Performance Data Advocacy for Continuing Professional Development in Health Professions.

ABSTRACT: Efforts to optimize continuing professional development (CPD) are ongoing and include advocacy for the use of clinician performance data. Several educational and quality-based frameworks support the use of performance data to achieve intended improvement outcomes. Although intuitively appealing, the role of performance data for CPD has been uncertain and its utility mainly assumed. In this Scholarly Perspective, the authors briefly review and trace arguments that have led to the conclusion that performance data are essential for CPD. In addition, they summarize and synthesize a recent and ongoing research program exploring the relationship physicians have with performance data. They draw on Collins, Onwuegbuzie, and Johnson's legitimacy model and Dixon-Woods' integrative approach to generate inferences and ways of moving forward. This interpretive approach encourages questioning or raising of assumptions about related concepts and draws on the perspectives (i.e., interpretive work) of the research team to identify the most salient points to guide future work. The authors identify 6 stimuli for future programs of research intended to support broader and better integration of performance data for CPD. Their aims are to contribute to the discourse on data advocacy for CPD by linking conceptual, methodologic, and analytic processes and to stimulate discussion on how to proceed on the issue of performance data for CPD purposes. They hope to move the field from a discussion on the utility of data for CPD to deeper integration of relevant conceptual frameworks.

The Impact of Integrated Palliative Care on Survival in Idiopathic Pulmonary Fibrosis: A Retrospective Multicenter Comparison.

Background: Early and integrated palliative care is recommended for patients with idiopathic pulmonary fibrosis. Unfortunately, palliative care delivery remains poor due to various barriers in practice. This study describes various palliative care delivery models in a real-world cohort of patients with idiopathic pulmonary fibrosis, examines the predictors of survival in this cohort of patients, and explores the impact of palliative care on survival. Design: Charts were reviewed retrospectively and analyzed. The primary outcome was survival during a 4-year follow-up period. Two multivariable models were created to examine the impact of therapeutic strategies including palliative intervention on survival. Results: 298 patients with idiopathic pulmonary fibrosis were enrolled from 3 interstitial lung disease clinics with different palliative care models in Edmonton, Canada; Bristol, UK; and Kingston, Canada. 200 (67%) patients received palliative care and 119 (40%) died during follow up. Primary palliative care models (Edmonton and Bristol) delivered palliative care to 96% and 100% respectively compared 21% in the referral model (Queens). Palliative care [adjusted hazard ratio (aHR) .28 (.12-.65)] along with the use of antifibrotics [aHR .56 (.37-.84)], and body mass index >30 [aHR .47 (.37-.85)] reduced the risk of death in our idiopathic pulmonary fibrosis cohort. Opioid use was associated with worse survival [aHR 2.11 (1.30-23.43)]. Conclusions: Both palliative care and antifibrotic use were associated with survival benefit in this cohort of patients with idiopathic pulmonary fibrosis after adjusting for covariates. The benefit was seen despite differences in disease severity and different palliative care delivery models.

Paving the Way Forward for Evidence-Based Continuing Professional Development.

ABSTRACT: Continuing professional development (CPD) fosters lifelong learning and enables health care providers to keep their knowledge and skills current with rapidly evolving health care practices. Instructional methods promoting critical thinking and decision making contribute to effective CPD interventions. The delivery methods influence the uptake of content and the resulting changes in knowledge, skills, attitudes, and behavior. Educational approaches are needed to ensure that CPD meets the changing needs of health care providers. This article examines the development approach and key recommendations embedded in a CE Educator's toolkit created to evolve CPD practice and foster a learning experience that promotes self-awareness, self-reflection, competency, and behavioral change. The Knowledge-to-Action framework was used in designing the toolkit. The toolkit highlighted three intervention formats: facilitation of small group learning, case-based learning, and reflective learning. Strategies and guidelines to promote active learning principles in CPD activities within different modalities and learning contexts were included. The goal of the toolkit is to assist CPD providers to design educational activities that optimally support health care providers' self-reflection and knowledge translation into their clinical environment and contribute to practice improvement, thus achieving the outcomes of the quintuple aim.

The Adoption of AI in Mental Health Care-Perspectives From Mental Health Professionals: Qualitative Descriptive Study.

BACKGROUND: Artificial intelligence (AI) is transforming the mental health care environment. AI tools are increasingly accessed by clients and service users. Mental health professionals must be prepared not only to use AI but also to have conversations about it when delivering care. Despite the potential for AI to enable more efficient and reliable and higher-quality care delivery, there is a persistent gap among mental health professionals in the adoption of AI. OBJECTIVE: A needs assessment was conducted among mental health professionals to (1) understand the learning needs of the workforce and their attitudes toward AI and (2) inform the development of AI education curricula and knowledge translation products. METHODS: A qualitative descriptive approach was taken to explore the needs of mental health professionals regarding their adoption of AI through semistructured interviews. To reach maximum variation sampling, mental health professionals (eg, psychiatrists, mental health nurses, educators, scientists, and social workers) in various settings across Ontario (eg, urban and rural, public and private sector, and clinical and research) were recruited. RESULTS: A total of 20 individuals were recruited. Participants included practitioners (9/20, 45% social workers and 1/20, 5% mental health nurses), educator scientists (5/20, 25% with dual roles as professors/lecturers and researchers), and practitioner scientists (3/20, 15% with dual roles as researchers and psychiatrists and 2/20, 10% with dual roles as researchers and mental health nurses). Four major themes emerged: (1) fostering practice change and building self-efficacy to integrate AI into patient care; (2) promoting system-level change to accelerate the adoption of AI in mental health; (3) addressing the importance of organizational readiness as a catalyst for AI adoption; and (4) ensuring that mental health professionals have the education, knowledge, and skills to harness AI in optimizing patient care. CONCLUSIONS: AI technologies are starting to emerge in mental health care. Although many digital tools, web-based services, and mobile apps are designed using AI algorithms, mental health professionals have generally been slower in the adoption of AI. As indicated by this study's findings, the implications are 3-fold. At the individual level, digital professionals must see the value in digitally compassionate tools that retain a humanistic approach to care. For mental health professionals, resistance toward AI adoption must be acknowledged through educational initiatives to raise awareness about the relevance, practicality, and benefits of AI. At the organizational level, digital professionals and leaders must collaborate on governance and funding structures to promote employee buy-in. At the societal level, digital and mental health professionals should collaborate in the creation of formal AI training programs specific to mental health to address knowledge gaps. This study promotes the design of relevant and sustainable education programs to support the adoption of AI within the mental health care sphere.

Preparing for an Artificial Intelligence-Enabled Future: Patient Perspectives on Engagement and Health Care Professional Training for Adopting Artificial Intelligence Technologies in Health Care Settings.

BACKGROUND: As new technologies emerge, there is a significant shift in the way care is delivered on a global scale. Artificial intelligence (AI) technologies have been rapidly and inexorably used to optimize patient outcomes, reduce health system costs, improve workflow efficiency, and enhance population health. Despite the widespread adoption of AI technologies, the literature on patient engagement and their perspectives on how AI will affect clinical care is scarce. Minimal patient engagement can limit the optimization of these novel technologies and contribute to suboptimal use in care settings. OBJECTIVE: We aimed to explore patients' views on what skills they believe health care professionals should have in preparation for this AI-enabled future and how we can better engage patients when adopting and deploying AI technologies in health care settings. METHODS: Semistructured interviews were conducted from August 2020 to December 2021 with 12 individuals who were a patient in any Canadian health care setting. Interviews were conducted until thematic saturation occurred. A thematic analysis approach outlined by Braun and Clarke was used to inductively analyze the data and identify overarching themes. RESULTS: Among the 12 patients interviewed, 8 (67%) were from urban settings and 4 (33%) were from rural settings. A majority of the participants were very comfortable with technology (n=6, 50%) and somewhat familiar with AI (n=7, 58%). In total, 3 themes emerged: cultivating patients' trust, fostering patient engagement, and establishing data governance and validation of AI technologies. CONCLUSIONS: With the rapid surge of AI solutions, there is a critical need to understand patient values in advancing the quality of care and contributing to an equitable health system. Our study demonstrated that health care professionals play a synergetic role in the future of AI and digital technologies. Patient engagement is vital in addressing underlying health inequities and fostering an optimal care experience. Future research is warranted to understand and capture the diverse perspectives of patients with various racial, ethnic, and socioeconomic backgrounds.

Exploring Systemic Influences on Data-Informed Learning: Document Review of Policies, Procedures, and Legislation from Canada and the United States.

INTRODUCTION: Despite the support for and benefits of data-driven learning, physician engagement is variable. This study explores systemic influences of physician use of data for performance improvement in continuing professional development (CPD) by analyzing and interpreting data sources from organizational and institutional documents. METHODS: The document analysis is the third phase of a mixed-methods explanatory sequential study examining cultural factors that influence data-informed learning. A gray literature search was conducted for organizations both in Canada and the United States. The analysis contains nonparticipant observations from professional learning bodies and medical specialty organizations with established roles within the CPD community known to lead and influence change in CPD. RESULTS: Sixty-two documents were collected from 20 Canadian and American organizations. The content analysis identified the following: (1) a need to advocate for data-informed self-assessment and team-based learning strategies; (2) privacy and confidentiality concerns intersect at the point of patient data collection and physician-generated outcomes and need to be acknowledged; (3) a nuanced data strategy approach for each medical specialty is needed. DISCUSSION: This analysis broadens our understanding of system-level factors that influence the extent to which health information custodians and physicians are motivated to engage with data for learning.

Action plans in idiopathic pulmonary fibrosis: a qualitative study-'I do what I can do'.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive, incurable fibrotic lung disease in which patients and caregivers report a high symptom burden. Symptoms are often poorly managed and patients and caregivers struggle to alleviate their distress in the absence of self-management support. AIM: To explore perceptions of symptoms, symptom management strategies and self-efficacy for patients with IPF and caregivers who received self-management education and action plans created and provided in a Multidisciplinary Collaborative Interstitial Lung Disease (MDC-ILD) Clinic. DESIGN: A qualitative study was conducted with participants recruited from the MDC-ILD Clinic. Participants received an early integrated palliative approach; most attended ILD pulmonary rehabilitation and some received home care support. Semistructured interviews were conducted. Patient participants completed Measure Yourself Medical Outcome Profile (MYMOP) for symptom assessment and Chronic Obstructive Pulmonary Disease Self-Efficacy Scale to assess self-management efficacy. RESULTS: Thirteen patients and eight self-declared caregiver participants were interviewed. IPF severity ranged from mild to advanced disease. Participants integrated and personalised self-management strategies. They were intentional and confident, focused on living well and engaged in anticipatory planning. Twelve participants completed the MYMOP. Five reported dyspnoea. Four reported fatigue as an additional or only symptom. One reported cough. Five declared no dyspnoea, cough or fatigue. Participants reported 80% self-efficacy in symptom management. CONCLUSIONS: The approach to symptom self-management and education was beneficial to patients with IPF and caregiver participants. Participants personalised the strategies, focusing on living, and planned both in the moment and for the future. They were confident and expressed dignity and meaning in their lives.

Artificial Intelligence Education Programs for Health Care Professionals: Scoping Review.

BACKGROUND: As the adoption of artificial intelligence (AI) in health care increases, it will become increasingly crucial to involve health care professionals (HCPs) in developing, validating, and implementing AI-enabled technologies. However, because of a lack of AI literacy, most HCPs are not adequately prepared for this revolution. This is a significant barrier to adopting and implementing AI that will affect patients. In addition, the limited existing AI education programs face barriers to development and implementation at various levels of medical education. OBJECTIVE: With a view to informing future AI education programs for HCPs, this scoping review aims to provide an overview of the types of current or past AI education programs that pertains to the programs' curricular content, modes of delivery, critical implementation factors for education delivery, and outcomes used to assess the programs' effectiveness. METHODS: After the creation of a search strategy and keyword searches, a 2-stage screening process was conducted by 2 independent reviewers to determine study eligibility. When consensus was not reached, the conflict was resolved by consulting a third reviewer. This process consisted of a title and abstract scan and a full-text review. The articles were included if they discussed an actual training program or educational intervention, or a potential training program or educational intervention and the desired content to be covered, focused on AI, and were designed or intended for HCPs (at any stage of their career). RESULTS: Of the 10,094 unique citations scanned, 41 (0.41%) studies relevant to our eligibility criteria were identified. Among the 41 included studies, 10 (24%) described 13 unique programs and 31 (76%) discussed recommended curricular content. The curricular content of the unique programs ranged from AI use, AI interpretation, and cultivating skills to explain results derived from AI algorithms. The curricular topics were categorized into three main domains: cognitive, psychomotor, and affective. CONCLUSIONS: This review provides an overview of the current landscape of AI in medical education and highlights the skills and competencies required by HCPs to effectively use AI in enhancing the quality of care and optimizing patient outcomes. Future education efforts should focus on the development of regulatory strategies, a multidisciplinary approach to curriculum redesign, a competency-based curriculum, and patient-clinician interaction.

Accelerating the Appropriate Adoption of Artificial Intelligence in Health Care: Protocol for a Multistepped Approach.

BACKGROUND: Significant investments and advances in health care technologies and practices have created a need for digital and data-literate health care providers. Artificial intelligence (AI) algorithms transform the analysis, diagnosis, and treatment of medical conditions. Complex and massive data sets are informing significant health care decisions and clinical practices. The ability to read, manage, and interpret large data sets to provide data-driven care and to protect patient privacy are increasingly critical skills for today's health care providers. OBJECTIVE: The aim of this study is to accelerate the appropriate adoption of data-driven and AI-enhanced care by focusing on the mindsets, skillsets, and toolsets of point-of-care health providers and their leaders in the health system. METHODS: To accelerate the adoption of AI and the need for organizational change at a national level, our multistepped approach includes creating awareness and capacity building, learning through innovation and adoption, developing appropriate and strategic partnerships, and building effective knowledge exchange initiatives. Education interventions designed to adapt knowledge to the local context and address any challenges to knowledge use include engagement activities to increase awareness, educational curricula for health care providers and leaders, and the development of a coaching and practice-based innovation hub. Framed by the Knowledge-to-Action framework, we are currently in the knowledge creation stage to inform the curricula for each deliverable. An environmental scan and scoping review were conducted to understand the current state of AI education programs as reported in the academic literature. RESULTS: The environmental scan identified 24 AI-accredited programs specific to health providers, of which 11 were from the United States, 6 from Canada, 4 from the United Kingdom, and 3 from Asian countries. The most common curriculum topics across the environmental scan and scoping review included AI fundamentals, applications of AI, applied machine learning in health care, ethics, data science, and challenges to and opportunities for using AI. CONCLUSIONS: Technologies are advancing more rapidly than organizations, and professionals can adopt and adapt to them. To help shape AI practices, health care providers must have the skills and abilities to initiate change and shape the future of their discipline and practices for advancing high-quality care within the digital ecosystem. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/30940.

Health Care Costs at the End of Life for Patients with Idiopathic Pulmonary Fibrosis. Evaluation of a Pilot Multidisciplinary Collaborative Interstitial Lung Disease Clinic.

Rationale: Even though idiopathic pulmonary fibrosis (IPF) is a disease with high morbidity and mortality and no cure, palliative care is rarely implemented, leading to high symptom burden and unmet care needs. In 2012, we implemented a multidisciplinary collaborative (MDC) care model linking clinic and community multidisciplinary teams to provide an early integrated palliative approach, focusing on early symptom management and advance care planning.Objectives: To evaluate the differences in resource use and associated costs of end-of-life care between patients with IPF who received early integrated palliative care and patients with IPF who received conventional treatment.Methods: Using administrative health data, we identified all patients in the Province of Alberta, Canada, who presented to a hospital with an IPF diagnosis between January 1, 2012, and December 31, 2018, and died within this time frame. We compared three groups of patients: those who received MDC care (our clinic patients), specialist care (SC; respirologist), or non-specialist care (NSC; no contact with a respiratory clinic). The primary outcomes were healthcare resource use and costs in the year before death.Results: Of 2,768 patients across the three study groups, in the last year of life, MDC patients were more than three times as likely as SC patients to have received antifibrotic therapies (odds ratio [OR], 3.0; 95% confidence interval [CI], 1.8-5.2), almost twice as likely to have received pulmonary rehabilitation (OR, 1.9; 95% CI, 1.1-3.4), and 36% more likely to have received opiates (OR, 1.4; 95% CI, 0.8-2.3). The median total healthcare costs in the last 3 months of life were approximately C$7,700 lower for MDC patients than for those receiving SC, driven primarily by fewer hospitalizations and emergency department visits. MDC patients were also less likely to die in the hospital (44.9% MDC vs. 64.9% SC vs. 66.8% NSC; P < 0.001) and had the highest rates of no hospitalization in the last year of life.Conclusions: An integrated palliative approach in IPF is associated with improvements in the quality of end-of-life care and reduction in costs. Transformation of care models is required to deliver palliative care for patients with IPF. MDC teams within such models can address the high burden of unmet needs for symptom management, advance care planning, and community support in this complex population.

Optimizing Licensed Practical Nurses in Home Care: Their Role, Scope and Opportunities.

This research examined the role and scope of licensed practical nurses (LPNs) in home care (HC) and case management. Case management is relatively new to LPNs in Alberta having been added to their list of competencies in 2015. The extent to which LPNs are performing functions and the circumstances or criteria that shape their reported case management functions and role are not clear. Our research questions were: a) What roles do LPNs play within HC and case management? and b) What roles could LPNs play within HC and case management given their scope of practice to achieve optimal client outcomes and system efficiencies? We used a mixed methods multiple case study design to engage LPNs in case management practice, their managers and HC leaders from rural, urban and suburban HC offices. Approaches for data collection included semi-structured interviews, participant observation, focus groups, document review and survey.