Understanding pathways from implementation to sustainment: a longitudinal, mixed methods analysis of promising practices implemented in the Veterans Health Administration.

BACKGROUND: The Veterans Health Administration (VHA) is the United States largest learning health system. The Diffusion of Excellence (DoE) program is a large-scale model of diffusion that identifies and diffuses evidence-informed practices across VHA. During the period of 2016-2021, 57 evidence-informed practices were implemented across 82 VHA facilities. This setting provides a unique opportunity to understand sustainment determinants and pathways. Our objective was to characterize the longitudinal pathways of practices as they transition from initial implementation to long-term sustainment at each facility. METHODS: A longitudinal, mixed-methods evaluation of 82 VHA facilities. Eighty-two facility representatives, chosen by leadership as points-of-contact for 57 DoE practices, were eligible for post-implementation interviews and annual sustainment surveys. Primary outcomes (implementation, sustainment), and secondary outcomes (institutionalization, effectiveness, anticipated sustainment) at four time-points were collected. We performed descriptive statistics and directed content analysis using Hailemariam et al.'s factors influencing sustainment. RESULTS: After approximately five years post-implementation (e.g., 2021 sustainment outcomes), of the 82 facilities, about one-third fully sustained their practice compared to one-third that did not fully sustain their practice because it was in a "liminal" stage (neither sustained nor discontinued) or permanently discontinued. The remaining one-third of facilities had missing 2021 sustainment outcomes. A higher percentage of facilities (70%) had inconsistent primary outcomes (changing over time) compared to facilities (30%) with consistent primary outcomes (same over time). Thirty-four percent of facilities with sustained practices reported resilience since they overcame implementation and sustainment barriers. Facilities with sustained practices reported more positive secondary outcomes compared to those that did not sustain their practice. Key factors facilitating practice sustainment included: demonstrating practice effectiveness/benefit, sufficient organizational leadership, sufficient workforce, and adaptation/alignment with local context. Key factors hindering practice sustainment included: insufficient workforce, not able to maintain practice fidelity/integrity, critical incidents related to the COVID-19 pandemic, organizational leadership did not support sustainment of practice, and no ongoing support. CONCLUSIONS: We identified diverse pathways from implementation to sustainment, and our data underscore that initial implementation outcomes may not determine long-term sustainment outcomes. This longitudinal evaluation contributes to understanding impacts of the DoE program, including return on investment, achieving learning health system goals, and insights into achieving high-quality healthcare in VHA.

Building CapaCITY/É for sustainable transportation: protocol for an implementation science research program in healthy cities.

INTRODUCTION: Improving sustainable transportation options will help cities tackle growing challenges related to population health, congestion, climate change and inequity. Interventions supporting active transportation face many practical and political hurdles. Implementation science aims to understand how interventions or policies arise, how they can be translated to new contexts or scales and who benefits. Sustainable transportation interventions are complex, and existing implementation science frameworks may not be suitable. To apply and adapt implementation science for healthy cities, we have launched our mixed-methods research programme, CapaCITY/É. We aim to understand how, why and for whom sustainable transportation interventions are successful and when they are not. METHODS AND ANALYSIS: Across nine Canadian municipalities and the State of Victoria (Australia), our research will focus on two types of sustainable transportation interventions: all ages and abilities bicycle networks and motor vehicle speed management interventions. We will (1) document the implementation process and outcomes of both types of sustainable transportation interventions; (2) examine equity, health and mobility impacts of these interventions; (3) advance implementation science by developing a novel sustainable transportation implementation science framework and (4) develop tools for scaling up and scaling out sustainable transportation interventions. Training activities will develop interdisciplinary scholars and practitioners able to work at the nexus of academia and sustainable cities. ETHICS AND DISSEMINATION: This study received approval from the Simon Fraser University Office of Ethics Research (H22-03469). A Knowledge Mobilization Hub will coordinate dissemination of findings via a website; presentations to academic, community organisations and practitioner audiences; and through peer-reviewed articles.

Implementation Science to Achieve Equity in Heart Failure Care: A Scientific Statement From the American Heart Association.

Guideline-directed medical therapies and guideline-directed nonpharmacological therapies improve quality of life and survival in patients with heart failure (HF), but eligible patients, particularly women and individuals from underrepresented racial and ethnic groups, are often not treated with these therapies. Implementation science uses evidence-based theories and frameworks to identify strategies that facilitate uptake of evidence to improve health. In this scientific statement, we provide an overview of implementation trials in HF, assess their use of conceptual frameworks and health equity principles, and provide pragmatic guidance for equity in HF. Overall, behavioral nudges, multidisciplinary care, and digital health strategies increased uptake of therapies in HF effectively but did not include equity goals. Few HF studies focused on achieving equity in HF by engaging stakeholders, quantifying barriers and facilitators to HF therapies, developing strategies for equity informed by theory or frameworks, evaluating implementation measures for equity, and titrating strategies for equity. Among these HF equity studies, feasibility was established in using various educational strategies to promote organizational change and equitable care. A couple include ongoing randomized controlled pragmatic trials for HF equity. There is great need for additional HF implementation trials designed to promote delivery of equitable guideline-directed therapy.

Practice-Oriented Research: An Introduction to New Developments and Future Directions.

Aimed at understanding and improving psychological therapies as they are conducted in clinical routine, practice-oriented research (POR) is now a well-established approach to the scientific foundations of mental health care services. Resting on the accumulation of a wide range of practice-based evidence related to treatment outcome and process, as well as factors associated with the participants of psychotherapy and its context, POR is ripe for new developments - regarding what to investigate and how to investigate it. This paper is the introduction of a series devoted to recent advances and future directions of POR as their pertained to routine outcome monitoring, technologies and artificial intelligence, the integration of constructs and methods from program evaluation and implementation science, and the investigation of populations with limited financial resources across various regions of the world. The series also includes commentaries from two leaders of POR.

Effectiveness and Implementation of a Text Messaging mHealth Intervention to Prevent Childhood Obesity in Mexico in the COVID-19 Context: Mixed Methods Study.

BACKGROUND: Promoting physical activity (PA) and healthy feeding (HF) is crucial to address the alarming increase in obesity rates in developing countries. Leveraging mobile phones for behavior change communication to encourage infant PA and promote HF is particularly significant within the Mexican context. OBJECTIVE: This study aims to explore the effectiveness and feasibility of mHealth interventions aimed at promoting PA and HF among primary caregivers (PCs) of Mexican children under the age of 5 years. Additionally, the study aims to disseminate insights gained from intervention implementation amidst the COVID-19 pandemic and assess the potential of behavior change mHealth interventions on a broader population scale. METHODS: NUTRES, an mHealth intervention, underwent an effectiveness-implementation hybrid trial. Over 36 weeks, participants in the intervention group (IG), totaling 230 individuals, received approximately 108 SMS text messages tailored to their children's age. These messages covered topics such as PA and HF and emphasized the significance of proper child nutrition amidst the COVID-19 pandemic. NUTRES participants were recruited from both urban and rural health units across 2 states in Mexico. Given the COVID-19 context, both baseline and follow-up surveys were conducted via mobile or fixed telephone. The evaluation of effectiveness and implementation used a mixed methods approach. Qualitative analysis delved into participants' experiences with NUTRES and various implementation indicators, including acceptance, relevance, and coverage. Grounded theory was used for coding and analysis. Furthermore, difference-in-differences regression models were used to discern disparities between groups (comparison group [CG] versus IG) concerning knowledge and practices pertaining to infant PA and HF. RESULTS: Of the total 494 PCs enrolled in NUTRES, 334 persisted until the end of the study, accounting for 67.6% (334/494) participation across both groups. A majority of PCs (43/141, 30.5%, always; and 97/141, 68.8%, sometimes) used the SMS text message information. Satisfaction and acceptability toward NUTRES were notably high, reaching 98% (96/98), with respondents expressing that NUTRES was "good," "useful," and "helpful" for enhancing child nutrition. Significant differences after the intervention were observed in PA knowledge, with social interaction favored (CG: 8/135, 5.9% vs IG: 20/137, 14.6%; P=.048), as well as in HF practice knowledge. Notably, sweetened beverage consumption, associated with the development of chronic diseases, showed divergence (CG: 92/157, 58.6% vs IG: 110/145, 75.9%; P=.003). In the difference-in-differences model, a notable increase of 0.03 in knowledge regarding the benefits of PA was observed (CG: mean 0.13, SD 0.10 vs IG: mean 0.16, SD 0.11; P=.02). PCs expressed feeling accompanied and supported, particularly amidst the disruption of routine health care services during the COVID-19 pandemic. CONCLUSIONS: While NUTRES exhibited a restricted impact on targeted knowledge and behaviors, the SMS text messages functioned effectively as both a reminder and a source of new knowledge for PCs of Mexican children under 5 years of age. The key lessons learned were as follows: mHealth intervention strategies can effectively maintain communication with individuals during emergencies, such as the COVID-19 pandemic; methodological and implementation barriers can constrain the effectiveness of mHealth interventions; and using mixed methods approaches ensures the complementary nature of results. The findings contribute valuable evidence regarding the opportunities and constraints associated with using mobile phones to enhance knowledge and practices concerning PA and HF among PCs of children under 5 years old. TRIAL REGISTRATION: ClinicalTrials.gov NCT04250896; https://clinicaltrials.gov/ct2/show/NCT04250896.

Advancing Translation of Clinical Research Into Practice and Population Health Impact Through Implementation Science.

Translational and implementation sciences aim to prioritize and guide efforts to create greater efficiency and speed of scientific innovation across the translational science continuum to improve patient and population health. Key principles and practices rooted in translational and implementation science may be incorporated into clinical trials research, particularly pragmatic trials, to improve the relevance and impact of scientific innovation. This thematic review intends to raise awareness on the value of translational and implementation science in clinical research and to encourage its use in designing and implementing clinical trials across the translational research continuum. Herein, we describe the gap in translating research findings into clinical practice, introduce translational and implementation science, and describe the principles and practices from implementation science that can be used in clinical trial research across the translational continuum to inform clinical practice, to improve population health impact, and to address health care inequities.

How can a behavioral economics lens contribute to implementation science?

BACKGROUND: Implementation science in health is an interdisciplinary field with an emphasis on supporting behavior change required when clinicians and other actors implement evidence-based practices within organizational constraints. Behavioral economics has emerged in parallel and works towards developing realistic models of how humans behave and categorizes a wide range of features of choices that can influence behavior. We argue that implementation science can be enhanced by the incorporation of approaches from behavioral economics. Main body First, we provide a general overview of implementation science and ways in which implementation science has been limited to date. Second, we review principles of behavioral economics and describe how concepts from BE have been successfully applied to healthcare including nudges deployed in the electronic health record. For example, de-implementation of low-value prescribing has been supported by changing the default in the electronic health record. We then describe what a behavioral economics lens offers to existing implementation science theories, models and frameworks, including rich and realistic models of human behavior, additional research methods such as pre-mortems and behavioral design, and low-cost and scalable implementation strategies. We argue that insights from behavioral economics can guide the design of implementation strategies and the interpretation of implementation studies. Key objections to incorporating behavioral economics are addressed, including concerns about sustainment and at what level the strategies work. CONCLUSION: Scholars should consider augmenting implementation science theories, models, and frameworks with relevant insights from behavioral economics. By drawing on these additional insights, implementation scientists have the potential to boost efforts to expand the provision and availability of high quality care.

Patient and healthcare professional perspectives on the Practical Guide to Implementing PROMs in Gender-Affirming Care (PG-PROM-GAC): analysis of open-ended responses from patients and healthcare professionals.

IMPORTANCE: Several international calls have been made for evidence-based patient-reported outcome measure (PROM) implementation for gender-affirming care. The Practical Guide to Implementing PROMs in Gender-Affirming Care (PG-PROM-GAC) is a resource which can help guide PROM implementation efforts, developed using a three-phase participatory research approach with transgender and gender-diverse (TGD) patients and gender-affirming healthcare professionals. However, thoughts and perspectives from TGD patients and gender-affirming healthcare professionals on the PG-PROM-GAC need to be investigated. OBJECTIVE: Investigate patient and healthcare professional perspectives on the PG-PROM-GAC through analysis of open-ended survey results. DESIGN: Qualitative study analysing open-ended responses from TGD patients and gender-affirming healthcare professionals. SETTING: Participants were recruited from a UK National Health System (NHS) gender clinic. PARTICIPANTS: Patients receiving care at an NHS gender clinic and healthcare professionals working at an NHS gender clinic were eligible for participation. Eligible participants were invited to participate in this study via email. INTERVENTION: Participants were sent an open-ended survey to collect responses on the PG-PROM-GAC. MAIN OUTCOMES AND MEASURES: Data were thematically analysed by two independent researchers and interpreted following guidance from established methods in implementation science. RESULTS: A total of 64 TGD patients and 9 gender-affirming healthcare professionals responded to the open-ended survey (mean (SD) age: 35 (16) and 48 (8), respectively). Four main themes emerged from the data: overall opinions and support for the PG-PROM-GAC, presentation of the PG-PROM-GAC, impact of gender clinic resources on PROM implementation and impact of PROM selection on implementation. Data were used to iterate the PG-PROM-GAC in response to participant feedback. CONCLUSIONS AND RELEVANCE: The PG-PROM-GAC is an acceptable and feasible resource that can be used by clinicians, researchers and policymakers to guide PROM implementation for gender-affirming care settings, helping to align gender-affirming care with patient needs.

Leveraging Artificial Intelligence for Expediting Implementation Efforts.

Expedited implementation of evidence into practice and policymaking is critical to ensure the delivery of effective care and improve health-care outcomes. Implementation science deals with the designing of methods and strategies for increasing and facilitating the uptake of evidence into practice and policymaking. Nevertheless, the process of designing and selecting methods and strategies for implementing evidence is complicated because of the complexity of health-care settings where implementation is desired. Artificial intelligence (AI) has revolutionized a range of fields, including genomics, education, drug trials, research, and health care. This commentary discusses how AI can be leveraged to expedite implementation science efforts for transforming health-care practice. Four key aspects of AI use in implementation science are highlighted: (a) AI for implementation planning (e.g., needs assessment, predictive analytics, and data management), (b) AI for developing implementation tools and guidelines, (c) AI for designing and applying implementation strategies, and (d) AI for monitoring and evaluating implementation outcomes. Use of AI along the implementation continuum from planning to delivery and evaluation can enable more precise and accurate implementation of evidence into practice.

Implementation of a Clinical Vessel Wall MR Imaging Program at an Academic Medical Center.

BACKGROUND AND PURPOSE: The slow adoption of new advanced imaging techniques into clinical practice has been a long-standing challenge. Principles of implementation science and the reach, effectiveness, adoption, implementation, maintenance (RE-AIM) framework were used to build a clinical vessel wall imaging program at an academic medical center. MATERIALS AND METHODS: Six phases for implementing a clinical vessel wall MR imaging program were contextualized to the RE-AIM framework. Surveys were designed and distributed to MR imaging technologists and clinicians. Effectiveness was measured by surveying the perceived diagnostic value of vessel wall imaging among MR imaging technologists and clinicians, trends in case volumes in the clinical vessel wall imaging examination, and the number of coauthored vessel wall imaging-focused publications and abstracts. Adoption and implementation were measured by surveying stakeholders about workflow. Maintenance was measured by surveying MR imaging technologists on the value of teaching materials and online tip sheets. The Integration dimension was measured by the number of submitted research grants incorporating vessel wall imaging protocols. Feedback during the implementation phases and solicited through the survey is qualitatively summarized. Quantitative results are reported using descriptive statistics. RESULTS: Six phases of the RE-AIM framework focused on the following: 1) determining patient and disease representation, 2) matching resource availability and patient access, 3) establishing vessel MR wall imaging (VWI) expertise, 4) forming interdisciplinary teams, 5) iteratively refining workflow, and 6) integrating for maintenance and scale. Survey response rates were 48.3% (MR imaging technologists) and 71.4% (clinicians). Survey results showed that 90% of the MR imaging technologists agreed that they understood how vessel wall MR imaging adds diagnostic value to patient care. Most clinicians (91.3%) reported that vessel wall MR imaging results changed their diagnostic confidence or patient management. Case volumes of clinical vessel wall MR imaging performed from 2019 to 2022 rose from 22 to 205 examinations. Workflow challenges reported by MR imaging technologists included protocoling examinations and scan length. Feedback from ordering clinicians included the need for education about VWI indications, limitations, and availability. During the 3-year implementation period of the program, the interdisciplinary teams coauthored 27 publications and abstracts and submitted 13 research grants. CONCLUSIONS: Implementation of a clinical imaging program can be successful using the principles of the RE-AIM framework. Through iterative processes and the support of interdisciplinary teams, a vessel wall MR imaging program can be integrated through a dedicated clinical pipeline, add diagnostic value, support educational and research missions at an academic medical center, and become a center for excellence.

Navigating the field of implementation science towards maturity: challenges and opportunities.

BACKGROUND: The field of implementation science has significantly expanded in size and scope over the past two decades, although work related to understanding implementation processes have of course long preceded the more systematic efforts to improve integration of evidence-based interventions into practice settings. While this growth has had significant benefits to research, practice, and policy, there are some clear challenges that this period of adolescence has uncovered. MAIN BODY: This invited commentary reflects on the development of implementation science, its rapid growth, and milestones in its establishment as a viable component of the biomedical research enterprise. The authors reflect on progress in research and training, and then unpack some of the consequences of rapid growth, as the field has grappled with the competing challenges of legitimacy among the research community set against the necessary integration and engagement with practice and policy partners. The article then enumerates a set of principles for the field's next developmental stage and espouses the aspirational goal of a "big tent" to support the next generation of impactful science. CONCLUSION: For implementation science to expand its relevance and impact to practice and policy, researchers must not lose sight of the original purpose of the field-to support improvements in health and health care at scale, the importance of building a community of research and practice among key partners, and the balance of rigor, relevance, and societal benefit.

Improving acute myocardial infarction care in northern Tanzania: barrier identification and implementation strategy mapping.

BACKGROUND: Evidence-based care for acute myocardial infarction (AMI) reduces morbidity and mortality. Prior studies in Tanzania identified substantial gaps in the uptake of evidence-based AMI care. Implementation science has been used to improve uptake of evidence-based AMI care in high-income settings, but interventions to improve quality of AMI care have not been studied in sub-Saharan Africa. METHODS: Purposive sampling was used to recruit participants from key stakeholder groups (patients, providers, and healthcare administrators) in northern Tanzania. Semi-structured in-depth interviews were conducted using a guide informed by the Consolidated Framework for Implementation Research (CFIR). Interview transcripts were coded to identify barriers to AMI care, using the 39 CFIR constructs. Barriers relevant to emergency department (ED) AMI care were retained, and the Expert Recommendations for Implementing Change (ERIC) tool was used to match barriers with Level 1 recommendations for targeted implementation strategies. RESULTS: Thirty key stakeholders, including 10 patients, 10 providers, and 10 healthcare administrators were enrolled. Thematic analysis identified 11 barriers to ED-based AMI care: complexity of AMI care, cost of high-quality AMI care, local hospital culture, insufficient diagnostic and therapeutic resources, inadequate provider training, limited patient knowledge of AMI, need for formal implementation leaders, need for dedicated champions, failure to provide high-quality care, poor provider-patient communication, and inefficient ED systems. Seven of these barriers had 5 strong ERIC recommendations: access new funding, identify and prepare champions, conduct educational meetings, develop educational materials, and distribute educational materials. CONCLUSIONS: Multiple barriers across several domains limit the uptake of evidence-based AMI care in northern Tanzania. The CFIR-ERIC mapping approach identified several targeted implementation strategies for addressing these barriers. A multi-component intervention is planned to improve uptake of evidence-based AMI care in Tanzania.

Codesign of Lynch ChoicesTM : Using implementation science to create a clinically deliverable patient decision support website to transform cancer genetics care pathways.

BACKGROUND: Resources including Patient Decision Aids (PtDA) are useful and valued by patients and clinicians to provide information and complement shared decision-making. Despite their promise, few PtDA exist for patients with genetic cancer susceptibility facing difficult decisions about risk management. We aimed to fill this gap, partnering with patients to codesign Lynch ChoicesTM , a PtDA website for families with Lynch Syndrome. In addition to a Patient Reference Panel, we purposively invited an international stakeholder panel including charities, public bodies, clinical and academic experts. Implementation strategies and frameworks were employed to optimise translation of research findings to improve care. METHODS: Patient/stakeholder suggestions were incorporated in a transparent Table of Changes and prioritised using the Person-Based Approach throughout planning and codesign of Lynch ChoicesTM . An interactive stakeholder meeting was convened to identify barriers and facilitators to clinical implementation of the PtDA. RESULTS: Patient and stakeholder partnerships drove the direction of the research throughout codesign, resulting in several iterative refinements to the PtDA prior to roll out including the addition of illustrations/videos, clearer presentation of cancer risks and increased accessibility for lower literacy. Barriers and facilitators identified from stakeholders were used to create an implementation process map. CONCLUSIONS: Creating an effective, engaging PtDA is not enough. Systematic uptake in real world clinical practice, with its resource limitations, is needed to optimise benefit to patients and clinicians. Assessment of speed and breadth of dissemination and usage will be collected to further evidence the benefit of embedding implementation science methods from the outset to translate research findings into clinical practice.

Aligning organisational priorities and implementation science for cancer research.

BACKGROUND: The challenge of implementing evidence into routine clinical practice is well recognised and implementation science offers theories, models and frameworks to promote investigation into delivery of evidence-based care. Embedding implementation researchers into health systems is a novel approach to ensuring research is situated in day-to-day practice dilemmas. To optimise the value of embedded implementation researchers and resources, the aim of this study was to investigate stakeholders' views on opportunities for implementation science research in a cancer setting that holds potential to impact on care. The research objectives were to: 1) Establish stakeholder and theory informed organisation-level implementation science priorities and 2) Identify and prioritise a test case pilot implementation research project. METHODS: We undertook a qualitative study using semi-structured interviews. Participants held either a formal leadership role, were research active or a consumer advocate and affiliated with either a specialist cancer hospital or a cancer alliance of ten hospitals. Interview data were summarised and shared with participants prior to undertaking both thematic analysis, to identify priority areas for implementation research, and content analysis, to identify potential pilot implementation research projects. The selected pilot Implementation research project was prioritised using a synthesis of an organisational and implementation prioritisation framework - the organisational priority setting framework and APEASE framework. RESULTS: Thirty-one people participated between August 2022 and February 2023. Four themes were identified: 1) Integration of services to address organisational priorities e.g., tackling fragmented services; 2) Application of digital health interventions e.g., identifying the potential benefits of digital health interventions; 3) Identification of potential for implementation research, including deimplementation i.e., discontinuing ineffective or low value care and; 4) Focusing on direct patient engagement e.g., wider consumer awareness of the challenges in delivering cancer care. Six potential pilot implementation research projects were identified and the EMBED project, to support clinicians to refer appropriate patients with cancer for genetic testing, was selected using the synthesised prioritisation framework. CONCLUSIONS: Using a theory informed and structured approach the alignment between strategic organisational priorities and implementation research priorities can be identified. As a result, the implementation research focus can be placed on activities with the highest potential impact.

Generative AI in healthcare: an implementation science informed translational path on application, integration and governance.

BACKGROUND: Artificial intelligence (AI), particularly generative AI, has emerged as a transformative tool in healthcare, with the potential to revolutionize clinical decision-making and improve health outcomes. Generative AI, capable of generating new data such as text and images, holds promise in enhancing patient care, revolutionizing disease diagnosis and expanding treatment options. However, the utility and impact of generative AI in healthcare remain poorly understood, with concerns around ethical and medico-legal implications, integration into healthcare service delivery and workforce utilisation. Also, there is not a clear pathway to implement and integrate generative AI in healthcare delivery. METHODS: This article aims to provide a comprehensive overview of the use of generative AI in healthcare, focusing on the utility of the technology in healthcare and its translational application highlighting the need for careful planning, execution and management of expectations in adopting generative AI in clinical medicine. Key considerations include factors such as data privacy, security and the irreplaceable role of clinicians' expertise. Frameworks like the technology acceptance model (TAM) and the Non-Adoption, Abandonment, Scale-up, Spread and Sustainability (NASSS) model are considered to promote responsible integration. These frameworks allow anticipating and proactively addressing barriers to adoption, facilitating stakeholder participation and responsibly transitioning care systems to harness generative AI's potential. RESULTS: Generative AI has the potential to transform healthcare through automated systems, enhanced clinical decision-making and democratization of expertise with diagnostic support tools providing timely, personalized suggestions. Generative AI applications across billing, diagnosis, treatment and research can also make healthcare delivery more efficient, equitable and effective. However, integration of generative AI necessitates meticulous change management and risk mitigation strategies. Technological capabilities alone cannot shift complex care ecosystems overnight; rather, structured adoption programs grounded in implementation science are imperative. CONCLUSIONS: It is strongly argued in this article that generative AI can usher in tremendous healthcare progress, if introduced responsibly. Strategic adoption based on implementation science, incremental deployment and balanced messaging around opportunities versus limitations helps promote safe, ethical generative AI integration. Extensive real-world piloting and iteration aligned to clinical priorities should drive development. With conscientious governance centred on human wellbeing over technological novelty, generative AI can enhance accessibility, affordability and quality of care. As these models continue advancing rapidly, ongoing reassessment and transparent communication around their strengths and weaknesses remain vital to restoring trust, realizing positive potential and, most importantly, improving patient outcomes.