ArticleJournal of the Association of Medical Microbiology and Infectious Disease Canada = Journal officiel de l'Association pour la microbiologie medicale et l'infectiologie Canada2024
Misattribution Bias of COVID-19 Hospitalizations in Alberta Using an Admission Algorithm.
Article in Journal of the Association of Medical Microbiology and Infectious Disease Canada = Journal officiel de l'Association pour la microbiologie medicale et l'infectiologie Canada, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: With initial waves of COVID-19, many public health systems assumed each COVID-19 positive hospitalization was a direct cause from COVID-19 infection. Since January 2022, Alberta Health Services Communicable Disease Control Hospitalization Team (CDC-HT) implemented an admission criteria algorithm to adjudicate COVID-19 as a direct, contributing, or unrelated cause for all COVID-19 admissions in Alberta. Methods: This quality improvement initiative sought to improve the admission algorithm's precision in reporting COVID-19 admissions. Patient hospitalization records from January-February 2022 with a positive COVID-19 test in the last 30 days were proportionally sampled in a geographically stratified manner across Alberta health zones. 261 patient records were sampled and determination of COVID-19 attribution by CDC-HT algorithm was compared to adjudication by a panel of infectious diseases physicians with extensive COVID-19 clinical experience. Results: Of 261 sampled COVID-19 admissions, blinded physician adjudication determined 39.9% were direct-cause, 17.2% contributing-cause, and 37.6% unrelated-cause. Within the same cohort the CDC-HT admission algorithm adjudicated 42.9% direct-cause, 24.5% contributing-cause, and 30.3% unrelated-cause. Cohen's kappa was 0.475, providing only moderate agreement. The majority of discrepancy was from over-attribution of unrelated hospitalizations as contributing cause. Implementation of this algorithm in Alberta throughout 2022 showed a fluctuating proportion of direct plus contributing COVID-19 hospitalizations as low as 40%. Conclusion: There was misattribution bias in COVID-19 hospitalization determination using the admission algorithm. The findings from this analysis led to improvements in the algorithm to improve precision. Public health jurisdictions should review their COVID-19 hospitalization reporting approaches to ensure validity and consideration of incidental cases.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.