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Accepted for/Published in: JMIR Medical Informatics

Date Submitted: Jul 27, 2023
Open Peer Review Period: Jul 27, 2023 - Sep 21, 2023
Date Accepted: Feb 22, 2024
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Evaluation of SNOMED CT Grouper Accuracy and Coverage in Organizing the Electronic Health Record Problem List by Clinical System: Observational Study

Senior R, Tsai T, Ratliff W, Nadler L, Balu S, Malcolm E, McPeek Hinz E

Evaluation of SNOMED CT Grouper Accuracy and Coverage in Organizing the Electronic Health Record Problem List by Clinical System: Observational Study

JMIR Med Inform 2024;12:e51274

DOI: 10.2196/51274

PMID: 38836556

PMCID: 11151346

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Evaluation of SNOMED-CT Grouper Accuracy and Coverage in the Electronic Health Record Problem List Organized by Clinical System/Condition: Observational Review

  • Rashaud Senior; 
  • Timothy Tsai; 
  • William Ratliff; 
  • Lisa Nadler; 
  • Suresh Balu; 
  • Elizabeth Malcolm; 
  • Eugenia McPeek Hinz

ABSTRACT

Background:

The Problem List (PL) is often poorly organized which makes the use for clinical care more challenging over time.

Objective:

To measure the accuracy of diagnoses sorting for PL system/conditions groupers based on SNOMED-CT concepts mapped to ICD-10 codes.

Methods:

We developed 21 system/condition-based groupers using SNOMED-CT hierarchal concepts refined with Boolean logic to re-organize the ICD-10-based PL in our electronic health record (EHR). We extracted the PL from a convenience sample of 50 patients divided across age and sex in a deidentified format for evaluation. Two clinicians independently determined whether a PL diagnosis was correctly attributed to a system/condition grouper. Discrepancies were discussed and, if no consensus was reached, were adjudicated by a third clinician. Descriptive statistics and Cohen’s kappa statistic for interrater reliability were calculated.

Results:

Our 50-patient sample had a total of 869 diagnoses (range 4–59; median 12, IQR 9-23.75). The reviewers initially agreed on 821 placements. Of the remaining 48 items, 16 required adjudication, leading to a final count of 787 True Positives and 37 True Negatives. We determined PL diagnoses were grouped with Sensitivity 97.6%, Specificity 58.7%, Positive Predictive Value 96.8%, and F1 Score 0.972. After discussion, the calculated kappa statistic was 0.9, confirming “near perfect” agreement.

Conclusions:

We successfully developed a structured methodology to organize diagnoses on the problem list that supports clinical review.


 Citation

Please cite as:

Senior R, Tsai T, Ratliff W, Nadler L, Balu S, Malcolm E, McPeek Hinz E

Evaluation of SNOMED CT Grouper Accuracy and Coverage in Organizing the Electronic Health Record Problem List by Clinical System: Observational Study

JMIR Med Inform 2024;12:e51274

DOI: 10.2196/51274

PMID: 38836556

PMCID: 11151346

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