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Purpose: The purpose of this qualitative study is to demonstrate the use of patient-reported outcome measure-based journey maps in facilitating clinicians’ ability to communicate with patients about their well-being at each phase of their cancer journey. Methods: Individual semi-structured online and phone interviews were conducted with older adults in British Columbia, Canada. Participants (n = 6) were asked to describe their cancer experiences associated with their well-being score using the Edmonton Symptom Assessment System revised questionnaire throughout their cancer journey (i.e., pre-diagnosis, diagnosis, treatment, to post-treatment). Results: Six older adults who received cancer treatment were interviewed. Six journey maps were developed with evidence of fluctuation in participants’ level of well-being through their cancer journeys. Conclusion: Journey maps can facilitate patient-clinician communication for tailoring interventions and draw clinicians’ attention to additional prompts to better understand patients’ well-being throughout the cancer journey.

Objectif : L’objectif de la présente étude qualitative est de montrer que l’utilisation de cartes de parcours établies à partir des résultats rapportés par les patients facilite la communication entre les cliniciens et les patients lorsqu’il est question de bien-être, à toutes les étapes de l’expérience du cancer. Méthodologie : Des entrevues semi-structurées ont été menées en ligne et par téléphone auprès de 6 personnes âgées de la Colombie-Britannique, au Canada. Elles devaient décrire leur expérience du cancer et l’associer à un score de bien-être en utilisant le questionnaire révisé de l’échelle d’évaluation des symptômes d’Edmonton (revised Edmonton Symptom Assessment Scale ou ESAS-r) tout au long de la trajectoire des soins (pré-diagnostic, diagnostic, traitement, post-traitement). Résultats : En tout, 6 personnes âgées ayant reçu un traitement oncologique ont participé aux entrevues, et 6 cartes de parcours ont été créées; on y constate une fluctuation du niveau de bien-être pendant l’expérience du cancer. Conclusion : Les cartes de parcours facilitent la communication entre le patient et le clinicien, permettent d’adapter les interventions et attirent l’attention des cliniciens sur différents signes afin qu’ils comprennent mieux le bien-être des patients tout au long de l’expérience du cancer.

BackgroundIn recent years, there has been an upwelling of artificial intelligence (AI) studies in the health care literature. During this period, there has been an increasing number of proposed standards to evaluate the quality of health care AI studies. ObjectiveThis rapid umbrella review examines the use of AI quality standards in a sample of health care AI systematic review articles published over a 36-month period. MethodsWe used a modified version of the Joanna Briggs Institute umbrella review method. Our rapid approach was informed by the practical guide by Tricco and colleagues for conducting rapid reviews. Our search was focused on the MEDLINE database supplemented with Google Scholar. The inclusion criteria were English-language systematic reviews regardless of review type, with mention of AI and health in the abstract, published during a 36-month period. For the synthesis, we summarized the AI quality standards used and issues noted in these reviews drawing on a set of published health care AI standards, harmonized the terms used, and offered guidance to improve the quality of future health care AI studies. ResultsWe selected 33 review articles published between 2020 and 2022 in our synthesis. The reviews covered a wide range of objectives, topics, settings, designs, and results. Over 60 AI approaches across different domains were identified with varying levels of detail spanning different AI life cycle stages, making comparisons difficult. Health care AI quality standards were applied in only 39% (13/33) of the reviews and in 14% (25/178) of the original studies from the reviews examined, mostly to appraise their methodological or reporting quality. Only a handful mentioned the transparency, explainability, trustworthiness, ethics, and privacy aspects. A total of 23 AI quality standard–related issues were identified in the reviews. There was a recognized need to standardize the planning, conduct, and reporting of health care AI studies and address their broader societal, ethical, and regulatory implications. ConclusionsDespite the growing number of AI standards to assess the quality of health care AI studies, they are seldom applied in practice. With increasing desire to adopt AI in different health topics, domains, and settings, practitioners and researchers must stay abreast of and adapt to the evolving landscape of health care AI quality standards and apply these standards to improve the quality of their AI studies.

In 2021, Canada Health Infoway and the University of Victoria's Gender, Sex, and Sexual Orientation Research Team hosted a series of discussions to successfully and safely modernize gender, sex, and sexual orientation information practices within digital health systems. Five main topic areas were covered: (1) terminology standards; (2) digital health and electronic health record functions; (3) policy and practice implications; (4) primary care settings; and (5) acute and tertiary care settings. In this viewpoint paper, we provide priorities for future research and implementation projects and recommendations that emerged from these discussions.

Objectives To conceptualize new methods for integrating patient-centered measurement into team-based care. Methods A standalone portal was introduced into a rural clinic to support conceptualization of new methods for integration of patient-centered measurement in team-based care. The portal housed mental health-related online resources, three patient-reported measures and a self-action plan. Six providers and four patients used the portal for four months. Our data collection techniques included clinic discussions, one-on-one interviews, workflow diagrams and data generated through the portal. Analysis was supported through coding interview transcripts, looking across multiple sources of research data and research team discussions. Results Our research team conceptualized five team-based patient-centered measurement methods through this study. Patient-centered measurement Team Mapping offfers a technique to provide greater clarity of care-team roles and responsibilities in data collected through patient-centered measurement. Longitudinal Care Alignment can guide the care-team on incorporating patient-centered measurement into ongoing provider–patient interactions. Digital Tool Exploration can be used to evaluate a team's readiness toward digital tool adoption, and the impact of these tools. Team-based quality improvement serves as a framework for engaging teams in patient-centered quality improvement. Shared learning is a method that promotes patientprovider interactions that validate patient's perspectives of their care. Conclusion The portal illuminated new methods for the integration of patient-centered measurement in team-based care. The first three proposed patient-centered measurement methods provides ways to assess how a clinic can incorporate patient-centered measurement methods into team-based care. The latter two methods focus on the aim of patient-generated data in which patient's values and perspectives are represented and quality of patient-centered care can be evaluated. Further testing is needed to assess the utility of these patient-centered measurement methods across different clinical settings and domains.

BackgroundPatient-centered measurement (PCM) aims to improve the overall quality of care through the collection and sharing of patient values, outcomes, and perspectives. However, the use of PCM in care team decisions remains limited. Integrated knowledge translation (IKT) offers a collaborative, adaptive approach to explore best practices for incorporating PCM into primary care practices by involving knowledge users, including patients and providers, in the exploratory process. ObjectiveThis study aims to test the feasibility of using patient-generated data in team-based care; describe the use of these data for team-based mental health care; and summarize patient and provider care experiences with PCM. MethodsWe conducted a multi-method exploratory study in a rural team-based primary care clinic using IKT to co-design, implement, and evaluate the use of PCM in team-based mental health care. Care pathways, workflows, and quality improvement activities were adjusted iteratively to improve integration efforts. Patient and provider experiences were evaluated using individual interviews relating to the use of PCM and patient portals in practice. All meeting notes, interview summaries, and emails were analyzed to create a narrative evaluation. ResultsDuring co-design, a care workflow was developed to incorporate electronically collected patient-generated data from the patient portal into the electronic medical record, and customized educational tools and resources were added. During implementation, care pathways and patient workflows for PCM were developed. Patients found portal use easy, educational, and validating, but data entries were not used during care visits. Providers saw the portal as extra work, and the lack of portal and electronic medical record integration was a major barrier. The IKT approach was invaluable for addressing workflow changes and understanding the ongoing barriers to PCM use and quality improvement. ConclusionsAlthough the culture toward using PCM is changing, the use of PCM during care has not been successful. Patients felt validated and supported through portal use and could be empowered to bring these data to their visits. Training, modeling, and adaptable PCM methods are required before PCM can be integrated into routine care.

Abstract The presence of donor-specific antibodies (DSA) such as antibodies directed against donor class I human leucocyte antigen (e.g., HLA-A) is a major barrier to kidney transplant success. As a proof of concept, functionalized magnetic nanoparticles have been designed to eliminate DSA from saline, blood and plasma of healthy donors and sensitized patients. Specific HLA-A1 protein was covalently bound to functionalized cobalt nanoparticles (fNP), human serum albumin (HSA) as control. fNP were added to anti-HLA class I-spiked saline, spiked volunteers’ whole blood, and to whole blood and plasma of sensitized patients ex vivo. Anti-HLA-A1 antibody levels were determined with Luminex technology. Antibodies' median fluorescent intensity (MFI) was defined as the primary outcome. Furthermore, the impact of fNP treatment on blood coagulation and cellular uptake was determined. Treatment with fNP reduced MFI by 97 ± 2% and by 94 ± 4% (p