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Validity of ICD-10-based algorithms to identify patients with influenza in inpatient and outpatient settings.
Benack, Kirk; Nyandege, Abner; Nonnenmacher, Edward; Jan, Saira; Setoguchi, Soko; Gerhard, Tobias; Strom, Brian L; Horton, Daniel B.
Afiliación
  • Benack K; Department of Anesthesiology, Montefiore Medical Center, Bronx, New York, USA.
  • Nyandege A; Rutgers Robert Wood Johnson Medical School, Piscataway, New Jersey, USA.
  • Nonnenmacher E; Center for Pharmacoepidemiology and Treatment Science, Institute for Health, Health Care Policy and Aging Research, New Brunswick, New Jersey, USA.
  • Jan S; Center for Pharmacoepidemiology and Treatment Science, Institute for Health, Health Care Policy and Aging Research, New Brunswick, New Jersey, USA.
  • Setoguchi S; Bayshore Analytics and Integrated Solutions LLC, Belford, New Jersey, USA.
  • Gerhard T; Horizon Blue Cross Blue Shield of New Jersey, Newark, New Jersey, USA.
  • Strom BL; Center for Pharmacoepidemiology and Treatment Science, Institute for Health, Health Care Policy and Aging Research, New Brunswick, New Jersey, USA.
  • Horton DB; Department of Medicine, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA.
Pharmacoepidemiol Drug Saf ; 33(4): e5788, 2024 Apr.
Article en En | MEDLINE | ID: mdl-38556924
ABSTRACT

PURPOSE:

To evaluate the validity of ICD-10-CM code-based algorithms as proxies for influenza in inpatient and outpatient settings in the USA.

METHODS:

Administrative claims data (2015-2018) from the largest commercial insurer in New Jersey (NJ), USA, were probabilistically linked to outpatient and inpatient electronic health record (EHR) data containing influenza test results from a large NJ health system. The primary claims-based algorithms defined influenza as presence of an ICD-10-CM code for influenza, stratified by setting (inpatient/outpatient) and code position for inpatient encounters. Test characteristics and 95% confidence intervals (CIs) were calculated using test-positive influenza as a reference standard. Test characteristics of alternative outpatient algorithms incorporating CPT/HCPCS testing codes and anti-influenza medication pharmacy claims were also calculated.

RESULTS:

There were 430 documented influenza test results within the study period (295 inpatient, 135 outpatient). The claims-based influenza definition had a sensitivity of 84.9% (95% CI 72.9%-92.1%), specificity of 96.3% (95% CI 93.1%-98.0%), and PPV of 83.3% (95% CI 71.3%-91.0%) in the inpatient setting, and a sensitivity of 76.7% (95% CI 59.1%-88.2%), specificity of 96.2% (95% CI 90.6%-98.5%), PPV of 85.2% (95% CI 67.5%-94.1%) in the outpatient setting. Primary inpatient discharge diagnoses had a sensitivity of 54.7% (95% CI 41.5%-67.3%), specificity of 99.6% (95% CI 97.7%-99.9%), and PPV of 96.7% (95% CI 83.3%-99.4%). CPT/HCPCS codes and anti-influenza medication claims were present for few outpatient encounters (sensitivity 3%-10%).

CONCLUSIONS:

In a large US healthcare system, inpatient ICD-10-CM codes for influenza, particularly primary inpatient diagnoses, had high predictive value for test-positive influenza. Outpatient ICD-10-CM codes were moderately predictive of test-positive influenza.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Pacientes Ambulatorios / Gripe Humana Límite: Humans Idioma: En Revista: Pharmacoepidemiol Drug Saf Asunto de la revista: EPIDEMIOLOGIA / TERAPIA POR MEDICAMENTOS Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Pacientes Ambulatorios / Gripe Humana Límite: Humans Idioma: En Revista: Pharmacoepidemiol Drug Saf Asunto de la revista: EPIDEMIOLOGIA / TERAPIA POR MEDICAMENTOS Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos