Best Practices for the Provision of Virtual Care: A Systematic Review of Current Guidelines

Virtual care in community pharmacy services: a scoping review

BACKGROUND

The integration of virtual care has been essential for maintaining continuity of patient care during and after the COVID-19 pandemic. Community pharmacists were among the healthcare professionals who used virtual care to provide remote pharmacy services. However, the use of virtual care in community pharmacy has not been comprehensively reviewed.

OBJECTIVE

To provide an overview of the types of virtual care platforms used in community pharmacy, their purposes, barriers, and facilitators, and to identify strategies for optimizing virtual care in this setting.

METHODS

The scoping review followed Joanna Briggs Institute (JBI) methodology for scoping reviews. A comprehensive search strategy was employed to identify studies across MEDLINE, Embase, CINAHL, Scopus, and grey literature sources. Two levels of screening were performed, and data were extracted using a pre-specified form. The data were analyzed through qualitative content analysis, and the PRISMA-ScR was used to report the results.

RESULTS

A total of 3580 citations were assessed and 32 studies were included in the review. The qualitative data were summarized into five categories: (1) virtual care tools and technologies used in community pharmacy, (2) purpose of virtual care, (3) barriers to using virtual care, (4) facilitators of virtual care adoption, and (5) strategies to optimize virtual care use.

CONCLUSION

Virtual care in community pharmacy showed promise in enhancing pharmacy services. Despite operational barriers and inequities in access, facilitators such as adequate training and technological advancements supported its implementation. Future efforts should address these challenges and refine virtual care for broader and equitable integration.

Establishing Best Practices in Telehealth Care for Adults with Developmental Disabilities in the United States: An e-Delphi Study

Background: Telehealth care is now a key element of mainstream health care since the COVID-19 pandemic, with all types of health care providers joining the digital revolution. As a population experiencing health care disparities, adults with developmental disabilities and their supporters have described variable experiences with telehealth care that contribute to overall care quality and health outcomes. Methods: This e-Delphi study established consensus on best practices in telehealth care for adults with developmental disabilities in the United States. Online surveys and videoconferencing interviews were conducted with 44 expert panelists with experience with telehealth care and developmental disabilities, including adults with developmental disabilities, family members, direct support professionals, nurses, and health care providers. Results: Three rounds of surveys resulted in a set of 9 guidelines consisting of 42 items. The guidelines addressed 1) appropriate situations for telehealth care, 2) communication needs and preferences, 3) support person collaboration, 4) education and anticipatory guidance, 5) reminders, 6) coordination of care, 7) equitable and fair access, 8) privacy and safety, and 9) evidence-based practice. Conclusion: Health care providers can adopt these best practice guidelines to ensure telehealth care is provided equitably and safely to adults with developmental disabilities. Policy advocacy is needed for the uptake of these guidelines and for health care providers and adults with developmental disabilities to access the resources needed for safe and effective telehealth care use.

Artificial Intelligence Supporting the Training of Communication Skills in the Education of Health Care Professions: Scoping Review

BACKGROUND

Communication is a crucial element of every health care profession, rendering communication skills training in all health care professions as being of great importance. Technological advances such as artificial intelligence (AI) and particularly machine learning (ML) may support this cause: it may provide students with an opportunity for easily accessible and readily available communication training.

OBJECTIVE

This scoping review aimed to summarize the status quo regarding the use of AI or ML in the acquisition of communication skills in academic health care professions.

METHODS

We conducted a comprehensive literature search across the PubMed, Scopus, Cochrane Library, Web of Science Core Collection, and CINAHL databases to identify articles that covered the use of AI or ML in communication skills training of undergraduate students pursuing health care profession education. Using an inductive approach, the included studies were organized into distinct categories. The specific characteristics of the studies, methods and techniques used by AI or ML applications, and main outcomes of the studies were evaluated. Furthermore, supporting and hindering factors in the use of AI and ML for communication skills training of health care professionals were outlined.

RESULTS

The titles and abstracts of 385 studies were identified, of which 29 (7.5%) underwent full-text review. Of the 29 studies, based on the inclusion and exclusion criteria, 12 (3.1%) were included. The studies were organized into 3 distinct categories: studies using AI and ML for text analysis and information extraction, studies using AI and ML and virtual reality, and studies using AI and ML and the simulation of virtual patients, each within the academic training of the communication skills of health care professionals. Within these thematic domains, AI was also used for the provision of feedback. The motivation of the involved agents played a major role in the implementation process. Reported barriers to the use of AI and ML in communication skills training revolved around the lack of authenticity and limited natural flow of language exhibited by the AI- and ML-based virtual patient systems. Furthermore, the use of educational AI- and ML-based systems in communication skills training for health care professionals is currently limited to only a few cases, topics, and clinical domains.

CONCLUSIONS

The use of AI and ML in communication skills training for health care professionals is clearly a growing and promising field with a potential to render training more cost-effective and less time-consuming. Furthermore, it may serve learners as an individualized and readily available exercise method. However, in most cases, the outlined applications and technical solutions are limited in terms of access, possible scenarios, the natural flow of a conversation, and authenticity. These issues still stand in the way of any widespread implementation ambitions.

i-CLIMATE: a "clinical climate informatics" action framework to reduce environmental pollution from healthcare

Addressing environmental pollution and climate change is one of the biggest sociotechnical challenges of our time. While information technology has led to improvements in healthcare, it has also contributed to increased energy usage, destructive natural resource extraction, piles of e-waste, and increased greenhouse gases. We introduce a framework "Information technology-enabled Clinical cLimate InforMAtics acTions for the Environment" (i-CLIMATE) to illustrate how clinical informatics can help reduce healthcare's environmental pollution and climate-related impacts using 5 actionable components: (1) create a circular economy for health IT, (2) reduce energy consumption through smarter use of health IT, (3) support more environmentally friendly decision-making by clinicians and health administrators, (4) mobilize healthcare workforce environmental stewardship through informatics, and (5) Inform policies and regulations for change. We define Clinical Climate Informatics as a field that applies data, information, and knowledge management principles to operationalize components of the i-CLIMATE Framework.