ArticleInternational journal of population data science2019
Achieving quality primary care data: a description of the Canadian Primary Care Sentinel Surveillance Network data capture, extraction, and processing in Alberta.
Article in International journal of population data science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 15 citations in OpenAlex.
- Data Harmonization Methods and Data Quality Assessment for Integrating Routinely Collected Data Across Multiple Sources: A Systematic Review.Advances in health information science and practice · 2026Pooled it
- Challenges for Data Quality in the Clinical Data Life Cycle: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Exploring Technological Solutions for Interoperability Between Patient Electronic Medical Records and Clinical Registries: Scoping Review.Journal of medical Internet research · 2026Article
- Enhancing primary care quality improvement through national data collection and validation: the primary care quality initiative in Sweden.Scandinavian journal of primary health care · 2025Article
- Comparing the Quality of Primary Care Electronic Health Record Data in Australia and Canada: Case Study in Osteoarthritis.Journal of medical Internet research · 2025Article
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- Can routinely collected primary healthcare data be used to assess Aboriginal children's health and wellbeing longitudinally? A retrospective analysis of electronic medical records from an Aboriginal community-controlled health service in Central Australia.International journal of population data science · 2025Article
- Australian general practitioner perceptions to sharing clinical data for secondary use: a mixed method approach.BMC primary care · 2022Article
- A cross-sectional study evaluating cardiovascular risk and statin prescribing in the Canadian Primary Care Sentinel Surveillance Network database.BMC primary care · 2022Observational
- A data quality assessment to inform hypertension surveillance using primary care electronic medical record data from Alberta, Canada.BMC public health · 2021Article
- Primary care EMR and administrative data linkage in Alberta, Canada: describing the suitability for hypertension surveillance.BMJ health & care informatics · 2020Article
- Methods to improve the quality of smoking records in a primary care EMR database: exploring multiple imputation and pattern-matching algorithms.BMC medical informatics and decision making · 2020Article
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Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionElectronic medical record (EMR) databases have become increasingly popular for secondary purposes, such as health research. The Canadian Primary Care Sentinel Surveillance Network (CPCSSN) is the first and only pan-Canadian primary care EMR data repository, with de-identified health information for almost two million Canadians. Comprehensive and freely available documentation describing the data 'lifecycle' is important for assessing potential data quality issues and appropriate interpretation of research findings. Here, we describe the flow and transformation of CPCSSN data in the province of Alberta. APPROACH: In Alberta, the data originate from 54 publicly-funded primary care settings, including one community pediatric clinic, with 318 providers contributing de-identified EMR data for 410,951 patients (as of December 2018). Data extraction methods have been developed for five different EMR systems, and include both backend and automated frontend extractions. The raw EMR data are transformed according to specific rules, including trimming implausible values, converting values and free text to standard terminologies or classification systems, and structuring the data into a common CPCSSN format. Following local data extraction and processing, the data are transferred to a central repository and made available for research and disease surveillance.
conclusionThis paper aims to provide important contextual information to future CPCSSN data users.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.