Evidence map›Paper›PMID 33882604›Full record

ReviewYearbook of medical informatics2021

Managing Pandemic Responses with Health Informatics - Challenges for Assessing Digital Health Technologies.

Farah Magrabi, Elske Ammenwerth, Catherine K Craven, Kathrin Cresswell, Nicolet F De Keizer, Stephanie K Medlock, Philip J Scott, Zoie Shui-Yee Wong, Andrew Georgiou

Open access · hybridAbstract readReview
In one paragraph

Review in Yearbook of medical informatics, 2021. 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
0.8field-weighted citation impact, top 29% 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, 8 citations in OpenAlex.

  1. Review
  2. Bibliometric Analysis of Health Technology Research: 1990~2020.International journal of environmental research and public health · 2022
    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

9 authors at 7 institutions in 6 countries.

Farah MagrabiAustralian Institute of Health Innovation, Macquarie University, Sydney, Australia.
Elske AmmenwerthUMIT, Private University for Health Sciences, Medical Informatics and Technology, Institute of Medical Informatics, Hall in Tirol, Austria.
Catherine K CravenInstitute for Health Care Delivery Science, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Kathrin CresswellUsher Institute, The University of Edinburgh, United Kingdom.
Nicolet F De KeizerAmsterdam UMC, University of Amsterdam, Department of Medical Informatics, Amsterdam Public Health research institute, The Netherlands.
Stephanie K MedlockAmsterdam UMC, University of Amsterdam, Department of Medical Informatics, Amsterdam Public Health research institute, The Netherlands.
Philip J ScottUniversity of Portsmouth, Centre for Healthcare Modelling and Informatics, Portsmouth, United Kingdom.
Zoie Shui-Yee WongGraduate School of Public Health, St. Luke's International University, Tokyo, Japan.
Andrew GeorgiouAustralian Institute of Health Innovation, Macquarie University, Sydney, Australia.
Amsterdam University Medical Centers · NLMacquarie University · AUIcahn School of Medicine at Mount Sinai · USSt. Luke's International University · JPUMIT - Private Universität für Gesundheitswissenschaften, Medizinische Informatik und Technik · ATUniversity of Edinburgh · GBUniversity of Portsmouth · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo highlight the role of technology assessment in the management of the COVID-19 pandemic.

methodAn overview of existing research and evaluation approaches along with expert perspectives drawn from the International Medical Informatics Association (IMIA) Working Group on Technology Assessment and Quality Development in Health Informatics and the European Federation for Medical Informatics (EFMI) Working Group for Assessment of Health Information Systems.

resultsEvaluation of digital health technologies for COVID-19 should be based on their technical maturity as well as the scale of implementation. For mature technologies like telehealth whose efficacy has been previously demonstrated, pragmatic, rapid evaluation using the complex systems paradigm which accounts for multiple sociotechnical factors, might be more suitable to examine their effectiveness and emerging safety concerns in new settings. New technologies, particularly those intended for use on a large scale such as digital contract tracing, will require assessment of their usability as well as performance prior to deployment, after which evaluation should shift to using a complex systems paradigm to examine the value of information provided. The success of a digital health technology is dependent on the value of information it provides relative to the sociotechnical context of the setting where it is implemented.

conclusionCommitment to evaluation using the evidence-based medicine and complex systems paradigms will be critical to ensuring safe and effective use of digital health technologies for COVID-19 and future pandemics. There is an inherent tension between evaluation and the imperative to urgently deploy solutions that needs to be negotiated.

Indexed as

COVID-19Medical InformaticsTechnology Assessment, BiomedicalHumans

Identifiers

PMID33882604
PMCPMC8416188
OpenAlexW3156725397

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.