Artificial intelligence technologies and compassion in healthcare: A systematic scoping review.

Background: Advances in artificial intelligence (AI) technologies, together with the availability of big data in society, creates uncertainties about how these developments will affect healthcare systems worldwide. Compassion is essential for high-quality healthcare and research shows how prosocial caring behaviors benefit human health and societies. However, the possible association between AI technologies and compassion is under conceptualized and underexplored. Objectives: The aim of this scoping review is to provide a comprehensive depth and a balanced perspective of the emerging topic of AI technologies and compassion, to inform future research and practice. The review questions were: How is compassion discussed in relation to AI technologies in healthcare? How are AI technologies being used to enhance compassion in healthcare? What are the gaps in current knowledge and unexplored potential? What are the key areas where AI technologies could support compassion in healthcare? Materials and methods: A systematic scoping review following five steps of Joanna Briggs Institute methodology. Presentation of the scoping review conforms with PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews). Eligibility criteria were defined according to 3 concept constructs (AI technologies, compassion, healthcare) developed from the literature and informed by medical subject headings (MeSH) and key words for the electronic searches. Sources of evidence were Web of Science and PubMed databases, articles published in English language 2011-2022. Articles were screened by title/abstract using inclusion/exclusion criteria. Data extracted (author, date of publication, type of article, aim/context of healthcare, key relevant findings, country) was charted using data tables. Thematic analysis used an inductive-deductive approach to generate code categories from the review questions and the data. A multidisciplinary team assessed themes for resonance and relevance to research and practice. Results: Searches identified 3,124 articles. A total of 197 were included after screening. The number of articles has increased over 10 years (2011, n = 1 to 2021, n = 47 and from Jan-Aug 2022 n = 35 articles). Overarching themes related to the review questions were: (1) Developments and debates (7 themes) Concerns about AI ethics, healthcare jobs, and loss of empathy; Human-centered design of AI technologies for healthcare; Optimistic speculation AI technologies will address care gaps; Interrogation of what it means to be human and to care; Recognition of future potential for patient monitoring, virtual proximity, and access to healthcare; Calls for curricula development and healthcare professional education; Implementation of AI applications to enhance health and wellbeing of the healthcare workforce. (2) How AI technologies enhance compassion (10 themes) Empathetic awareness; Empathetic response and relational behavior; Communication skills; Health coaching; Therapeutic interventions; Moral development learning; Clinical knowledge and clinical assessment; Healthcare quality assessment; Therapeutic bond and therapeutic alliance; Providing health information and advice. (3) Gaps in knowledge (4 themes) Educational effectiveness of AI-assisted learning; Patient diversity and AI technologies; Implementation of AI technologies in education and practice settings; Safety and clinical effectiveness of AI technologies. (4) Key areas for development (3 themes) Enriching education, learning and clinical practice; Extending healing spaces; Enhancing healing relationships. Conclusion: There is an association between AI technologies and compassion in healthcare and interest in this association has grown internationally over the last decade. In a range of healthcare contexts, AI technologies are being used to enhance empathetic awareness; empathetic response and relational behavior; communication skills; health coaching; therapeutic interventions; moral development learning; clinical knowledge and clinical assessment; healthcare quality assessment; therapeutic bond and therapeutic alliance; and to provide health information and advice. The findings inform a reconceptualization of compassion as a human-AI system of intelligent caring comprising six elements: (1) Awareness of suffering (e.g., pain, distress, risk, disadvantage); (2) Understanding the suffering (significance, context, rights, responsibilities etc.); (3) Connecting with the suffering (e.g., verbal, physical, signs and symbols); (4) Making a judgment about the suffering (the need to act); (5) Responding with an intention to alleviate the suffering; (6) Attention to the effect and outcomes of the response. These elements can operate at an individual (human or machine) and collective systems level (healthcare organizations or systems) as a cyclical system to alleviate different types of suffering. New and novel approaches to human-AI intelligent caring could enrich education, learning, and clinical practice; extend healing spaces; and enhance healing relationships. Implications: In a complex adaptive system such as healthcare, human-AI intelligent caring will need to be implemented, not as an ideology, but through strategic choices, incentives, regulation, professional education, and training, as well as through joined up thinking about human-AI intelligent caring. Research funders can encourage research and development into the topic of AI technologies and compassion as a system of human-AI intelligent caring. Educators, technologists, and health professionals can inform themselves about the system of human-AI intelligent caring.

Haptic medicine.

The paper introduces haptic medicine--healthcare based on loving touch for healing and preventing disease. We describe the effects of loving touch (a square inch of our skin has over 1000 nerves) on the body, brain and mind. We describe two web-based health education and media projects. The first, HYPERLINK "http://www.21stcenturymed.org" www.21stcenturymed.org is a place for health practitioners to start learning about touch and resources. The second project, Humans Without Borders, is a multi-lingual self help education website for everyday people. Teaching materials for these projects are based on our previous work with a form of haptic medicine known as psychophysiophilosophy with patients at Stanford Hospital, Kaiser Permanente and Lucille Packard Children's Hospital. We describe psychophysiophilosophy, relate motherly love to recent discoveries in neurosciences and give hints on ways to increase motherly love in each of us. We present a plan for moving into the future by re-introducing haptic medicine into our daily lives through self-help and as an adjunct for current physician practice. There is an exercise in self-help for the reader and an appendix of recent clinical research with profound benefits on the use of human touch for over 40 conditions.

Application of Six Sigma/CAP methodology: controlling blood-product utilization and costs.

Blood-product components are a limited commodity whose cost is rising. Many patients benefit from their use, but patients who receive transfusions face an unnecessary increased risk for developing infections; fatal, febrile, or allergic reactions; and circulatory overload. To improve patient care, safety, and resource stewardship, transfusion practices must be evaluated for appropriateness (Wilson et al. 2002). A multihospital health system undertook a rigorous study of blood-product utilization patterns and management processes to address cost-control problems in the organization. The system leveraged two process improvement tools widely implemented outside of the healthcare industry: (1) Six Sigma methodology to identify blood-utilization drivers and to standardize transfusion practice, and (2) change acceleration process model to drive effective change. The initiative resulted in a decreased rate of inappropriate transfusions of packed red blood cell from 16 percent to less than 5 percent, improved clinician use of a blood-component order form, establishment of internal benchmarks, enhanced laboratory-to-clinician communication, and better blood-product expense control. The project further demonstrated how out-of-industry tools and methodologies can be adopted, adapted, and systematically applied to generate positive change (Black and Revere 2006).

Global medicine technology.

In little more than a decade, linkages between health care technologies of different cultures and continents have merged, resulting in global medicine technology. The next generation of young scientists and clinicians from both the research and clinical communities are merging established ancient technologies from outside the U.S. with modern medical technology and forging new ground in an increasingly challenging health care climate. Presently researchers, clinicians and communities are active in finding ways of using global medical technology to attack our most difficult and chronic (therefore expensive) health care problems. Using recent inventions, such as the fMRI, researchers and clinicians are understanding how and why they work. This chapter briefly discusses key ideas in the movement towards global medical technology: healthcare culture, mind-brain-body dialogue, and self-care including a self care exercise for the spine.

Intelligent agent software for medicine.

An important trend for the future of health technology will be the increasing use of intelligent agent software for medical applications. As the complexity of situations faced by both patients and health care providers grows, conventional interfaces that rely on users to manually transfer data and manually perform each problem-solving step, won't be able to keep up. This article describes how software agents that incorporate learning, personalization, proactivity, context-sensitivity and collaboration will lead to a new generation of medical applications that will streamline user interfaces and enable more sophisticated communication and problem-solving.