Clinically useful prediction of hospital admissions in an older population.
BMC Geriatr
; 20(1): 95, 2020 03 06.
Article
em En
| MEDLINE
| ID: mdl-32143637
ABSTRACT
BACKGROUND:
The healthcare for older adults is insufficient in many countries, not designed to meet their needs and is often described as disorganized and reactive. Prediction of older persons at risk of admission to hospital may be one important way for the future healthcare system to act proactively when meeting increasing needs for care. Therefore, we wanted to develop and test a clinically useful model for predicting hospital admissions of older persons based on routine healthcare data.METHODS:
We used the healthcare data on 40,728 persons, 75-109 years of age to predict hospital in-ward care in a prospective cohort. Multivariable logistic regression was used to identify significant factors predictive of unplanned hospital admission. Model fitting was accomplished using forward selection. The accuracy of the prediction model was expressed as area under the receiver operating characteristic (ROC) curve, AUC.RESULTS:
The prediction model consisting of 38 variables exhibited a good discriminative accuracy for unplanned hospital admissions over the following 12 months (AUC 0.69 [95% confidence interval, CI 0.68-0.70]) and was validated on external datasets. Clinically relevant proportions of predicted cases of 40 or 45% resulted in sensitivities of 62 and 66%, respectively. The corresponding positive predicted values (PPV) was 31 and 29%, respectively.CONCLUSION:
A prediction model based on routine administrative healthcare data from older persons can be used to find patients at risk of admission to hospital. Identifying the risk population can enable proactive intervention for older patients with as-yet unknown needs for healthcare.Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Admissão do Paciente
/
Avaliação Geriátrica
Tipo de estudo:
Etiology_studies
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Observational_studies
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Prognostic_studies
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Risk_factors_studies
Limite:
Aged
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Aged80
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Female
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Humans
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Male
Idioma:
En
Revista:
BMC Geriatr
Assunto da revista:
GERIATRIA
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
Suécia