Evidence map›Paper›PMID 33021485›Full record

ArticleJournal of medical Internet research2020

Evaluation of a Heart Failure Telemonitoring Program Through a Microsimulation Model: Cost-Utility Analysis.

Chris Boodoo, Qi Zhang, Heather J Ross, Ana Carolina Alba, Audrey Laporte, Emily Seto

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Chris BoodooInstitute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.ORCID 0000-0002-5733-7697
Qi ZhangInstitute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.ORCID 0000-0002-4006-1516
Heather J RossTed Rogers Centre for Heart Research, University Health Network, Toronto, ON, Canada.ORCID 0000-0003-4384-3027
Ana Carolina AlbaTed Rogers Centre for Heart Research, University Health Network, Toronto, ON, Canada.ORCID 0000-0003-2744-2696
Audrey LaporteInstitute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.ORCID 0000-0002-5667-9206
Emily SetoInstitute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.ORCID 0000-0002-8723-5915

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHeart failure (HF) is a major public health issue in Canada that is associated with high prevalence, morbidity, and mortality rates and high financial and social burdens. Telemonitoring (TM) has been shown to improve all-cause mortality and hospitalization rates in patients with HF. The Medly program is a TM intervention integrated as standard of care at a large Canadian academic hospital for ambulatory patients with HF that has been found to improve patient outcomes. However, the cost-effectiveness of the Medly program is yet to be determined.

objectiveThis study aims to conduct a cost-utility analysis of the Medly program compared with the standard of care for HF in Ontario, Canada, from the perspective of the public health care payer.

methodsUsing a microsimulation model, individual patient data were simulated over a 25-year time horizon to compare the costs and quality-adjusted life years (QALYs) between the Medly program and standard care for patients with HF treated in the ambulatory care setting. Data were sourced from a Medly Program Evaluation study and literature to inform model parameters, such as Medly's effectiveness in reducing mortality and hospitalizations, health care and intervention costs, and model transition probabilities. Scenario analyses were conducted in relation to HF severity and TM deployment models. One-way deterministic effectiveness analysis and probabilistic sensitivity analysis were performed to explore the impact on the results of uncertainty in model parameters.

resultsThe Medly program was associated with an average total cost of Can $102,508 (US $77,626) per patient and total QALYs of 5.51 per patient compared with the average cost of Can $97,497 (US $73,831) and QALYs of 4.95 per patient in the Standard Care Group. This led to an incremental cost of Can $5011 (US $3794) and incremental QALY of 0.566, resulting in an incremental cost-effectiveness ratio of Can $8850 (US $6701)/QALY. Cost-effectiveness improved in relation to patients with advanced HF and with deployment models in which patients used their own equipment. Baseline and alternative scenarios consistently showed probabilities of cost-effectiveness greater than 85% at a willingness-to-pay threshold of Can $50,000 (US $37,718). Although the results showed some sensitivity to assumptions about effectiveness parameters, the intervention was found to remain cost-effective.

conclusionsThe Medly program for patients with HF is cost-effective compared with standard care using commonly reported willingness-to-pay thresholds. This study provides evidence for decision makers on the use of TM for HF, supports the use of a nurse-led model of TM that embeds clinically validated algorithms, and informs the use of economic modeling for future evaluations of early-stage health informatics technology.

Indexed as

CanadaCost-Benefit AnalysisFemaleHeart FailureHumansMaleMiddle AgedQuality-Adjusted Life YearsTelemedicinecost effectivenesscost utility analysisheart failuremicrosimulationmobile phonetelemedicine

Identifiers

PMID33021485
PMCPMC7576467

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.