Mamlin B.W., Heinze D.T., and McDonald C.J. Automated extraction and normalization of findings from cancer-related free-text radiology reports. AMIA Annu Symp Proc (2003) 420-424
6. Embi P.J., Jain A., Clark J., Bizjack S., Hornung R., and Harris C.M. Effect of a clinical trial alert system on physician participation in trial recruitment. Arch Intern Med 165 19 (2005) 2272-2277
7. Hazlehurst B., Sittig D.F., Stevens V.J., et al. Natural language processing in the electronic medical record assessing clinician adherence to tobacco treatment guidelines. Am J Prev Med 29 5 (2005) 434-439
8. Honigman B., Lee J., Rothschild J., et al. Using computerized data to identify adverse drug events in outpatients. J Am Med Inform Assoc 8 3 (2001) 254-266
9. Melton G.B., and Hripcsak G. Automated detection of adverse events using natural language processing of discharge summaries. J Am Med Inform Assoc 12 4 (2005) 448-457
10. Aronsky D., Kasworm E., Jacobson J.A., Haug P.J., and Dean N.C. Electronic screening of dictated reports to identify patients with do-not-resuscitate status. J Am Med Inform Assoc 11 5 (2004) 403-409
11. Hripcsak G., Kuperman G.J., and Friedman C. Extracting findings from narrative reports: software transferability and sources of physician disagreement. Methods Inf Med 37 1 (1998) 1-7
12. Hazlehurst B., Frost H.R., Sittig D.F., and Stevens V.J. MediClass: A system for detecting and classifying encounter-based clinical events in any electronic medical record. J Am Med Inform Assoc 12 5 (2005) 517-529
13. Fiszman M., Chapman W.W., Aronsky D., Evans R.S., and Haug P.J. Automatic detection of acute bacterial pneumonia from chest x-ray reports. J Am Med Inform Assoc 7 6 (2000) 593-604
14. Sequist T.D., Gandhi T.K., Karson A.S., et al. A randomized trial of electronic clinical reminders to improve quality of care for diabetes and coronary artery disease. J Am Med Inform Assoc 12 4 (2005) 431-437
15. Jurafsky D., and Martin J.H. Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition (2000), Prentice Hall, Upper Saddle River, NJ
16. Grishman R. Information Extraction: Techniques and Challenges (1997) Paper presented at: International Summer School SCIE-97
17. Mutalik P.G., Deshpande A., and Nadkarni P.M. Use of general-purpose negation detection to augment concept indexing of medical documents: a quantitative study using the UMLS. J Am Med Inform Assoc 8 6 (2001) 598-609
18. Chapman W.W., Bridewell W., Hanbury P., Cooper G.F., and Buchanan B.G. A simple algorithm for identifying negated findings and diseases in discharge summaries. J Biomed Inform 34 5 (2001) 301-310
19. Kleene S.C. Representation of events in nerve nets and finite automata. In: Shannon C., and McCarthy J. (Eds). Automata Studies (1956), Princeton University Press, Princeton, NJ 3-41
20. Friedl J.E.F. Mastering Regular Expressions. 2nd ed (2002), O'Reilly and Associates, Sebastopol, CA
21. Ruch P., Baud R., Geissbuhler A., and Rassinoux A.M. Comparing general and medical texts for information retrieval based on natural language processing: an inquiry into lexical disambiguation. Medinfo 10 Pt 1 (2001) 261-265
22. Turchin A., Pendergrass M.L., and Kohane I.S. DITTO-a tool for identification of patient cohorts from the text of physician notes in the electronic medical record. AMIA Annu Symp Proc (2005) 744-748
23. Berlowitz D.R., Ash A.S., Hickey E.C., et al. Inadequate management of blood pressure in a hypertensive population. N Engl J Med 339 27 (1998) 1957-1963
24. Okonofua E.C., Simpson K.N., Jesri A., Rehman S.U., Durkalski V.L., and Egan B.M. Therapeutic inertia is an impediment to achieving the Healthy People 2010 blood pressure control goals. Hypertension 47 3 (2006) 345-351
25. The sixth report of the Joint National Committee on prevention, detection, evaluation, and treatment of high blood pressure. Arch Intern Med 157 21 (1997) 2413-2446