Long-Term Care Models and Dependence Probability Tables by Acuity Level: New Empirical Evidence from Switzerland
Journal
Insurance: Mathematics and Economics
ISSN
0167-6687
Type
journal article
Date Issued
2018-06-02
Author(s)
Abstract
Due to the demographic changes and population aging occurring in many countries, the financing of long-
term care (LTC) poses a systemic threat. The scarcity of knowledge about the probability of an elderly
person needing help with activities of daily living has hindered the development of insurance solutions
that complement existing social systems. In this paper, we consider two models: a frailty level model
that studies the evolution of a dependent person through mild, moderate and severe dependency states
to death and a type of care model that distinguishes between care received at home and care received
in an institution. We develop and interpret the expressions for the state- and time-dependent transition
probabilities in a semi-Markov framework. Then, we empirically assess these probabilities using a novel
longitudinal dataset covering all LTC needs in Switzerland over a 20-year period. As a key result, we are
the first to derive dependence probability tables by acuity level, gender and age for the Swiss population.
We find that the transition probabilities differ significantly by gender, age and time spent in the frailty
level and type of care states.
term care (LTC) poses a systemic threat. The scarcity of knowledge about the probability of an elderly
person needing help with activities of daily living has hindered the development of insurance solutions
that complement existing social systems. In this paper, we consider two models: a frailty level model
that studies the evolution of a dependent person through mild, moderate and severe dependency states
to death and a type of care model that distinguishes between care received at home and care received
in an institution. We develop and interpret the expressions for the state- and time-dependent transition
probabilities in a semi-Markov framework. Then, we empirically assess these probabilities using a novel
longitudinal dataset covering all LTC needs in Switzerland over a 20-year period. As a key result, we are
the first to derive dependence probability tables by acuity level, gender and age for the Swiss population.
We find that the transition probabilities differ significantly by gender, age and time spent in the frailty
level and type of care states.
Language
English
Refereed
Yes
Publisher
North Holland Publ. Co.
Volume
81
Start page
51
End page
70
Pages
20
Subject(s)
Division(s)
Contact Email Address
joel.wagner@unil.ch
Additional Information
Prof. Wagner is Professor at the HEC Lausanne; http://people.unil.ch/joelwagner; joel.wagner@unil.ch
Eprints ID
255401