Evidence map›Paper›PMID 36628458›Full record

ArticleInternational journal of technology assessment in health care2023

Using early health economic modeling to inform medical innovation development: a soft robotic sock in poststroke patients in Singapore.

Yi Wang, Fan-Zhe Low, Yin-Yi Low, Hwa-Sen Lai, Jeong-Hoon Lim, Chen-Hua Yeow, Yot Teerawattananon

Abstract read
In one paragraph

Article in International journal of technology assessment in health care, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. 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

7 authors.

Yi WangSaw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.ORCID https://orcid.org/0000-0003-1934-9926
Fan-Zhe LowDepartment of Biomedical Engineering, National University of Singapore, Singapore, Singapore.
Yin-Yi LowDepartment of Biomedical Engineering, National University of Singapore, Singapore, Singapore.
Hwa-Sen LaiDepartment of Biomedical Engineering, National University of Singapore, Singapore, Singapore.
Jeong-Hoon LimDepartment of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Chen-Hua YeowDepartment of Biomedical Engineering, National University of Singapore, Singapore, Singapore.
Yot TeerawattananonSaw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.

Funding

Bill and Melinda Gates Foundation OPP1202541National Research Foundation Singapore R-397-000-346-281
6 · The paper itself

Abstract

objectivesBased on a real-world collaboration with innovators in applying early health economic modeling, we aimed to offer practical steps that health technology assessment (HTA) researchers and innovators can follow and promote the usage of early HTA among research and development (R&D) communities.

methodsThe HTA researcher was approached by the innovator to carry out an early HTA ahead of the first clinical trial of the technology, a soft robotic sock for poststroke patients. Early health economic modeling was selected to understand the potential value of the technology and to help uncover the information gap. Threshold analysis was used to identify the target product profiles. Value-of-information analysis was conducted to understand the uncertainties and the need for further research.

resultsBased on the expected price and clinical effectiveness by the innovator, the new technology was found to be cost-saving compared to the current practice. Risk reduction in deep vein thrombosis and ankle contracture, the incidence rate of ankle contracture, the compliance rate of the new technology, and utility scores were found to have high impacts on the value-for-money of the new technology. The value of information was low if the new technology can achieve the expected clinical effectiveness. A list of parameters was recommended for data collection in the impending clinical trial.

conclusionsThis work, based on a real-world collaboration, has illustrated that early health economic modeling can inform medical innovation development. We provided practical steps in order to achieve more efficient R&D investment in medical innovation moving forward.

Indexed as

RoboticsCost-Benefit AnalysisEconomics, MedicalHumansSingaporeTechnology Assessment, Biomedicalearly health technology assessmentmedical innovationreal-world applicationstroketarget product profiles

Identifiers

PMID36628458
PMCPMC11574750

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.