Abstract

BackgroundHypertension is a common chronic condition affecting nearly a quarter of Canadians. Hypertension surveillance in Canada typically relies on administrative data and/or national surveys. Routinely-captured data from primary care electronic medical records (EMRs) are a complementary source for chronic disease surveillance, with longitudinal patient-level details such as sociodemographics, blood pressure, weight, prescribed medications, and behavioural risk factors. As EMR data are generated from patient care and administrative tasks, assessing data quality is essential before using for secondary purposes. This study evaluated the quality of primary care EMR data from one province in Canada within the context of hypertension surveillance.MethodsWe conducted a cross-sectional, descriptive study using primary care EMR data collected by two practice-based research networks in Alberta, Canada. There were 48,377 adults identified with hypertension from 53 clinics as of June 2018. Summary statistics were used to examine the quality of data elements considered relevant for hypertension surveillance.ResultsPatient year of birth and sex were complete, but other sociodemographic information (ethnicity, occupation, education) was largely incomplete and highly variable. Height, weight, body mass index and blood pressure were complete for most patients (over 90%), but a small proportion of outlying values indicate data inaccuracies were present. Most patients had a relevant laboratory test present (e.g. blood glucose/glycated hemoglobin, lipid profile), though a very small proportion of values were outside a biologically plausible range. Details of prescribed antihypertensive medication, such as start date, strength, dose, frequency, were mostly complete. Nearly 80% of patients had a smoking status recorded, though only 66% had useful information (i.e. categorized as current, past, or never), and less than half had their alcohol use described; information related to amount, frequency or duration was not available.ConclusionsBlood pressure and prescribed medications in primary care EMR data demonstrated good completeness and plausibility, and contribute valuable information for hypertension epidemiology and surveillance. The use of other clinical, laboratory, and sociodemographic variables should be used carefully due to variable completeness and suspected data errors. Additional strategies to improve these data at the point of entry and after data extraction (e.g. statistical methods) are required.

Highlights

  • Hypertension is a common chronic condition affecting nearly a quarter of Canadians

  • The use of other clinical, laboratory, and sociodemographic variables should be used carefully due to variable completeness and suspected data errors

  • In the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) data for Alberta, there were 205,364 adult patients who had at least one primary care encounter in the previous two years; of these, 48,377 patients were identified with hypertension and who were not labelled ‘inactive’ at the practice or deceased

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Summary

Introduction

Hypertension is a common chronic condition affecting nearly a quarter of Canadians. Hypertension surveillance in Canada typically relies on administrative data and/or national surveys. Routinely-captured data from primary care electronic medical records (EMRs) are a complementary source for chronic disease surveillance, with longitudinal patient-level details such as sociodemographics, blood pressure, weight, prescribed medications, and behavioural risk factors. In Canada, administrative databases, which include in-patient hospital discharges and physician billing claims, are often used to report on hypertension prevalence estimates, such as the Canadian Chronic Disease Surveillance System (CCDSS) [2]. While administrative sources provide population-level data for those who have encountered the healthcare system, there are a lack of clinical details that are essential for better understanding the patient context and disease severity, including blood pressure (BP), body mass index (BMI), and lifestyle risk factors. These surveys are costly to maintain, response rates are often low, and the cross-sectional design does not allow for longitudinal follow-up

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