"Family doctors are also people": a qualitative analysis of how family physicians managed competing personal and professional responsibilities during the COVID-19 pandemic.

BACKGROUND: Family physicians (FPs) fill an essential role in public health emergencies yet have frequently been neglected in pandemic response plans. This exclusion harms FPs in their clinical roles and has unintended consequences in the management of concurrent personal responsibilities, many of which were amplified by the pandemic. The objective of our study was to explore the experiences of FPs during the first year of the COVID-19 pandemic to better understand how they managed their competing professional and personal priorities. METHODS: We conducted semi-structured interviews with FPs from four Canadian regions between October 2020 and June 2021. Employing a maximum variation sampling approach, we recruited participants until we achieved saturation. Interviews explored FPs' personal and professional roles and responsibilities during the pandemic, the facilitators and barriers that they encountered, and any gender-related experiences. Transcribed interviews were thematically analysed. RESULTS: We interviewed 68 FPs during the pandemic and identified four overarching themes in participants' discussion of their personal experiences: personal caregiving responsibilities, COVID-19 risk navigation to protect family members, personal health concerns, and available and desired personal supports for FPs to manage their competing responsibilities. While FPs expressed a variety of ways in which their personal experiences made their professional responsibilities more complicated, rarely did that affect the extent to which they participated in the pandemic response. CONCLUSIONS: For FPs to contribute fully to a pandemic response, they must be factored into pandemic plans. Failure to appreciate their unique role and circumstances often leaves FPs feeling unsupported in both their professional and personal lives. Comprehensive planning in anticipation of future pandemics must consider FPs' varied responsibilities, health concerns, and necessary precautions. Having adequate personal and practice supports in place will facilitate the essential role of FPs in responding to a pandemic crisis while continuing to support their patients' primary care needs.

Understanding intersectional inequality in access to primary care providers using multilevel analysis of individual heterogeneity and discriminatory accuracy.

BACKGROUND: Despite the Canadian healthcare system's commitment to equity, evidence for disparate access to primary care (PC) providers exists across individual social identities/positions. Intersectionality allows us to reflect the realities of how social power shapes healthcare experiences at an individual's interdependent and intersecting social identities/positions. The objectives of this study were to determine: (1) the extent to which intersections can be used classify those who had/did not have a PC provider; (2) the degree to which each social identity/position contributes to the ability to classify individuals as having a PC provider; and (3) predicted probabilities of having a PC provider for each intersection. METHODS AND FINDINGS: Using national cross-sectional data from 241,445 individuals in Canada aged ≥18, we constructed 320 intersections along the dimensions of gender, age, immigration status, race, and income to examine the outcome of whether one had a PC provider. Multilevel analysis of individual heterogeneity and discriminatory accuracy, a multi-level model using individual-level data, was employed to address intersectional objectives. An intra-class correlation coefficient (ICC) of 23% (95%CI: 21-26%) suggests that these intersections could, to a very good extent, explain individual variation in the outcome, with age playing the largest role. Not all between-intersection variance in this outcome could be explained by additive effects of dimensions (remaining ICC: 6%; 95%CI: 2-16%). The highest intersectional predicted probability existed for established immigrant, older South Asian women with high income. The lowest intersectional predicted probability existed for recently immigrated, young, Black men with low income. CONCLUSIONS: Despite a "universal" healthcare system, our analysis demonstrated a substantial amount of inequity in primary care across intersections of gender, age, immigration status, race, and income.

Sex differences in the clinical presentation of early psychosis in a primary care setting.

Primary care is an important part of the help-seeking pathway for young people experiencing early psychosis, but sex differences in clinical presentation in these settings are unexplored. We aimed to identify sex differences in clinical presentation to primary care services in the 1-year period prior to a first diagnosis of psychotic disorder. We identified first-onset cases of non-affective psychotic disorder over a 10-year period (2005-2015) using health administrative data linked with electronic medical records (EMRs) from primary care (n = 465). Detailed information on encounters in the year prior to first diagnosis was abstracted, including psychiatric symptoms, other relevant behaviours, and diagnoses recorded by the family physician (FP). We used modified Poisson regression models to examine sex differences in the signs, symptoms, and diagnoses recorded by the FP, adjusting for various clinical and sociodemographic factors. Positive symptoms (PR = 0.76, 95%CI: 0.58, 0.98) and substance use (PR = 0.54, 95%CI: 0.40, 0.72) were less prevalent in the medical records of women. Visits by women were more likely to be assigned a diagnosis of depression or anxiety (PR = 1.18, 95%CI: 1.00, 1.38), personality disorder (PR = 5.49, 95%CI: 1.22, 24.62), psychological distress (PR = 11.29, 95%CI: 1.23, 103.91), and other mental or behavioral disorders (PR = 3.49, 95%CI: 1.14, 10.66) and less likely to be assigned a diagnosis of addiction (PR = 0.33, 95%CI: 0.13, 0.87). We identified evidence of sex differences in the clinical presentation of early psychosis and recorded diagnoses in the primary care EMR. Further research is needed to better understand sex differences in clinical presentation in the primary care context, which can facilitate better understanding, detection, and intervention for first-episode psychotic disorders.

Patients' experiences with a community fruit and vegetable box program prescribed by their health provider.

BACKGROUND: Food insecurity is "the state of being without reliable access to a sufficient quantity of affordable, nutritious food". Observational studies have associated food insecurity with many negative health effects including the development and exacerbations of chronic diseases, higher health care use and increased mortality. Health care providers prescribing food is a growing area of interest and research, however it is not known how patients feel about receiving fruit and vegetable prescriptions (FVRx) from their health provider versus other means of food provision. This pilot study was conducted to explore the experiences and opinions of Canadian adults with food insecurity who were recipients of a FVRx box program prescribed by their health provider. METHODS: Potential participants were recruited to 3 focus groups using flyers included in their monthly food box. Questions were kept open to encourage participation of all group members. The focus groups were audiotaped, transcribed verbatim, and analyzed by the research team using descriptive qualitative research methodology. RESULTS: Participants described shame and frustration trying to obtain enough food through local food banks. In comparison, they perceived their team dietitian, family physician or addictions physician as directly helping them with their health by prescribing food. The boxed fruit and vegetables were prepared in many ways and often shared to reduce waste and to reduce the food insecurity of extended family members. Positive effects of the FVRx on physical and mental health were reported. Participants believed that follow up with their health provider helped support them and their behavioural changes towards better nutrition. Limitations of the program included lack of choice, non-flexible pick-up times and the program being limited to 6 months. Being able to choose their own fruit and vegetables, instead of receiving a set box, was suggested by most to help meal planning and to increase autonomy. CONCLUSIONS: Health providers prescribing FVRx boxes to adult patients with food insecurity was positively received in this study. Evaluation of similar programs in other regions in Canada and internationally, and comparison of food prescriptions to basic income guarantee programs is recommended.

Perceptions of Artificial Intelligence Use in Primary Care: A Qualitative Study with Providers and Staff of Ontario Community Health Centres.

PURPOSE: To understand staff and health care providers' views on potential use of artificial intelligence (AI)-driven tools to help care for patients within a primary care setting. METHODS: We conducted a qualitative descriptive study using individual semistructured interviews. As part of province-wide Learning Health Organization, Community Health Centres (CHCs) are a community-governed, team-based delivery model providing primary care for people who experience marginalization in Ontario, Canada. CHC health care providers and staff were invited to participate. Interviews were audio-recorded and transcribed verbatim. We performed a thematic analysis using a team approach. RESULTS: We interviewed 27 participants across 6 CHCs. Participants lacked in-depth knowledge about AI. Trust was essential to acceptance of AI; people need to be receptive to using AI and feel confident that the information is accurate. We identified internal influences of AI acceptance, including ease of use and complementing clinical judgment rather than replacing it. External influences included privacy, liability, and financial considerations. Participants felt AI could improve patient care and help prevent burnout for providers; however, there were concerns about the impact on the patient-provider relationship. CONCLUSIONS: The information gained in this study can be used for future research, development, and integration of AI technology.

Training and capacity development in patient-oriented research: Ontario SPOR SUPPORT Unit (OSSU) initiatives.

BACKGROUND: In Canada, the Canadian Institutes of Health Research launched the Strategy for Patient-Oriented Research (SPOR) in 2011. The strategy defines 'patient-oriented research' as a continuum of research that engages patients as partners, focuses on patient priorities, and leads to improved patient outcomes. The overarching term 'patient' is inclusive of individuals with personal experience of a health issue as well as informal caregivers including family and friends. The vision for the strategy is improved patient experiences and outcomes through the integration of patient-oriented research findings into practice, policy, and health system improvement. Building capacity in patient-oriented research among all relevant stakeholders, namely patients, practitioners, organizational leaders, policymakers, researchers, and research funders is a core element of the strategy. MAIN BODY: The objective of this paper is to describe capacity building initiatives in patient-oriented research led by the Ontario SPOR SUPPORT Unit in Ontario, Canada over the period 2014-2020. CONCLUSION: The Ontario SPOR SUPPORT Unit Working Group in Training and Capacity Development has led numerous capacity building initiatives: developed a Capacity Building Compendium (accessed greater than 45,000 times); hosted Masterclasses that have trained hundreds of stakeholders (patients, practitioners, organizational leaders, policymakers, researchers, and trainees) in the conduct and use of patient-oriented research; funded the development of online curricula on patient-oriented research that have reached thousands of stakeholders; developed a patient engagement resource center that has been accessed by tens of thousands of stakeholders; identified core competencies for research teams and research environments to ensure authentic and meaningful patient partnerships in health research; and shared these resources and learnings with stakeholders across Canada, North America, and internationally.

In 2011, Canada developed a Strategy for Patient-Oriented Research. The aim of the strategy was to ensure that patients were included as equal partners in research, with the goal to improve the patient experience and enhance health outcomes using research findings to influence clinical care, policy, and health system improvement. Building capacity in patient-oriented research is a core element of the strategy. Since 2014, the Ontario SPOR SUPPORT Unit has led numerous initiatives to build capacity in patient-oriented research. Successes include a Capacity Building Compendium (a catalogue of resources that has been accessed greater than 45,000 times); courses on how to do and how to use patient-oriented research that have trained hundreds of patients, practitioners, organizational leaders, policymakers, and researchers; created online patient-oriented research materials; developed a patient engagement resource center; identified what is required to ensure authentic and meaningful patient partnerships in research; and shared these resources and learnings widely.

Understanding data provenance when using electronic medical records for research: Lessons learned from the Deliver Primary Healthcare Information (DELPHI) database.

Introduction: We set out to assess the impact of Choosing Wisely Canada recommendations (2014) on reducing unnecessary health investigations and interventions in primary care across Southwestern Ontario. Methods: We used the Deliver Primary Healthcare Information (DELPHI) database, which stores deidentified electronic medical records (EMR) of nearly 65,000 primary care patients across Southwestern Ontario. When conducting research using EMR data, data provenance (i.e., how the data came to be) should first be established. We first considered DELPHI data provenance in relation to longitudinal analyses, flagging a change in EMR software that occurred during 2012 and 2013. We attempted to link records between EMR databases produced by different software using probabilistic linkage and inspected 10 years of data in the DELPHI database (2009 to 2019) for data quality issues, including comparability over time. Results: We encountered several issues resulting from this change in EMR software. These included limited linkage of records between software without a common identifier; data migration issues that distorted procedure dates; and unusual changes in laboratory test and medication prescription volumes. Conclusion: This study reinforces the necessity of assessing data provenance and quality for new research projects. By understanding data provenance, we can anticipate related data quality issues such as changes in EMR data over time-which represent a growing concern as longitudinal data analyses increase in feasibility and popularity.

Focused practice in family medicine: Quantitative study.

OBJECTIVE: To determine factors associated with having a focused practice among a sample of family medicine graduates in Canada and to assess the characteristics of FPs with focused practices and the range of services provided by these FPs in relation to the full scope of office-based care. DESIGN: Secondary analyses of cross-sectional data from the 2013-2014 Western Family Medicine Resident Follow-Up Survey. SETTING: Western University in London, Ont. PARTICIPANTS: Western University family medicine residency graduates who completed the program between 1985 and 2012. MAIN OUTCOME MEASURES: Physician and practice characteristics and the clinical services that survey participants provide. RESULTS: Completion of postgraduate third-year (PGY3) training was associated with having a focused practice. Focused practice FPs were more likely to be remunerated by fee-for-service, alternative payment plans, or alternative funding plans compared with non-focused practice FPs, who were more likely to participate in group payment models. Focused practice FPs appeared to be a heterogeneous group who were distinguished by being either an office-based focused practice FP (OBFFP) or a non-office-based focused practice FP (NOBFFP). Office-based focused practice FPs were less likely than NOBFFPs to have completed PGY3 training and more likely to work under a fee-for-service or group payment model. Further, the OBFFP group offered a greater variety of primary care services than the NOBFFP group, but offered less variety than non-focused practice FPs. CONCLUSION: Completion of PGY3 training and payment through certain remuneration models were both associated with focused practice. Important differences exist between OBFFPs and NOBFFPs. The overall service provision of focused practice FPs was centred on specialized areas, especially among those practising in non-office-based settings. Novel findings from this study provide insights for family medicine education, work force planning, and policy making in the Canadian health system.

Virtual family physician care during COVID-19: a mixed methods study using health administrative data and qualitative interviews.

BACKGROUND: The onset of the COVID-19 pandemic necessitated a rapid shift in primary health care from predominantly in-person to high volumes of virtual care. The pandemic afforded the opportunity to conduct a deep regional examination of virtual care by family physicians in London and Middlesex County, Ontario, Canada that would inform the foundation for virtual care in our region post-pandemic. OBJECTIVES: (1) to determine volumes of in-person and virtual family physicians visits and characteristics of the family physicians and patients using them during the early COVID-19 pandemic; (2) to determine how virtual visit volumes changed over the pandemic, compared to in-person; and (3) to explore family physicians' experience in virtual visit adoption and implementation. METHODS: We conducted a concurrent mixed-methods study of family physicians from March to October 2020. The quantitative component examined mean weekly number of total, in-person and virtual visits using health administrative data. Differences in outcomes according to physician and practice characteristics for pandemic periods were compared to pre-pandemic. The qualitative study employed Constructivist Grounded Theory, conducting semi-structured family physicians interviews; analyzing data iteratively using constant comparative analysis. We mapped themes from the qualitative analysis to quantitative findings. RESULTS: Initial volumes of patients decreased, driven by fewer in-person visits. Virtual visit volumes increased dramatically; family physicians described using telephone almost entirely. Rural family physicians reported video connectivity issues. By early second wave, total family physician visit volume returned to pre-pandemic volumes. In-person visits increased substantially; family physicians reported this happened because previously scarce personal protective equipment became available. Patients seen during the pandemic were older, sicker, and more materially deprived. CONCLUSION: These results can inform the future of virtual family physician care including the importance of continued virtual care compensation, the need for equitable family physician payment models, and the need to attend to equity for vulnerable patients. Given the move to virtual care was primarily a move to telephone care, the modality of care delivery that is acceptable to both family physicians and their patients must be considered.

Is primary health care ready for artificial intelligence? What do primary health care stakeholders say?

BACKGROUND: Effective deployment of AI tools in primary health care requires the engagement of practitioners in the development and testing of these tools, and a match between the resulting AI tools and clinical/system needs in primary health care. To set the stage for these developments, we must gain a more in-depth understanding of the views of practitioners and decision-makers about the use of AI in primary health care. The objective of this study was to identify key issues regarding the use of AI tools in primary health care by exploring the views of primary health care and digital health stakeholders. METHODS: This study utilized a descriptive qualitative approach, including thematic data analysis. Fourteen in-depth interviews were conducted with primary health care and digital health stakeholders in Ontario. NVivo software was utilized in the coding of the interviews. RESULTS: Five main interconnected themes emerged: (1) Mismatch Between Envisioned Uses and Current Reality-denoting the importance of potential applications of AI in primary health care practice, with a recognition of the current reality characterized by a lack of available tools; (2) Mechanics of AI Don't Matter: Just Another Tool in the Toolbox- reflecting an interest in what value AI tools could bring to practice, rather than concern with the mechanics of the AI tools themselves; (3) AI in Practice: A Double-Edged Sword-the possible benefits of AI use in primary health care contrasted with fundamental concern about the possible threats posed by AI in terms of clinical skills and capacity, mistakes, and loss of control; (4) The Non-Starters: A Guarded Stance Regarding AI Adoption in Primary Health Care-broader concerns centred on the ethical, legal, and social implications of AI use in primary health care; and (5) Necessary Elements: Facilitators of AI in Primary Health Care-elements required to support the uptake of AI tools, including co-creation, availability and use of high quality data, and the need for evaluation. CONCLUSION: The use of AI in primary health care may have a positive impact, but many factors need to be considered regarding its implementation. This study may help to inform the development and deployment of AI tools in primary health care.

Complex skills are required for new primary health care researchers: a training program responds.

BACKGROUND: Current dimensions of the primary health care research (PHC) context, including the need for contextualized research methods to address complex questions, and the co-creation of knowledge through partnerships with stakeholders - require PHC researchers to have a comprehensive set of skills for engaging effectively in high impact research. MAIN BODY: In 2002 we developed a unique program to respond to these needs - Transdisciplinary Understanding and Training on Research - Primary Health Care (TUTOR-PHC). The program's goals are to train a cadre of PHC researchers, clinicians, and decision makers in interdisciplinary research to aid them in tackling current and future challenges in PHC and in leading collaborative interdisciplinary research teams. Seven essential educational approaches employed by TUTOR-PHC are described, as well as the principles underlying the curriculum. This program is unique because of its pan-Canadian nature, longevity, and the multiplicity of disciplines represented. Program evaluation results indicate: 1) overall program experiences are very positive; 2) TUTOR-PHC increases trainee interdisciplinary research understanding and activity; and 3) this training assists in developing their interdisciplinary research careers. Taken together, the structure of the program, its content, educational approaches, and principles, represent a complex whole. This complexity parallels that of the PHC research context - a context that requires researchers who are able to respond to multiple challenges. CONCLUSION: We present this description of ways to teach and learn the advanced complex skills necessary for successful PHC researchers with a view to supporting the potential uptake of program components in other settings.

Sex and gender differences in symptoms of early psychosis: a systematic review and meta-analysis.

First-episode psychosis (FEP) can be quite variable in clinical presentation, and both sex and gender may account for some of this variability. Prior literature on sex or gender differences in symptoms of psychosis have been inconclusive, and a comprehensive summary of evidence on the early course of illness is lacking. The objective of this study was to conduct a systematic review and meta-analysis of the literature to summarize prior evidence on the sex and gender differences in the symptoms of early psychosis. We conducted an electronic database search (MEDLINE, Scopus, PsycINFO, and CINAHL) from 1990 to present to identify quantitative studies focused on sex or gender differences in the symptoms of early psychosis. We used random effects models to compute pooled standardized mean differences (SMD) and risk ratios (RR), with 95% confidence intervals (CI), for a range of symptoms. Thirty-five studies met the inclusion criteria for the systematic review, and 30 studies were included in the meta-analysis. All studies examined sex differences. Men experienced more severe negative symptoms (SMD = - 0.15, 95%CI = - 0.21, - 0.09), whereas women experienced more severe depressive symptoms (SMD = 0.21, 95%CI = 0.14, 0.27) and had higher functioning (SMD = 0.16, 95%CI = 0.10, 0.23). Women also had a lower prevalence of substance use issues (RR = 0.65, 95%CI = 0.61, 0.69). Symptoms of early psychosis varied between men and women; however, we were limited in our ability to differentiate between biological sex and gender factors. These findings may help to inform early detection and intervention efforts to better account for sex and gender differences in early psychosis presentation.

Development of a prognostic prediction model to estimate the risk of multiple chronic diseases: constructing a copula-based model using Canadian primary care electronic medical record data.

INTRODUCTION: The ability to estimate risk of multimorbidity will provide valuable information to patients and primary care practitioners in their preventative efforts. Current methods for prognostic prediction modelling are insufficient for the estimation of risk for multiple outcomes, as they do not properly capture the dependence that exists between outcomes. OBJECTIVES: We developed a multivariate prognostic prediction model for the 5-year risk of diabetes, hypertension, and osteoarthritis that quantifies and accounts for the dependence between each disease using a copula-based model. METHODS: We used data from the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) from 2009 onwards, a collection of electronic medical records submitted by participating primary care practitioners across Canada. We identified patients 18 years and older without all three outcome diseases and observed any incident diabetes, osteoarthritis, or hypertension within 5-years, resulting in a large retrospective cohort for model development and internal validation (n=425,228). First, we quantified the dependence between outcomes using unadjusted and adjusted Ø coefficients. We then estimated a copula-based model to quantify the non-linear dependence between outcomes that can be used to derive risk estimates for each outcome, accounting for the observed dependence. Copula-based models are defined by univariate models for each outcome and a dependence function, specified by the parameter θ. Logistic regression was used for the univariate models and the Frank copula was selected as the dependence function. RESULTS: All outcome pairs demonstrated statistically significant dependence that was reduced after adjusting for covariates. The copula-based model yielded statistically significant θ parameters in agreement with the adjusted and unadjusted Ø coefficients. Our copula-based model can effectively be used to estimate trivariate probabilities. DISCUSSION: Quantitative estimates of multimorbidity risk inform discussions between patients and their primary care practitioners around prevention in an effort to reduce the incidence of multimorbidity.

Primary Care Informatics Response to Covid-19 Pandemic: Adaptation, Progress, and Lessons from Four Countries with High ICT Development.

OBJECTIVE: Internationally, primary care practice had to transform in response to the COVID pandemic. Informatics issues included access, privacy, and security, as well as patient concerns of equity, safety, quality, and trust. This paper describes progress and lessons learned. METHODS: IMIA Primary Care Informatics Working Group members from Australia, Canada, United Kingdom and United States developed a standardised template for collection of information. The template guided a rapid literature review. We also included experiential learning from primary care and public health perspectives. RESULTS: All countries responded rapidly. Common themes included rapid reductions then transformation to virtual visits, pausing of non-COVID related informatics projects, all against a background of non-standardized digital development and disparate territory or state regulations and guidance. Common barriers in these four and in less-resourced countries included disparities in internet access and availability including bandwidth limitations when internet access was available, initial lack of coding standards, and fears of primary care clinicians that patients were delaying care despite the availability of televisits. CONCLUSIONS: Primary care clinicians were able to respond to the COVID crisis through telehealth and electronic record enabled change. However, the lack of coordinated national strategies and regulation, assurance of financial viability, and working in silos remained limitations. The potential for primary care informatics to transform current practice was highlighted. More research is needed to confirm preliminary observations and trends noted.

Qualitative Study of Long-Haul Truck Drivers' Health and Healthcare Experiences.

OBJECTIVE: Long-haul truck drivers suffer increased health risk, but how they use healthcare is unknown. The objectives of this study were to explore the health experiences of these drivers, their healthcare experiences, and their relationship with their main medical provider. METHODS: In-depth semi-structured interviews were conducted with 13 Canadian long-haul truck drivers. The majority (85%) were men and recruited at a truck stop on a major transport corridor between Canada and the United States. RESULTS: Through phenomenological analysis of the transcribed interviews, themes of perseverance, isolation, dehumanization, and working in a hidden world emerged as major influences on the health experiences of these drivers. Barriers to their medical provider were also revealed. CONCLUSIONS: Continuous exposure to a stressful work environment and inadequate access to primary care likely negatively affect the health of long-haul truck drivers. Given the experiences of this small group of drivers, improved healthcare and health resource availability might mitigate the risk of this occupational group.

Advancing cross-national planning and partnership: Proceedings from the International Multimorbidity Symposium 2019.

The International Multimorbidity Symposium was held in November 2019 at Western University to achieve three main objectives: to discuss progress and findings from various jurisdictions; to facilitate collaboration through group discussion to identify strategies to move multimorbidity research forward; and to create concrete plans to ensure advances in multimorbidity research and knowledge can be achieved through cross-national partnership. This event included keynote presentations, elevator pitch presentations and breakout sessions and there was a total of 35 attendees from eight countries, representing diverse disciplines and training levels. The overall themes arising from the event were: the importance of integrating the study and management of multimorbidity from both the primary care and public health perspectives; meaningful engagement and collaboration with patients and caregivers to understand key dimensions of multimorbidity; the considerable benefit of collaborative international partnerships; and the need to spread and scale innovations for health care systems that can better respond to the complex needs of patients and caregivers who are living with multimorbidity. Finally, it was well-acknowledged among the attendees that expanding the collaboration and discussion among international colleagues via in-person and virtual events will be important to move multimorbidity research forward.

Development and evaluation of an osteoarthritis risk model for integration into primary care health information technology.

BACKGROUND: We developed and evaluated a prognostic prediction model that estimates osteoarthritis risk for use by patients and practitioners that is designed to be appropriate for integration into primary care health information technology systems. Osteoarthritis, a joint disorder characterized by pain and stiffness, causes significant morbidity among older Canadians. Because our prognostic prediction model for osteoarthritis risk uses data that are readily available in primary care settings, it supports targeting of interventions delivered as part of clinical practice that are aimed at risk reduction. METHODS: We used the CPCSSN (Canadian Primary Sentinel Surveillance Network) database, which contains aggregated electronic health information from a cohort of primary care practices, to develop and evaluate a prognostic prediction model to estimate 5-year osteoarthritis risk, addressing contextual challenges of data availability and missingness. We constructed a retrospective cohort of 383,117 eligible primary care patients who were included in the cohort if they had an encounter with their primary care practitioner between 1 January 2009 and 31 December 2010. Patients were excluded if they had a diagnosis of osteoarthritis prior to their first visit in this time period. Incident cases of osteoarthritis were observed. The model was constructed to predict incident osteoarthritis based on age, sex, BMI, previous leg injury, and osteoporosis. Evaluation of the model used internal 10-fold cross-validation; we argue that internal validation is particularly appropriate for a model that is to be integrated into the same context from which the data were derived. RESULTS: The resulting prediction model for 5-year risk of osteoarthritis diagnosis demonstrated state-of-the-art discrimination (estimated AUROC 0.84) and good calibration (assessed visually.) The model relies only on information that is readily available in Canadian primary care settings, and hence is appropriate for integration into Canadian primary care health information technology. CONCLUSIONS: If the contextual challenges arising when using primary care electronic medical record data are appropriately addressed, highly discriminative models for osteoarthritis risk may be constructed using only data commonly available in primary care. Because the models are constructed from data in the same setting where the model is to be applied, internal validation provides strong evidence that the resulting model will perform well in its intended application.

Artificial Intelligence and Primary Care Research: A Scoping Review.

PURPOSE: Rapid increases in technology and data motivate the application of artificial intelligence (AI) to primary care, but no comprehensive review exists to guide these efforts. Our objective was to assess the nature and extent of the body of research on AI for primary care. METHODS: We performed a scoping review, searching 11 published or gray literature databases with terms pertaining to AI (eg, machine learning, bayes* network) and primary care (eg, general pract*, nurse). We performed title and abstract and then full-text screening using Covidence. Studies had to involve research, include both AI and primary care, and be published in Eng-lish. We extracted data and summarized studies by 7 attributes: purpose(s); author appointment(s); primary care function(s); intended end user(s); health condition(s); geographic location of data source; and AI subfield(s). RESULTS: Of 5,515 unique documents, 405 met eligibility criteria. The body of research focused on developing or modifying AI methods (66.7%) to support physician diagnostic or treatment recommendations (36.5% and 13.8%), for chronic conditions, using data from higher-income countries. Few studies (14.1%) had even a single author with a primary care appointment. The predominant AI subfields were supervised machine learning (40.0%) and expert systems (22.2%). CONCLUSIONS: Research on AI for primary care is at an early stage of maturity. For the field to progress, more interdisciplinary research teams with end-user engagement and evaluation studies are needed.

Ratios and determinants of maternal mortality: a comparison of geographic differences in the northern and southern regions of Cameroon.

BACKGROUND: While maternal mortality has declined worldwide in the past 25 years, this is not the case for Cameroon. Since there is a predominantly young population in this country, high maternal mortality ratios may persist. Maternal mortality ratios vary within countries, yet it is unknown if the North and South, the most distinct parts of Cameroon, differ in terms of ratios and determinants of maternal mortality. METHODS: This study explored ratios and determinants of maternal mortality in women of childbearing age (15-49 years) and assessed differences between the North and South. We used the Cameroon Demographic and Health Surveys (2004 and 2011) to extract a sample of 18,665 living or deceased women who had given birth. Multivariable logistic regression was used to explore the relationship between maternal mortality and sociocultural, economic and healthcare factors. RESULTS: Maternal mortality ratios were different for the two regions and increased in the North in 2011 compared to 2004. In the North, any level of education and being Muslim were protective against maternal mortality. Meanwhile, the odds of maternal mortality decreased with increasing age, and having secondary or higher education in the South. Domestic violence and ethnicity were associated with maternal death in the South. Increasing parity was protective of maternal death in both the North and South. CONCLUSIONS: Maternal mortality ratios and determinants varied between women of childbearing age in the North and South of Cameroon. These reinforce recommendations for region specific strategies that will improve health communication, community education programs, curb domestic violence and train more community health workers to connect pregnant women with the health system. Programs to reduce maternal death among women with low parity and little or no education should be national priority.

Ethical Use of Electronic Health Record Data and Artificial Intelligence: Recommendations of the Primary Care Informatics Working Group of the International Medical Informatics Association.

OBJECTIVE: To create practical recommendations for the curation of routinely collected health data and artificial intelligence (AI) in primary care with a focus on ensuring their ethical use. METHODS: We defined data curation as the process of management of data throughout its lifecycle to ensure it can be used into the future. We used a literature review and Delphi exercises to capture insights from the Primary Care Informatics Working Group (PCIWG) of the International Medical Informatics Association (IMIA). RESULTS: We created six recommendations: (1) Ensure consent and formal process to govern access and sharing throughout the data life cycle; (2) Sustainable data creation/collection requires trust and permission; (3) Pay attention to Extract-Transform-Load (ETL) processes as they may have unrecognised risks; (4) Integrate data governance and data quality management to support clinical practice in integrated care systems; (5) Recognise the need for new processes to address the ethical issues arising from AI in primary care; (6) Apply an ethical framework mapped to the data life cycle, including an assessment of data quality to achieve effective data curation. CONCLUSIONS: The ethical use of data needs to be integrated within the curation process, hence running throughout the data lifecycle. Current information systems may not fully detect the risks associated with ETL and AI; they need careful scrutiny. With distributed integrated care systems where data are often used remote from documentation, harmonised data quality assessment, management, and governance is important. These recommendations should help maintain trust and connectedness in contemporary information systems and planned developments.