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IntroductionEffective chronic disease care is dependent on well-organised quality improvement (QI) strategies that monitor processes of care and outcomes for optimal care delivery. Although healthcare is provincially/territorially structured in Canada, there are national networks such as the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) as important facilitators for national QI-based studies to improve chronic disease care. The goal of our study is to improve the understanding of how patients with chronic kidney disease (CKD) are managed in primary care and the variation across practices and provinces and territories to drive improvements in care delivery.Methods and analysisThe CPCSSN database contains anonymised health information from the electronic medical records for patients of participating primary care practices (PCPs) across Canada (n=1200). The dataset includes information on patient sociodemographics, medications, laboratory results and comorbidities. Leveraging validated algorithms, case definitions and guidelines will help define CKD and the related processes of care, and these enable us to: (1) determine prevalent CKD burden; (2) ascertain the current practice pattern on risk identification and management of CKD and (3) study variation in care indicators (eg, achievement of blood pressure and proteinuria targets) and referral pattern for specialist kidney care. The process of care outcomes will be stratified across patients' demographics as well as provider and regional (provincial/territorial) characteristics. The prevalence of CKD stages 3-5 will be presented as age-sex standardised prevalence estimates stratified by province and as weighted averages for population rates with 95% CIs using census data. For each PCP, age-sex standardised prevalence will be calculated and compared with expected standardised prevalence estimates. The process-based outcomes will be defined using established methods.Ethics and disseminationThe CPCSSN is committed to high ethical standards when dealing with individual data collected, and this work is reviewed and approved by the Network Scientific Committee. The results will be published in peer-reviewed journals and presented at relevant national and international scientific meetings.

Background: Children's exposure to toxic stress (e.g., parental depression, violence, poverty) predicts developmental and physical health problems resulting in health care system burden. Supporting parents to develop parenting skills can buffer the effects of toxic stress, leading to healthier outcomes for those children. Parenting interventions that focus on promoting parental reflective function (RF), i.e., parents' capacity for insight into their child's and their own thoughts, feelings, and mental states, may understand help reduce societal health inequities stemming from childhood stress exposures. The Attachment and Child Health (ATTACHTM) program has been implemented and tested in seven rapid-cycling pilot studies (n = 64) and found to significantly improve parents' RF in the domains of attachment, parenting quality, immune function, and children's cognitive and motor development. The purpose of the study is to conduct an effectiveness-implementation hybrid (EIH) Type II study of ATTACHTM to assess its impacts in naturalistic, real-world settings delivered by community agencies rather than researchers under more controlled conditions.Methods: The study is comprised of a quantitative pre/post-test quasi-experimental evaluation of the ATTACHTM program, and a qualitative examination of implementation feasibility using thematic analysis via Normalization Process Theory (NPT). We will work with 100 families and their children (birth to 36-months-old). Study outcomes include: the Parent Child Interaction Teaching Scale to assess parent-child interaction; the Parental Reflective Function and Reflective Function Questionnaires to assess RF; and the Ages and Stages Questionnaire - 3rd edition to examine child development, all administered pre-, post-, and 3-month-delayed post-assessment. Blood samples will be collected pre- and post- assessment to assess immune biomarkers. Further, we will conduct one-on-one interviews with study participants, health and social service providers, and administrators (total n = 60) from each collaborating agency, using NPT to explore perceptions and experiences of intervention uptake, the fidelity assessment tool and e-learning training as well as the benefits, barriers, and challenges to ATTACHTM implementation.Discussion: The proposed study will assess effectiveness and implementation to help understand the delivery of ATTACHTM in community agencies.Trial Registration: Name of registry: https://clinicaltrials.gov/.Registration Number: NCT04853888 . Date of registration: April 22, 2021. [ABSTRACT FROM AUTHOR]

Background: The dementias are long-term, chronic conditions caused by progressive neurological degeneration. Current literature suggests that cardiovascular disease risk factors may contribute to the onset of dementia; however, evidence of these associations is inconsistent.Objectives: This study aimed to examine the impact of risk factors on dementia onset in older adults diagnosed and managed in Canadian primary care settings.Methods: A retrospective cohort study was employed utilizing electronic medical records data in the Canadian Primary Care Sentinel Surveillance Network (CPCSSN). Patients aged 65+ years with no dementia diagnosis at baseline who were followed from 2009 to 2017 with a run-in year to exclude existing undiagnosed dementia cases. Multivariate Cox proportional hazard models were used to estimate risk.Results: Age was associated with an increased incidence risk of dementia in both examined age groups: 65-79 years (13%) and 80+ years (5%). History of depression increased dementia risk by 38% and 34% in the age groups. There were significant associations with lower social deprivation area quintile, smoking history, osteoarthritis, and diabetes mellitus in patients aged 65-79 years but not in those aged 80+ years. Sex, hypertension, obesity, dyslipidemia, and the use of antihypertensive medications and statins were not associated with risk of incident dementia diagnosis.Conclusions: The association between chronic health conditions and dementia onset is complicated. Primary care electronic medical record data might be useful for research in this topic, though follow-up time is still relatively short to observe a clear causal relationship. Future studies with more complete data may provide evidence for dementia preventive strategies within primary care practice. [ABSTRACT FROM AUTHOR]

To compare characteristics of patients with and without physical activity noted in primary care electronic medical records. We used pan-Canadian family physician electronic medical record data from the Canadian Primary Care Sentinel Surveillance Network (CPSSSN) to compare patient and provider characteristics on one visit per patient selected at random. Since patients were nested by providers, univariate statistics were explored then a multilevel model was constructed. The dataset included 769,185 patients, of whom 14,828 (1.9%) had physical activity information documented. Male patients, aged 25–34.9, no comorbidities prior to the random visit date, moderate or elevated blood pressure risk categories prior to the random visit date, the least materially deprived quintile, and with median body mass index in the normal category prior to the random visit date had the most physical activity mentions. Of the 879 family physicians in the sample, just over half (56.1%) documented physical activity at least once across their patients. More female physicians and physicians who practised in academic sites documented physical activity. In a two-level logistic model to predict physical activity documented in the randomly selected visit: older than mean patient age, having fewer comorbidities, younger than mean family physician age, academic teaching sites, and electronic medical record systems were statistically significant covariates. This work adds to existing literature by describing the frequency and the patient and family physician characteristics of physical activity documentation in the Canadian primary care context. Overall, patient physical activity was rarely documented in electronic medical records. • Electronic medical records can show documentation patterns of family physicians. • Of 769,185 primary care visits 14,828 (1.9%) had physical activity documented. • Documentation of physical activity differs by electronic medical record system. • Physical activity documentation varies by community or academic teaching clinics. • Future work is needed to ensure documentation within existing clinical workflow. [ABSTRACT FROM AUTHOR]

Background: Clostridium difficile infection (CDI) is prevalent in long-term care (LTC) facilities in the United States, Canada, Europe and Australia. However, to our knowledge, CDI surveillance in LTC facilities has not been documented provincially in Alberta or any other Canadian province. This study aims to identify the incidence of CDI in LTC facilities and describe the demographic characteristics of the affected population. Methods: Administrative data from 172 LTC facilities in Alberta, Canada, was obtained from April 1, 2012, and September 30, 2013. Results: The majority of LTC CDI cases were either residents who resided in a LTC facility for more than 72 hours and had no hospitalizations in the previous four weeks (65.7%), or residents who had a hospital visit between 72 hours and four weeks prior to their CDI case (30.3%). Fluid and electrolyte disorders, congestive heart failure, and cardiac arrhythmias were the most common co-morbidities. Approximately 30% of residents died within 60 days of their CDI episode. Conclusions: There is a need to implement routine surveillance to continue monitoring CDI in LTC facilities to assess these findings further and to evaluate changes over time in response to improvement initiatives related to CDI prevention and clinical management. [ABSTRACT FROM AUTHOR]

Background: Most antibiotics dispensed by community pharmacies in Canada are prescribed by family physicians, but using the prescribing information contained within primary care electronic medical records (EMRs) for secondary purposes can be challenging owing to variable data quality. We used antibiotic medications as an exemplar to validate a machine-learning approach for cleaning and coding medication data in a pan-Canadian primary care EMR database., Methods: The Canadian Primary Care Sentinel Surveillance Network database contained an estimated 42 million medication records, which we mapped to an Anatomic Therapeutic Chemical (ATC) code by applying a semisupervised classification model developed using reference standard labels derived from the Health Canada Drug Product Database. We validated the resulting ATC codes in a subset of antibiotic records (16 119 unique strings) to determine whether the algorithm correctly classified the medication according to manual review of the original medication record., Results: In the antibiotic subset, the algorithm showed high validity (sensitivity 99.5%, specificity 92.4%, positive predictive value 98.6%, negative predictive value 97.0%) in classifying whether the medication was an antibiotic., Interpretation: Our machine-learning algorithm classified unstructured antibiotic medication data from primary care with a high degree of accuracy. Access to cleaned EMR data can support important secondary uses, including community-based antibiotic prescribing surveillance and practice improvement., Competing Interests: Competing interests: None declared., (© 2023 CMA Impact Inc. or its licensors.)