International Classification of Diseases clinical coding training: An international survey

Lucia Otero Varela; Chelsea Doktorchik; Natalie Wiebe; Danielle A Southern; Søren Knudsen; Pallavi Mathur; Hude Quan; Cathy A Eastwood

doi:10.1177/18333583221106509

International Classification of Diseases clinical coding training: An international survey

Lucia Otero Varela
, Chelsea Doktorchik
, Natalie Wiebe
, Danielle A Southern
, Søren Knudsen
, Pallavi Mathur
, Hude Quan
, Cathy A Eastwood

University of Calgary

Publikation: Artikel i tidsskrift og konference artikel i tidsskrift › Tidsskriftartikel › Forskning › peer review

Abstract

The International Classification of Diseases (ICD) is widely used by clinical coders worldwide for clinical coding morbidity data into administrative health databases. Accordingly, hospital data quality largely depends on the coders’ skills acquired during ICD training, which varies greatly across countries.

Originalsprog	Udefineret/Ukendt
Tidsskrift	Health information management : journal of the Health Information Management Association of Australia
ISSN	1322-4913
DOI	https://doi.org/10.1177/18333583221106509
Status	Udgivet - 1 jul. 2022

Emneord

international classification of diseases
clinical coding
health information management
education
data accuracy
data quality

Adgang til dokumentet

10.1177/18333583221106509Licens: CC BY-NC

otero-varela-et-al-2022-international-classification-of-diseases-clinical-coding-training-an-international-surveyForlagets udgivne version, 833 KBLicens: CC BY-NC

Citationsformater

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International Classification of Diseases clinical coding training: An international survey. / Otero Varela, Lucia; Doktorchik, Chelsea; Wiebe, Natalie et al.
I: Health information management : journal of the Health Information Management Association of Australia, 01.07.2022.

Publikation: Artikel i tidsskrift og konference artikel i tidsskrift › Tidsskriftartikel › Forskning › peer review

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T1 - International Classification of Diseases clinical coding training: An international survey

AU - Otero Varela, Lucia

AU - Doktorchik, Chelsea

AU - Wiebe, Natalie

AU - Southern, Danielle A

AU - Knudsen, Søren

AU - Mathur, Pallavi

AU - Quan, Hude

AU - Eastwood, Cathy A

PY - 2022/7/1

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KW - clinical coding

KW - health information management

KW - education

KW - data accuracy

KW - data quality

KW - international classification of diseases

KW - clinical coding

KW - health information management

KW - education

KW - data accuracy

KW - data quality

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