Abstract

BackgroundWe study the longevity and medical resource usage of a large sample of insureds aged 65 years or older drawn from a large health insurance dataset. Yearly counts of each subject's emergency room and ambulance service use and hospital admissions are made. Occurrence of mortality is also monitored. The study aims to capture the simultaneous dependence between their demand for healthcare and survival.MethodsWe demonstrate the benefits of taking a joint approach to modelling longitudinal and survival processes by using a large dataset from a Spanish medical mutual company. This contains historical insurance information for 39,137 policyholders aged 65+ (39.5% men and 60.5% women) across the eight-year window of the study. The joint model proposed incorporates information on longitudinal demand for care in a weighted cumulative effect that places greater emphasis on more recent than on past service demand.ResultsA strong significant and positive relationship between the exponentially weighted demand for emergency, ambulance and hospital services is found with risk of death (alpha = 1.462, p < 0.001). Alternative weighting specifications are tested, but in all cases they show that a joint approach indicates a close connection between health care demand and time-to-death. Additionally, the model allows us to predict individual survival curves dynamically as new information on demand for services becomes known.ConclusionsThe joint model fitted demonstrates the utility of analysing demand for medical services and survival simultaneously. Likewise, it allows the personalized prediction of survival in advanced age subjects.

Highlights

  • Rising rates of longevity are closely tied to the growth in demand for medical attention and long-term care services, the increasing usage of which extends longevity even further

  • Joint models of longitudinal and survival data enable us to estimate the simultaneous association between survival and the demand for care, and serve as a tool for predicting risk of death based on personalized medical records

  • The aim of this paper is to examine the use of joint modelling techniques for predicting survival

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Summary

Background

We study the longevity and medical resource usage of a large sample of insureds aged 65 years or older drawn from a large health insurance dataset. Counts of each subject's emergency room and ambulance service use and hospital admissions are made. The study aims to capture the simultaneous dependence between their demand for healthcare and survival

Methods
Results
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22. Rizopoulos JM
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