tetano
Editor, Senior Moderator
Pharmacoepidemiol Drug Saf
. 2024 Apr;33(4):e5788.
doi: 10.1002/pds.5788. Validity of ICD-10-based algorithms to identify patients with influenza in inpatient and outpatient settings
Kirk Benack[SUP] 1 2 [/SUP], Abner Nyandege[SUP] 3 [/SUP], Edward Nonnenmacher[SUP] 3 4 [/SUP], Saira Jan[SUP] 5 [/SUP], Soko Setoguchi[SUP] 3 6 7 [/SUP], Tobias Gerhard[SUP] 3 7 8 [/SUP], Brian L Strom[SUP] 3 9 [/SUP], Daniel B Horton[SUP] 3 7 10 [/SUP]
Affiliations
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.
Keywords: ICD‐10‐CM; algorithm; diagnosis; influenza; validation.
. 2024 Apr;33(4):e5788.
doi: 10.1002/pds.5788. Validity of ICD-10-based algorithms to identify patients with influenza in inpatient and outpatient settings
Kirk Benack[SUP] 1 2 [/SUP], Abner Nyandege[SUP] 3 [/SUP], Edward Nonnenmacher[SUP] 3 4 [/SUP], Saira Jan[SUP] 5 [/SUP], Soko Setoguchi[SUP] 3 6 7 [/SUP], Tobias Gerhard[SUP] 3 7 8 [/SUP], Brian L Strom[SUP] 3 9 [/SUP], Daniel B Horton[SUP] 3 7 10 [/SUP]
Affiliations
- PMID: 38556924
- DOI: 10.1002/pds.5788
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.
Keywords: ICD‐10‐CM; algorithm; diagnosis; influenza; validation.