Clinically useful prediction of hospital admissions in an older population

Abstract

Background The health care 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 health-care 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 health-care data.Methods We used the health-care 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 health-care 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 health care.

Maneuvering the care puzzle: Experiences of participation in care by frail older persons with significant care needs living at home

“…First, individuals were selected for the intervention through the use of a prediction model. The algorithm calculates a risk score for hospitalization based on age, health care utilization and selected diagnoses (Marcusson et al, 2020 ). The individuals with the highest risk score of the total population aged 75 years and more were selected, approximately 10%.…”

Classifying home care clients’ risk of unplanned hospitalization with the resident assessment instrument

“…Screening instruments for identifying home-dwelling old people at risk of hospitalization have been developed and validated in previous studies. These instruments are based on self-reported information about medical conditions [8,[10][11][12], electronic medical records [7,14] and risk assessments made by a general practitioner [9]. The reported AUCs have ranged from 0.62 to 0.74 (poor or moderate accuracy) depending on the assessment tool, population, setting and follow-up.…”

“…A prognostic tool for identifying home care clients at high risk of unplanned hospitalization could help targeting comprehensive assessment to those in the most urgent need. However, to the best of authors' knowledge, none of the previously described prognostic case-finding scales [7][8][9][10][11][12][13][14][15] have been validated for the frail population needing home care services.…”

Staff experiences of a new tool for comprehensive geriatric assessment in primary care (PASTEL): a focus group study

“…The staff involved in the intervention had no previous experience of geriatric assessment in primary care. The participating primary care centres were presented with a list of patients with increased risk for hospitalisation selected with a statistical prediction model [19]. These patients were invited to an interview with a registered nurse guided by the PASTEL form.…”

“…The experiences of our participants reflect the specific intervention they were part of [17]. They assessed patients selected with a digital prediction model [19], which limits generalisability to some extent. Still, a substantial part of the results reflects experiences of CGA in general, for example the challenge to capture the individual views and preferences of an older adult and to have conversations about the future or end of life.…”