Administrative health data validity: Changes over 19 years

ObjectiveTo evaluate validity of hospital-discharged abstract administrative health data (DAD) over years through chart reviews. MethodsWe analyzed three chart review cohorts (4,008 patients in 2003, 3,045 in 2015, and 9,024 in 2022) in Calgary, Canada. Nurse reviewers determined the presence or absence of 17 clinical conditions employing similar protocols. The reviews were linked with DAD using a unique lifetime identifier, chart number, and admission date. We evaluated the validity of DAD, coded in ICD-10-Canada version, in recording conditions by comparing against chart reviews. The C-statistics was calculated in predicting in-hospital mortality. ResultsThe mean difference in prevalence between chart reviews and DAD for these 17 conditions was 2.1% in 2003, 7.6% in 2015, and 6.3% in 2022. However, some conditions were relatively stable, such as diabetes (1.9%, 2.1%, and 1.1%) and metastatic cancer (0.3%, 1.1%, and 0.4%). For 17 conditions, the sensitivity ranged 39.6-85.1% in 2003, 1.3-85.2% in 2015, and 3.0-89.7% in 2022. The C-statistics for in-hospital mortality based on DAD was 0.84 in 2003, 0.81 in 2015, and 0.78 in 2022. ConclusionDAD increasingly under-coded conditions over 19 years. The validity of DAD decreased but remained relatively stable for certain conditions mandated for coding. The under-coding exerted minimal impact on in-hospital mortality prediction. ImplicationsThe under-coding could be primarily due to the increase of hospital patient volumes and the limited time allocated to coders. Consequently, there is a need to develop artificial intelligence methods based on electronic medical records to support coding practices and improve coding quality.

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Publication Details

Journal
International Journal for Population Data Science
Published
2024-09-10
DOI
https://doi.org/10.23889/ijpds.v9i5.2634
Primary Topic
Health Systems, Economic Evaluations, Quality of Life
Type
article
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article

Administrative health data validity: Changes over 19 years

Cheligeer Cheligeer, Yuan Xu, Guosong Wu, Hude Quan et al.
International Journal for Population Data Science
Health Systems, Economic Evaluations, Quality of Life
article

Administrative health data validity: Changes over 19 years

Cheligeer Cheligeer, Yuan Xu, Guosong Wu, Hude Quan, Natalie Sapiro, Seungwon Lee, Bing Li, Catherine Eastwood, Jie Pan
article en

Abstract

ObjectiveTo evaluate validity of hospital-discharged abstract administrative health data (DAD) over years through chart reviews. MethodsWe analyzed three chart review cohorts (4,008 patients in 2003, 3,045 in 2015, and 9,024 in 2022) in Calgary, Canada. Nurse reviewers determined the presence or absence of 17 clinical conditions employing similar protocols. The reviews were linked with DAD using a unique lifetime identifier, chart number, and admission date. We evaluated the validity of DAD, coded in ICD-10-Canada version, in recording conditions by comparing against chart reviews. The C-statistics was calculated in predicting in-hospital mortality. ResultsThe mean difference in prevalence between chart reviews and DAD for these 17 conditions was 2.1% in 2003, 7.6% in 2015, and 6.3% in 2022. However, some conditions were relatively stable, such as diabetes (1.9%, 2.1%, and 1.1%) and metastatic cancer (0.3%, 1.1%, and 0.4%). For 17 conditions, the sensitivity ranged 39.6-85.1% in 2003, 1.3-85.2% in 2015, and 3.0-89.7% in 2022. The C-statistics for in-hospital mortality based on DAD was 0.84 in 2003, 0.81 in 2015, and 0.78 in 2022. ConclusionDAD increasingly under-coded conditions over 19 years. The validity of DAD decreased but remained relatively stable for certain conditions mandated for coding. The under-coding exerted minimal impact on in-hospital mortality prediction. ImplicationsThe under-coding could be primarily due to the increase of hospital patient volumes and the limited time allocated to coders. Consequently, there is a need to develop artificial intelligence methods based on electronic medical records to support coding practices and improve coding quality.

International Journal for Population Data ScienceVol. 9(5)
Alberta Health Services (CA), University of Calgary (CA), Libin Cardiovascular Institute of Alberta (CA)
Openalex Percentile: Top 81%
Health Systems, Economic Evaluations, Quality of Life
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