Evidence map›Paper›PMID 30400921›Full record

ArticleBMC health services research2018

A qualitative exploration of early assessment of innovative medical technologies.

Iben Fasterholdt, Anne Lee, Kristian Kidholm, Knud Bonnet Yderstræde, Kjeld Møller Pedersen

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in BMC health services research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.4field-weighted citation impact, top 17% of its field
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

3 citing papers in PubMed, 19 citations in OpenAlex.

  1. Commentary: Reflections on defining Early HTA.International journal of technology assessment in health care · 2025
    Article
  2. Health technology assessment framework for artificial intelligence-based technologies.International journal of technology assessment in health care · 2024
    Article
  3. 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

5 authors at 2 institutions in 1 country.

Iben FasterholdtCIMT - Centre for Innovative Medical Technology, Odense University Hospital, Sdr. Boulevard 29, Entrance 102, 3rd floor, 5000, Odense C, Denmark. if@rsyd.dk.ORCID http://orcid.org/0000-0002-4088-5822
Anne LeeCIMT - Centre for Innovative Medical Technology, Odense University Hospital, Sdr. Boulevard 29, Entrance 102, 3rd floor, 5000, Odense C, Denmark.
Kristian KidholmCIMT - Centre for Innovative Medical Technology, Odense University Hospital, Sdr. Boulevard 29, Entrance 102, 3rd floor, 5000, Odense C, Denmark.
Knud Bonnet YderstrædeDepartment of Medical Endocrinology, Odense University Hospital, Odense, Denmark.
Kjeld Møller PedersenDepartment of Business and Economics, University of Southern Denmark, Odense, Denmark.
University of Southern Denmark · DKOdense University Hospital · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHospitals increasingly make decisions about early development of and investment in innovative medical technologies (IMTs), but at present often without an early assessment of their potential to ensure selection of the most promising candidates for further development. This paper explores how early assessment is carried out in different health organisations and then discusses relevant learning points for hospitals.

methodsA qualitative study design with a structured interview guide covering four themes was used. Content analyses of interview notes were performed covering four predetermined themes: context, basis for decision-making, process and structure, and perceptions. A fifth theme, handling cognitive bias, was identified during data analysis.

resultsA total of 11 organisations participated; eight from the private health industry and three public hospitals. The interviews identified four areas in which early assessment is performed in similar manner across the studied organisations and four areas where differences exist between public hospitals and private organisations. Public hospitals indicate a lower degree of formalised early assessment and less satisfaction with how early assessment is performed, compared to private organisations. Based on the above findings, two learning points may carry promise for hospitals. First, having dedicated prioritising committees for IMTs making stop/go decisions. This committee is separate from the IMT development processes and involved staff. Secondly, the committee should base decisions on a transparent early assessment decision-support tool, which include a broad set of domains, is iterative, describes uncertainty, and minimise cognitive biases.

conclusionsSimilarities and differences in the way early assessment is done in different health organisations were identified. These findings suggest promising learning points for the development of an early assessment model for hospitals.

Indexed as

Technology Assessment, BiomedicalTherapies, InvestigationalBiomedical TechnologyDecision MakingDelivery of Health CareHospitals, PublicHumansQualitative ResearchEarly assessmentHealth technology assessmentInnovationInterview

Identifiers

PMID30400921
PMCPMC6220450
OpenAlexW2899976208

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.