Literature DB >> 8135178

Performance analysis of manual and automated systemized nomenclature of medicine (SNOMED) coding.

G W Moore1, J J Berman.   

Abstract

Many pathology departments rely on the accuracy of computer-generated diagnostic coding for surgical specimens. At present, there are no published guidelines to assure the quality of coding devices. To assess the performance of systemized nomenclature of medicine (SNOMED) coding software, manual coding was compared with automated coding in 9353 consecutive surgical pathology reports at the Baltimore Veterans Affairs Medical Center. Manual SNOMED coding produced 13,454 morphologic codes comprising 519 distinct codes; 209 were unique codes (assigned to only one report apiece). Automated coding obtained 23,744 morphologic codes comprising 498 distinct codes, of which 129 were unique codes. Only 44 (.5%) instances were found in which automated coding missed key diagnoses on surgical case reports. Thus, automated coding compared favorably with manual coding. To achieve the maximum performance, departments should monitor the output from automatic coders. Modifications in reporting style, code dictionaries, and coding algorithms can lead to improved coding performance.

Mesh:

Year:  1994        PMID: 8135178     DOI: 10.1093/ajcp/101.3.253

Source DB:  PubMed          Journal:  Am J Clin Pathol        ISSN: 0002-9173            Impact factor:   2.493


  8 in total

1.  Integration of the analytical and alphabetical ICD10 in a coding help system. Proposal of a theoretical model for the ICD representation.

Authors:  C Bouchet; O Bodenreider; F Kohler
Journal:  Stud Health Technol Inform       Date:  1998

2.  Automating SNOMED coding using medical language understanding: a feasibility study.

Authors:  Y A Lussier; L Shagina; C Friedman
Journal:  Proc AMIA Symp       Date:  2001

3.  Doublet method for very fast autocoding.

Authors:  Jules J Berman
Journal:  BMC Med Inform Decis Mak       Date:  2004-09-15       Impact factor: 2.796

4.  Use of SNOMED CT to represent clinical research data: a semantic characterization of data items on case report forms in vasculitis research.

Authors:  Rachel L Richesson; James E Andrews; Jeffrey P Krischer
Journal:  J Am Med Inform Assoc       Date:  2006-06-23       Impact factor: 4.497

5.  Evaluating a computerized tool for coding patient information.

Authors:  C Bouchet; F Empereur; F Kohler
Journal:  Proc AMIA Symp       Date:  1998

6.  Automatic SNOMED coding.

Authors:  G W Moore; J J Berman
Journal:  Proc Annu Symp Comput Appl Med Care       Date:  1994

7.  A SNOMED analysis of three years' accessioned cases (40,124) of a surgical pathology department: implications for pathology-based demographic studies.

Authors:  J J Berman; G W Moore; W H Donnelly; J K Massey; B Craig
Journal:  Proc Annu Symp Comput Appl Med Care       Date:  1994

8.  Resources for comparing the speed and performance of medical autocoders.

Authors:  Jules J Berman
Journal:  BMC Med Inform Decis Mak       Date:  2004-06-15       Impact factor: 2.796

  8 in total

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