Evaluation of the Rosa Chatbot Providing Genetic Information to Patients at Risk of Hereditary Breast and Ovarian Cancer: Qualitative Interview Study

Allies not enemies-creating a more empathetic and uplifting patient experience through technology and art

OBJECTIVE

To understand whether art and technology (mainly conversational agents) may help oncology patients to experience a more humanized journey.

METHODS

This narrative review encompasses a comprehensive examination of the existing literature in this field by a multicenter, multidisciplinary, and multiprofessional team aiming to analyze the current developments and potential future directions of using art and technology for patient engagement.

RESULTS

We identified three major themes of patient engagement with art and three major themes of patient engagement with technologies. Two real-case scenarios are reported from our experience to practically envision how findings from the literature can be implemented in different contexts.

CONCLUSION

Art therapy and technologies can be ancillary supports for healthcare professionals but are not substitutive of their expertise and responsibilities. Such tools may help to convey a more empathetic and uplifting patient journey if properly integrated within clinical practice, whereby the humanistic touch of medicine remains pivotal.

Uptake of Cancer Genetic Services for Chatbot vs Standard-of-Care Delivery Models: The BRIDGE Randomized Clinical Trial

Importance

Increasing numbers of unaffected individuals could benefit from genetic evaluation for inherited cancer susceptibility. Automated conversational agents (ie, chatbots) are being developed for cancer genetics contexts; however, randomized comparisons with standard of care (SOC) are needed.

Objective

To examine whether chatbot and SOC approaches are equivalent in completion of pretest cancer genetic services and genetic testing.

Design, Setting, and Participants

This equivalence trial (Broadening the Reach, Impact, and Delivery of Genetic Services [BRIDGE] randomized clinical trial) was conducted between August 15, 2020, and August 31, 2023, at 2 US health care systems (University of Utah Health and NYU Langone Health). Participants were aged 25 to 60 years, had had a primary care visit in the previous 3 years, were eligible for cancer genetic evaluation, were English or Spanish speaking, had no prior cancer diagnosis other than nonmelanoma skin cancer, had no prior cancer genetic counseling or testing, and had an electronic patient portal account.

Intervention

Participants were randomized 1:1 at the patient level to the study groups at each site. In the chatbot intervention group, patients were invited in a patient portal outreach message to complete a pretest genetics education chat. In the enhanced SOC control group, patients were invited to complete an SOC pretest appointment with a certified genetic counselor.

Main Outcomes and Measures

Primary outcomes were completion of pretest cancer genetic services (ie, pretest genetics education chat or pretest genetic counseling appointment) and completion of genetic testing. Equivalence hypothesis testing was used to compare the study groups.

Results

This study included 3073 patients (1554 in the chatbot group and 1519 in the enhanced SOC control group). Their mean (SD) age at outreach was 43.8 (9.9) years, and most (2233 of 3063 [72.9%]) were women. A total of 204 patients (7.3%) were Black, 317 (11.4%) were Latinx, and 2094 (75.0%) were White. The estimated percentage point difference for completion of pretest cancer genetic services between groups was 2.0 (95% CI, -1.1 to 5.0). The estimated percentage point difference for completion of genetic testing was -1.3 (95% CI, -3.7 to 1.1). Analyses suggested equivalence in the primary outcomes.

Conclusions and Relevance

The findings of the BRIDGE equivalence trial support the use of chatbot approaches to offer cancer genetic services. Chatbot tools can be a key component of sustainable and scalable population health management strategies to enhance access to cancer genetic services.

Trial Registration

ClinicalTrials.gov Identifier: NCT03985852.

The impact and future of artificial intelligence in medical genetics and molecular medicine: an ongoing revolution

Artificial intelligence (AI) platforms have emerged as pivotal tools in genetics and molecular medicine, as in many other fields. The growth in patient data, identification of new diseases and phenotypes, discovery of new intracellular pathways, availability of greater sets of omics data, and the need to continuously analyse them have led to the development of new AI platforms. AI continues to weave its way into the fabric of genetics with the potential to unlock new discoveries and enhance patient care. This technology is setting the stage for breakthroughs across various domains, including dysmorphology, rare hereditary diseases, cancers, clinical microbiomics, the investigation of zoonotic diseases, omics studies in all medical disciplines. AI's role in facilitating a deeper understanding of these areas heralds a new era of personalised medicine, where treatments and diagnoses are tailored to the individual's molecular features, offering a more precise approach to combating genetic or acquired disorders. The significance of these AI platforms is growing as they assist healthcare professionals in the diagnostic and treatment processes, marking a pivotal shift towards more informed, efficient, and effective medical practice. In this review, we will explore the range of AI tools available and show how they have become vital in various sectors of genomic research supporting clinical decisions.

Roles, Users, Benefits, and Limitations of Chatbots in Health Care: Rapid Review

BACKGROUND

Chatbots, or conversational agents, have emerged as significant tools in health care, driven by advancements in artificial intelligence and digital technology. These programs are designed to simulate human conversations, addressing various health care needs. However, no comprehensive synthesis of health care chatbots' roles, users, benefits, and limitations is available to inform future research and application in the field.

OBJECTIVE

This review aims to describe health care chatbots' characteristics, focusing on their diverse roles in the health care pathway, user groups, benefits, and limitations.

METHODS

A rapid review of published literature from 2017 to 2023 was performed with a search strategy developed in collaboration with a health sciences librarian and implemented in the MEDLINE and Embase databases. Primary research studies reporting on chatbot roles or benefits in health care were included. Two reviewers dual-screened the search results. Extracted data on chatbot roles, users, benefits, and limitations were subjected to content analysis.

RESULTS

The review categorized chatbot roles into 2 themes: delivery of remote health services, including patient support, care management, education, skills building, and health behavior promotion, and provision of administrative assistance to health care providers. User groups spanned across patients with chronic conditions as well as patients with cancer; individuals focused on lifestyle improvements; and various demographic groups such as women, families, and older adults. Professionals and students in health care also emerged as significant users, alongside groups seeking mental health support, behavioral change, and educational enhancement. The benefits of health care chatbots were also classified into 2 themes: improvement of health care quality and efficiency and cost-effectiveness in health care delivery. The identified limitations encompassed ethical challenges, medicolegal and safety concerns, technical difficulties, user experience issues, and societal and economic impacts.

CONCLUSIONS

Health care chatbots offer a wide spectrum of applications, potentially impacting various aspects of health care. While they are promising tools for improving health care efficiency and quality, their integration into the health care system must be approached with consideration of their limitations to ensure optimal, safe, and equitable use.

Patients' perceptions and practices of informing relatives: a qualitative study within a randomised trial on healthcare-assisted risk disclosure

In a multicentre randomised controlled trial (DIRECT), we evaluate whether an intervention of providing direct letters from healthcare professionals to at-risk relatives (ARRs) affects the proportion of ARRs contacting a cancer genetics clinic, compared with patient-mediated disclosure alone (control). With the aim to explore how the patients included in the trial perceived and performed risk communication with their ARRs we analysed 17 semi-structured interviews with reflexive thematic analysis. All patients described that they disclosed risk information to all close relatives themselves. No integrity-related issues were reported by patients offered the intervention, and all of them accepted direct letters to all their ARRs. Patients' approaches to informing distant relatives were unpredictable and varied from contacting all distant ARRs, sharing the burden with the family, utilising the offer of sending direct letters, vaguely relying on others to inform, or postponing disclosure. Most patients limited their responsibility to the disclosure, although others wanted relatives to get genetic counselling or felt a need to provide additional information to the ARRs before ending their mission. We also identified confusion about the implication of test results, who needed risk information, and who was responsible for informing ARRs. These misunderstandings possibly also affected risk disclosure. This study revealed that despite accepting the direct letters to be sent to all relatives, the patients also contributed to risk disclosure in other ways. It was only in some situations to distant relatives that the healthcare-assisted letter was the only means of communication to the ARRs.