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

Abstract

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

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

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.

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.

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