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Methods Inf Med 1996; 35(02): 108-111
DOI: 10.1055/s-0038-1634644
Original Article
Schattauer GmbH

Improving Coded Data Entry by an Electronic Patient Record System

J. H. Hohnloser
1   Med. Klinik, Klinikum Innenstadt Ludwig-Maximilians-Universiäit München, München, Germany
,
F. Puerner
1   Med. Klinik, Klinikum Innenstadt Ludwig-Maximilians-Universiäit München, München, Germany
,
H. Soltanian
1   Med. Klinik, Klinikum Innenstadt Ludwig-Maximilians-Universiäit München, München, Germany
› Author Affiliations
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Publication History

Publication Date:
14 February 2018 (online)

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Abstract

Data are presented on the use of a browsing and encoding utility to improve coded data entry for an electronic patient record system. Traditional and computerized discharge summaries were compared: during three phases of coding ICD-9 diagnoses phase I, no coding; phase II, manual coding, and phase III, computerized semiautomatic coding. Our data indicate that (1) only 50% of all diagnoses in a discharge summary are encoded manually; (2) using a computerized browsing and encoding utility this percentage may increase by 64%; (3) when forced to encode manually, users may “shift” as much as 84% of relevant diagnoses from the appropriate coding section to other sections thereby “bypassing” the need to encode, this was reduced by up to 41 % with the computerized approach, and (4) computerized encoding can improve completeness of data encoding, from 46 to 100%. We conclude that the use of a computerized browsing and encoding tool can increase data quality and the percentage of documented data. Mechanisms bypassing the need to code can be avoided.

Keywords

Browser - ICD-9 - Computerized - Encoding - Electronic Patient Record - Natural Language Processing
 

  • REFERENCES

  • 1 Mansky T, Scriba PC, Fassl H, Friedrich HJ. Diagnosis encoding: how and to what purpose? (editorial). Dtsch Med Wochenschr 1986; 111: 1707-8.
    Article in Thieme ConnectPubMedGoogle Scholar
  • 2 Frisse ME, Cousins SB, Hassan SW. Information retrieval using a “digital book shelf”. In: Proc Annu Symp Comput Appl Med Care. 1991: 803-7.
    PubMedGoogle Scholar
  • 3 Harbourt AM, Syed EJ, Hole WT, Kingsland L. The ranking algorithm of the Coach browser for the UMLS metathesaurus. In: Proc Annu Symp Comput Appl Med Care. 1993: 720-4.
    PubMedGoogle Scholar
  • 4 International Classification of Diseases. Basic tabulation list with Alphabetical Index (Ninth rev.). Geneva: World Health Organization; 1978
    Google Scholar
  • 5 International Classification of Procedures in Medicine. Geneva: World Health Organization; 1978
    Google Scholar
  • 6 CPT (Physicians’ Current Procedural Terminology). Chicago: American Medical Association; 1991
    Google Scholar
  • 7 Rad JD. The Read Codes. Woodgate, Loughborough, Leicestershire: Centre for Coding and Classification; 1990
    Google Scholar
  • 8 Rothwell DJ, Hause LL. SNOMED and microcomputers in anatomic pathology. Med Inform 1983; 8: 23-31.
    PubMedGoogle Scholar
  • 9 Hohnloser JH, Purner F. PADS (Patient Archiving and Documentation System): a computerized patient record with educational aspects. Int J Clin Monit Comput 1992; 9: 71-84.
    CrossrefPubMedGoogle Scholar
  • 10 Heathfield HA, Winstanley G, Kirkham N. A menu-driven knowledge base browsing tool. Med Inf 1990; 15: 151-9.
    PubMedGoogle Scholar
  • 11 Klimczak JC, Hahn AW, Hausam RR, Sievert ME, Mitchell JA. A system for browsing the SNOMED International vocabulary. Biomed Sci Instrum 1994; 30: 127-32.
    PubMedGoogle Scholar
  • 12 Hohnloser JH, Pürner F, Kadlec P. Experiments in coding clinical information: An analysis of clinicians using a computerised coding tool. Comp Biomed Res 1995; 28: 393-401.
    CrossrefPubMedGoogle Scholar
  • 13 Hohnloser JH, Prüner F, Kadlec P. Coding medical concepts: A controlled experiment with a computerised coding tool. Int J Clin Mon Comp 1995; 12: 141-5.
    CrossrefPubMedGoogle Scholar