Abstract
Background: Demand for home care services is increasing in Japan, and a 24-hour on-call system could be a burden for primary care physicians. Identifying high-risk patients who need frequent emergency house calls could help physicians prepare and allocate medical resources. The aim of the present study was to develop a risk score to predict the frequent use of emergency house calls in patients who receive regular home visits.Methods: We conducted a retrospective cohort study with linked medical and long-term care claims data from two Japanese cities. Participants were ≥65 years of age and had newly started regular home visits between July 2014 and March 2018 in Tsukuba city and between July 2012 and March 2017 in Kashiwa city. A total of 4,888 eligible patients were randomly divided into a derivation cohort (n=3,259) and a validation cohort (n=1,629). The primary outcome was the frequent use of emergency house calls, defined as the use once per month or more on average during each observation period. We considered pre-specified variables, such as age, gender, medical procedure performed in home health care, long-term care need level, and medical diagnosis at the start of the regular home visit. We used the least absolute shrinkage and selection operator (Lasso) method to select predictor variables. Results: The frequent use of emergency house calls was observed in 13.0% participants (424/3,259) in the derivation cohort and 12.9% participants (210/1,629) in the validation cohort. The risk score included three variables with the following point assignments: home oxygen therapy (4 points); care need level 4-5 (2 point); cancer (5 point). The area under the curve (AUC) in the derivation cohort was 0.708, whereas the AUC of a model that included all pre-specified variables was 0.729. The AUC in the derivation cohort was 0.708, showing moderate discrimination. Conclusions: This easy-to-use risk score would be useful for assessing high-risk patients and would allow the burden on primary care physicians to be reduced through measures such as clustering high-risk patients in well-equipped medical facilities.