Abstract
Background
Dependency in older ages is increasing. Many older persons receive care while living in the community. We aimed to identify the predictive value of four clinical measurements to predict home care intensity in older patients following discharge from hospital to home care over 90 days.
Methods
We included 425 inpatients from the “Frailty Department–Local Palliative Care Network” of the local social health authority (ASST) Lecco, Italy (mean age 75.4 years, SD 14.5; female 75.5%). Changes in Health, End-stage disease, and Signs and Symptoms, light version (CHESS-Lite), activities of daily living (ADL), frailty, and the Service Urgency Algorithm. Receiver operative curves were used to calculate the area under the curve (AUC) for predicting Home Care Intensity coefficient (ratio of the number of days when any home care was provided 90 days post-discharge). The interRAI Contact Assessment Instrument was used to calculate these measures.
Results
Analysis was stratified using six different home care intensity score cut-offs. CHESS-Lite had a higher AUC for predicting home care intensity at all cut-off levels but was best for predicting the highest level of home care intensity (≥ 0.8) where the AUC was 0.71 (0.64–0.79). The frailty index also had an acceptable AUC. ADL had the lowest AUC.
Conclusions
Health instability measured with CHESS-Lite has a high predictive value for identifying home care intensity in geriatric patients after discharge from hospital to home, especially in persons with higher home care intensity scores. Geriatric patients with high health instability should be focused on at discharge to prioritize assessment and initiate timely services for home care support.
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Acknowledgements
The authors are extremely grateful to Dr. Paolo Pizzol for his assistance in processing data from the interRAI and Massimo Re for his assistance in processing data from the management data of the Frailty Department. The authors are also extremely grateful to medical, nursing, and management staff of hospital units and Frailty Department thanks to which it was possible to carry out the project.
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This study is based on administrative anonymized data and informed consent is not required according to Italian law.
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This study is based on administrative anonymized data and ethical approval is not required according to Italian law.
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Scaccabarozzi, G., Palmer, K., Onder, G. et al. Predicting care intensity in geriatric home care patients: a comparison of different measures. Aging Clin Exp Res 32, 281–287 (2020). https://doi.org/10.1007/s40520-019-01427-9
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DOI: https://doi.org/10.1007/s40520-019-01427-9