Positive Predictive Value of ICD-10 Diagnosis Codes for COVID-19

ICD-10诊断代码对COVID-19的阳性预测值

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Abstract

PURPOSE: To examine the positive predictive value (PPV) of International Classification version 10 (ICD-10) diagnosis codes for Coronavirus disease 2019 (COVID-19). PATIENTS AND METHODS: Medical record review of all patients assigned a diagnosis code of COVID-19 (DB342A or DB972A) at six Danish departments of infectious diseases from February 27 through May 4, 2020. Confirmed COVID-19 diagnosis was defined as either: 1) definite, a positive polymerase chain reaction (PCR) for severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) on a respiratory sample combined with symptoms suggestive of COVID-19: 2) probable, clinical presentation of COVID-19 without detection of SARS-CoV-2 and no alternative diagnoses considered more likely; or 3) possible, clinical presentation of COVID-19 without detection of SARS-CoV-2, and the patient was discharged or deceased before further investigations were carried out. We computed the PPV with 95% confidence intervals (CI) as the number of patients with confirmed (i.e., definite, probable, and possible) COVID-19 divided by the number of patients assigned a diagnosis code for COVID-19. RESULTS: The study included 710 patients with a median age of 61 years (interquartile range [IQR] 47-74) and 285/710 (40%) were female. COVID-19 was confirmed in 706/710 (99%) with 705/710 (99%) categorized as definite, 1/710 (0.1%) as probable, and 0 patients as possible COVID-19. The diagnosis was disproven in 4/710 (0.6%) patients who were hospitalized due to bacterial pneumonia (n = 2), influenza (n = 1), and urinary tract infection (n = 1). The overall PPV for COVID-19 was 99% (95% CI 99-100) and remained consistently high among all subgroups including sex, age groups, calendar period, and stratified by diagnosis code and department of infectious diseases (range 97-100%). CONCLUSION: The overall PPV of diagnosis codes for COVID-19 in Denmark was high and may be suitable for future registry-based prognosis studies of COVID-19.

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