Evidence map›Paper›PMID 33079693›Full record

SynthesisJournal of medical Internet research2020

Adoption of Digital Technologies in Health Care During the COVID-19 Pandemic: Systematic Review of Early Scientific Literature.

Davide Golinelli, Erik Boetto, Gherardo Carullo, Andrea Giovanni Nuzzolese, Maria Paola Landini, Maria Pia Fantini

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 243 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
243citing papers in PubMed, 9 pooled it
–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

243 citing papers in PubMed, 9 syntheses or guidelines pooled it.

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  8. Effect of mobile application types on stroke rehabilitation: a systematic review.Journal of neuroengineering and rehabilitation · 2023
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  20. Virtual Care and Compassion for Migrants and Refugees: A Scoping Review.Journal of immigrant and minority health · 2026
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183 more citing papers are in PubMed but not listed here.

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

6 authors.

Davide Golinelli *Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy.ORCID 0000-0001-7331-9520
Erik Boetto *Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy.ORCID 0000-0002-2509-159X
Gherardo CarulloDepartment of Italian and Supranational Public Law, University of Milan, Milan, Italy.ORCID 0000-0001-9810-0736
Andrea Giovanni NuzzoleseSTLab, ISTC-CNR, Rome, Italy.ORCID 0000-0003-2928-9496
Maria Paola LandiniIRCCS Istituto Ortopedico Rizzoli, Bologna, Italy.ORCID 0000-0002-2842-9824
Maria Pia FantiniDepartment of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy.ORCID 0000-0002-3257-6552

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic is favoring digital transitions in many industries and in society as a whole. Health care organizations have responded to the first phase of the pandemic by rapidly adopting digital solutions and advanced technology tools.

objectiveThe aim of this review is to describe the digital solutions that have been reported in the early scientific literature to mitigate the impact of COVID-19 on individuals and health systems.

methodsWe conducted a systematic review of early COVID-19-related literature (from January 1 to April 30, 2020) by searching MEDLINE and medRxiv with appropriate terms to find relevant literature on the use of digital technologies in response to the pandemic. We extracted study characteristics such as the paper title, journal, and publication date, and we categorized the retrieved papers by the type of technology and patient needs addressed. We built a scoring rubric by cross-classifying the patient needs with the type of technology. We also extracted information and classified each technology reported by the selected articles according to health care system target, grade of innovation, and scalability to other geographical areas.

resultsThe search identified 269 articles, of which 124 full-text articles were assessed and included in the review after screening. Most of the selected articles addressed the use of digital technologies for diagnosis, surveillance, and prevention. We report that most of these digital solutions and innovative technologies have been proposed for the diagnosis of COVID-19. In particular, within the reviewed articles, we identified numerous suggestions on the use of artificial intelligence (AI)-powered tools for the diagnosis and screening of COVID-19. Digital technologies are also useful for prevention and surveillance measures, such as contact-tracing apps and monitoring of internet searches and social media usage. Fewer scientific contributions address the use of digital technologies for lifestyle empowerment or patient engagement.

conclusionsIn the field of diagnosis, digital solutions that integrate with traditional methods, such as AI-based diagnostic algorithms based both on imaging and clinical data, appear to be promising. For surveillance, digital apps have already proven their effectiveness; however, problems related to privacy and usability remain. For other patient needs, several solutions have been proposed, such as telemedicine or telehealth tools. These tools have long been available, but this historical moment may actually be favoring their definitive large-scale adoption. It is worth taking advantage of the impetus provided by the crisis; it is also important to keep track of the digital solutions currently being proposed to implement best practices and models of care in future and to adopt at least some of the solutions proposed in the scientific literature, especially in national health systems, which have proved to be particularly resistant to the digital transition in recent years.

Indexed as

Artificial IntelligenceCoronavirus InfectionsPandemicsPneumonia, ViralBetacoronavirusCOVID-19Delivery of Health CareHumansPrivacySARS-CoV-2Social MediaTechnologyTelemedicineCOVID-19digital heatheHealthimpactliteraturemitigatepandemicreviewSARS-CoV-2

Identifiers

PMID33079693
PMCPMC7652596

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.