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PURPOSE Information about social determinants of health (SDOH) is essential for primary care clinicians in the delivery of equitable, comprehensive care, as well as for program planning and resource allocation. SDOH are rarely captured consistently in clinical settings, however. Artificial intelligence (AI) could potentially fill these data gaps, but it needs to be designed collaboratively and thoughtfully. We report on a codesign process with primary care clinicians to understand how an AI tool could be developed, implemented, and used in practice. METHODS We conducted semistructured, 50-minute workshops with a large urban family health team in Toronto, Ontario, Canada asking their feedback on a proposed AI- based tool used to derive patient SDOH from electronic health record data. An inductive thematic analysis was used to describe participants' perspectives regarding the implementation and use of the proposed tool. RESULTS Fifteen participants contributed across 4 workshops. Most patient SDOH information was not available or was difficult to find in their electronic health record. Discussions focused on 3 areas related to the implementation and use of an AI tool to derive social data: people, process, and technology. Participants recommended starting with 1 or 2 social determinants (income and housing were suggested as priorities) and emphasized the need for adequate resources, staff, and training materials. They noted many challenges, including how to discuss the use of AI with patients and how to confirm their social needs identified by the AI tool. CONCLUSIONS Our codesign experience provides guidance from end users on the appropriate and meaningful design and implementation of an AI-based tool for social data in primary care. Key words: primary care; artificial intelligence; codesign; qualitative methods; social factors in health and health care; practice-based research; vulnerable populations https://doi.org/10.1370/afm.3117, INTRODUCTION Artificial intelligence (AI) has increasingly become part of our society, including in health care. The use of AI in primary care, in particular, has the potential for widespread impact [...]

PURPOSE Precarious employment, defined by temporary contracts, unstable employment, or job insecurity, is increasingly common and is associated with inconsistent access to benefits, lower income, and greater exposure to physical and psycholosocial hazards. Clinicians can benefit from a simple approach to screen for precarious employment to improve their understanding of a patient's social context, help with diagnoses, and inform treatment plans and intersectional interventions. Our objective was to validate a screening tool for precarious employment. METHODS We used a 3-item screening tool that covered key aspects of precarious employment: non-standard employment, variable income, and violations of occupational health and safety rights and protections. Answers were compared with classification using the Poverty and Employment Precarity in Southern Ontario Employment Index. Participants were aged 18 years and older, fluent in English, and employed. They were recruited in 7 primary care clinic waiting rooms in Toronto, Canada over 12 months. RESULTS A total of 204 people aged 18-72 years (mean 38 [SD 11.3]) participated, of which 93 (45.6%) identified as men and 119 (58.3%) self-reported as White. Participants who reported 2 or more of the 3 items as positive were almost 4 times more likely to be precariously employed (positive likelihood ratio = 3.84 [95% CI, 2.15-6.80]). CONCLUSIONS A 3-item screening tool can help identify precarious employment. Our tool is useful for starting a conversation about employment precarity and work conditions in clinical settings. Implementation of this screening tool in health settings could enable better targeting of resources for managing care and connecting patients to legal and employment support services. Key words: employment; health inequities; primary care; screening; social determinants of health, INTRODUCTION Employment is a key social determinant of health, impacting income, access to basic necessities, and social status. (1) Employment typically determines a person's income, ability to afford necessities, and [...]

BackgroundWith large volumes of longitudinal data in electronic medical records from diverse patients, primary care is primed for disruption by artificial intelligence (AI) technology. With AI applications in primary care still at an early stage in Canada and most countries, there is a unique opportunity to engage key stakeholders in exploring how AI would be used and what implementation would look like.ObjectiveTo identify the barriers that patients, providers, and health leaders perceive in relation to implementing AI in primary care and strategies to overcome them.Design12 virtual deliberative dialogues. Dialogue data were thematically analyzed using a combination of rapid ethnographic assessment and interpretive description techniques.SettingVirtual sessions.ParticipantsParticipants from eight provinces in Canada, including 22 primary care service users, 21 interprofessional providers, and 5 health system leaders.ResultsThe barriers that emerged from the deliberative dialogue sessions were grouped into four themes: (1) system and data readiness, (2) the potential for bias and inequity, (3) the regulation of AI and big data, and (4) the importance of people as technology enablers. Strategies to overcome the barriers in each of these themes were highlighted, where participatory co-design and iterative implementation were voiced most strongly by participants.LimitationsOnly five health system leaders were included in the study and no self-identifying Indigenous people. This is a limitation as both groups may have provided unique perspectives to the study objective.ConclusionsThese findings provide insight into the barriers and facilitators associated with implementing AI in primary care settings from different perspectives. This will be vital as decisions regarding the future of AI in this space is shaped.

PURPOSE The Coronavirus disease 2019 (COVID-19) pandemic is an unprecedented global public health crisis. Mass vaccination is the safest and fastest pandemic exit strategy. Mass vaccination clinics are a particularly important tool in quickly achieving herd immunity. Primary care physicians have played a crucial role in organizing and running vaccination clinics. In this special report, we synthesize existing guidelines and peer-reviewed studies to provide physicians with practical guidance on planning and implementing COVID-19 mass vaccination clinics. METHODS PubMed, Ovid MEDLINE and Embase were used to search for relevant literature using search terms that included COVID-19, mass vaccination, and best practice. We also identified and analyzed national and international guidelines. RESULTS Forty-six relevant articles, reports, and guidelines were identified and synthesized. Articles included mass vaccination clinic guidelines and studies before and during the COVID-19 pandemic. Key considerations for COVID-19 mass vaccination clinics include leadership and role designation, site selection, clinic layout and workflow, day-to-day operations, infection prevention, and communication strategies. CONCLUSIONS Planning and implementing a successful COVID-19 mass vaccination clinic requires several key considerations. Primary care plays an important role in organizing clinics and ensuring populations made vulnerable by social and economic policies are being reached. Ongoing data collection is required to evaluate and continuously improve COVID-19 mass vaccination efforts. As the severe acute respiratory syndrome coronavirus 2 (SARSCoV-2) vaccine rollout occurs in various countries, research will be required to identify the main factors for success to inform future pandemic responses. VISUAL ABSTRACT Ann Fam Med 2022;20:149-156. https://doi.org/10.1370/afm.2773., INTRODUCTION In just 2 years, the pandemic of coronavirus disease 2019 (COVID-19) has resulted in 380 million confirmed cases and 10 million deaths, with numbers continuing to rise. (1) Public [...]

Background: The BETTER intervention is an effective comprehensive evidence-based program for chronic disease prevention and screening (CDPS) delivered by trained prevention practitioners (PPs), a new role in primary care. An adapted program, BETTER HEALTH, delivered by public health nurses as PPs for community residents in low income neighbourhoods, was recently shown to be effective in improving CDPS actions. To obtain a nuanced understanding about the CDPS needs of community residents and how the BETTER HEALTH intervention was perceived by residents, we studied how the intervention was adapted to a public health setting then conducted a post-visit qualitative evaluation by community residents through focus groups and interviews. Methods: We first used the ADAPT-ITT model to adapt BETTER for a public health setting in Ontario, Canada. For the post-PP visit qualitative evaluation, we asked community residents who had received a PP visit, about steps they had taken to improve their physical and mental health and the BETTER HEALTH intervention. For both phases, we conducted focus groups and interviews; transcripts were analyzed using the constant comparative method. Results: Thirty-eight community residents participated in either adaptation (n = 14, 64% female; average age 54 y) or evaluation (n = 24, 83% female; average age 60 y) phases. In both adaptation and evaluation, residents described significant challenges including poverty, social isolation, and daily stress, making chronic disease prevention a lower priority. Adaptation results indicated that residents valued learning about CDPS and would attend a confidential visit with a public health nurse who was viewed as trustworthy. Despite challenges, many recipients of BETTER HEALTH perceived they had achieved at least one personal CDPS goal post PP visit. Residents described key relational aspects of the visit including feeling valued, listened to and being understood by the PP. The PPs also provided practical suggestions to overcome barriers to meeting prevention goals. Conclusions: Residents living in low income neighbourhoods faced daily stress that reduced their capacity to make preventive lifestyle changes. Key adapted features of BETTER HEALTH such as public health nurses as PPs were highly supported by residents. The intervention was perceived valuable for the community by providing access to disease prevention. Trial registration: #NCT03052959, 10/02/2017. [ABSTRACT FROM AUTHOR]

Unemployment is more common among people living with HIV (PLWH) compared to the general population. PLWH who are employed have better physical and mental health outcomes compared to unemployed PLWH. The main objective of this mixed-methods study was to conduct a program evaluation of Employment Action (EACT), a community-based program that assists PLWH in Toronto, Ontario, Canada to maintain meaningful employment. We extracted quantitative data from two HIV services databases used by EACT, and collected qualitative data from 12 individuals who had been placed into paid employment through EACT. From 131 clients included in the analysis, 38.1% (n = 50) maintained their job for at least 6 weeks within the first year of enrollment in the EACT program. Gender, ethnicity, age, and first language did not predict employment maintenance. Our interviews highlighted the barriers and facilitators to effective service delivery. Key recommendations include implementing skills training, embedding PLWH as EACT staff, and following up with clients once they gain employment. Investment in social programs such as EACT are essential for strengthening their data collection capacity, active outreach to service users, and sufficient planning for the evaluation phase prior to program implementation. [ABSTRACT FROM AUTHOR]

PURPOSE Employment is a key social determinant of health. People who are unemployed typically have worse health than those employed. Illness and disability can result in unemployment and be a barrier to regaining employment. We combined a systematic review and knowledge synthesis to identify both studies of employment interventions in health care settings and common characteristics of successful interventions. METHODS We searched the peer-reviewed literature (1995-2017), and titles and abstracts were screened for inclusion and exclusion criteria by 2 independent reviewers. We extracted data on the study setting, participants, intervention, methods, and findings. We also conducted a narrative synthesis and iteratively developed a conceptual model to inform future primary care interventions. RESULTS Of 6,729 unique citations, 88 articles met our criteria. Most articles (89%) focused on people with mental illness. The majority of articles (74%) tested interventions that succeeded in helping participants gain employment. We identified 5 key features of successful interventions: (1) a multidisciplinary team that communicates regularly and collaborates, (2) a comprehensive package of services, (3) one-on-one and tailored components, (4) a holistic view of health and social needs, and (5) prospective engagement with employers. CONCLUSIONS Our findings can inform new interventions that focus on employment as a social determinant of health. Although hiring a dedicated employment specialist may not be feasible for most primary care organizations, pathways using existing resources with links to external agencies can be created. As precarious work becomes more common, helping patients engage in safe and productive employment could improve health, access to health care, and well-being. Key words: social determinants of health; employment; systematic review; work; health care settings; working conditions; chronic disease; vulnerable populations; primary care, INTRODUCTION Employment status is a key social determinant of health. (1,2) Being employed influences our financial security, sense of self, social connections, and social status. Unemployment is associated with worse [...]

Background Adherence to medicines is low for a variety of reasons, including the cost borne by patients. Some jurisdictions publicly fund medicines for the general population, but many jurisdictions do not, and such policies are contentious. To our knowledge, no trials studying free access to a wide range of medicines have been conducted. Methods and findings We randomly assigned 786 primary care patients who reported not taking medicines due to cost between June 1, 2016 and April 28, 2017 to either free distribution of essential medicines (n = 395) or to usual medicine access (n = 391). The trial was conducted in Ontario, Canada, where hospital care and physician services are publicly funded for the general population but medicines are not. The trial population was mostly female (56%), younger than 65 years (83%), white (66%), and had a low income from wages as the primary source (56%). The primary outcome was medicine adherence after 2 years. Secondary outcomes included control of diabetes, blood pressure, and low-density lipoprotein (LDL) cholesterol in patients taking relevant treatments and healthcare costs over 2 years. Adherence to all appropriate prescribed medicines was 38.7% in the free distribution group and 28.6% in the usual access group after 2 years (absolute difference 10.1%; 95% confidence interval (CI) 3.3 to 16.9, p = 0.004). There were no statistically significant differences in control of diabetes (hemoglobin A1c 0.27; 95% CI -0.25 to 0.79, p = 0.302), systolic blood pressure (-3.9; 95% CI -9.9 to 2.2, p = 0.210), or LDL cholesterol (0.26; 95% CI -0.08 to 0.60, p = 0.130) based on available data. Total healthcare costs over 2 years were lower with free distribution (difference in median CAN$1,117; 95% CI CAN$445 to CAN$1,778, p = 0.006). In the free distribution group, 51 participants experienced a serious adverse event, while 68 participants in the usual access group experienced a serious adverse event (p = 0.091). Participants were not blinded, and some outcomes depended on participant reports. Conclusions In this study, we observed that free distribution of essential medicines to patients with cost-related nonadherence substantially increased adherence, did not affect surrogate health outcomes, and reduced total healthcare costs over 2 years. Trial registration ClinicalTrials.gov NCT02744963., Author(s): Nav Persaud 1,2,3,4,*, Michael Bedard 5, Andrew Boozary 6, Richard H. Glazier 1,2,3,7,8, Tara Gomes 1,2,9,10, Stephen W. Hwang 2,4,11, Peter Juni 4,11, Michael R. Law 12, Muhammad Mamdani [...]