Estimation of the excess mortality in chronic diseases from prevalence and incidence data

TL;DR

This paper investigates methods to improve the estimation of excess mortality in younger populations with chronic diseases using prevalence and incidence data, addressing biases and extending age applicability.

Contribution

It analyzes the causes of bias in current excess mortality estimates for younger ages and proposes strategies to enhance accuracy below age 50.

Findings

Identifies key biases affecting estimates in younger populations

Proposes methodological improvements for more reliable estimates

Extends the age range for excess mortality estimation

Abstract

Aggregated health data such as claims data from health insurances become more and more available for research purposes. Estimates of excess mortality from prevalence and incidence of a chronic condition have only been possible for ages 50 years and older and have shown to be unstable in younger ages. The aim of this article is to explore the reasons why estimates of excess mortality for younger ages are prone to bias and what can be done to extend the age range to ages below 50 years.