Medical Experts' Agreement on Risk Assessment Based on All Possible Combinations of the COVID-19 Predictors-A Novel Approach for Public Health Screening and Surveillance.
Int J Environ Res Public Health
; 19(24)2022 12 10.
Article
in English
| MEDLINE | ID: covidwho-2155107
ABSTRACT
During the initial phase of the coronavirus disease 2019 (COVID-19) pandemic, there was a critical need to create a valid and reliable screening and surveillance for university staff and students. Consequently, 11 medical experts participated in this cross-sectional study to judge three risk categories of either low, medium, or high, for all 1536 possible combinations of 11 key COVID-19 predictors. The independent experts' judgement on each combination was recorded via a novel dashboard-based rating method which presented combinations of these predictors in a dynamic display within Microsoft Excel. The validated instrument also incorporated an innovative algorithm-derived deduction for efficient rating tasks. The results of the study revealed an ordinal-weighted agreement coefficient of 0.81 (0.79 to 0.82, p-value < 0.001) that reached a substantial class of inferential benchmarking. Meanwhile, on average, the novel algorithm eliminated 76.0% of rating tasks by deducing risk categories based on experts' ratings for prior combinations. As a result, this study reported a valid, complete, practical, and efficient method for COVID-19 health screening via a reliable combinatorial-based experts' judgement. The new method to risk assessment may also prove applicable for wider fields of practice whenever a high-stakes decision-making relies on experts' agreement on combinations of important criteria.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Public Health
/
COVID-19
Type of study:
Observational study
/
Prognostic study
/
Randomized controlled trials
Limits:
Humans
Language:
English
Year:
2022
Document Type:
Article
Affiliation country:
Ijerph192416601
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