Multimorbidity and Blood Pressure Control in Patients Attending Primary Care in Canada.

BACKGROUND: There has been conflicting evidence on the association between multimorbidity and blood pressure (BP) control. This study aimed to investigate this associations in people with hypertension attending primary care in Canada, and to assess whether individual long-term conditions are associated with BP control. METHODS: This was a cross-sectional study in people with hypertension attending primary care in Toronto between January 1, 2017 and December 31, 2019. Uncontrolled BP was defined as systolic BP ≥ 140 mmHg or diastolic BP ≥ 90 mmHg. A list of 11 a priori selected chronic conditions was used to define multimorbidity. Multimorbidity was defined as having ≥1 long-term condition in addition to hypertension. Logistic regression models were used to estimate the association between multimorbidity (or individual long-term conditions) with uncontrolled BP. RESULTS: A total of 67 385 patients with hypertension were included. They had a mean age of 70, 53.1% were female, 80.6% had multimorbidity, and 35.7% had uncontrolled BP. Patients with multimorbidity had lower odds of uncontrolled BP than those without multimorbidity (adjusted OR = 0.72, 95% CI 0.68-0.76). Among the long-term conditions, diabetes (aOR = 0.73, 95%CI 0.70-0.77), heart failure (aOR = 0.81, 95%CI 0.73-0.91), ischemic heart disease (aOR = 0.74, 95%CI 0.69-0.79), schizophrenia (aOR = 0.79, 95%CI 0.65-0.97), depression/anxiety (aOR = 0.91, 95%CI 0.86-0.95), dementia (aOR = 0.87, 95%CI 0.80-0.95), and osteoarthritis (aOR = 0.89, 95%CI 0.85-0.93) were associated with a lower likelihood of uncontrolled BP. CONCLUSION: We found that multimorbidity was associated with better BP control. Several conditions were associated with better control, including diabetes, heart failure, ischemic heart disease, schizophrenia, depression/anxiety, dementia, and osteoarthritis.

Using ICD-9 diagnostic codes for external validation of topic models derived from primary care electronic medical record clinical text data.

Background/Objectives: Unsupervised topic models are often used to facilitate improved understanding of large unstructured clinical text datasets. In this study we investigated how ICD-9 diagnostic codes, collected alongside clinical text data, could be used to establish concurrent-, convergent- and discriminant-validity of learned topic models. Design/Setting: Retrospective open cohort design. Data were collected from primary care clinics located in Toronto, Canada between 01/01/2017 through 12/31/2020. Methods: We fit a non-negative matrix factorization topic model, with K = 50 latent topics/themes, to our input document term matrix (DTM). We estimated the magnitude of association between each Boolean-valued ICD-9 diagnostic code and each continuous latent topical vector. We identified ICD-9 diagnostic codes most strongly associated with each latent topical vector; and qualitatively interpreted how these codes could be used for external validation of the learned topic model. Results: The DTM consisted of 382,666 documents and 2210 words/tokens. We correlated concurrently assigned ICD-9 diagnostic codes with learned topical vectors, and observed semantic agreement for a subset of latent constructs (e.g. conditions of the breast, disorders of the female genital tract, respiratory disease, viral infection, eye/ear/nose/throat conditions, conditions of the urinary system, and dermatological conditions, etc.). Conclusions: When fitting topic models to clinical text corpora, researchers can leverage contemporaneously collected electronic medical record data to investigate the external validity of fitted latent variable models.

Health system use among patients with mental health conditions in a community based sample in Toronto, Canada: A retrospective cohort study.

OBJECTIVE: To identify hospital and primary care health service use among people with mental health conditions or addictions in an integrated primary-secondary care database in Toronto, Ontario. METHOD: This was a retrospective cohort study of adults with mental health diagnoses using data from the Health Databank Collaborative (HDC), a primary care-hospital linked database in Toronto. Data were included up to March 31st 2019. Negative binomial and logistic regression were used to evaluate associations between health care utilization and various patient characteristics and mental health diagnoses. RESULTS: 28,482 patients age 18 or older were included. The adjusted odds of at least one mental health diagnosis were higher among younger patients (18-30 years vs. 81+years aOR = 1.87; 95% CI:1.68-2.08) and among female patients (aOR = 1.35; 95% CI: 1.27-1.42). Patients with one or more mental health diagnoses had higher adjusted rates of hospital visits compared to those without any mental health diagnosis including addiction (aRR = 1.74, 95% CI: 1.58-1.91) and anxiety (aRR = 1.28, 95% CI: 1.23-1.32). 14.5% of patients with a psychiatric diagnosis were referred to the hospital for specialized psychiatric services, and 38% of patients referred were eventually seen in consultation. The median wait time from the date of referral to the date of consultation was 133 days. CONCLUSIONS: In this community, individuals with mental health diagnoses accessed primary and hospital-based health care at greater rates than those without mental health diagnoses. Wait times for specialized psychiatric care were long and most patients who were referred did not have a consultation. Information about services for patients with mental health conditions can be used to plan and monitor more integrated care across sectors, and ultimately improve outcomes.

Marginal Structural Models Using Calibrated Weights With SuperLearner: Application to Type II Diabetes Cohort.

As different scientific disciplines begin to converge on machine learning for causal inference, we demonstrate the application of machine learning algorithms in the context of longitudinal causal estimation using electronic health records. Our aim is to formulate a marginal structural model for estimating diabetes care provisions in which we envisioned hypothetical (i.e. counterfactual) dynamic treatment regimes using a combination of drug therapies to manage diabetes: metformin, sulfonylurea and SGLT-2i. The binary outcome of diabetes care provisions was defined using a composite measure of chronic disease prevention and screening elements [27] including (i) primary care visit, (ii) blood pressure, (iii) weight, (iv) hemoglobin A1c, (v) lipid, (vi) ACR, (vii) eGFR and (viii) statin medication. We used several statistical learning algorithms to describe causal relationships between the prescription of three common classes of diabetes medications and quality of diabetes care using the electronic health records contained in National Diabetes Repository. In particular, we generated an ensemble of statistical learning algorithms using the SuperLearner framework based on the following base learners: (i) least absolute shrinkage and selection operator, (ii) ridge regression, (iii) elastic net, (iv) random forest, (v) gradient boosting machines, and (vi) neural network. Each statistical learning algorithm was fitted using the pseudo-population generated from the marginalization of the time-dependent confounding process. Covariate balance was assessed using the longitudinal (i.e. cumulative-time product) stabilized weights with calibrated restrictions. Our results indicated that the treatment drop-in cohorts (with respect to metformin, sulfonylurea and SGLT-2i) may have improved diabetes care provisions in relation to treatment naïve (i.e. no treatment) cohort. As a clinical utility, we hope that this article will facilitate discussions around the prevention of adverse chronic outcomes associated with type II diabetes through the improvement of diabetes care provisions in primary care.

Specialist wait time reporting using family physicians' electronic medical record data: a mixed method study of feasibility and clinical utility.

BACKGROUND: More than 50% of Canadian adult patients wait longer than four weeks to see a specialist after referral from primary care. Access to accurate wait time information may help primary care physicians choose the timeliest specialist to address a patient's specific needs. We conducted a mixed-methods study to assess if primary to specialist care wait times can be extracted from electronic medical records (EMR), analyzed the wait time information, and used focus groups and interviews to assess the potential clinical utility of the wait time information. METHODS: Two family practices were recruited to examine primary care physician to specialist wait times between January 2016 and December 2017, using EMR data. The primary outcome was the median wait time from physician referral to specialist appointment for each specialty service. Secondary outcomes included the physician and patient characteristics associated with wait times as well as qualitative analyses of physician interviews about the resulting wait time reports. RESULTS: Wait time data can be extracted from the primary care EMR and converted to a report format for family physicians and specialists to review. After data cleaning, there were 7141 referrals included from 4967 unique patients. The 5 most common specialties referred to were Dermatology, Gastroenterology, Ear Nose and Throat, Obstetrics and Gynecology and Urology. Half of the patients were seen by a specialist within 42 days, 75% seen within 80 days and all patients within 760 days. There were significant differences in wait times by specialty, for younger patients, and those with urgently labelled medical situations. Overall, wait time reports were perceived by clinicians to be important since they could help family physicians decide how to triage referrals and might lead to system improvements. CONCLUSIONS: Wait time information from primary to specialist care can aid in decision-making around specialist referrals, identify bottlenecks, and help with system planning. This mixed method study is a starting point to review the importance of providing wait time data for both family physicians, specialists and local health systems. Future work can be directed towards developing wait time reporting functionality and evaluating if wait time information will help increase system efficiency and/or improve provider and patient satisfaction.

Primary Care Severe Asthma Registry and Education Project (PCSAR-EDU): Phase 1 - an e-Delphi for registry definitions and indices of clinician behaviour.

INTRODUCTION: Although most asthma is mild to moderate, severe asthma accounts for disproportionate personal and societal costs. Poor co-ordination of care between primary care and specialist settings is recognised as a barrier to achieving optimal outcomes. The Primary Care Severe Asthma Registry and Education (PCSAR-EDU) project aims to address these gaps through the interdisciplinary development and evaluation of both a 'real-world' severe asthma registry and an educational programme for primary care providers. This manuscript describes phase 1 of PCSAR-EDU which involves establishing interdisciplinary consensus on criteria for the: (1) definition of severe asthma; (2) generation of a severe asthma registry and (3) definition of an electronic-medical record data-based Clinician Behaviour Index (CBI). METHODS AND ANALYSIS: In phase 1, a modified e-Delphi activity will be conducted. Delphi panellists (n≥13) will be invited to complete a 30 min online survey on three separate occasions (i.e., three separate e-Delphi 'rounds') over a 3-month period. Expert opinion will be collected via an open-ended survey ('Open' round 1) and 5-point Likert scale and ranking surveys ('Closed' round 2 and 3). A fourth and final Delphi round will occur via synchronous meeting, whereby panellists approve a finalised ideal 'core criteria list', CBI and corresponding item weighting. ETHICS AND DISSEMINATION: Ethical approval has been obtained for the activities involved in phase 1 from the University of Toronto's Human Research Ethics Programme (approval number 39695). Future ethics approvals will depend on information gathered in the proceeding phase; thus, ethical approval for phase 2 and 3 of this study will be sought sequentially. Findings will be disseminated through conference presentations, peer-reviewed publications and knowledge translation tools.

Non-negative matrix factorization temporal topic models and clinical text data identify COVID-19 pandemic effects on primary healthcare and community health in Toronto, Canada.

OBJECTIVE: To demonstrate how non-negative matrix factorization can be used to learn a temporal topic model over a large collection of primary care clinical notes, characterizing diverse COVID-19 pandemic effects on the physical/mental/social health of residents of Toronto, Canada. MATERIALS AND METHODS: The study employs a retrospective open cohort design, consisting of 382,666 primary care progress notes from 44,828 patients, 54 physicians, and 12 clinics collected 01/01/2017 through 31/12/2020. Non-negative matrix factorization uncovers a meaningful latent topical structure permeating the corpus of primary care notes. The learned latent topical basis is transformed into a multivariate time series data structure. Time series methods and plots showcase the evolution/dynamics of learned topics over the study period and allow the identification of COVID-19 pandemic effects. We perform several post-hoc checks of model robustness to increase trust that descriptive/unsupervised inferences are stable over hyper-parameter configurations and/or data perturbations. RESULTS: Temporal topic modelling uncovers a myriad of pandemic-related effects from the expressive clinical text data. In terms of direct effects on patient-health, topics encoding respiratory disease symptoms display altered dynamics during the pandemic year. Further, the pandemic was associated with a multitude of indirect patient-level effects on topical domains representing mental health, sleep, social and familial dynamics, measurement of vitals/labs, uptake of prevention/screening maneuvers, and referrals to medical specialists. Finally, topic models capture changes in primary care practice patterns resulting from the pandemic, including changes in EMR documentation strategies and the uptake of telemedicine. CONCLUSION: Temporal topic modelling applied to a large corpus of rich primary care clinical text data, can identify a meaningful topical/thematic summarization which can provide policymakers and public health stakeholders a passive, cost-effective, technology for understanding holistic impacts of the COVID-19 pandemic on the primary healthcare system and community/public-health.

Using Primary Care Clinical Text Data and Natural Language Processing to Identify Indicators of COVID-19 in Toronto, Canada.

The objective of this study was to investigate whether a rule-based natural language processing (NLP) system, applied to primary care clinical text data, could be used to monitor COVID-19 viral activity in Toronto, Canada. We employed a retrospective cohort design. We included primary care patients with a clinical encounter between January 1, 2020 and December 31, 2020 at one of 44 participating clinical sites. During the study timeframe, Toronto first experienced a COVID-19 outbreak between March-2020 and June-2020; followed by a second viral resurgence from October-2020 through December-2020. We used an expert derived dictionary, pattern matching tools and contextual analyzer to classify primary care documents as 1) COVID-19 positive, 2) COVID-19 negative, or 3) unknown COVID-19 status. We applied the COVID-19 biosurveillance system across three primary care electronic medical record text streams: 1) lab text, 2) health condition diagnosis text and 3) clinical notes. We enumerated COVID-19 entities in the clinical text and estimated the proportion of patients with a positive COVID-19 record. We constructed a primary care COVID-19 NLP-derived time series and investigated its correlation with independent/external public health series: 1) lab confirmed COVID-19 cases, 2) COVID-19 hospitalizations, 3) COVID-19 ICU admissions, and 4) COVID-19 intubations. A total of 196,440 unique patients were observed over the study timeframe, of which 4,580 (2.3%) had at least one positive COVID-19 document in their primary care electronic medical record. Our NLP-derived COVID-19 time series describing the temporal dynamics of COVID-19 positivity status over the study timeframe demonstrated a pattern/trend which strongly mirrored that of other external public health series under investigation. We conclude that primary care text data passively collected from electronic medical record systems represent a high quality, low-cost source of information for monitoring/surveilling COVID-19 impacts on community health.

Implementation of targeted screening for poverty in a large primary care team in Toronto, Canada: a feasibility study.

BACKGROUND: Poverty has a significant influence on health. Efforts to optimize income and reduce poverty could make a difference to the lives of patients and their families. Routine screening for poverty in primary care is an important first step but rarely occurs in Canada. We aimed to implement a targeted screening and referral process in a large, distributed primary care team in Toronto, Ontario, Canada. The main outcome was the proportion of targeted patients screened. METHODS: This implementation evaluation was conducted with a large community-based primary care team in north Toronto. The primary care team serves relatively wealthy neighborhoods with pockets of poverty. Physicians were invited to participate. We implemented targeted screening by combining census information on neighborhood-level deprivation with postal codes in patient records. For physicians agreeing to participate, we added prompts to screen for poverty to the charts of adult patients living in the most deprived areas. Standardized electronic medical record templates recommended a referral to a team case worker for income optimization, for those patients screening positive. We recorded the number and percentages of participants at each stage, from screening to receiving advice on income optimization. RESULTS: 128 targeted patients with at least one visit (25%) were screened. The primary care team included 86 physicians distributed across 19 clinical locations. Thirty-four physicians (39%) participated. Their practices provided care for 27,290 patients aged 18 or older; 852 patients (3%) were found to be living in the most deprived neighborhoods. 509 (60%) had at least one office visit over the 6 months of follow up. 25 patients (20%) screened positive for poverty, and 13 (52%) were referred. Eight patients (62% of those referred) were ultimately seen by a caseworker for income optimization. CONCLUSIONS: We implemented a targeted poverty screening program combined with resources to optimize income for patients in a large, distributed community-based primary care team. Screening was feasible; however, only a small number of patients were linked to the intervention Further efforts to scale and spread screening and mitigation of poverty are warranted; these should include broadening the targeted population beyond those living in the most deprived areas.

Over-use of thyroid testing in Canadian and UK primary care in frequent attenders: A cross-sectional study.

BACKGROUND: Thyroid-stimulating hormone (TSH) is a common test used to detect and monitor clinically significant hypo- and hyperthyroidism. Population-based screening of asymptomatic adults for thyroid disorders is not recommended. OBJECTIVE: The research objectives were to determine patterns of TSH testing in Canadian and English primary care practices, as well as patient and physician practice characteristics associated with testing TSH for primary care patients with no identifiable indication. METHODS: In this 2-year cross-sectional observational study, Canadian and English electronic medical record databases were used to identify patients and physician practices. Cohorts of patients aged 18 years or older, without identifiable indications for TSH testing, were generated from these databases. Analyses were performed using a random-effects logistic regression to determine patient and physician practice characteristics associated with increased testing. We determined the proportion of TSH tests performed concurrently with at least one common screening blood test (lipid profile or hemoglobin A1c). Standardised proportions of TSH test per family practice were used to examine the heterogeneity in the populations. RESULTS: At least one TSH test was performed in 35.97% (N = 489 663) of Canadian patients and 29.36% (N = 1 030 489) of English patients. Almost all TSH tests in Canada and England (95.69% and 99.23% respectively) were within the normal range (0.40-5.00 mU/L). A greater number of patient-physician encounters was the strongest predictor of TSH testing. It was determined that 51.40% of TSH tests in Canada and 76.55% in England were performed on the same day as at least one other screening blood test. There was no association between the practice size and proportion of asymptomatic patients tested. CONCLUSIONS: This comparative binational study found TSH patterns suggestive of over-testing and potentially thyroid disorder screening in both countries. There may be significant opportunities to improve the appropriateness of TSH ordering in Canada and England and therefore improve the allocation of limited system resources.

Trends in diabetes medication use in Australia, Canada, England, and Scotland: a repeated cross-sectional analysis in primary care.

BACKGROUND: Several new classes of glucose-lowering medications have been introduced in the past two decades. Some, such as sodium-glucose cotransporter 2 inhibitors (SGLT2s), have evidence of improved cardiovascular outcomes, while others, such as dipeptidyl peptidase-4 inhibitors (DPP4s), do not. It is therefore important to identify their uptake in order to find ways to support the use of more effective treatments. AIM: To analyse the uptake of these new classes among patients with type 2 diabetes. DESIGN AND SETTING: This was a retrospective repeated cross-sectional analysis in primary care. Rates of medication uptake in Australia, Canada, England, and Scotland were compared. METHOD: Primary care Electronic Medical Data on prescriptions (Canada, UK) and dispensing data (Australia) from 2012 to 2017 were used. Individuals aged ≥40 years on at least one glucose-lowering drug class in each year of interest were included, excluding those on insulin only. Proportions of patients in each nation, for each year, on each class of medication, and on combinations of classes were determined. RESULTS: Data from 238 619 patients were included in 2017. The proportion of patients on sulfonylureas (SUs) decreased in three out of four nations, while metformin decreased in Canada. Use of combinations of metformin and new drug classes increased in all nations, replacing combinations involving SUs. In 2017, more patients were on DPP4s (between 19.1% and 27.6%) than on SGLT2s (between 10.1% and 15.3%). CONCLUSION: New drugs are displacing SUs. However, despite evidence of better outcomes, the adoption of SGLT2s lagged behind DPP4s.

Cardiovascular risk factor documentation and management in primary care electronic medical records among people with schizophrenia in Ontario, Canada: retrospective cohort study.

OBJECTIVES: In order to address the substantial increased risk of cardiovascular disease among people with schizophrenia, it is necessary to identify the factors responsible for some of that increased risk. We analysed the extent to which these risk factors were documented in primary care electronic medical records (EMR), and compared their documentation by patient and provider characteristics. DESIGN: Retrospective cohort study. SETTING: EMR database of the University of Toronto Practice-Based Research Network Data Safe Haven. PARTICIPANTS: 197 129 adults between 40 and 75 years of age; 4882 with schizophrenia and 192 427 without. PRIMARY AND SECONDARY OUTCOME MEASURES: Documentation of cardiovascular disease risk factors (age, sex, smoking history, presence of diabetes, blood pressure, whether a patient is currently on medication to reduce blood pressure, total cholesterol and high-density lipoprotein cholesterol). RESULTS: Documentation of cardiovascular risk factors was more complete among people with schizophrenia (74.5% of whom had blood pressure documented at least once in the last 2 years vs 67.3% of those without, p>0.0001). Smoking status was not documented in 19.8% of those with schizophrenia and 20.8% of those without (p=0.0843). Factors associated with improved documentation included older patients (OR for ages 70-75 vs 45-49=3.51, 95% CI 3.26 to 3.78), male patients (OR=1.39, 95% CI 1.33 to 1.45), patients cared for by a female provider (OR=1.52, 95% CI 1.12 to 2.07) and increased number of encounters (OR for ≥10 visits vs 3-5 visits=1.53, 95% CI 1.46 to 1.60). CONCLUSIONS: Documentation of cardiovascular risk factors was better among people with schizophrenia than without, although overall documentation was inadequate. Efforts to improve documentation of risk factors are warranted in order to facilitate improved management.

Choosing Wisely Canada campaign associated with less overuse of thyroid testing: Retrospective parallel cohort study.

OBJECTIVE: To assess the effectiveness of a Choosing Wisely Canada (CWC) initiative to improve thyroid-stimulating hormone (TSH) test ordering for patients with no identified indication for this test. DESIGN: Retrospective parallel cohort study using routinely collected electronic medical record (EMR) data. The CWC initiative included supporting primary care leads in each participating family health team, providing education on better test ordering, and allowing adaptation appropriate to each local context. SETTING: Toronto, Ont, and surrounding areas. PARTICIPANTS: Family physicians contributing EMR data to the University of Toronto Practice-Based Research Network and their patients aged 18 or older. MAIN OUTCOME MEASURES: Proportion of adult patients with a TSH test done in a 2-year period (2016 to 2017) in the absence of EMR data with an indication for TSH testing; proportion of TSH test results in the normal range for those patients; and change in the rate of TSH screening in sites participating in the CWC initiative compared with sites not participating. RESULTS: A total of 150 944 patients (51.7% of studied adults) had no identified indication for TSH testing; 33.4% of those patients were seen by physicians in the family health teams participating in the CWC initiative. Overall, 35.1% of all patients with no identified indication had at least 1 TSH test between January 1, 2016, and December 31, 2017. The 119 physicians participating in the CWC initiative decreased their monthly rate of testing by 0.23% from 2016 to 2017, a relative reduction of 13.2%. The 233 physicians not participating decreased testing by 0.04%, a relative reduction of 1.8%. The monthly difference between the 2 groups was 0.19% (95% CI -0.02 to -0.35 P = .03), a relative difference of 11.4%. The TSH testing decreased for almost all CWC patient subgroups. More than 95% of patients tested in both groups had TSH results in the normal range. CONCLUSION: This study found high rates of TSH testing without identified indications in the practices studied. A CWC initiative implemented in primary care was effective in reducing TSH testing.

Trends in end digit preference for blood pressure and associations with cardiovascular outcomes in Canadian and UK primary care: a retrospective observational study.

OBJECTIVES: To study systematic errors in recording blood pressure (BP) as measured by end digit preference (EDP); to determine associations between EDP, uptake of Automated Office BP (AOBP) machines and cardiovascular outcomes. DESIGN: Retrospective observational study using routinely collected electronic medical record data from 2006 to 2015 and a survey on year of AOBP acquisition in Toronto, Canada in 2017. SETTING: Primary care practices in Canada and the UK. PARTICIPANTS: Adults aged 18 years or more. MAIN OUTCOME MEASURES: Mean rates of EDP and change in rates. Rates of EDP following acquisition of an AOBP machine. Associations between site EDP levels and mean BP. Associations between site EDP levels and frequency of cardiovascular outcomes. RESULTS: 707 227 patients in Canada and 1 558 471 patients in the UK were included. From 2006 to 2015, the mean rate of BP readings with both systolic and diastolic pressure ending in zero decreased from 26.6% to 15.4% in Canada and from 24.2% to 17.3% in the UK. Systolic BP readings ending in zero decreased from 41.8% to 32.5% in the 3 years following the purchase of an AOBP machine. Sites with high EDP had a mean systolic BP of 2.0 mm Hg in Canada, and 1.7 mm Hg in the UK, lower than sites with no or low EDP. Patients in sites with high levels of EDP had a higher frequency of stroke (standardised morbidity ratio (SMR) 1.15, 95% CI 1.12 to 1.17), myocardial infarction (SMR 1.16, 95% CI 1.14 to 1.19) and angina (SMR 1.25, 95% CI 1.22 to 1.28) than patients in sites with no or low EDP. CONCLUSIONS: Acquisition of an AOBP machine was associated with a decrease in EDP levels. Sites with higher rates of EDP had lower mean BPs and a higher frequency of adverse cardiovascular outcomes. The routine use of manual office-based BP measurement should be reconsidered.

Agreement between primary care and hospital diagnosis of schizophrenia and bipolar disorder: A cross-sectional, observational study using record linkage.

People with serious mental illness die 10-25 years sooner than people without these conditions. Multiple challenges to accessing and benefitting from healthcare have been identified amongst this population, including a lack of coordination between mental health services and general health services. It has been identified in other conditions such as diabetes that accurate documentation of diagnosis in the primary care chart is associated with better quality of care. It is suspected that if a patient admitted to the hospital with serious mental illness is then discharged without adequate identification of their diagnosis in the primary care setting, follow up (such as medication management and care coordination) may be more difficult. We identified cohorts of patients with schizophrenia and bipolar disorder who accessed care through the North York Family Health Team (a group of 77 family physicians in Toronto, Canada) and North York General Hospital (a large community hospital) between January 1, 2012 and December 31, 2014. We identified whether labeling for these conditions was concordant between the two settings and explored predictors of concordant labeling. This was a retrospective cross-sectional study using de-identified data from the Health Databank Collaborative, a linked primary care-hospital database. We identified 168 patients with schizophrenia and 370 patients with bipolar disorder. Overall diagnostic concordance between primary care and hospital records was 23.2% for schizophrenia and 15.7% for bipolar disorder. Concordance was higher for those with multiple (2+) inpatient visits (for schizophrenia: OR 2.42; 95% CI 0.64-9.20 and for bipolar disorder: OR 8.38; 95% CI 3.16-22.22). Capture-recapture modeling estimated that 37.4% of patients with schizophrenia (95% CI 20.7-54.1) and 39.6% with bipolar disorder (95% CI 25.7-53.6) had missing labels in both settings when adjusting for patients' age, sex, income quintiles and co-morbidities. In this sample of patients accessing care at a large family health team and community hospital, concordance of diagnostic information about serious mental illness was low. Interventions should be developed to improve diagnosis and continuity of care across multiple settings.

Impact of the Diabetes Canada Guideline Dissemination Strategy on the Prescription of Vascular Protective Medications: A Retrospective Cohort Study, 2010-2015.

OBJECTIVE: The 2013 Diabetes Canada guidelines launched targeted dissemination tools and a simple assessment for vascular protection. We aimed to 1) examine changes associated with the launch of the 2013 guidelines and additional dissemination efforts in the rates of vascular protective medications prescribed in primary care for older patients with diabetes and 2) examine differences in the rates of prescriptions of vascular protective medications by patient and provider characteristics. RESEARCH DESIGN AND METHODS: The study population included patients (≥40 years of age) from the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) with type 2 diabetes and at least one clinic visit from April 2010 to December 2015. An interrupted time series analysis was used to assess the proportion of eligible patients prescribed a statin, ACE inhibitor (ACEI)/angiotensin receptor blocker (ARB), or antiplatelet prescription in each quarter. Proton pump inhibitor (PPI) prescriptions were the reference control. RESULTS: A dynamic cohort was used where participants were enrolled each quarter using a prespecified set of conditions (range 25,985-70,693 per quarter). There were no significant changes in statin (P = 0.43), ACEI/ARB (P = 0.42), antiplatelet (P = 0.39), or PPI (P = 0.16) prescriptions at baseline (guideline intervention). After guideline publication, there was a significant change in slope for statin (-0.52% per quarter, SE 0.15, P < 0.05), ACEI/ARB (-0.38% per quarter, SE 0.13, P < 0.05), and reference PPI (-0.18% per quarter, SE 0.05, P < 0.05) prescriptions. CONCLUSIONS: There was a decrease in prescribing trends over time that was not specific to vascular protective medications. More effective knowledge translation strategies are needed to improve vascular protection in diabetes in order for patients to receive the most effective interventions.

Agreement between hospital and primary care on diagnostic labeling for COPD and heart failure in Toronto, Canada: a cross-sectional observational study.

Patients with chronic obstructive pulmonary disease (COPD) or heart failure (HF) are frequently cared for in hospital and in primary care settings. We studied labeling agreement for COPD and HF for patients seen in both settings in Toronto, Canada. This was a retrospective observational study using linked hospital-primary care electronic data from 70 family physicians. Patients were 20 years of age or more and had at least one visit in both settings between 1 January 2012 and 31 December 2014. We recorded labeling concordance and associations with clinical factors. We used capture-recapture models to estimate the size of the populations. COPD concordance was 34%; the odds ratios (ORs) of concordance increased with aging (OR 1.84 for age 75+ vs. <65, 95% CI 0.92-3.69) and more inpatient admissions (OR 2.89 for 3+ visits vs. 0 visits, 95% CI 1.59-5.26). HF concordance was 33%; the ORs of concordance decreased with aging (OR 0.39 for 75+ vs. <65, 95% CI 0.18-0.86) and increased with more admissions (OR = 2.39; 95% CI 1.33-4.30 for 3+ visits vs. 0 visits). Based on capture-recapture models, 21-24% additional patients with COPD and 18-20% additional patients with HF did not have a label in either setting. The primary care prevalence was estimated as 748 COPD patients and 834 HF patients per 100,000 enrolled adult patients. Agreement levels for COPD and HF were low and labeling was incomplete. Further research is needed to improve labeling for these conditions.

Would you like to add a weight after this blood pressure, doctor? Discovery of potentially actionable associations between the provision of multiple screens in primary care.

RATIONALE, AIMS, AND OBJECTIVE: Guidelines recommend screening for risk factors associated with chronic diseases but current electronic prompts have limited effects. Our objective was to discover and rank associations between the presence of screens to plan more efficient prompts in primary care. METHODS: Risk factors with the greatest impact on chronic diseases are associated with blood pressure, body mass index, waist circumference, glycaemic and lipid levels, smoking, alcohol use, diet, and exercise. We looked for associations between the presence of screens for these in electronic medical records. We used association rule mining to describe relationships among items, factor analysis to find latent categories, and Cronbach α to quantify consistency within latent categories. RESULTS: Data from 92 140 patients in or around Toronto, Ontario, were included. We found positive correlations (lift >1) between the presence of all screens. The presence of any screen was associated with confidence greater than 80% that other data on items with high prevalence (blood pressure, glycaemic and lipid levels, or smoking) would also be present. A cluster of rules predicting the presence of blood pressure were ranked highest using measures of interestingness such as standardized lift. We found 3 latent categories using factor analysis; these were laboratory tests, vital signs, and lifestyle factors; Cronbach α ranged between .58 for lifestyle factors and .88 for laboratory tests. CONCLUSIONS: Associations between the provision of important screens can be discovered and ranked. Rules with promising combinations of associated screens could be used to implement data driven alerts.

Is glycemia control in Canadians with diabetes individualized? A cross-sectional observational study.

OBJECTIVE: Diabetes guidelines recommend individualized glycemic targets: tighter control in younger, healthier patients and consideration of more moderate control in the elderly and those with coexisting illnesses. Our objective was to examine whether glycemic control varied by age and comorbidities in Canadian primary care. RESEARCH DESIGN AND METHODS: Cross-sectional study using data from the electronic medical records of 537 primary care providers across Canada; 30 416 patients with diabetes, aged 40 or above, with at least one encounter and one hemoglobin A1c (HbA1c) measurement between 1 January 2012 and 31 December 2013. The outcome was the most recent HbA1c, categorized into three levels of control: tight (<7.0% or <53 mmol/mol), moderate (7.0%-8.5%, 53 mmol/mol-69.5 mmol/mol) and uncontrolled (>8.5% or >69.5 mmol/mol). We adjusted for several factors associated with glycemic control including treatment intensity. RESULTS: Younger patients (aged 40-49) were more likely to have moderate as opposed to tight control than the older patients (aged 80+) (OR 1.28; 95% CI 1.11 to 1.49, p=0.001). The youngest were also more likely to have uncontrolled as opposed to moderately controlled glycemia (OR 3.39; 95% CI 2.75 to 4.17, p<0.0001). Patients with no or only one comorbidity were more likely to have moderate as opposed to tight control than those with three or more comorbidities (OR 1.66;95% CI 1.46 to 1.90, p<0.0001). CONCLUSIONS: Levels of glycemic control, given age and comorbidities appear to differ from guideline recommendations. Research is needed to understand these discrepancies and develop methods to assist providers in personalizing glycemic targets.