Modeling Early Warning Systems: Construction and Validation of a Discrete Event Simulation Model for Heart Failure

Fernando Albuquerque de Almeida*, Isaac Corro Ramos, Maureen Rutten-van Mölken, Maiwenn Al

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

4 Citations (Scopus)
42 Downloads (Pure)


Objectives: Developing and validating a discrete event simulation model that is able to model patients with heart failure managed with usual care or an early warning system (with or without a diagnostic algorithm) and to account for the impact of individual patient characteristics in their health outcomes. Methods: The model was developed using patient-level data from the Trans-European Network – Home-Care Management System study. It was coded using RStudio Version 1.3.1093 (version 3.6.2.) and validated along the lines of the Assessment of the Validation Status of Health-Economic decision models tool. The model includes 20 patient and disease characteristics and generates 8 different outcomes. Model outcomes were generated for the base-case analysis and used in the model validation. Results: Patients managed with the early warning system, compared with usual care, experienced an average increase of 2.99 outpatient visits and a decrease of 0.02 hospitalizations per year, with a gain of 0.81 life years (0.45 quality-adjusted life years) and increased average total costs of €11 249. Adding a diagnostic algorithm to the early warning system resulted in a 0.92 life year gain (0.57 quality-adjusted life years) and increased average costs of €9680. These patients experienced a decrease of 0.02 outpatient visits and 0.65 hospitalizations per year, while they avoided being hospitalized 0.93 times. The model showed robustness and validity of generated outcomes when comparing them with other models addressing the same problem and with external data. Conclusions: This study developed and validated a unique patient-level simulation model that can be used for simulating a wide range of outcomes for different patient subgroups and treatment scenarios. It provides useful information for guiding research and for developing new treatment options by showing the hypothetical impact of these interventions on a large number of important heart failure outcomes.

Original languageEnglish
Pages (from-to)1435-1445
Number of pages11
JournalValue in Health
Issue number10
Publication statusPublished - Oct 2021

Bibliographical note

Funding Information:
Funding/Support: This work was funded by Philips under a framework contract between the Erasmus School of Health Policy and Management , Erasmus University Rotterdam , and Philips .

Publisher Copyright:
© 2021 ISPOR–The Professional Society for Health Economics and Outcomes Research


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