A parsimonious model to validate cost-effectiveness analyses on preventive health care

Background

The effect of preventive health care on health expenditures is ambiguous. On the one hand, prevention reduces the costs of future morbidity. On the other hand, prevention leads to costs of life extension. The purpose of this paper is to develop a parsimonious model that determines for a preventive measure of interest whether savings from preventing morbidity are more than offset by the costs of living longer, resulting in a net expenditure increase.

Methods

A theoretical model was built based on a Weibull survival function. It includes savings and life extension costs over the remaining lifetime. The model was applied to the example of obesity prevention.

Results

The model shows that the cost consequences of prevention are essentially driven by two factors: i) the relative reduction of morbidity-related costs, which determines the amount of savings from avoiding morbidity; and ii) the hazard ratio of death, which determines the amount of life extension costs. In the application example, the model is able to validate the results of a more complex cost-effectiveness model on obesity prevention.

Conclusions

This work provides new insight into the lifetime cost consequences of prevention. The model can be used both to check plausibility of the results of other models and to conduct an independent analysis.

Event simulation and external validation applied in published health economic models for obesity: a systematic review

INTRODUCTION

This study aims to determine methodological variations in the event simulation approaches of published health economic decision models, in the field of obesity, and to investigate whether their predictiveness and validity were investigated via external event validation techniques, which investigate how well the model reproduces reality.

AREAS COVERED

A systematic review identified a total of 87 relevant papers, of which 72 that simulated obesity-associated events were included. Most frequently simulated events were coronary heart disease (≈ 83%), type 2 diabetes (≈ 74%), and stroke (≈ 66%). Only for ten published model-based health economic assessments in obesity an external event validation was performed (14%; 10 of 72), and only for one the predictiveness and validity of the event simulation was investigated in a cohort of obese subjects.

EXPERT COMMENTARY

We identified a wide range of obesity related event simulation approaches. Published obesity models lack information on the predictive quality and validity of the applied event simulation approaches. Further work on comparing and validating these event simulation approaches is required to investigate their predictiveness and validity, which will offer guidance future modelling in the field of obesity.