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How well can familial hypercholesterolemia be identified in an electronic health record database?
Katherine E Mues1, Alina N Bogdanov2, Keri L Monda1
1Center for Observational Research, Amgen Inc., Thousand Oaks, CA, USA, kmues@amgen.com.
Insights
Identifying familial hypercholesterolemia (FH) using SNOMED codes in EHRs shows high accuracy but low positive predictive value compared to clinical criteria. This highlights challenges in FH patient identification within large electronic health record databases.
Area of Science:
- Cardiovascular Medicine
- Genetics
- Health Informatics
Background:
- Familial hypercholesterolemia (FH) is a genetic condition causing high cholesterol and increased coronary heart disease (CHD) risk, often undiagnosed.
- The Dutch Lipid Network Criteria (DLNC) aid FH diagnosis using clinical and genetic factors.
- Electronic Health Records (EHRs) utilize Systematized Nomenclature of Medicine (SNOMED) codes for diagnoses, including FH.
Purpose of the Study:
- To assess the agreement between FH identification using SNOMED and ICD-10 CM codes versus the DLNC within an EHR database.
- To evaluate the diagnostic performance of SNOMED codes for FH in a real-world clinical setting.
Main Methods:
- A cohort of patients with hypercholesterolemia was analyzed from the Practice Fusion EHR database.
- Sensitivity, specificity, and predictive values were calculated comparing SNOMED/ICD-10 CM codes to DLNC criteria (scores ≥6 and >8).
Main Results:
- Among over 900,000 patients, 2,180 FH cases were identified via SNOMED codes; zero via ICD-10 CM.
- Compared to DLNC score >8, SNOMED codes showed 84.4% sensitivity, 99.4% specificity, and 6.4% PPV.
- Compared to DLNC score ≥6, SNOMED codes demonstrated 36.8% sensitivity, 99.5% specificity, and 18.7% PPV.
Conclusions:
- SNOMED codes offer high sensitivity and specificity for identifying FH patients compared to clinical criteria.
- The low positive predictive value (PPV) of SNOMED codes indicates challenges in accurately identifying FH patients in EHRs.
- Discordance between coding systems and clinical criteria underscores difficulties in FH detection within large health databases.
Background:
Familial hypercholesterolemia (FH) is a condition characterized by high cholesterol levels and increased risk for coronary heart disease (CHD) that often goes undiagnosed. The Dutch Lipid Network Criteria (DLNC) are used to identify FH in clinical settings via physical examination, personal and family history of CHD, in addition to the presence of deleterious mutations of the LDLR, ApoB, and PCSK9 genes. Agreement between clinical and genetic diagnosis of FH varies. While an ICD diagnosis code was not available for coding FH until 2016, Systematized Nomenclature of Medicine (SNOMED) clinical concept codes, including genetic diagnoses, for FH have been utilized in electronic health records (EHRs).
Objective:
To evaluate the concordance of identifying FH via SNOMED and ICD-10 CM codes vs the DLNC in an EHR database.
Methods:
Using the Practice Fusion EHR database, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value were calculated comparing an FH cohort identified via SNOMED and ICD-10 CM codes to one identified via the DLNC.
Results:
Among 907,616 patients with hypercholesterolemia, 2,180 were identified as FH via SNOMED code (zero were identified via ICD-10 CM), 259 had a DLNC score 6-8 (probable FH), and 45 had a DLNC score >8 (definite FH). Compared to DLNC score >8, the sensitivity, specificity, and PPV of the FH SNOMED code were 84.4%, 99.4%, and 6.4%, respectively. Compared to DLNC score ≥6, the sensitivity was 36.8% and the specificity was 99.5% with a PPV of 18.7%.
Conclusion:
Compared to the clinical criteria for FH, identification of FH patients via SNOMED diagnosis codes had high sensitivity and specificity, but low PPV. The discordance of these two techniques in identifying FH patients speaks to the challenges in identifying FH patients in large electronic databases such as administrative claims and EHR.
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