Methods Inf Med 1996; 35(02): 104-107
DOI: 10.1055/s-0038-1634643
Original Article
Schattauer GmbH

Coding Clinical Information: Analysis of Clinicians Using Computerized Coding

J. H. Hohnloser
1   Medizinische Klinik, Klinikum Innenstadt, Ludwig-Maximilians-University, Munich, Germany
,
P. Kadlec
1   Medizinische Klinik, Klinikum Innenstadt, Ludwig-Maximilians-University, Munich, Germany
,
F. Puerner
1   Medizinische Klinik, Klinikum Innenstadt, Ludwig-Maximilians-University, Munich, Germany
› Author Affiliations
Further Information

Publication History

Publication Date:
14 February 2018 (online)

Abstract

Data are presented of a controlled experiment with a computerized browsing and encoding tool. Eighteen practicing clinicians extracted medical concepts from two narrative exercise cases using two approaches, traditional and computer-assisted use of ICD-9.

Our results indicate that by using a computerized coding tool the completeness of coding can be improved by up to 55%, that by enforcing mandatory as opposed to optional modifier codes results in lower rates of incomplete coding (0 and 55%, respectively), higher rates of correct coding (41 to 92%) and no change in incorrect code, and that manual coding takes twice as long than coding with the help of the computerized coding tool. Clinicians need 59% more time for processing the whole set of codes than is suggested by the sum of individual codes. We conclude that the use of a computerized coding tool can save time and result in higher quality codes. However, the real time spent on coding may be underestimated when looking at individual coding times, instead of the whole task of processing a clinical scenario.

 
  • REFERENCES

  • 1 International Classification of Diseases. Basic tabulation list with Alphabetical Index (9th Rev. Ed., 2 vols) Geneva: World Health Organisation; 1978
  • 2 Rothwell DJ, Hause LL. SNOMED and microcomputers in anatomic pathology. Med Inf 1983; 8: 23-31.
  • 3 Unified Medical Language System. Fact Sheet. Bethesda Md: National Library of Medicine; 1989
  • 4 Hohnloser JH, König A, Fischer MR, Emmerich B. Data quality in computerized patient records: Analysis of a hematology biopsy report database. Int J Clin Monit Comp 1994; 11: 233-40.
  • 5 Klar R, Kaufmehl K. Die Qualiäit der Diagnosenstatistik nach der neuen Bundespflege-satzverordnung. In: Überla K, Rienhoff O, Victor N. eds Medizinische Informatik und Statistik. Heidelberg: Springer Verlag; 1988: 23-6.
  • 6 Lloyd SS, Rissing IP. Physician and coding errors in patient records. JAMA 1985; 10: 1330-6.
  • 7 Nietzschke E, Wiegand M. Fehleranalyse bei der Diagnoseverschlüsselung nach ICD-9 gemäß der Bundespflege-satzverordnung. Z Orthop 1992; 130: 371-7.
  • 8 Hohnloser IH, Puerner F. PADS – A Patient Archiving and Documentation System. Int J Clin Monit Comp 1992; 9: 71-84.
  • 9 Scriba PC, Mansky T, Fassl H, Friedrich HJ. Diagnoseschlüssel des Zentrums für Innere Medizin und des Medizinischen Zentrums. 1. Auflage 1986