The COVID-19 pandemic, like all global crises in human history, is causing unprecedented health and economic disruptions in many countries. However, at the same time, this new situation is favoring the transition to digital solutions in many industries and in society as a whole. One example of this transition is education [1]; this entire sector, from primary schools to universities, has developed new strategies for teaching remotely, shifting from lectures in classrooms to live conferencing or web-based courses [2]. Similarly, health care organizations have responded to the COVID-19 pandemic through the rapid adoption of digital solutions and advanced technology tools. During a pandemic, digital technology can mitigate or even solve many challenges, thus improving health care delivery. Digital tools have been applied to address acute needs that have arisen as a direct or indirect consequence of the pandemic (eg, apps for patient tracing, remote triage emergency services). However, many of the solutions that have been developed and implemented during the emergency could be consolidated in the future, contributing to the definition and adoption of new digital models of care.

The list of new digital solutions is rapidly growing [3]. In addition to “video visits,” these options include email and mobile phone apps as well as use of wearable devices, chatbots, artificial intelligence (AI)–powered diagnostic tools, voice-interface systems, and mobile sensors such as smart watches, oxygen monitors, or thermometers. A new category of service is the oversight of persons in home quarantine and large-scale population surveillance. Telemedicine and remote consultation have already proven to be effective at a time when access to health services for patients who do not have COVID-19 or for patients with nonacute COVID-19 is prevented, impeded, or postponed. In fact, according to Keesara et al [4], instead of using a model structured on the historically necessary model of in-person interactions between patients and their clinicians through a face-to-face model of care, current health care services and patient assistance can be guaranteed remotely through digital technologies.

Before the COVID-19 pandemic, it was expected that digital transformation in health care would be as disruptive as the transformations seen in other industries. However, as discussed by Hermann et al [5] and affirmed by Perakslis [6], “despite new technologies being constantly introduced, this change had yet to materialize.” The spread of COVID-19 appears to have finally provided an ineludibly sound reason to fully embrace the digital transformation. Moreover, simulations show that many countries will probably face several waves of contagion, and new lockdowns will probably occur [7]. Therefore, it has become necessary to review the digital technologies that have been used during the emergency period and consider them for continued use over time or cyclically in the event of recurring outbreaks.

According to Hermann et al [5], digital technologies can be categorized based on the patient needs they address in health care: diagnosis, prevention, treatment, adherence, lifestyle, and patient engagement. We argue that it is necessary to understand which digital technologies have been adopted to face the COVID-19 crisis and whether and how they can still be useful after the emergency phase. To achieve this, it is crucial to cover as many aspects as possible of digital technology use in health care in response to the COVID-19 pandemic.

The aim of this study is therefore 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.

We conducted a systematic review of the early scientific literature, following the Preferred Reporting Items for Systematic Reviews (PRISMA) approach [8], to include quantitative and qualitative studies using diverse designs to describe which digital solutions have been reported to respond and mitigate the effects of the COVID-19 pandemic. This review focuses on health research, which includes biomedical, epidemiological, clinical, public health, and health systems research.

The initial search was implemented on May 11, 2020, and was limited to the timespan from January 1 to April 30, 2020. The search query consisted of terms considered adequate by the authors to review the literature on the use of digital technologies in response to COVID-19. Therefore, we searched the MEDLINE database using the following search terms and database-appropriate syntax:

We also searched the COVID-19/SARS-CoV-2 section of medRxiv, a preprint server for health science papers that have yet to be peer-reviewed, for studies related to digital technologies, using the search string COVID-19 digital technology with the same timespan restriction applied to the MEDLINE search.

The search strategies and eligibility criteria used are provided in Multimedia Appendix 1.

We included articles for review if they were studies with original data or results referring to digital tools or interventions for COVID-19 and if they addressed the needs of patients or health care systems in the evaluation.

An article was excluded if it was not a study with original results; it did not focus on digital solutions for COVID-19; the full text was not available; or it was not written in English.

A two-stage screening process was used to assess the relevance of the identified studies. For the first level of screening, only the title and abstract were reviewed to preclude waste of resources in procuring articles that did not meet the minimum inclusion criteria. The titles and abstracts of the initially identified studies were checked by two independent investigators (DG and EB). For the second level of screening, all citations deemed relevant after the title and abstract screening were procured for subsequent review of the full-text article.

A spreadsheet in Excel (Microsoft Corporation) was developed to extract study characteristics such as the paper title, journal, publication date, type of technology, and patient needs addressed. In particular, we categorized the retrieved papers according to patient needs (diagnosis, prevention, treatment, adherence, lifestyle, and patient engagement). For the categorization of patient needs, we adapted the definition by Hermann et al [5], which reports the concept of “customer needs addressed” by the health care industry, to identify the patient health needs addressed by digital technology during the early phase of the COVID-19 pandemic.

The definition of patient needs is reported in Table 1. We added “surveillance” as an additional patient need to those identified by Hermann et al [5] given the importance of early identification and confinement of patients with COVID-19 to preserve population health, and a category of “other” to include any needs that were not considered in the previous categories.

We built a scoring rubric by cross-classifying the patient needs addressed by the technology (or technologies) reported in each article with the type of technology itself. We relied on the report “Assessing the impact of digital transformation of Health Services” by the Expert Panel on Effective Ways of Investigating in Health (EXPH) of the European Commission [16] to classify the types of digital technologies (ie, AI, big data, chatbots, electronic health records [EHRs], mobile apps, robotics, sensors, telehealth, and telemedicine), integrating it with terms found within the analyzed articles when necessary (ie, blockchain, Internet of Things [IoT], internet search engines, social media, and mobile tracing).

We also extracted information and classified each technology reported by the selected articles according to health care system targets, grade of innovation, and scalability to other geographical areas. To do this, we also relied on the classifications and definitions reported by the EXPH (Table 2) [16].

Some of the analyzed articles described multiple technologies. For these articles, we reported all the health care system targets addressed by the proposed technologies. However, we found it impractical to assign different grades of innovation and scalability for each technology reported. Therefore, we chose to report only the highest grade of innovation or scalability assigned to the technologies within each article (eg, innovating>substituting>complementing>supporting).

Two of the authors (DG and EB) independently classified all identified articles in the predefined categories. Any disagreements were resolved through discussion and consensus between the two reviewers. If disagreement persisted, another reviewer (GC) was called as a tiebreaker.

Given the characteristics of this literature review, which aims to describe proposed digital solutions, and the nature and design of the included studies, assessments of the risk of bias and the study quality were not possible and therefore were not performed.

The search identified 269 articles (174 from PubMed and 95 from medRxiv), of which 124 full-text articles were assessed and included in the review after screening (Figure 1).

Out of the 124 selected articles, 65 (52.4%) addressed the use of digital technologies for diagnosis (Figure 2), 46 (37.1%) addressed surveillance, 46 (37.1%) addressed prevention, 38 (30.6%) addressed treatment, 15 (12.1%) addressed adherence, 12 (9.7%) addressed lifestyle, 11 (8.9%) addressed patient engagement, and 6 (4.8%) addressed other purposes. Considering the share of peer-reviewed articles, we found that for diagnosis, 39/65 articles (60%) were peer-reviewed; for surveillance, 29/46 (63%); for prevention, 30/46 (65%); for treatment, 33/38 (87%); for adherence, 15/15 (100%); for lifestyle, 11/12 (92%); for patient engagement, 11/11 (100%); and for other, 5 (83.3%).

In Table 3, we provide an extract of the characteristics of the included articles. An extended version of this table is provided in the supplementary material (Table S1, Multimedia Appendix 2).

In Table 4, we cross-classify the use of technology and the type of technology. As an example, 24 articles describe the use of AI tools for the diagnosis of COVID-19, while 34 describe the use of telehealth or telemedicine for treatment purposes. All included articles and related analyses are reported in Multimedia Appendix 2 (Table S1).

Given the heterogeneity of the included technologies and solutions, we summarized the findings through a narrative synthesis. In fact, some patient needs share the same technology for health issues, which can be considered superimposable (eg, prevention and surveillance are often addressed by the same technology, such as mobile surveillance apps); this is also evident from Table 4, where many articles report technologies addressing more than one health need. Accordingly, in the following paragraphs, we describe the digital technologies and solutions starting from the patient needs they are designed to mitigate. We then discuss some of the retrieved articles that we deemed most interesting for each patient need.

Although SARS-CoV-2 is causing a pandemic worldwide, it is also favoring the rapid adoption of digital solutions and advanced technology tools in health care. On the one hand, physicians and health systems may need to track large populations of patients on a daily basis for surveillance purposes [4]. On the other hand, they may need rapid diagnostic tests for COVID-19 screening, to reduce the workload, and to enable patients to receive early diagnoses and timely treatments. This can also be achieved with the help of digital technologies, which were already available in different industries before the current crisis. These tools have now been quickly implemented in health care due to the pandemic [104].

In this systematic review of the early scientific literature in response to COVID-19, we describe numerous digital solutions and technologies addressing several patient and health care needs. The constantly updated scientific literature is a source of important ideas and suggestions for finding innovative solutions that guarantee patient care during and possibly after the COVID-19 crisis.

In the field of diagnosis, digital solutions that integrate with the traditional methods of clinical, molecular or serological diagnosis, such as AI-based diagnostic algorithms based both on imaging and clinical data, seem promising.

For surveillance, digital apps have already proven their effectiveness [142-144]; however, problems related to privacy and usability remain [145]. For other patient needs, several solutions have been proposed, such as telemedicine or telehealth tools. These tools have long been available; however, this historical moment could actually favor their definitive large-scale adoption.

The fact that the digital technologies proposed in the analyzed scientific literature mainly address the fields of diagnosis, prevention, and surveillance probably reflects the emergency phase of the COVID-19 pandemic. As time passes, well-known digital tools could be proposed for different purposes and patient needs, such as adherence, lifestyle, and patient engagement, which are considered to be important determinants of patient health [146] despite the lower attention paid to them in the early scientific literature.

In addition to the patient needs addressed by digital technologies, our review sheds light on the most used digital technology tools. Given the early phase of the pandemic and its reflection on the articles included in this review, the technologies that have shown to be more easily and quickly implementable can be also considered as the most scalable. In fact, the speed with which these technologies have been deployed demonstrates their ease of adoption and manageability in many different contexts, despite their deployment during the course of a pandemic. Many of these solutions have demonstrated a technical, economic, regulatory and usability weight that is sufficiently low to allow their rapid and effective use, at least during the emergency phase. Among these solutions, we report AI tools for diagnosis, big data analytics and mobile tracing for surveillance and prevention, and telemedicine and telehealth, which have proved to be transversal tools for diagnosis, prevention, and treatment.

We advocate that many of the digital technologies that have been quickly implemented in this emergency phase can also be adopted in the following phases of the pandemic, as also stated by Fagherazzi et al [147]. However, this implementation is easier said than done. According to the article by Keesara et al [4], “Covid-19 and Health Care’s Digital Revolution,” in the context of the digital leap caused by the COVID-19 pandemic in the United States (and worldwide) [4], while private corporations and education institutions have made rapid transitions to remote work and videoconferencing, the health care system is still lagging behind in adopting digital solutions. This is mainly due to the fact that clinical workflows and economic incentives have been developed for a face-to-face model of care that, during this pandemic, contributes to the spread of the virus to uninfected patients who are seeking medical care. In addition to the history of health care policies, there are limiting factors to the implementation of tools such as telemedicine, including a legal framework that is not yet fully designed to regulate the use of innovative IT systems in health care, as well as an inadequate information and communications technology infrastructure and an obsolete reimbursement and payment structure.

Many countries are facing these regulatory issues: the challenges for digital health have become a global issue in the public health response to COVID-19 and future outbreaks. Digital tools such as telemedicine should indeed be integrated into international and national guidelines for public health preparedness, alongside the definition of national regulations and funding frameworks in the context of public health emergencies. To switch to new digital models of care, increasing the digital expertise of health care professionals and educating the population are fundamental issues. Moreover, by implementing a data-sharing mechanism, digitally collected and stored data will be a precious tool for epidemiological surveillance that, as discussed earlier, is fundamental in controlling the epidemic spread. Lastly, to describe and assess the impact of digital tools during outbreaks, scientific evaluation frameworks should be defined [41].

This literature review presents some limitations. First, the research was conducted in a period of epidemiological emergency. Thus, the number of daily publications is high, and it is difficult to keep up to date. As a result, we have been forced to select articles in a reduced time span, potentially missing some studies and including studies that have yet to be peer-reviewed. Secondly, due to the design of the review, the search could not be fully comprehensive, as it was conducted exclusively on the MEDLINE database and medRxiv to preserve both time and resources; however, PubMed/MEDLINE is reported to be the primary database used by health science faculties [148], and medRxiv is one of the main repositories of COVID-19 research [149]. Finally, the articles and concepts included in this preliminary review certainly need to be integrated at the end of this international emergency phase.

The COVID-19 pandemic is favoring the implementation of digital solutions with unprecedented speed and impact. It is therefore recommended to keep track of the ideas and solutions being proposed today to implement best practices and models of care tomorrow and to be prepared for future national and international emergencies. It is worth taking advantage of the impetus provided by the crisis we are currently experiencing to implement at least some of the solutions proposed in the scientific literature, especially in national health systems, which in recent years have proved to be particularly resistant to the digital transition.