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Adoption of Digital Technologies in Health Care During the COVID-19 Pandemic: Systematic Review of Early Scientific Literature.
Golinelli, Davide; Boetto, Erik; Carullo, Gherardo; Nuzzolese, Andrea Giovanni; Landini, Maria Paola; Fantini, Maria Pia.
  • Golinelli D; Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy.
  • Boetto E; Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy.
  • Carullo G; Department of Italian and Supranational Public Law, University of Milan, Milan, Italy.
  • Nuzzolese AG; STLab, ISTC-CNR, Rome, Italy.
  • Landini MP; IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy.
  • Fantini MP; Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy.
J Med Internet Res ; 22(11): e22280, 2020 11 06.
Article in English | MEDLINE | ID: covidwho-979616
ABSTRACT

BACKGROUND:

The 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.

OBJECTIVE:

The 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.

METHODS:

We 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.

RESULTS:

The 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.

CONCLUSIONS:

In 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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Artificial Intelligence / Telemedicine / Coronavirus Infections / Delivery of Health Care / Pandemics Type of study: Diagnostic study / Observational study / Prognostic study / Randomized controlled trials / Reviews / Systematic review/Meta Analysis Limits: Humans Language: English Journal: J Med Internet Res Journal subject: Medical Informatics Year: 2020 Document Type: Article Affiliation country: 22280

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Artificial Intelligence / Telemedicine / Coronavirus Infections / Delivery of Health Care / Pandemics Type of study: Diagnostic study / Observational study / Prognostic study / Randomized controlled trials / Reviews / Systematic review/Meta Analysis Limits: Humans Language: English Journal: J Med Internet Res Journal subject: Medical Informatics Year: 2020 Document Type: Article Affiliation country: 22280