Comparing reliability of ICD-10-based COVID-19 comorbidity data to manual chart review, a retrospective cross-sectional study

© 2021 Wiley Periodicals LLC..

International Statistical Classification of Disease and Related Health Problems, 10th Revision codes (ICD-10) are used to characterize cohort comorbidities. Recent literature does not demonstrate standardized extraction methods.

OBJECTIVE: Compare COVID-19 cohort manual-chart-review and ICD-10-based comorbidity data; characterize the accuracy of different methods of extracting ICD-10-code-based comorbidity, including the temporal accuracy with respect to critical time points such as day of admission.

DESIGN: Retrospective cross-sectional study.

MEASUREMENTS: ICD-10-based-data performance characteristics relative to manual-chart-review.

RESULTS: Discharge billing diagnoses had a sensitivity of 0.82 (95% confidence interval [CI]: 0.79-0.85; comorbidity range: 0.35-0.96). The past medical history table had a sensitivity of 0.72 (95% CI: 0.69-0.76; range: 0.44-0.87). The active problem list had a sensitivity of 0.67 (95% CI: 0.63-0.71; range: 0.47-0.71). On day of admission, the active problem list had a sensitivity of 0.58 (95% CI: 0.54-0.63; range: 0.30-0.68)and past medical history table had a sensitivity of 0.48 (95% CI: 0.43-0.53; range: 0.30-0.56).

CONCLUSIONS AND RELEVANCE: ICD-10-based comorbidity data performance varies depending on comorbidity, data source, and time of retrieval; there are notable opportunities for improvement. Future researchers should clearly outline comorbidity data source and validate against manual-chart-review.

Medienart:

E-Artikel

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

Zur Gesamtaufnahme - volume:94

Enthalten in:

Journal of medical virology - 94(2022), 4 vom: 15. Apr., Seite 1550-1557

Sprache:

Englisch

Beteiligte Personen:

Schaefer, Joseph W [VerfasserIn]
Riley, Joshua M [VerfasserIn]
Li, Michael [VerfasserIn]
Cheney-Peters, Dianna R [VerfasserIn]
Venkataraman, Chantel M [VerfasserIn]
Li, Chris J [VerfasserIn]
Smaltz, Christa M [VerfasserIn]
Bradley, Conor G [VerfasserIn]
Lee, Crystal Y [VerfasserIn]
Fitzpatrick, Danielle M [VerfasserIn]
Ney, David B [VerfasserIn]
Zaret, Dina S [VerfasserIn]
Chalikonda, Divya M [VerfasserIn]
Mairose, Joshua D [VerfasserIn]
Chauhan, Kashyap [VerfasserIn]
Szot, Margaret V [VerfasserIn]
Jones, Robert B [VerfasserIn]
Bashir-Hamidu, Rukaiya [VerfasserIn]
Mitsuhashi, Shuji [VerfasserIn]
Kubey, Alan A [VerfasserIn]

Links:

Volltext

Themen:

COVID-19
Comorbidity
Comparative Study
Electronic health records
International Classification of Diseases
Journal Article
Research design
Validation Study

Anmerkungen:

Date Completed 04.03.2022

Date Revised 16.07.2022

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1002/jmv.27492

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM333873238