ArticleRisk management and healthcare policy2021
Predicting Individual Risk of Emergency Hospital Admissions - A Retrospective Validation Study.
Article in Risk management and healthcare policy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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1 citing paper in PubMed.
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeA high number of hospital admissions may indicate poor general health and less than optimal health care across sectors. To prevent hospital admissions, previous studies have focused on predicting readmissions relating to a defined index admission and specific condition, whereas generic models suited for community-dwelling persons are lacking. The aim of this study was to validate a generic model that predicted risk of emergency hospital admission within the following three months and to investigate regional variation. MATERIALS AND
methodsThis study is an observational register-based validation study of a prediction model. The prediction model was based on a population of frail elderly, persons with non-communicable diseases, and persons with three emergency hospital admissions using information about diagnoses and hospital contacts. The prediction model consisted of two stages. In the first stage, covariate associations to admissions are estimated from observed data in one year. In the second stage, admissions are predicted in the coming three months based on observed estimations from the first stage. The validity of the model was calculated by comparing predicted and observed admissions from August 1st to October 31st, 2016.
resultsThe study included 112,026 persons. In nationwide data, area under the curve (AUC) was 0.7742 (95% CI 0.7698-0.7786), and the positive predictive value was 52% for the 99th percentile (the top 1%). AUC varied between regions from 0.6914 in Southern Denmark (95% CI 0.6779-0.7049) to 0.8224 (95% CI 0.8064-0.8384) in North Denmark. AUC was higher with nationwide data compared to regional.
conclusionThe model performed satisfactorily in predicting individual risk of emergency hospital admission.
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