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BackgroundPatient engagement is the active collaboration between patient partners and health system partners towards a goal of making decisions that centre patient needs—thus improving experiences of care, and overall effectiveness of health services in alignment with the Quintuple Aim. An important but challenging aspect of patient engagement is including diverse perspectives particularly those experiencing health inequities. When such populations are excluded from decision-making in health policy, practice and research, we risk creating a healthcare ecosystem that reinforces structural marginalisation and perpetuates health inequities.ApproachDespite the growing body of literature on knowledge coproduction, few have addressed the role of power relations in patient engagement and offered actionable steps for engaging diverse patients in an inclusive way with a goal of improving health equity. To fill this knowledge gap, we draw on theoretical concepts of power, our own experience codesigning a novel model of patient engagement that is equity promoting, Equity Mobilizing Partnerships in Community, and extensive experience as patient partners engaged across the healthcare ecosystem. We introduce readers to a new conceptual tool, the Power Wheel, that can be used to analyse the interspersion of power in the places and spaces of patient engagement.ConclusionAs a tool for ongoing praxis (reflection +action), the Power Wheel can be used to report, reflect and resolve power asymmetries in patient-partnered projects, thereby increasing transparency and illuminating opportunities for equitable transformation and social inclusion so that health services can meet the needs and priorities of all people.

Introduction Health Equity Assessments (HEAs) are decision‐support frameworks or tools used to evaluate the equity impacts of policies, programmes and initiatives. However, HEAs are often conducted without meaningful engagement from the individuals and communities most affected by health inequities. This lack of social participation limits the relevance and effectiveness of HEAs, leaving systemic inequities unaddressed and opportunities for impactful change unrealized. An alternative is to involve people with diverse lived/living experiences in conducting and offering HEAs—so that people most impacted, and most excluded by decision‐making can offer recommendations to improve the way they access and utilise care. Methods Equity Mobilizing Partnerships in Community (EMPaCT) is a scalable, participatory citizen engagement model that integrates lived/living experiences into the HEA process. EMPaCT's Five Steps to a Community‐Engaged Health Equity Assessment (CEn‐HEA) was co‐designed with community members typically excluded from decision‐making. This process fosters psychological safety, trust‐building, and power‐sharing between underserved communities and decision‐makers. The CEn‐HEA systematically analyzes inequities across downstream (individual), midstream (community), and upstream (structural) levels to generate actionable, equity‐focused recommendations. Results The EMPaCT CEn‐HEA framework produces context‐specific recommendations that address immediate project needs while advancing long‐term, systemic change. The framework is a participatory process that centres community voices, builds trust, amplifies lived/living expertise, and fosters equity‐driven decision‐making that can lead to measurable improvements in healthcare policies, programmes, and practices. Conclusion In this paper, we examine the challenges and opportunities associated HEAs; introduce EMPaCT's CEn‐HEA framework as a co‐designed, innovative, and community‐engaged approach to health equity analysis; and discuss methods for measuring and evaluating the health equity impacts of these efforts. Patient or Public Contribution Patient and community involvement were central to the design, development and implementation of this project and resulting manuscript. Equity Mobilizing Partnerships in Community (EMPaCT), including its Community‐Engaged Health Equity Assessment (CEn‐HEA) framework, was co‐created with diverse patient partners who have lived/living experiences of health inequities. In the preparation of this manuscript, patient partners were involved in codesign sessions to define the focus, structure and language of the manuscript. They collaborated in discussions to refine key concepts, articulate challenges and highlight solutions that are grounded in their lived realities. In the preparation of this manuscript, patient partners reviewed early drafts, contributed feedback to ensure accessibility and relevance of the content and shaped the actionable recommendations. This manuscript reflects EMPaCT's commitment to justice, inclusion and meaningful change.

Introduction: In 2015, an integrated care and payment initiative (ICPI)—launched as the “Integrated Funding Model”—aimed at integrating care and payment across hospitals and homes to improve quality and decrease cost of care was piloted in Ontario. One of the main sources of cost containment for ICPIs is the shortened acute length of hospital stay due to early discharge. Unpaid care provided by friends and relatives is instrumental to success of such interventions. Increased reliance on informal caregivers, however, might contribute to known adverse health and financial consequences of caregiving making caregivers’ contributions to ICPIs unsustainable in the long run. Despite this, caregivers are often underrepresented in ICPI designs and evaluations. The purpose of this study was to develop an instrument (Caregiver Experience Survey [CES]) that measures the consequences of ICPI on caregivers.Methods: A multiphase study design was used to develop CES:1) Development of a questionnaire pool: Guided by a modified “Triple Aim” framework, grey and scoping literature reviews focusing on quantitative articles were conducted to identify common instruments used to measure caregivers’ health, experience, and costs. Findings were shared with key stakeholders (caregivers, patients, researchers, and policy makers) to gain first-hand knowledge on what should be measured from caregivers’ perspectives. A series of literature reviews were then conducted focusing on psychometric properties of identified instruments.2) Development of CES: Specific items or questionnaires were chosen in consultation with the research team; CES was then developed and revised in consultation with caregivers.3) Pilot sample and psychometric properties: To test the validity and reliability of CES, it is being administrated among a sample of ICPI caregivers.Results: CES has 58 items and 3 main domains (health, experience, and costs). EQ-5D-5L is used to measure caregivers’ health. The 4-item version of the Zarit Burden Interview is used to measure caregiving burden. Eighteen questions were adopted from a variety of questionnaires to measure caregivers’ experiences in and before leaving the hospital, and in the community. The cost section contains 21 items to measure the economic value of informal care, productivity loss, opportunity costs, and uses of healthcare and social services. Additionally, sociodemographic information is gathered (10 items).Discussion: CES is a generic survey that captures the entirety of a caregiver’s experience with ICPI allowing for a thorough investigation of its unintended impacts on caregivers. When the effects of ICPI are known, measures can be taken to provide caregivers with adequate support ensuring the sustainability of their contribution.Conclusion, Lessons Learned, Suggestions for Future Research: This study provides evidence that contributes to the design and evaluation of ICPIs. Lessons learned from stakeholder engagement resulted in identification of three main areas that require further investigation: caregivers’ healthcare utilization costs, changes in patients’ care utilization due to presence of caregivers, and the dyadic pattern of care for patients/caregivers.Limitations: Reviews were limited to electronic health sciences databases and quantitative studies; additionally, the scoping review was limited to Alzheimer/Dementia caregiving.Consequently, landmark instruments might have been missed in development of the questionnaire pool.

With the growing interest in using AI and machine learning (ML) in medicine, there is an increasing number of literature covering the application and ethics of using AI and ML in areas of medicine such as clinical psychiatry. The problem is that there is little literature covering the economic aspects associated with using ML in clinical psychiatry. This study addresses this gap by specifically studying the economic implications of using ML in clinical psychiatry. In this paper, we evaluate the economic implications of using ML in clinical psychiatry through using three problem-oriented case studies, literature on economics, socioeconomic and medical AI, and two types of health economic evaluations. In addition, we provide details on fairness, legal, ethics and other considerations for ML in clinical psychiatry.