Disruptions in Primary Care among People with Schizophrenia in Ontario, Canada, During the COVID-19 Pandemic.

OBJECTIVE: To investigate how primary care access, intensity and quality of care changed among patients living with schizophrenia before and after the onset of the COVID-19 pandemic in Ontario, Canada. METHODS: This cohort study was performed using primary care electronic medical record data from the University of Toronto Practice-Based Research Network (UTOPIAN), a network of > 500 family physicians in Ontario, Canada. Data were collected during primary care visits from 2643 patients living with schizophrenia. Rates of primary care health service use (in-person and virtual visits with family physicians) and key preventive health indices indicated in antipsychotic monitoring (blood pressure readings, hemoglobin A1c, cholesterol and complete blood cell count [CBC] tests) were measured and compared in the 12 months before and after onset of the COVID-19 pandemic. RESULTS: Access to in-person care dropped with the onset of the COVID-19 pandemic. During the first year of the pandemic only 39.5% of patients with schizophrenia had at least one in-person visit compared to 81.0% the year prior. There was a corresponding increase in virtual visits such that 78.0% of patients had a primary care appointment virtually during the pandemic period. Patients prescribed injectable antipsychotics were more likely to continue having more frequent in-person appointments during the pandemic than patients prescribed only oral or no antipsychotic medications. The proportion of patients who did not have recommended tests increased from 41.0% to 72.4% for blood pressure readings, from 48.9% to 60.2% for hemoglobin A1c, from 57.0% to 67.8% for LDL cholesterol and 45.0% to 56.0% for CBC tests during the pandemic. CONCLUSIONS: There were substantial decreases in preventive care after the onset of the pandemic, although primary care access was largely maintained through virtual care. Addressing these deficiencies will be essential to promoting health equity and reducing the risk of poor health outcomes.

Evaluation of Electronic Medical Record Administrative data Linked Database (EMRALD).

BACKGROUND: Primary care electronic medical records (EMRs) represent a potentially rich source of information for research and evaluation. OBJECTIVE: To assess the completeness of primary care EMR data compared with administrative data. STUDY DESIGN: Retrospective comparison of provincial health-related administrative databases and patient records for more than 50,000 patients of 54 physicians in 15 geographically distinct clinics in Ontario, Canada, contained in the Electronic Medical Record Administrative data Linked Database (EMRALD). METHODS: Physician billings, laboratory tests, medications, specialist consultation letters, and hospital discharges captured in EMRALD were compared with health-related administrative data in a universal access healthcare system. RESULTS: The mean (standard deviation [SD]) percentage of clinic primary care outpatient visits captured in EMRALD compared with administrative data was 94.4% (4.88%). Consultation letters from specialists for first consultations and for hospital discharges were captured at a mean (SD) rate of 72.7% (7.98%) and 58.5% (15.24%), respectively, within 30 days of the occurrence. The mean (SD) capture within EMRALD of the most common laboratory tests billed and the most common drugs dispensed was 67.3% (21.46%) and 68.2% (8.32%), respectively, for all clinics. CONCLUSIONS: We found reasonable capture of information within the EMR compared with administrative data, with the advantage in the EMR of having actual laboratory results, prescriptions for patients of all ages, and detailed clinical information. However, the combination of complete EMR records and administrative data is needed to provide a full comprehensive picture of patient health histories and processes, and outcomes of care.

Diabetics can be identified in an electronic medical record using laboratory tests and prescriptions.

OBJECTIVE: With the increasing use of electronic medical records (EMRs) comes the potential to efficiently evaluate and improve quality of care. We set out to determine if diabetics could be accurately identified using structured data contained within an EMR. STUDY DESIGN AND SETTING: We used a 5% random sample of adult patients (969 patients) within a convenience sample of 17 primary care physicians using Practices Solutions EMR in Ontario. A reference standard of diabetes status was manually confirmed by reviewing each patient's record. Accuracy for identifying people with diabetes was assessed using various combinations of laboratory tests and prescriptions. EMR data was also compared with administrative data. RESULTS: A rule of one elevated blood sugar or a prescription for an antidiabetic medication had a 83.1% sensitivity, 98.2% specificity, 80.0% positive predictive value (PPV) and 98.5% negative predictive value (NPV) compared with the reference standard of diabetes status. CONCLUSION: We found that the use of structured data within an EMR could be used to identify patients with diabetes. Our results have positive implications for policy makers, researchers, and clinicians as they develop registries of diabetic patients to examine quality of care using EMR data.

Validation of physician billing and hospitalization data to identify patients with ischemic heart disease using data from the Electronic Medical Record Administrative data Linked Database (EMRALD).

BACKGROUND: Reporting of ischemic heart disease (IHD) prevalence in Canada has been based on self-report or patients presenting to hospital. However, IHD often presents and can be managed in the outpatient setting. OBJECTIVES: To determine whether the combination of hospital data and physician billings could accurately identify patients with IHD. METHODS: A random sample of 969 adult patients from the Electronic Medical Record Administrative data Linked Database (EMRALD) - an electronic medical record database of primary care physicians in Ontario linked to administrative data for the province of Ontario - was used. A number of combinations of physician billing and hospital discharge abstracts were tested to determine the accuracy of using administrative data to identify IHD patients. RESULTS: Two physician billings within a one-year period (with one of the billings by a specialist or a family physician in a hospital or emergency room setting) or a hospital discharge abstract gave a sensitivity of 77.0% (95% CI 68.2% to 85.9%), a specificity of 98.0% (95% CI 97.0% to 98.9%), a positive predictive value of 78.8% (95% CI 70.1% to 87.5%), a negative predictive value of 97.7% (95% CI 96.8% to 98.7%) and a kappa of 0.76 (95% CI 0.68 to 0.83). CONCLUSIONS: A combination of physician billing and hospital discharge abstracts can be used to identify patients with IHD. Population prevalence of IHD can be measured using administrative data.

HISTORIQUE : Les taux de prévalence de cardiopathie ischémique (CPI) au Canada se fondent sur l'autoévaluation de patients qui consultent à l'hôpital. Cependant, la CPI est fréquente et peut être traitée en consultations externes. OBJECTIFS : Déterminer si l'association de données hospitalières et de facturation des médecins permettrait de dépister avec précision les patients ayant une CPI. MÉTHODOLOGIE : Les chercheurs ont utilisé un échantillon aléatoire de 969 patients adultes de la base de données EMRALD liée aux données administratives des dossiers médicaux électroniques, une base de données électronique des dossiers médicaux des médecins de premier recours de l'Ontario liée aux données administratives de la province de l'Ontario. Ils ont vérifié plusieurs associations de facturation et de registres de sorties des hôpitaux pour déterminer l'exactitude des données administratives pour dépister les patients ayant une CPI. RÉSULTATS : Deux modes de facturation de médecins au cours d'une période d'un an (l'une provenant des facturations d'un spécialiste ou d'un médecin de famille en milieu hospitalier ou au département d'urgence) ou un registre de sorties des hôpitaux ont assuré une sensibilité de 77,0 % (95 % IC 68,2 % à 85,9 %), une spécificité de 98,0 % (95 % IC 97,0 % à 98,9 %), une valeur prédictive positive de 78,8 % (95 % IC 70,1 % à 87,5 %), une valeur prédictive négative de 97,7 % (95 % IC 96,8 % à 98,7 %) et un kappa de 0,76 (95 % IC 0,68 à 0,83). CONCLUSION : Une association de facturation des médecins et de registres de sorties des hôpitaux peut permettre de dépister les patients ayant une CPI. On peut mesurer la prévalence de CPI en population au moyen de données administratives.

De-identification of primary care electronic medical records free-text data in Ontario, Canada.

BACKGROUND: Electronic medical records (EMRs) represent a potentially rich source of health information for research but the free-text in EMRs often contains identifying information. While de-identification tools have been developed for free-text, none have been developed or tested for the full range of primary care EMR data METHODS: We used deid open source de-identification software and modified it for an Ontario context for use on primary care EMR data. We developed the modified program on a training set of 1000 free-text records from one group practice and then tested it on two validation sets from a random sample of 700 free-text EMR records from 17 different physicians from 7 different practices in 5 different cities and 500 free-text records from a group practice that was in a different city than the group practice that was used for the training set. We measured the sensitivity/recall, precision, specificity, accuracy and F-measure of the modified tool against manually tagged free-text records to remove patient and physician names, locations, addresses, medical record, health card and telephone numbers. RESULTS: We found that the modified training program performed with a sensitivity of 88.3%, specificity of 91.4%, precision of 91.3%, accuracy of 89.9% and F-measure of 0.90. The validations sets had sensitivities of 86.7% and 80.2%, specificities of 91.4% and 87.7%, precisions of 91.1% and 87.4%, accuracies of 89.0% and 83.8% and F-measures of 0.89 and 0.84 for the first and second validation sets respectively. CONCLUSION: The deid program can be modified to reasonably accurately de-identify free-text primary care EMR records while preserving clinical content.

Trends in risk factors for cardiovascular disease in Canada: temporal, socio-demographic and geographic factors.

BACKGROUND: Temporal trends in risk factors for cardiovascular disease and the impact of socio-economic status on these risk factors remain unclear. METHODS: Using data from the National Population Health Survey and the Canadian Community Health Survey, we examined national trends in heart disease, hypertension, diabetes mellitus, obesity and smoking prevalence from 1994 to 2005, adjusting for age and sex. We stratified data by income adequacy category, body mass index and region of residence. RESULTS: An estimated 1.29 million Canadians reported having heart disease in 2005, representing increases of 19% for men and 2% for women, relative to 1994. Heart disease increased significantly in the lowest income category (by 27%), in the lower middle income category (by 37%) and in the upper middle income category (by 12%); however, it increased by only 6% in the highest income group. Diabetes increased in all but the highest income group: by 56% in the lowest income group, by 93% in the lower middle income group and by 59% in the upper middle income group. Hypertension increased in all income groups: by 85% in the lowest income group, by 80% in the lower middle income group, by 91% in the upper middle income group and by 117% in the highest income group. Obesity also increased in all income groups: by 20% in the lowest income group, by 25% in the lower middle income group, by 33% in the upper middle income group and by 37% in the highest income group. In addition to socio-economic status, obesity and overweight also modified the trends in risk factors. Diabetes increased to a greater extent among obese participants (61% increase) and overweight participants (25% increase), as did hypertension, which increased by 80% among obese individuals and by 74% among overweight individuals. Trends in diabetes, hypertension and obesity were consistent for all provinces. INTERPRETATION: During the study period, heart disease, hypertension, diabetes and obesity increased for all or most income groups in Canada. Further interventions supporting modification of lifestyle and risk factors are needed to prevent future cardiovascular disease.