eQuality: Electronic quality assessment from narrative clinical reports

Mayo Clinic Proceedings

Volumn 81, Issue 11, 2006, Pages 1472-1481

  Brown, Steven H ^a,b,c,g   Speroff, Theodore ^a,c,d,e   Fielstein, Elliot M ^a,b,c,e   Bauer, Brent A ^f   Wahner Roedler, Dietlind L ^f   Greevy, Robert ^c,e   Elkin, Peter L ^f  

^a DEPARTMENT OF VETERANS AFFAIRS   (United States)

^b VANDERBILT UNIVERSITY MEDICAL CENTER   (United States)

^c VETERANS AFFAIRS MEDICAL CENTER   (United States)

^d Veterans Affairs National Quality Scholars Junior Faculty   (United States)

^e VANDERBILT UNIVERSITY SCHOOL OF MEDICINE   (United States)

^f Mayo Clinic   (United States)

^g Mayo Clinic College of Medicine ^*  (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; AUTOMATION; DISABILITY; ELECTRONIC MEDICAL RECORD; EVALUATION; EXPERT SYSTEM; MEDICAL DOCUMENTATION; MEDICAL EXAMINATION; PERFORMANCE; SENSITIVITY AND SPECIFICITY;

EID: 33750584022     PISSN: 00256196     EISSN: None     Source Type: Journal    
DOI: 10.4065/81.11.1472     Document Type: Article

References (68)

1. Perlin JB, Kolodner RM, Roswell RH. The Veterans Health Administration: quality, value, accountability, and information as transforming strategies for patient-centered care. Am J Manag Care. 2004;10(11,pt 2):828-836.
2. Boodman S. No end to errors. Washington Post. December 3, 2002:HE01
3. Rundle R. In the drive to mine medical data, VHA is the unlikely leader. Wall Street Journal. December 10, 2001:1.
4. Kolodner RM. Computerizing Large Integrated Health Networks: The VA Success. New York, NY: Springer-Verlag; 1997.
5. Brown SH, Lincoln MJ, Groen PJ, Kolodner RM. VistA: U.S. Department of Veterans Affairs national-scale HIS. Int J Med Inform. 2003;69:135-156.
6. Chute CG, Yang Y. An evaluation of concept based latent semantic indexing for clinical information retrieval. Proc Annu Symp Comput Appl Med Care. 1992:639-643.
7. Hersh WR, Hickam DH. A comparison of two methods for indexing and retrieval from a full-text medical database. Med Decis Making. 1993;13:220-226.
8. Hersh WR, Hickam DH, Leone TJ. Words, concepts, or both: optimal indexing units for automated information retrieval. Proc Annu Symp Comput Appl Med Care. 1992:644-648.
9. Goldman JA, Chu WW, Parker DS, Goldman RM. Term domain distribution analysis: a data mining tool for text databases. Methods Inf Med. 1999;38:96-101.
10. Murff HJ, Forster AJ, Peterson JF, Fiskio JM, Heiman HL, Bates DW. Electronically screening discharge summaries for adverse medical events. J Am Med inform Assoc. 2003 July-Aug;10:339-350. Epub 2003 Mar 28.
11. Baud RH, Lovis C, Ruch P, Rassinoux AM. Conceptual search in electronic patient record. Medinfo. 2001;10(pt 1):156-160.
12. Hersh WR, Greenes RA. SAPHIRE-an information retrieval system featuring concept matching, automatic indexing, probabilistic retrieval, and hierarchical relationships. Comput Biomed Res. 1990;23:410-425.
13. Aronsky D, Fiszman M, Chapman WW, Haug PJ. Combining decision support methodologies to diagnose pneumonia. Proc AMIA Symp. 2001:12-16.
14. Chapman WW, Fizman M, Chapman BE, Haug PJ. A comparison of classification algorithms to automatically identify chest X-ray reports that support pneumonia. J Biomed Inform. 2001;34:4-14.
15. Elkins JS, Friedman C, Boden-Albala B, Sacco RL, Hripcsak G. Coding neuroradiology reports for the Northern Manhattan Stroke Study: a comparison of natural language processing and manual review. Comput Biomed Res. 2000;33:1-10.
16. Fiszman M, Chapman WW, Aronsky D, Evans RS, Haug PJ. Automatic detection of acute bacterial pneumonia from chest X-ray reports. J Am Med Inform Assoc. 2000;7:593-604.
17. Friedman C, Knirsch C, Shagina L, Hripcsak G. Automating a severity score guideline for community-acquired pneumonia employing medical language processing of discharge summaries. Proc AMIA Symp. 1999:256-260.
18. Hripcsak G, Austin JH, Alderson PO, Friedman C. Use of natural language processing to translate clinical information from a database of 889,921 chest radiographic reports. Radiology. 2002;224:157-163.
19. Hripcsak G, Friedman C, Alderson PO, DuMouchel W, Johnson SB, Clayton PD. Unlocking clinical data from narrative reports: a study of natural language processing. Ann intern Med. 1995;122:681-688.
20. Hripcsak G, Knirsch CA, Jain NL, Pablos-Mendez A. Automated tuberculosis detection. J Am Med Inform Assoc. 1997;4:376-381.
21. Mamlin BW, Heinze DT, McDonald CJ. Automated extraction and normalization of findings from cancer-related free-text radiology reports. AMIA Annu Symp Proc. 2003:420-424.
22. Nadkarni P, Chen R, Brandt C. UMLS concept indexing for production databases: a feasibility study. J Am Med Inform Assoc. 2001;8:80-91.
23. Trick WE, Chapman WW, Wisniewski MF, Peterson BJ, Solomon SL, Weinstein RA. Electronic interpretation of chest radiograph reports to detect central venous catheters. Infect Control Hosp Epidemiol. 2003;24:950-954.
24. Sager N, Lyman M, Tick LJ, Nhan NT, Bucknall CE. Natural language processing of asthma discharge summaries for the monitoring of patient care. Proc Annu Symp Comput Appl Med Care. 1993:265-268.
25. Friedman C. A broad-coverage natural language processing system. Proc AMIA Symp. 2000:270-274.
26. Ruch P, Baud R, Geissbuhler A, Rassinoux AM. Comparing general and medical texts for information retrieval based on natural language processing: an inquiry into lexical disambiguation. Medinfo. 2001;10(pt 1):261-265.
27. Sager N, Lyman M, Nhan NT, Tick LJ. Medical language processing: applications to patient data representation and automatic encoding. Methods Inf Med. 1995:34:140-146.
28. Barrows RC Jr, Busuioc M, Friedman C. Limited parsing of notational text visit notes: ad-hoc vs. NLP approaches. Proc AMIA Symp. 2000:51-55.
29. Hyun S, Bakken S, Friedman C, Johnson SB. Natural language processing challenges in HIV/AIDS clinic notes. AMIA Annu Symp Proc. 2003: 872.
30. Sager N, Bross ID, Story G, Bastedo P, Marsh E, Shedd D. Automatic encoding of clinical narrative. Comput Biol Med. 1982;12:43-56.
31. Xu H, Friedman C. Facilitating research in pathology using natural language processing. AMIA Annu Symp Proc. 2003:1057.
32. Bates DW, Evans RS, Murff H, Stetson PD, Pizziferri L, Hripcsak G. Detecting adverse events using information technology. J Am Med Inform Assoc. 2003;10:115-128.
33. Rindflesch TC, Tanabe L, Weinstein JN, Hunter L. EDGAR: extraction of drugs, genes and relations from the biomedical literature. Pac Symp Biocomput. 2000:517-528.
34. Wehbe FH, Armstrong BK, Peachey MR, Denny JC, Spickard A III. Formative evaluation to guide early deployment of an online content management tool for medical curriculum. AMIA Annu Symp Proc. 2003:1049.
35. Lovis C, Chapko MK, Martin DP, et al. Evaluation of a command-line parser-based order entry pathway for the Department of Veterans Affairs electronic patient record. J Am Med Inform Assoc. 2001;8:486-498.
36. Friedman C, Hripcsak G. Natural language processing and its future in medicine. Acad Med. 1999;74:890-895.
37. Rassinoux AM, Wagner JC, Lovis C, Baud RH, Rector A, Scherrer JR. Analysis of medical texts based on a sound medical model. Proc Annu Symp Comput Appl Med Care. 1995:27-31.
38. National Library of Medicine. SNOMED Clinical Terms® To Be Added To UMLS® Metathesaurus®. Available at: www.nlm.nih.gov/research/umls /Snomed/snomed_announcement.html. Accessed October 3, 2006.
39. Spademan KA, Campbell KE, Cote RA. SNOMED RT: a reference terminology for health care. Proc AMIA Annu Fall Symp. 1997:640-644.
40. Stearns MQ, Price C, Spackman KA, Wang AY. SNOMED clinical terms: overview of the development process and project status. Proc AMIA Symp. 2001:662-666.
41. Nelson SJ, Johnston D, Humphreys BL. Relationships in medical subject headings. In: Bean CA, Green R, eds. Relationships in the Organization of Knowledge. New York, NY: Kluwer Academic Publishers; 2001:171-184.
42. Hersh W, Mailhot M, Arnott-Smith C, Lowe H. Selective automated indexing of findings and diagnoses in radiology reports. J Biomed Inform. 2001;34:262-273.
43. Huang Y, Lowe HJ, Hersh WR. A pilot study of contextual UMLS indexing to improve the precision of concept-based representation in XML-structured clinical radiology reports. J Am Med Inform Assoc. 2003 Nov-Dec; 10:580-587. Epub 2003 Aug 4.
44. Taira RK, Johnson DB, Bhushan V, et al. A concept-based retrieval system for thoracic radiology. J Digit Imaging. 1996;9:25-36.
45. Happe A, Pouliquen B, Burgun A, Cuggia M, Le Beux P. Automatic concept extraction from spoken medical reports. Int J Med Inform. 2003;70:255-263.
46. Elkin PL, Ruggieri A, Bergstrom L, et al. A randomized controlled trial of concept based indexing of Web page content. Proc AMIA Symp. 2000:220-224.
47. Elkin PL, Ruggieri AP, Brown SH, et al. A randomized controlled trial of the accuracy of clinical record retrieval using SNOMED-RT as compared with ICD9-CM. Proc AMIA Symp. 2001:159-163.
48. Weeks WB, Mills PD, Waldron J, Brown SH, Speroff T, Coulson LR. A model for improving the quality and timeliness of compensation and pension examinations in VA facilities. J Healthc Manag. 2003;48:252-261.
49. Fielstein EM, Brown SH, Speroff T. Algorithmic de-identification of VA medical exam text for HIPAA privacy compliance: preliminary findings. Medinfo. 2004:1590.
50. Browne AC, Divita G, Aronson AR, McCray AT. UMLS language and vocabulary tools. AMIA Annu Symp Proc. 2003:798.
51. Brown SH, Bauer BA, Wahner-Roedler DL, Elkin PL. Coverage of oncology drug indication concepts and compositional semantics by SNOMED-CT. AMIA Annu Symp Proc. 2003:115-119.
52. Elkin PL, Brown SH. Automated enhancement of description logic-defined terminologies to facilitate mapping to ICD9-CM. J Biomed Inform. 2002;35:281-288.
53. Elkin PL, Brown SH, Husser CS, et al. Evaluation of the content coverage of SNOMED CT: ability of SNOMED clinical terms to represent clinical problem lists. Mayo Clin Proc. 2006;81:741-748.
54. Aronson AR. Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program. Proc AMIA Symp. 2001:17-21.
55. Pratt W, Yetisgen-Yildiz M. A study of biomedical concept identification: MetaMap vs. people. AMIA Annu Symp Proc. 2003:529-533.
56. Good PI. Permutation, Parametric and Bootstrap Tests of Hypotheses. 3rd ed. New York, NY: Springer; 2005.
57. R Foundation for Statistical Computing. The R Project for Statistical Computing. Available at: www.R-project.org. Accessed October 3, 2006.
58. Marzullo P, Parodi O, Sambuceti G, et al. Myocardial viability: nuclear medicine versus stress echocardiography. Echocardiography. 1995;12:291-302.
59. Chapman WW, Bridewell W, Hanbury P, Cooper GF, Buchanan BG. A simple algorithm for identifying negated findings and diseases in discharge summaries. J Biomed Inform. 2001;34:301-310.
60. Krauthammer M, Hripcsak G. A knowledge model for the interpretation and visualization of XLP-parsed discharged summaries. Proc AMIA Symp. 2001:339-343.
61. Mutalik PG, Deshpande A, Nadkarni PM. Use of general-purpose negation detection to augment concept indexing of medical documents: a quantitative study using the UMLS. J Am Med Inform Assoc. 2001;8:598-609.
62. Elkin PL, Brown SH, Bauer BA, et al. A controlled trial of automated classification of negation from clinical notes. BMC Med Inform Decis Mak [serial online]. 2005;5:13. Available at: www.pubmedcentral.gov/articlerender .fcgi?artid=1142321. Accessed October 3, 2006.
63. HEDIS 2.0: a precursor to national report cards for health plans. Bus Health. 1993;11:14.
64. NCQA releases HEDIS 2.0 standards: quality monitoring group prepares to test report card measures. QRC Advis. 1994;10:1-3.
65. Berry K. Legislative forum: HEDIS 2.0: a standardized method to evaluate health plans. J Healthc Qual. 1993;15:42.
66. Campbell S. Outcomes-based accreditation evolves slowly with JCAHO's Oryx initiative. Health Care Strateg Manage. 1997;15:12-13.
67. DeMott K. JCAHO introduces ORYX for outcomes-based accreditation. Qual Lett Healthc Lead. 1997;9:18-19.
68. Popovich M. The Joint Commission's ORYX initiative. Caring. 1998; 17:44-45.