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

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.