Evidence map›Paper›PMID 31029260›Full record

Trial reportInternational journal of medical informatics2019

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

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in International journal of medical informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Kin Wah FungNational Library of Medicine, Bethesda, MD, United States. Electronic address: kwfung@nlm.nih.gov.
Julia XuNational Library of Medicine, Bethesda, MD, United States.
S Trent RosenbloomVanderbilt University, Nashville, TN, United States.
James R CampbellUniversity of Nebraska Medical Center, Omaha, NE, United States.

Funding

Clinical and Informatics Research in Medical TerminologiesZIALM010013 · NLM · NATIONAL LIBRARY OF MEDICINE · PI FUNG, KIN WAH · 2018 to 2020
$1.6M
Intramural NIH HHS Z99 LM999999Intramural NIH HHS ZIA LM010013
6 · The paper itself

Abstract

objectiveClinical 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.

methodsDe-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.

resultsWith 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.

conclusionMap-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.

Indexed as

International Classification of DiseasesSystematized Nomenclature of MedicineAmbulatory Care FacilitiesElectronic Health RecordsHumansOutpatientsPhysiciansReproducibility of ResultsAdministrative codesCoding qualityICD-10-CMInter-terminology mappingSNOMED CT

Identifiers

PMID31029260
PMCPMC6487871

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.