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Pregled bibliografske jedinice broj: 1213190

Predicting missed health care visits during the COVID-19 pandemic using machine learning methods: Evidence from 55,500 individuals from 28 European Countries


Reuter, Anna; Smolić, Šime; Bärnighausen, Till; Sudharsanan, Nikkil
Predicting missed health care visits during the COVID-19 pandemic using machine learning methods: Evidence from 55,500 individuals from 28 European Countries // medRxiv: the preprint server for health sciences (2022) doi:10.1101/2022.03.01.22271611 (znanstveni, poslan)


CROSBI ID: 1213190 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Predicting missed health care visits during the COVID-19 pandemic using machine learning methods: Evidence from 55,500 individuals from 28 European Countries

Autori
Reuter, Anna ; Smolić, Šime ; Bärnighausen, Till ; Sudharsanan, Nikkil

Vrsta, podvrsta
Radovi u časopisima, znanstveni

Izvornik
MedRxiv: the preprint server for health sciences (2022)

Status rada
Poslan

Ključne riječi
machine learning algorithms ; Covid-19 ; missed health care visits ; SHARE Corona Survey ;

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Javno zdravstvo i zdravstvena zaštita, Ekonomija, Interdisciplinarne društvene znanosti



POVEZANOST RADA


Projekti:
EK-ESF-UP.01.3.2.03.0001 - SHARE - Istraživanje o zdravlju, starenju i umirovljenju u Europi (SHARE) (Smolić, Šime; Čipin, Ivan, EK - UP.01.3.2.03) ( POIROT)
EK-H2020-101015924 - Neplanirani zdravstveni, ekonomski i socijalni učinci odluka o kontroli epidemije COVID-19: spoznaje iz SHARE-a (SHARE-COVID19) (Smolić, Šime, EK - H2020-SC1-PHE-CORONAVIRUS-2020-2-RTD) ( POIROT)

Ustanove:
Ekonomski fakultet, Zagreb

Profili:

Avatar Url Šime Smolić (autor)

Poveznice na cjeloviti tekst rada:

doi www.medrxiv.org

Citiraj ovu publikaciju:

Reuter, Anna; Smolić, Šime; Bärnighausen, Till; Sudharsanan, Nikkil
Predicting missed health care visits during the COVID-19 pandemic using machine learning methods: Evidence from 55,500 individuals from 28 European Countries // medRxiv: the preprint server for health sciences (2022) doi:10.1101/2022.03.01.22271611 (znanstveni, poslan)
Reuter, A., Smolić, Š., Bärnighausen, T. & Sudharsanan, N. (2022) Predicting missed health care visits during the COVID-19 pandemic using machine learning methods: Evidence from 55,500 individuals from 28 European Countries. Poslan u medRxiv: the preprint server for health sciences. [Preprint] doi:10.1101/2022.03.01.22271611.
@unknown{unknown, author = {Reuter, Anna and Smoli\'{c}, \v{S}ime and B\"{a}rnighausen, Till and Sudharsanan, Nikkil}, year = {2022}, DOI = {10.1101/2022.03.01.22271611}, keywords = {machine learning algorithms, Covid-19, missed health care visits, SHARE Corona Survey, }, journal = {medRxiv: the preprint server for health sciences}, doi = {10.1101/2022.03.01.22271611}, title = {Predicting missed health care visits during the COVID-19 pandemic using machine learning methods: Evidence from 55,500 individuals from 28 European Countries}, keyword = {machine learning algorithms, Covid-19, missed health care visits, SHARE Corona Survey, } }
@unknown{unknown, author = {Reuter, Anna and Smoli\'{c}, \v{S}ime and B\"{a}rnighausen, Till and Sudharsanan, Nikkil}, year = {2022}, DOI = {10.1101/2022.03.01.22271611}, keywords = {machine learning algorithms, Covid-19, missed health care visits, SHARE Corona Survey, }, journal = {medRxiv: the preprint server for health sciences}, doi = {10.1101/2022.03.01.22271611}, title = {Predicting missed health care visits during the COVID-19 pandemic using machine learning methods: Evidence from 55,500 individuals from 28 European Countries}, keyword = {machine learning algorithms, Covid-19, missed health care visits, SHARE Corona Survey, } }

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