AI for Drug Repurposing in the Pandemic Response

Given the time criticality of finding treatments for the novel COVID-19 pandemic disease, drug repurposing has proved to be a vital strategy as the first response while de novo drug and vaccine developments are underway. Furthermore, Artificial Intelligence (AI) has also accelerated drug development in general. Key desirable features of AI that support a rapid and sustained response along the pandemic timeline include technical flexibility and efficiency (i.e. speed, resource-efficiency, algorithm adaptability), and clinical applicability and acceptability (i.e. scientific rigor, physiological applicability and practical implementation of proposed drugs). This chapter reviews a selection of AI-based applications used in drug development targeting COVID-19, including IDentif.AI-a small data platform for a rapid identification of optimal drug combinations, to illustrate the potential of AI in drug repurposing. The benefits and limitations of using Real-World Data are also discussed. The response to the COVID-19 pandemic has offered multiple learnings which highlight the need to strengthen both short- and long-term strategies in developing AI technologies, scientific and regulatory frameworks as well as worldwide collaborations to enable effective preparedness for future epidemic and pandemic risks. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Utilization of Health Resources During the Coronavirus Pandemic in Israel: Meuhedet Health Services' Real Data Analysis and Future Conclusions

Aim: This study aimed to examine the utilization of health resources during the first year of the COVID-19 pandemic in Israel through the analysis of Meuhedet Health Services' real-world database. Background(s): The history of COVID-19 in Israel comprises three waves: from February to May 2020, from May to November 2020, and from November 2020 to April 2021. Restrictions imposed on the Israeli population included travel limitations and even lockdowns. Meuhedet Health Services, the third largest health management organization in Israel, manages all its medical data through computerized electronic files and has collected various types of health services data from 2018 to 2020. This paper compared the consumption of Meuhedet Health Services over two consecutive years of the pandemic using a real-world database. Method(s): Electronic medical records from primary care physicians, laboratory tests, hospitalization medical histories, treatments in hospitals and institutes, visits to and treatments by community physicians, and prescriptions and medical equipment consumption were collected from 2018 to 2020. This research used aggregated, non-personalized, and decoded data from a cohort of insured individuals, and the research was approved by all the relevant institutional Helsinki Committees. The data analysis compared the corresponding data in a chosen month of the year with the data in the same month of the previous year. The differences were then scaled by the data corresponding to the month of the previous year, and the result was multiplied by 100 and plotted. To analyze drug consumption, we used the fixed price of every drug in a year multiplied by the difference in consumption of the drug in question between the month of the current year and the same month of the previous year, multiplied by 100. Result(s): A significant decrease was noted in hospitalization days, general hospital outpatient clinic visits, general hospital emergency room visits, and total numbers of visits to community physicians during the first lockdown in the first wave of the pandemic in comparison to 2019. At the end of the lockdown, however, a compensatory increase was noted in all services. In terms of drug consumption, the data showed no differences in the effects of the different waves. Our findings revealed that the first wave of COVID-19 was a shock, with a significant reduction in the consumption of health services, but this decrease attenuated with the second wave due to immediate management interventions and safety rules implemented in hospitals and clinics. Conclusion(s): People shun medical services during a fast-spreading epidemic that causes significant mortality. Since new variants of COVID-19 could be part of our lives for the next few years, we should learn how to continue living with the pandemic and develop alternative medical services to maintain healthy states. Digitization, remote services, telemedicine, and home care, including home hospitalization, should be part of the health services to cope with pandemic situations.Copyright © 2023 Klang et al.

Parallels between the future for MedTech and Agri-Tech, perspectives drawing on the British experience

In this chapter we explore the future for innovation in two related, but distinct, sectors. We consider the linkages between medical technology (MedTech) and agricultural technology (Agri-Tech) innovation in the UK. We ask and discuss questions: Who are the key actors in the innovation systems of MedTech and Agri-Tech in the UK? What are the core technologies driving the current waves of innovation in these two sectors? Can one industry learn from the other? Where is the scope for cooperation and synergies? We notice that both sectors are technologically linked through foundational technologies underpinning the majority of the observed innovation, e.g. big data, AI, IoT and robotics. The outputs of these technologies rely crucially on digital data for insight and decision support. However, Agri-Tech benefits from less complex stakeholder issues regarding data security and privacy. Both sectors are important to the UK going forwards, and both will be exposed to Brexit and consequences of the COVID pandemic. Our discussion on the future for innovation should be of particular interest to start-up leaders, entrepreneurs, investors, managers and policy-makers in MedTech, Agri-Tech and cognate sectors. © Springer Nature Switzerland AG 2021. All rights reserved.

The Usability, Feasibility, Acceptability, and Efficacy of Digital Mental Health Services in the COVID-19 Pandemic: Scoping Review, Systematic Review, and Meta-analysis.

BACKGROUND: After the rapid spread of the novel SARS-CoV-2, the short-term and long-term mental health impacts of the pandemic on the public, in particular on susceptible individuals, have been reported worldwide. Although digital mental health services expand accessibility while removing many barriers to in-person therapy, their usability, feasibility, acceptability, and efficacy require continued monitoring during the initial phase of the pandemic and its aftermath. OBJECTIVE: In this study, we aimed to understand what mental health services are offered, whether they are practical or acceptable, and to what extent digital mental health services are effective in response to the COVID-19 pandemic across high-income and low- and middle-income countries. METHODS: This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and the PRISMA Extension for Scoping Reviews (PRISMA-ScR) guideline. We implemented searches in PubMed (MEDLINE), Embase, PsycINFO, and Cochrane databases for studies that were published between December 2019 and November 2021 and that involved the use of digital mental health services. Two review authors screened, assessed, and extracted studies independently. The protocol was registered on the International Prospective Register of Systematic Reviews. RESULTS: This review identified 7506 articles through database searching. In total, 65 (0.9%) studies from 18 countries with 67,884 participants were eligible for the scoping review. Of the 65 studies, 16 (24.6%) were included in the meta-analysis. A total of 15 (23.1%) studies measured the usability; 31 (47.7%) studies evaluated the feasibility; 29 (44.6%) studies assessed the acceptability; and 51 (78.5%) studies assessed the efficacy. Web-based programs (21/65, 32.3%), videoconferencing platforms (16/65, 24.6%), smartphone apps (14/65, 21.5%), and SMS text messaging (5/65, 7.7%) were the main techniques. Psychotherapy (44/65, 67.7%) followed by psychoeducation (6/65, 9.2%) and psychological support (5/65, 7.7%) were commonly used. The results of the meta-analysis showed that digital mental health interventions were associated with a small reduction in depressive symptoms (standardized mean difference=-0.49; 95% CI -0.74 to -0.24; P<.001) and a moderate reduction in anxiety symptoms (standardized mean difference=-0.66; 95% CI -1.23 to -1.0; P=.02) significantly. CONCLUSIONS: The findings suggest that digital mental health interventions may be practical and helpful for the general population, at-risk individuals, and patients with preexisting mental disorders across high-income and middle-income countries. An expanded research agenda is needed to apply different strategies for addressing diverse psychological needs and develop integrated mental health services in the post-COVID-19 era. TRIAL REGISTRATION: PROSPERO CRD42022307695; https://tinyurl.com/2jcuwjym.

Remote decentralized clinical trials: a new opportunity for laboratory medicine.

The traditional venue of clinical trials has been hospitals or specialized research units, usually requiring participants to come on-site. Although their contribution to biomedical progress is beyond dispute, they are characterised by two crucial logistical and ultimately scientifical limitations: poor retention and poor generalizability of results, as patients often have problems in concluding the investigation on-site. Remote Decentralised Clinical Trials (RDCTs) take advantage of digital technologies to design trial activities closer to the home of participants, with the aims of minimizing travel to health facilities and the risk of infections, improving the quality of life of participants and caregivers, reducing work absenteeism, including broader cohorts of patients and possibly reducing costs. RDCTs represent a minority of current global research, but the Covid-19 pandemic brought them to the fore. The authors of this paper promote the spread of RDCTs, building on early recommendations from international institutions, and provide some examples of their use and potential benefits in laboratory medicine.

Overcoming Pilotitis in Digital Medicine at the Intersection of Data, Clinical Evidence, and Adoption

Worldwide, digital medicine technologies are being developed at a rapid rate. While these digital medicine technologies offer the potential to transform and revolutionize health care, many are at risk of stalling and remaining in the pilot stage, known as “pilotitis,” thus never reaching true potential. Therefore, overcoming “pilotitis” to increase the uptake of digital medicine technologies is a global concern. To date, several authors have proposed solutions to overcome various barriers owing to the “pilotitis” of digital medicine technologies, such as regulatory frameworks and patients’ data ownership;however, many areas require further consideration. This perspective piece identifies three barriers to the adoption and implementation of digital medicine technologies and proposes approaches for how to overcome them. Addressing such barriers may provide a pathway to success for digital medicine technologies to improve patient outcomes and increase the efficiency of healthcare delivery.

COVID-19 and the Transformation of Intensive Care Unit Telemedicine.

The concept of telecritical care has evolved over several decades. ICU Telemedicine providers using both the hub-and-spoke ICU telemedicine center and consultative service delivery models offered their services during the COVID-19 pandemic. Telemedicine center responses were more efficient, timely, and widely used than those of the consultative model. Bedside nurses, physicians, nurse practitioners, physician assistants, and respiratory therapists incorporated the use of ICU telemedicine tools into their practices and more frequently requested critical care specialist telemedicine support.

Open Innovation as the Catalyst in the Personalized Medicine to Personalized Digital Medicine Transition.

Personalized medicine (PM) bridges several disciplines for understanding and addressing prevalent, complex, or rare situations in human health (e.g., complex phenotyping, risk stratification, etc.); therefore, digital and technological solutions have been integrated in the field to boost innovation and new knowledge generation. The open innovation (OI) paradigm proposes a method by which to respectfully manage disruptive change in biomedical organizations, as experienced by many organizations during digital transformation and the COVID-19 pandemic. In this article, we focus on how this paradigm has catalyzed the transition from PM to personalized digital medicine in a large-volume research hospital. Methods, challenges, and results are discussed. This case study is an endeavor to confirm that OI strategies could help manage urgent needs from the healthcare environment, while achieving sustainability-oriented, accountable innovation.

Virtual Classrooms and Their Challenge of Interaction-An Evaluation of Chat Activities and Logs in an Online Course about Digital Medicine with Heterogeneous Participants.

Learning digital competencies can be successful if the information is also tried out immediately using interactive elements. However, interactive teaching poses a particular challenge, especially in large group formats. Various strategies are used to promote interaction, but there is little known about the results. This article shows different strategies and evaluates their influence on the interaction rate in a large group course over two terms that teaches digital medicine. Log files and participation in surveys as well as participation in chat were quantitatively evaluated. In addition, the chat messages themselves were evaluated qualitatively. For the evaluation, relation to the total number of participants was particularly relevant in order to be able to determine an interaction rate in the individual course sessions. A maximum average interaction rate of 90.97% could be determined over the entire term while the participants wrote an average of 3.96 comments during a session in the chat. In summary, this research could show that interactive elements should be well planned and used at regular intervals in order to reap the benefits.

Digital Medicine Community Perspectives and Challenges: Survey Study.

BACKGROUND: The field of digital medicine has seen rapid growth over the past decade. With this unfettered growth, challenges surrounding interoperability have emerged as a critical barrier to translating digital medicine into practice. In order to understand how to mitigate challenges in digital medicine research and practice, this community must understand the landscape of digital medicine professionals, which digital medicine tools are being used and how, and user perspectives on current challenges in the field of digital medicine. OBJECTIVE: The primary objective of this study is to provide information to the digital medicine community that is working to establish frameworks and best practices for interoperability in digital medicine. We sought to learn about the background of digital medicine professionals and determine which sensors and file types are being used most commonly in digital medicine research. We also sought to understand perspectives on digital medicine interoperability. METHODS: We used a web-based survey to query a total of 56 digital medicine professionals from May 1, 2020, to July 10, 2020, on their educational and work experience, the sensors, file types, and toolkits they use professionally, and their perspectives on interoperability in digital medicine. RESULTS: We determined that the digital medicine community comes from diverse educational backgrounds and uses a variety of sensors and file types. Sensors measuring physical activity and the cardiovascular system are the most frequently used, and smartphones continue to be the dominant source of digital health information collection in the digital medicine community. We show that there is not a general consensus on file types in digital medicine, and data are currently handled in multiple ways. There is consensus that interoperability is a critical impediment in digital medicine, with 93% (52) of survey respondents in agreement. However, only 36% (20) of respondents currently use tools for interoperability in digital medicine. We identified three key interoperability needs to be met: integration with electronic health records, implementation of standard data schemas, and standard and verifiable methods for digital medicine research. We show that digital medicine professionals are eager to adopt new tools to solve interoperability problems, and we suggest tools to support digital medicine interoperability. CONCLUSIONS: Understanding the digital medicine community, the sensors and file types they use, and their perspectives on interoperability will enable the development and implementation of solutions that fill critical interoperability gaps in digital medicine. The challenges to interoperability outlined by this study will drive the next steps in creating an interoperable digital medicine community. Establishing best practices to address these challenges and employing platforms for digital medicine interoperability will be essential to furthering the field of digital medicine.

The Metaverse in Current Digital Medicine

The metaverse has entered people's horizons through virtual reality, digital twinning, the Internet of Things, blockchain technology, etc. In the current healthcare system, the management of chronic diseases, such as chronic obstructive pulmonary disease (COPD) and obstructive sleep apnea-hypopnea syndrome (OSAHS), still faces challenges, such as uneven distribution of medical resources, and difficulty in follow-up, overburdening of specialists, and so on. However, metaverse medical platforms incorporating advanced AI technologies, such as industrial-scale digital twins, may address these issues. In this article, we discuss the application prospect of these technologies in digital medicine and the future of the medical metaverse.

The platform development, adherence and efficacy to a digital Brief therapy for insomnia (dBTI) during the COVID-19 pandemic.

Brief therapy for insomnia (BTI) is a short-term cognitive behavioral therapy for insomnia. At present, there is no study combining BTI with digital technology. However, in the context of the outbreak of coronavirus disease 2019 (COVID-19), patients with acute insomnia may need an online treatment which can quickly improve insomnia symptoms. Our team built a digital BTI (dBTI) platform based on the WeChat mini program. This research provides a framework design and a course design of dBTI, and evaluates the system via recruiting participants suffering from acute insomnia in pandemic. What's more, it explores patients' adherence, the efficiency of the system and their relationship. As the result demonstrates, 68% of participants have completed more than half of the course with medium to high adherence. Gender, pre-sleep arousal scale (PSAS) somatic score and insomnia severity index (ISI) score have affected participants' adherence, and higher adherence has led to better improvement in the severity of insomnia and somatic pre-sleep arousal. It is proved that the platform we built is effective, which not only offers an entry point for the study of how to set up a dBTI platform, but also provides theoretical basis for its clinical application.

Reimagining Connected Care in the Era of Digital Medicine.

The COVID-19 pandemic accelerated the adoption of remote patient monitoring technology, which offers exciting opportunities for expanded connected care at a distance. However, while the mode of clinicians' interactions with patients and their health data has transformed, the larger framework of how we deliver care is still driven by a model of episodic care that does not facilitate this new frontier. Fully realizing a transformation to a system of continuous connected care augmented by remote monitoring technology will require a shift in clinicians' and health systems' approach to care delivery technology and its associated data volume and complexity. In this article, we present a solution that organizes and optimizes the interaction of automated technologies with human oversight, allowing for the maximal use of data-rich tools while preserving the pieces of medical care considered uniquely human. We review implications of this "augmented continuous connected care" model of remote patient monitoring for clinical practice and offer human-centered design-informed next steps to encourage innovation around these important issues.

The effectiveness of automated digital health solutions at successfully managing obesity and obesity-associated disorders: A PICO-structured investigation.

Most adults in the UK and USA are classified as overweight or obese. Recent studies suggest that the prevalence of obesity has further increased during the SARS-CoV-2 pandemic and associated lockdowns. Digital technologies may be effective at managing obesity and related comorbidities, a potential further justified by social isolation and distancing circumstances. This review of published literature employed a Patient-Intervention-Comparison-Outcome structured approach on the use of digital solutions to determine the effectiveness of their use in the management and treatment of obesity, hypertension, and type 2 diabetes and included commercially available, automated devices and applications that did not require intervention from a clinician. Our search covered studies published between January 2004 and February 2019, and 18 papers were included in the final analysis. The digital solutions reviewed were smartphone applications, wearable activity trackers, and 'digital medicine offerings' (DMO), including ingestible sensors and wearable patches. This study found that not all interventions were effective at encouraging the lifestyle changes required for the management of obesity. Smartphone applications requiring interaction from the patient appeared to be more effective at encouraging engagement with treatment interventions than more passive wearable activity trackers. Automated feedback from smartphone applications was effective at managing type 2 diabetes, while DMO were effective at reducing blood pressure. With the advancement of new technologies alongside a rapid increase in the prevalence of obesity and associated disorders, further studies comparing the various technologies available in larger sample populations for longer periods would help determine the most cost-effective preventive and therapeutic strategies.

Characteristics of Mobile Health Platforms for Depression and Anxiety: Content Analysis Through a Systematic Review of the Literature and Systematic Search of Two App Stores.

BACKGROUND: Mobile health (mHealth) platforms show promise in the management of mental health conditions such as anxiety and depression. This has resulted in an abundance of mHealth platforms available for research or commercial use. OBJECTIVE: The objective of this review is to characterize the current state of mHealth platforms designed for anxiety or depression that are available for research, commercial use, or both. METHODS: A systematic review was conducted using a two-pronged approach: searching relevant literature with prespecified search terms to identify platforms in published research and simultaneously searching 2 major app stores-Google Play Store and Apple App Store-to identify commercially available platforms. Key characteristics of the mHealth platforms were synthesized, such as platform name, targeted condition, targeted group, purpose, technology type, intervention type, commercial availability, and regulatory information. RESULTS: The literature and app store searches yielded 169 and 179 mHealth platforms, respectively. Most platforms developed for research purposes were designed for depression (116/169, 68.6%), whereas the app store search reported a higher number of platforms developed for anxiety (Android: 58/179, 32.4%; iOS: 27/179, 15.1%). The most common purpose of platforms in both searches was treatment (literature search: 122/169, 72.2%; app store search: 129/179, 72.1%). With regard to the types of intervention, cognitive behavioral therapy and referral to care or counseling emerged as the most popular options offered by the platforms identified in the literature and app store searches, respectively. Most platforms from both searches did not have a specific target age group. In addition, most platforms found in app stores lacked clinical and real-world evidence, and a small number of platforms found in the published research were available commercially. CONCLUSIONS: A considerable number of mHealth platforms designed for anxiety or depression are available for research, commercial use, or both. The characteristics of these mHealth platforms greatly vary. Future efforts should focus on assessing the quality-utility, safety, and effectiveness-of the existing platforms and providing developers, from both commercial and research sectors, a reporting guideline for their platform description and a regulatory framework to facilitate the development, validation, and deployment of effective mHealth platforms.

Infection Control Behavior at Home During the COVID-19 Pandemic: Observational Study of a Web-Based Behavioral Intervention (Germ Defence).

BACKGROUND: To control the COVID-19 pandemic, people should adopt protective behaviors at home (self-isolation, social distancing, putting shopping and packages aside, wearing face coverings, cleaning and disinfecting, and handwashing). There is currently limited support to help individuals conduct these behaviors. OBJECTIVE: This study aims to report current household infection control behaviors in the United Kingdom and examine how they might be improved. METHODS: This was a pragmatic cross-sectional observational study of anonymous participant data from Germ Defence between May 6-24, 2020. Germ Defence is an open-access fully automated website providing behavioral advice for infection control within households. A total of 28,285 users sought advice from four website pathways based on household status (advice to protect themselves generally, to protect others if the user was showing symptoms, to protect themselves if household members were showing symptoms, and to protect a household member who is at high risk). Users reported current infection control behaviors within the home and intentions to change these behaviors. RESULTS: Current behaviors varied across all infection control measures but were between sometimes (face covering: mean 1.61, SD 1.19; social distancing: mean 2.40, SD 1.22; isolating: mean 2.78, SD 1.29; putting packages and shopping aside: mean 2.75, SD 1.55) and quite often (cleaning and disinfecting: mean 3.17, SD 1.18), except for handwashing (very often: mean 4.00, SD 1.03). Behaviors were similar regardless of the website pathway used. After using Germ Defence, users recorded intentions to improve infection control behavior across all website pathways and for all behaviors (overall average infection control score mean difference 0.30, 95% CI 0.29-0.31). CONCLUSIONS: Self-reported infection control behaviors other than handwashing are lower than is optimal for infection prevention, although handwashing is much higher. Advice using behavior change techniques in Germ Defence led to intentions to improve these behaviors. Promoting Germ Defence within national and local public health and primary care guidance could reduce COVID-19 transmission.

Digital Endpoints: Definition, Benefits, and Current Barriers in Accelerating Development and Adoption.

The assessment of health and disease requires a set of criteria to define health status and progression. These health measures are referred to as "endpoints." A "digital endpoint" is defined by its use of sensor-generated data often collected outside of a clinical setting such as in a patient's free-living environment. Applicable sensors exist in an array of devices and can be applied in a diverse set of contexts. For example, a smartphone's microphone might be used to diagnose or predict mild cognitive impairment due to Alzheimer's disease or a wrist-worn activity monitor (such as those found in smartwatches) may be used to measure a drug's effect on the nocturnal activity of patients with sickle cell disease. Digital endpoints are generating considerable excitement because they permit a more authentic assessment of the patient's experience, reveal formerly untold realities of disease burden, and can cut drug discovery costs in half. However, before these benefits can be realized, effort must be applied not only to the technical creation of digital endpoints but also to the environment that allows for their development and application. The future of digital endpoints rests on meaningful interdisciplinary collaboration, sufficient evidence that digital endpoints can realize their promise, and the development of an ecosystem in which the vast quantities of data that digital endpoints generate can be analyzed. The fundamental nature of health care is changing. With coronavirus disease 2019 serving as a catalyst, there has been a rapid expansion of home care models, telehealth, and remote patient monitoring. The increasing adoption of these health-care innovations will expedite the requirement for a digital characterization of clinical status as current assessment tools often rely upon direct interaction with patients and thus are not fit for purpose to be administered remotely. With the ubiquity of relatively inexpensive sensors, digital endpoints are positioned to drive this consequential change. It is therefore not surprising that regulators, physicians, researchers, and consultants have each offered their assessment of these novel tools. However, as we further describe later, the broad adoption of digital endpoints will require a cooperative effort. In this article, we present an analysis of the current state of digital endpoints. We also attempt to unify the perspectives of the parties involved in the development and deployment of these tools. We conclude with an interdependent list of challenges that must be collaboratively addressed before these endpoints are widely adopted.

Telemedicine in Malignant and Nonmalignant Hematology: Systematic Review of Pediatric and Adult Studies.

BACKGROUND: Telemedicine, including video-, web-, and telephone-based interventions, is used in adult and pediatric populations to deliver health care and communicate with patients. In the realm of hematology, telemedicine has recently been used to safely and efficiently monitor treatment side-effects, perform consultations, and broaden the reach of subspecialty care. OBJECTIVE: We aimed to synthesize and analyze information regarding the feasibility, acceptability, and potential benefits of telemedicine interventions in malignant and nonmalignant hematology, as well as assess the recognized limitations of these interventions. METHODS: Studies were identified through a comprehensive Medical Subject Headings (MeSH) search on the PubMed MEDLINE, Controlled Register of Clinical Trials (Cochrane CENTRAL from Wiley), Embase, and CINAHL (EBSCO) databases on February 7, 2018. A second search, utilizing the same search strategy, was performed on October 1, 2020. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines in the reporting of included evidence. Included studies were original articles researching the feasibility, acceptability, and clinical outcomes of telemedicine or telehealth interventions in pediatric or adult populations with malignant or nonmalignant hematological conditions. Data items in the extraction form included first author name, publication year, country, malignant or nonmalignant hematological condition or disease focus of the study, participant age, participant age subgroup (pediatric or adult), study design and setting, telemedicine intervention type and description, study purpose, and main study outcomes. RESULTS: A total of 32 articles met the preset criteria and were included in this study. Most (25/32) studies were conducted in adults, and the remaining (7/32) were conducted in the pediatric population. Of the 32 studies, 12 studied malignant hematological conditions, 18 studied nonmalignant conditions, and two studied both malignant and nonmalignant conditions. Study types included pilot study (11/32), retrospective study (9/32), randomized controlled trial (6/32), cross-sectional study (2/32), case study (1/32), pre-post study (1/32), noncomparative prospective study (1/32), and prospective cohort study (1/32). The three main types of telemedicine interventions utilized across all studies were video-based (9/32), telephone-based (9/32), and web-based interventions (14/32). Study results showed comparable outcomes between telemedicine and traditional patient encounter groups across both pediatric and adult populations for malignant and nonmalignant hematological conditions. CONCLUSIONS: Evidence from this review suggests that telemedicine use in nonmalignant and malignant hematology provides similar or improved health care compared to face-to-face encounters in both pediatric and adult populations. Telemedicine interventions utilized in the included studies were well received in both pediatric and adult settings. However, more research is needed to determine the efficacy of implementing more widespread use of telemedicine for hematological conditions.