Evidence map›Paper›PMID 39283475›Full record

ArticleApplied health economics and health policy2024

The Impact of Unrelated Future Medical Costs on Economic Evaluation Outcomes for Different Models of Diabetes.

Ting Zhao, Michelle Tew, Talitha Feenstra, Pieter van Baal, Michael Willis, William J Valentine, Philip M Clarke, Barnaby Hunt, James Altunkaya, An Tran-Duy and 14 more

Abstract read
In one paragraph

Article in Applied health economics and health policy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Review
  2. Article
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

24 authors.

Ting ZhaoMenzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, 7000, Australia.
Michelle TewCentre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.
Talitha FeenstraFaculty of Science and Engineering, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands.
Pieter van BaalErasmus School of Health Policy and Management, Erasmus University Rotterdam, Rotterdam, The Netherlands.
Michael WillisThe Swedish Institute for Health Economics, Lund, Sweden.
William J ValentineOssian Health Economics and Communications, Basel, Switzerland.
Philip M ClarkeNuffield Department of Population Health, Health Economics Research Centre, University of Oxford, Oxford, UK.
Barnaby HuntOssian Health Economics and Communications, Basel, Switzerland.
James AltunkayaNuffield Department of Population Health, Health Economics Research Centre, University of Oxford, Oxford, UK.
An Tran-DuyCentre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.
Richard F PollockCovalence Research Ltd, Harpenden, UK.
Samuel J P MalkinOssian Health Economics and Communications, Basel, Switzerland.
Andreas NilssonThe Swedish Institute for Health Economics, Lund, Sweden.
Phil McEwanHealth Economics and Outcomes Research Ltd., Cardiff, UK.
Volker FoosHealth Economics and Outcomes Research Ltd., Cardiff, UK.
Jose LealNuffield Department of Population Health, Health Economics Research Centre, University of Oxford, Oxford, UK.
Elbert S HuangCenter for Chronic Disease Research and Policy (CDRP), The University of Chicago, Chicago, IL, USA.
Neda LaiteerapongSection of General Internal Medicine, Department of Medicine, University of Chicago, Chicago, IL, USA.
Mark LamotteTh(is)2Modeling, Asse, Belgium.
Harry SmolenMedical Decision Modeling Inc., Indianapolis, IN, USA.
Jianchao QuanSchool of Public Health, LKS Faculty of Medicine, University of Hong Kong, Hong Kong, Hong Kong.
Luís MartinsTh(is)2Modeling, Asse, Belgium.
Mafalda RamosTh(is)2Modeling, Asse, Belgium.
Andrew J PalmerMenzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, 7000, Australia. andrew.palmer@utas.edu.au.ORCID 0000-0002-9703-7891

Funding

Research Design, Data, and Analytics CoreP30DK092949 · NIDDK · UNIVERSITY OF CHICAGO · PI MONICA E PEEK · 2011 to 2026
$10.0M
Research and Mentorship in Medical Decision Making for Chronic Diseases of Older AdultsK24AG069080 · NIA · UNIVERSITY OF CHICAGO · PI HUANG, ELBERT S. · 2020 to 2024
$583k
NIA NIH HHS K24 AG069080NIDDK NIH HHS P30 DK092949
6 · The paper itself

Abstract

objectiveThis study leveraged data from 11 independent international diabetes models to evaluate the impact of unrelated future medical costs on the outcomes of health economic evaluations in diabetes mellitus.

methodsEleven models simulated the progression of diabetes and occurrence of its complications in hypothetical cohorts of individuals with type 1 (T1D) or type 2 (T2D) diabetes over the remaining lifetime of the patients to evaluate the cost effectiveness of three hypothetical glucose improvement interventions versus a hypothetical control intervention. All models used the same set of costs associated with diabetes complications and interventions, using a United Kingdom healthcare system perspective. Standard utility/disutility values associated with diabetes-related complications were used. Unrelated future medical costs were assumed equal for all interventions and control arms. The statistical significance of changes on the total lifetime costs, incremental costs and incremental cost-effectiveness ratios (ICERs) before and after adding the unrelated future medical costs were analysed using t-test and summarized in incremental cost-effectiveness diagrams by type of diabetes.

resultsThe inclusion of unrelated costs increased mean total lifetime costs substantially. However, there were no significant differences between the mean incremental costs and ICERs before and after adding unrelated future medical costs. Unrelated future medical cost inclusion did not alter the original conclusions of the diabetes modelling evaluations.

conclusionsFor diabetes, with many costly noncommunicable diseases already explicitly modelled as complications, and with many interventions having predominantly an effect on the improvement of quality of life, unrelated future medical costs have a small impact on the outcomes of health economic evaluations.

Indexed as

Cost-Benefit AnalysisDiabetes Mellitus, Type 2Diabetes ComplicationsDiabetes Mellitus, Type 1Health Care CostsHumansMaleModels, EconomicQuality-Adjusted Life YearsUnited Kingdom

Identifiers

PMID39283475
PMCPMC11470878

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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.