Predicting missed health care visits during the COVID-19 pandemic using machine learning methods: Evidence from 55,500 individuals from 28 European Countries (CROSBI ID 328035)
Prilog u časopisu | ostalo
Podaci o odgovornosti
Reuter, Anna ; Smolić, Šime ; Bärnighausen, Till ; Sudharsanan, Nikkil
engleski
Predicting missed health care visits during the COVID-19 pandemic using machine learning methods: Evidence from 55,500 individuals from 28 European Countries
The COVID-19 pandemic has led many individuals to miss essential care. Machine-learning models that predict which patients are at greatest risk of missing care visits can help health administrators prioritize retentions efforts towards patients with the most need. Such approaches may be especially useful for efficiently targeting interventions for health systems overburdened by the COVID-19 pandemic.
machine learning algorithms ; Covid-19 ; missed health care visits ; SHARE Corona Survey ;
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Podaci o izdanju
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2022.
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1468-5833
10.1101/2022.03.01.22271611
Povezanost rada
Ekonomija, Interdisciplinarne društvene znanosti, Javno zdravstvo i zdravstvena zaštita