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DOI 10.5588/ijtld.19.0792

Медицинская библиотека · The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2020

Diagnostic code agreement for electronic health records and claims data for tuberculosis.

Iqbal S A, Isenhour C J, Mazurek G, Truman B I

СтатьяПоддержка службы здравоохранения СШАПеревод в очереди

Аннотация

OBJECTIVE

To measure the frequency of diseases related to latent tuberculosis infection (LTBI) and tuberculosis (TB), we assessed the agreement between diagnosis codes for TB or LTBI in electronic health records (EHRs) and insurance claims for the same person.

METHODS

In a US population-based, retrospective cohort study, we matched TB-related Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) EHR codes and International Statistical Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) claims codes. Furthermore, LTBI was identified using a published ICD-based algorithm and all LTBI- and TB-related SNOMED CT codes.

RESULTS

Of people with the 10 most frequent TB-related claim codes, 50% did not have an exact-matched EHR code. Positive tuberculin skin test was the most frequent unmatched EHR code and people with the 10 most frequent TB EHR codes, 40% did not have an exact-matched claim code. The most frequent unmatched claim code was TB screening encounter. EHR codes for LTBI matched to claims codes for TB testing; pulmonary TB; and nonspecific, positive or adverse tuberculin reaction.

CONCLUSION

TB-related EHR codes and claims diagnostic codes often disagree, and people with claims codes for LTBI have unexpected EHR codes, indicating the need to reconcile these coding systems.

Для цитирования: Iqbal S A, Isenhour C J, Mazurek G, Truman B I. Diagnostic code agreement for electronic health records and claims data for tuberculosis.. The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease. 2020. DOI: 10.5588/ijtld.19.0792.

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