Virtual care for improved global health

Virtual care in the health care system: A concept analysis

BACKGROUND

Health care providers need a better understanding of virtual care to recognise and use it for service delivery.

AIM

To provide a more comprehensive definition of the concept of virtual care.

METHOD

This study was conducted based on Walker and Avant's concept analysis method. A comprehensive review of the published texts in English from 2012 to 2022 was performed using the PubMed, Web of Science, Scopus, ProQuest, Science Direct, Ovid, CINAHL and Google Scholar databases.

RESULTS

The main aspects and attributes of virtual care, including the use of any information and communication technology in various formats such as platforms, telephone calls, messages, email consultation, remote monitoring, secure and two-way digital communication between health care providers and patients, the possibility of providing remote care synchronously or asynchronously, more interaction between patients and caregivers, the possibility of transferring information between patients and health care providers and within the teams themselves, symptom management, sending diagnostic results in the form of video visits, and providing follow-up care, are attributes that distinguish virtual care from telehealth, telemedicine and other methods of providing remote healthcare services.

CONCLUSION

Considering the positive and negative consequences of implementing virtual care, the findings of this study developed a basis for an operational definition of the concept so that providers can understand the meaning of virtual care and consider it when providing virtual care to patients. The findings of this study can be used in many international and national contexts in the health care system and in future studies on interventions to increase the use of virtual care.

Barriers to the implementation of virtual care programmes for patients with chronic wounds: Qualitative empirical research

AIM

To assess the barriers to the implementation of virtual care for patients with chronic wounds from wound therapists' perspective.

DESIGN

A qualitative study.

METHODS

The study was conducted in two consecutive phases: (1) literature review, (2) descriptive qualitative study. In the first phase, texts published in English until 2023 were identified using international databases. The entire text of the selected studies was evaluated independently by two reviewers. Data analysis was carried out using textual content analysis. In the second phase of the study, twelve participants from Iranian wound care clinics participated. Data were collected through focus group discussion and analysed using conventional content analysis. Integration of both phases was conducted in the data analysis stage.

RESULTS

The most important barriers in providing virtual care to patients with chronic wounds were identified into five categories including lack of policymaking in virtual care, ethical challenges in virtual information and communication technology, social, economic and cultural issues, IT users' insufficient knowledge and limitation of virtual care scope of practice.

CONCLUSION

The findings of the present study identified different barriers in the implementation of virtual care for patients with chronic wounds. In order to successfully develop a virtual care programme, it is necessary to adopt suitable policies regarding information and communication technology, provide the necessary legal frameworks, assign an adequate budget and consider the ethical, cultural, social and social issues.

IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE

Identifying barriers to developing a virtual care programme will help manage patients with chronic wounds at home.

IMPACT

This study accurately identifies barriers to providing virtual care for patients with chronic wounds and helps plan to address these barriers and facilitate the development of a virtual care programme for these patients at home.

REPORTING METHOD

This research has adhered to the SRQR reporting guideline.

NO PATIENT OR PUBLIC CONTRIBUTION

The involvement of patients or the public in the design, or conduct, or reporting, or dissemination plans of this research was not suitable.

Virtual Adaptation of an International Exchange Program in Medical Education

Medical education has drastically transformed during the COVID-19 pandemic. Measures such as adopting telemedicine visits, minimizing the number of trainees on service, discontinuing external rotations, and converting in-person to online didactics have been broadly and swiftly implemented. While these innovations have promoted greater interconnectivity amongst institutions and made continuing medical education possible, international exchange programs in medical education are still largely disrupted. In response to the changing guidelines and restrictions necessitated by the COVID-19 pandemic, the authors used Kern’s six-step approach to design and implement a virtual curriculum to replace the in-person activities of the 2020–2021 Neurology Peru-Rochester exchange program (NeuroPro). Twenty-seven trainees participated in this virtual adaptation. The average daily attendance was ≥85% and the program was rated 9/10 on average in a feedback survey (63% response rate). The median percentage of correct answers during the pre-test was 64% and it increased to 79% during the post-test (P = 0.003). Virtual adaptation of international exchange programs in medical education is feasible to safely continue international collaborative efforts to promote symbiotic building of local expertise and cross-cultural exchange during the ongoing COVID-19 pandemic and beyond.

Lessons for Oncology From the COVID-19 Pandemic: Operationalizing and Scaling Virtual Cancer Care in Health Systems

ABSTRACT

After several decades of slow expansion, the use of virtual care in oncology rapidly expanded during the COVID-19 pandemic. Data from cancer centers across the country show that most patients and providers were satisfied with components of virtual care, and virtual care may be able to improve access to care. However, the rapid implementation of programs during the pandemic worsened disparities in access to virtual care. Health systems must develop strategies to monitor quality, support patients and providers, promote health equity, and overcome regulatory challenges to successfully deliver care in hybrid systems that combine in-person and virtual care.

US primary care in 2029: A Delphi survey on the impact of machine learning

OBJECTIVE

To solicit leading health informaticians' predictions about the impact of AI/ML on primary care in the US in 2029.

DESIGN

A three-round online modified Delphi poll.

PARTICIPANTS

Twenty-nine leading health informaticians.

METHODS

In September 2019, health informatics experts were selected by the research team, and invited to participate the Delphi poll. Participation in each round was anonymous, and panelists were given between 4-8 weeks to respond to each round. In Round 1 open-ended questions solicited forecasts on the impact of AI/ML on: (1) patient care, (2) access to care, (3) the primary care workforce, (4) technological breakthroughs, and (5) the long-future for primary care physicians. Responses were coded to produce itemized statements. In Round 2, participants were invited to rate their agreement with each item along 7-point Likert scales. Responses were analyzed for consensus which was set at a predetermined interquartile range of ≤ 1. In Round 3 items that did not reach consensus were redistributed.

RESULTS

A total of 16 experts participated in Round 1 (16/29, 55%). Of these experts 13/16 (response rate, 81%), and 13/13 (response rate, 100%), responded to Rounds 2 and 3, respectively. As a result of developments in AI/ML by 2029 experts anticipated workplace changes including incursions into the disintermediation of physician expertise, and increased AI/ML training requirements for medical students. Informaticians also forecast that by 2029 AI/ML will increase diagnostic accuracy especially among those with limited access to experts, minorities and those with rare diseases. Expert panelists also predicted that AI/ML-tools would improve access to expert doctor knowledge.

CONCLUSIONS

This study presents timely information on informaticians' consensus views about the impact of AI/ML on US primary care in 2029. Preparation for the near-future of primary care will require improved levels of digital health literacy among patients and physicians.

Artificial intelligence and the future of psychiatry: Qualitative findings from a global physician survey

BACKGROUND

The potential for machine learning to disrupt the medical profession is the subject of ongoing debate within biomedical informatics.

OBJECTIVE

This study aimed to explore psychiatrists' opinions about the potential impact innovations in artificial intelligence and machine learning on psychiatric practice.

METHODS

In Spring 2019, we conducted a web-based survey of 791 psychiatrists from 22 countries worldwide. The survey measured opinions about the likelihood future technology would fully replace physicians in performing ten key psychiatric tasks. This study involved qualitative descriptive analysis of written responses ("comments") to three open-ended questions in the survey.

RESULTS

Comments were classified into four major categories in relation to the impact of future technology on: (1) patient-psychiatrist interactions; (2) the quality of patient medical care; (3) the profession of psychiatry; and (4) health systems. Overwhelmingly, psychiatrists were skeptical that technology could replace human empathy. Many predicted that 'man and machine' would increasingly collaborate in undertaking clinical decisions, with mixed opinions about the benefits and harms of such an arrangement. Participants were optimistic that technology might improve efficiencies and access to care, and reduce costs. Ethical and regulatory considerations received limited attention.

CONCLUSIONS

This study presents timely information on psychiatrists' views about the scope of artificial intelligence and machine learning on psychiatric practice. Psychiatrists expressed divergent views about the value and impact of future technology with worrying omissions about practice guidelines, and ethical and regulatory issues.

Continuous Monitoring Using a Wearable Device Detects Activity-Induced Heart Rate Changes After Administration of Amphetamine

Wearable digital devices offer potential advantages over traditional methods for the collection of health-related information, including continuous collection of dense data while study subjects are ambulatory or in remote settings. We assessed the utility of collecting continuous actigraphy and cardiac monitoring by deploying two US Food and Drug Administration (FDA) 510(k)-cleared devices in a phase I clinical trial of a novel compound, which included the use of an amphetamine challenge. The Phillips Actiwatch Spectrum Pro (Actiwatch) was used to assess mobility and sleep. The Preventice BodyGuardian (BodyGuardian) was used for monitoring heart rate (HR) and respiratory rate (RR), via single-lead electrocardiogram (ECG) recordings, together with physical activity. We measured data collection rates, compared device readouts with conventional measures, and monitored changes in HR measures during the amphetamine challenge. Completeness of data collection was good for the Actiwatch (96%) and lower for the BodyGuardian (80%). A good correlation was observed between device and in-clinic measures for HR (r = 0.99; P < 0.001), but was poor for RR (r = 0.39; P = 0.004). Manual reviews of selected ECG strips corresponding to HR measures below, within, and above the normal range were consistent with BodyGuardian measurements. The BodyGuardian device detected clear HR responses after amphetamine administration while subjects were physically active, whereas conventional measures collected at predefined timepoints while subjects were resting and supine did not. Wearable digital technology shows promise for monitoring human subjects for physiologic changes and pharmacologic responses, although fit-for-purpose evaluation and validation continues to be important prior to the wider deployment of these devices.

Why digital medicine depends on interoperability

Digital data are anticipated to transform medicine. However, most of today’s medical data lack interoperability: hidden in isolated databases, incompatible systems and proprietary software, the data are difficult to exchange, analyze, and interpret. This slows down medical progress, as technologies that rely on these data – artificial intelligence, big data or mobile applications – cannot be used to their full potential. In this article, we argue that interoperability is a prerequisite for the digital innovations envisioned for future medicine. We focus on four areas where interoperable data and IT systems are particularly important: (1) artificial intelligence and big data; (2) medical communication; (3) research; and (4) international cooperation. We discuss how interoperability can facilitate digital transformation in these areas to improve the health and well-being of patients worldwide.

Artificial Intelligence and the Future of Primary Care: Exploratory Qualitative Study of UK General Practitioners' Views

Background

The potential for machine learning to disrupt the medical profession is the subject of ongoing debate within biomedical informatics and related fields.

Objective

This study aimed to explore general practitioners’ (GPs’) opinions about the potential impact of future technology on key tasks in primary care.

Methods

In June 2018, we conducted a Web-based survey of 720 UK GPs’ opinions about the likelihood of future technology to fully replace GPs in performing 6 key primary care tasks, and, if respondents considered replacement for a particular task likely, to estimate how soon the technological capacity might emerge. This study involved qualitative descriptive analysis of written responses (“comments”) to an open-ended question in the survey.

Results

Comments were classified into 3 major categories in relation to primary care: (1) limitations of future technology, (2) potential benefits of future technology, and (3) social and ethical concerns. Perceived limitations included the beliefs that communication and empathy are exclusively human competencies; many GPs also considered clinical reasoning and the ability to provide value-based care as necessitating physicians’ judgments. Perceived benefits of technology included expectations about improved efficiencies, in particular with respect to the reduction of administrative burdens on physicians. Social and ethical concerns encompassed multiple, divergent themes including the need to train more doctors to overcome workforce shortfalls and misgivings about the acceptability of future technology to patients. However, some GPs believed that the failure to adopt technological innovations could incur harms to both patients and physicians.

Conclusions

This study presents timely information on physicians’ views about the scope of artificial intelligence (AI) in primary care. Overwhelmingly, GPs considered the potential of AI to be limited. These views differ from the predictions of biomedical informaticians. More extensive, stand-alone qualitative work would provide a more in-depth understanding of GPs’ views.

Semantic data interoperability, digital medicine, and e-health in infectious disease management: a review

Disease management requires the use of mixed languages when discussing etiology, diagnosis, treatment, and follow-up. All phases require data management, and, in the optimal case, such data are interdisciplinary and uniform and clear to all those involved. Such semantic data interoperability is one of the technical building blocks that support emerging digital medicine, e-health, and P4-medicine (predictive, preventive, personalized, and participatory). In a world where infectious diseases are on a trend to become hard-to-treat threats due to antimicrobial resistance, semantic data interoperability is part of the toolbox to fight more efficiently against those threats. In this review, we will introduce semantic data interoperability, summarize its added value, and analyze the technical foundation supporting the standardized healthcare system interoperability that will allow moving forward to e-health. We will also review current usage of those foundational standards and advocate for their uptake by all infectious disease-related actors.

Tracking health seeking behavior during an Ebola outbreak via mobile phones and SMS

The recent Ebola outbreak in West Africa was an exemplar for the need to rapidly measure population-level health-seeking behaviors, in order to understand healthcare utilization during emergency situations. Taking advantage of the high prevalence of mobile phones, we deployed a national SMS-poll and collected data about individual-level health and health-seeking behavior throughout the outbreak from 6694 individuals from March to June 2015 in Liberia. Using propensity score matching to generate balanced subsamples, we compared outcomes in our survey to those from a recent household survey (the 2013 Liberian Demographic Health Survey). We found that the matched subgroups had similar patterns of delivery location in aggregate, and utilizing data on the date of birth, we were able to show that facility-based deliveries were significantly decreased during, compared to after the outbreak (p < 0.05) consistent with findings from retrospective studies using healthcare-based data. Directly assessing behaviors from individuals via SMS also enabled the measurement of public and private sector facility utilization separately, which has been a challenge in other studies in countries including Liberia which rely mainly on government sources of data. In doing so, our data suggest that public facility-based deliveries returned to baseline values after the outbreak. Thus, we demonstrate that with the appropriate methodological approach to account for different population denominators, data sourced via mobile tools such as SMS polling could serve as an important low-cost complement to existing data collection strategies especially in situations where higher-frequency data than can be feasibly obtained through surveys is useful.