Using SNOMED CT-encoded problems to improve ICD-10-CM coding—A randomized controlled experiment

Kin Wah Fung, Julia Xu, S. Trent Rosenbloom, James R. Campbell

Research output: Contribution to journalArticle

Abstract

Objective: Clinical problems in the Electronic Health Record that are encoded in SNOMED CT can be translated into ICD-10-CM codes through the NLM's SNOMED CT to ICD-10-CM map (NLM Map). This study evaluates the potential benefits of using the map-generated codes to assist manual ICD-10-CM coding. Methods: De-identified clinic notes taken by the physician during an outpatient encounter were made available on a secure web server and randomly assigned for coding by professional coders with usual coding or map-assisted coding. Map-assisted coding made use of the problem list maintained by the physician and the NLM Map to suggest candidate ICD-10-CM codes to the coder. A gold standard set of codes for each note was established by the coders using a Delphi consensus process. Outcomes included coding time, coding reliability as measured by the Jaccard coefficients between codes from two coders with the same method of coding, and coding accuracy as measured by recall, precision and F-score according to the gold standard. Results: With map-assisted coding, the average coding time per note reduced by 1.5 min (p = 0.006). There was a small increase in coding reliability and accuracy (not statistical significant). The benefits were more pronounced in the more experienced than less experienced coders. Detailed analysis of cases in which the correct ICD-10-CM codes were not found by the NLM Map showed that most failures were related to omission in the problem list and suboptimal mapping of the problem list terms to SNOMED CT. Only 12% of the failures was caused by errors in the NLM Map. Conclusion: Map-assisted coding reduces coding time and can potentially improve coding reliability and accuracy, especially for more experienced coders. More effort is needed to improve the accuracy of the map-suggested ICD-10-CM codes.

Original languageEnglish (US)
Pages (from-to)19-25
Number of pages7
JournalInternational Journal of Medical Informatics
Volume126
DOIs
StatePublished - Jun 2019

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Systematized Nomenclature of Medicine
International Classification of Diseases
Physicians
Electronic Health Records
Outpatients

Keywords

  • Administrative codes
  • Coding quality
  • ICD-10-CM
  • Inter-terminology mapping
  • SNOMED CT

ASJC Scopus subject areas

  • Health Informatics

Cite this

Using SNOMED CT-encoded problems to improve ICD-10-CM coding—A randomized controlled experiment. / Fung, Kin Wah; Xu, Julia; Rosenbloom, S. Trent; Campbell, James R.

In: International Journal of Medical Informatics, Vol. 126, 06.2019, p. 19-25.

Research output: Contribution to journalArticle

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abstract = "Objective: Clinical problems in the Electronic Health Record that are encoded in SNOMED CT can be translated into ICD-10-CM codes through the NLM's SNOMED CT to ICD-10-CM map (NLM Map). This study evaluates the potential benefits of using the map-generated codes to assist manual ICD-10-CM coding. Methods: De-identified clinic notes taken by the physician during an outpatient encounter were made available on a secure web server and randomly assigned for coding by professional coders with usual coding or map-assisted coding. Map-assisted coding made use of the problem list maintained by the physician and the NLM Map to suggest candidate ICD-10-CM codes to the coder. A gold standard set of codes for each note was established by the coders using a Delphi consensus process. Outcomes included coding time, coding reliability as measured by the Jaccard coefficients between codes from two coders with the same method of coding, and coding accuracy as measured by recall, precision and F-score according to the gold standard. Results: With map-assisted coding, the average coding time per note reduced by 1.5 min (p = 0.006). There was a small increase in coding reliability and accuracy (not statistical significant). The benefits were more pronounced in the more experienced than less experienced coders. Detailed analysis of cases in which the correct ICD-10-CM codes were not found by the NLM Map showed that most failures were related to omission in the problem list and suboptimal mapping of the problem list terms to SNOMED CT. Only 12{\%} of the failures was caused by errors in the NLM Map. Conclusion: Map-assisted coding reduces coding time and can potentially improve coding reliability and accuracy, especially for more experienced coders. More effort is needed to improve the accuracy of the map-suggested ICD-10-CM codes.",
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