Evidence map›Paper›PMID 37832967›Full record

ReviewBMJ health & care informatics2023

Digital health and care: emerging from pandemic times.

Niels Peek, Mark Sujan, Philip Scott

Abstract readReview
In one paragraph

Review in BMJ health & care informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Recent Advances in AI and GenAI for Health Informatics.Healthcare (Basel, Switzerland) · 2026
    Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. 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

3 authors.

Niels PeekCentre for Health Informatics, The University of Manchester, Manchester, UK niels.peek@manchester.ac.uk.ORCID http://orcid.org/0000-0002-6393-9969
Mark SujanHuman Factors Everywhere Ltd, Woking, UK.ORCID http://orcid.org/0000-0001-6895-946X
Philip ScottInstitute of Management and Health, University of Wales Trinity Saint David, Swansea, UK.ORCID http://orcid.org/0000-0002-6289-4260

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In 2020, we published an editorial about the massive disruption of health and care services caused by the COVID-19 pandemic and the rapid changes in digital service delivery, artificial intelligence and data sharing that were taking place at the time. Now, 3 years later, we describe how these developments have progressed since, reflect on lessons learnt and consider key challenges and opportunities ahead by reviewing significant developments reported in the literature. As before, the three key areas we consider are digital transformation of services, realising the potential of artificial intelligence and wise data sharing to facilitate learning health systems. We conclude that the field of digital health has rapidly matured during the pandemic, but there are still major sociotechnical, evaluation and trust challenges in the development and deployment of new digital services.

Indexed as

COVID-19Learning Health SystemArtificial IntelligenceHumansPandemicsTrustArtificial intelligenceBMJ Health InformaticsCOVID-19InformaticsPublic health informatics

Identifiers

PMID37832967
PMCPMC10583078

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.