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Effect of battery longevity on costs and health outcomes associated with cardiac implantable electronic devices: a Markov model-based Monte Carlo simulation

INTRODUCTION: The effects of device and patient characteristics on health and economic outcomes in patients with cardiac implantable electronic devices (CIEDs) are unclear. Modeling can estimate costs and outcomes for patients with CIEDs under a variety of scenarios, varying battery longevity, comor...

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Autores principales: Schmier, Jordana K., Lau, Edmund C., Patel, Jasmine D., Klenk, Juergen A., Greenspon, Arnold J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5705743/
https://www.ncbi.nlm.nih.gov/pubmed/29110166
http://dx.doi.org/10.1007/s10840-017-0289-8
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author Schmier, Jordana K.
Lau, Edmund C.
Patel, Jasmine D.
Klenk, Juergen A.
Greenspon, Arnold J.
author_facet Schmier, Jordana K.
Lau, Edmund C.
Patel, Jasmine D.
Klenk, Juergen A.
Greenspon, Arnold J.
author_sort Schmier, Jordana K.
collection PubMed
description INTRODUCTION: The effects of device and patient characteristics on health and economic outcomes in patients with cardiac implantable electronic devices (CIEDs) are unclear. Modeling can estimate costs and outcomes for patients with CIEDs under a variety of scenarios, varying battery longevity, comorbidities, and care settings. The objective of this analysis was to compare changes in patient outcomes and payer costs attributable to increases in battery life of implantable cardiac defibrillators (ICDs) and cardiac resynchronization therapy defibrillators (CRT-D). METHODS AND RESULTS: We developed a Monte Carlo Markov model simulation to follow patients through primary implant, postoperative maintenance, generator replacement, and revision states. Patients were simulated in 3-month increments for 15 years or until death. Key variables included Charlson Comorbidity Index, CIED type, legacy versus extended battery longevity, mortality rates (procedure and all-cause), infection and non-infectious complication rates, and care settings. Costs included procedure-related (facility and professional), maintenance, and infections and non-infectious complications, all derived from Medicare data (2004–2014, 5% sample). Outcomes included counts of battery replacements, revisions, infections and non-infectious complications, and discounted (3%) costs and life years. An increase in battery longevity in ICDs yielded reductions in numbers of revisions (by 23%), battery changes (by 44%), infections (by 23%), non-infectious complications (by 10%), and total costs per patient (by 9%). Analogous reductions for CRT-Ds were 23% (revisions), 32% (battery changes), 22% (infections), 8% (complications), and 10% (costs). CONCLUSION: Based on modeling results, as battery longevity increases, patients experience fewer adverse outcomes and healthcare costs are reduced. Understanding the magnitude of the cost benefit of extended battery life can inform budgeting and planning decisions by healthcare providers and insurers. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10840-017-0289-8) contains supplementary material, which is available to authorized users.
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spelling pubmed-57057432017-12-04 Effect of battery longevity on costs and health outcomes associated with cardiac implantable electronic devices: a Markov model-based Monte Carlo simulation Schmier, Jordana K. Lau, Edmund C. Patel, Jasmine D. Klenk, Juergen A. Greenspon, Arnold J. J Interv Card Electrophysiol Multimedia Report INTRODUCTION: The effects of device and patient characteristics on health and economic outcomes in patients with cardiac implantable electronic devices (CIEDs) are unclear. Modeling can estimate costs and outcomes for patients with CIEDs under a variety of scenarios, varying battery longevity, comorbidities, and care settings. The objective of this analysis was to compare changes in patient outcomes and payer costs attributable to increases in battery life of implantable cardiac defibrillators (ICDs) and cardiac resynchronization therapy defibrillators (CRT-D). METHODS AND RESULTS: We developed a Monte Carlo Markov model simulation to follow patients through primary implant, postoperative maintenance, generator replacement, and revision states. Patients were simulated in 3-month increments for 15 years or until death. Key variables included Charlson Comorbidity Index, CIED type, legacy versus extended battery longevity, mortality rates (procedure and all-cause), infection and non-infectious complication rates, and care settings. Costs included procedure-related (facility and professional), maintenance, and infections and non-infectious complications, all derived from Medicare data (2004–2014, 5% sample). Outcomes included counts of battery replacements, revisions, infections and non-infectious complications, and discounted (3%) costs and life years. An increase in battery longevity in ICDs yielded reductions in numbers of revisions (by 23%), battery changes (by 44%), infections (by 23%), non-infectious complications (by 10%), and total costs per patient (by 9%). Analogous reductions for CRT-Ds were 23% (revisions), 32% (battery changes), 22% (infections), 8% (complications), and 10% (costs). CONCLUSION: Based on modeling results, as battery longevity increases, patients experience fewer adverse outcomes and healthcare costs are reduced. Understanding the magnitude of the cost benefit of extended battery life can inform budgeting and planning decisions by healthcare providers and insurers. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10840-017-0289-8) contains supplementary material, which is available to authorized users. Springer US 2017-11-06 2017 /pmc/articles/PMC5705743/ /pubmed/29110166 http://dx.doi.org/10.1007/s10840-017-0289-8 Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Multimedia Report
Schmier, Jordana K.
Lau, Edmund C.
Patel, Jasmine D.
Klenk, Juergen A.
Greenspon, Arnold J.
Effect of battery longevity on costs and health outcomes associated with cardiac implantable electronic devices: a Markov model-based Monte Carlo simulation
title Effect of battery longevity on costs and health outcomes associated with cardiac implantable electronic devices: a Markov model-based Monte Carlo simulation
title_full Effect of battery longevity on costs and health outcomes associated with cardiac implantable electronic devices: a Markov model-based Monte Carlo simulation
title_fullStr Effect of battery longevity on costs and health outcomes associated with cardiac implantable electronic devices: a Markov model-based Monte Carlo simulation
title_full_unstemmed Effect of battery longevity on costs and health outcomes associated with cardiac implantable electronic devices: a Markov model-based Monte Carlo simulation
title_short Effect of battery longevity on costs and health outcomes associated with cardiac implantable electronic devices: a Markov model-based Monte Carlo simulation
title_sort effect of battery longevity on costs and health outcomes associated with cardiac implantable electronic devices: a markov model-based monte carlo simulation
topic Multimedia Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5705743/
https://www.ncbi.nlm.nih.gov/pubmed/29110166
http://dx.doi.org/10.1007/s10840-017-0289-8
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