Cargando…

Achieving quality primary care data: a description of the Canadian Primary Care Sentinel Surveillance Network data capture, extraction, and processing in Alberta

INTRODUCTION: Electronic 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 in...

Descripción completa

Detalles Bibliográficos
Autores principales: Garies, S, Cummings, M, Forst, B, McBrien, K, Soos, B, Taylor, M, Drummond, N, Manca, D, Duerksen, K, Quan, H, Williamson, T
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Swansea University 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8142949/
https://www.ncbi.nlm.nih.gov/pubmed/34095540
http://dx.doi.org/10.23889/ijpds.v4i2.1132
_version_ 1783696652994871296
author Garies, S
Cummings, M
Forst, B
McBrien, K
Soos, B
Taylor, M
Drummond, N
Manca, D
Duerksen, K
Quan, H
Williamson, T
author_facet Garies, S
Cummings, M
Forst, B
McBrien, K
Soos, B
Taylor, M
Drummond, N
Manca, D
Duerksen, K
Quan, H
Williamson, T
author_sort Garies, S
collection PubMed
description INTRODUCTION: Electronic 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. CONCLUSION: This paper aims to provide important contextual information to future CPCSSN data users.
format Online
Article
Text
id pubmed-8142949
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Swansea University
record_format MEDLINE/PubMed
spelling pubmed-81429492021-06-04 Achieving quality primary care data: a description of the Canadian Primary Care Sentinel Surveillance Network data capture, extraction, and processing in Alberta Garies, S Cummings, M Forst, B McBrien, K Soos, B Taylor, M Drummond, N Manca, D Duerksen, K Quan, H Williamson, T Int J Popul Data Sci Population Data Science INTRODUCTION: Electronic 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. CONCLUSION: This paper aims to provide important contextual information to future CPCSSN data users. Swansea University 2019-07-29 /pmc/articles/PMC8142949/ /pubmed/34095540 http://dx.doi.org/10.23889/ijpds.v4i2.1132 Text en https://creativecommons.org/licenses/by/4.0/This work is licenced under a Creative Commons Attribution 4.0 International License.
spellingShingle Population Data Science
Garies, S
Cummings, M
Forst, B
McBrien, K
Soos, B
Taylor, M
Drummond, N
Manca, D
Duerksen, K
Quan, H
Williamson, T
Achieving quality primary care data: a description of the Canadian Primary Care Sentinel Surveillance Network data capture, extraction, and processing in Alberta
title Achieving quality primary care data: a description of the Canadian Primary Care Sentinel Surveillance Network data capture, extraction, and processing in Alberta
title_full Achieving quality primary care data: a description of the Canadian Primary Care Sentinel Surveillance Network data capture, extraction, and processing in Alberta
title_fullStr Achieving quality primary care data: a description of the Canadian Primary Care Sentinel Surveillance Network data capture, extraction, and processing in Alberta
title_full_unstemmed Achieving quality primary care data: a description of the Canadian Primary Care Sentinel Surveillance Network data capture, extraction, and processing in Alberta
title_short Achieving quality primary care data: a description of the Canadian Primary Care Sentinel Surveillance Network data capture, extraction, and processing in Alberta
title_sort achieving quality primary care data: a description of the canadian primary care sentinel surveillance network data capture, extraction, and processing in alberta
topic Population Data Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8142949/
https://www.ncbi.nlm.nih.gov/pubmed/34095540
http://dx.doi.org/10.23889/ijpds.v4i2.1132
work_keys_str_mv AT gariess achievingqualityprimarycaredataadescriptionofthecanadianprimarycaresentinelsurveillancenetworkdatacaptureextractionandprocessinginalberta
AT cummingsm achievingqualityprimarycaredataadescriptionofthecanadianprimarycaresentinelsurveillancenetworkdatacaptureextractionandprocessinginalberta
AT forstb achievingqualityprimarycaredataadescriptionofthecanadianprimarycaresentinelsurveillancenetworkdatacaptureextractionandprocessinginalberta
AT mcbrienk achievingqualityprimarycaredataadescriptionofthecanadianprimarycaresentinelsurveillancenetworkdatacaptureextractionandprocessinginalberta
AT soosb achievingqualityprimarycaredataadescriptionofthecanadianprimarycaresentinelsurveillancenetworkdatacaptureextractionandprocessinginalberta
AT taylorm achievingqualityprimarycaredataadescriptionofthecanadianprimarycaresentinelsurveillancenetworkdatacaptureextractionandprocessinginalberta
AT drummondn achievingqualityprimarycaredataadescriptionofthecanadianprimarycaresentinelsurveillancenetworkdatacaptureextractionandprocessinginalberta
AT mancad achievingqualityprimarycaredataadescriptionofthecanadianprimarycaresentinelsurveillancenetworkdatacaptureextractionandprocessinginalberta
AT duerksenk achievingqualityprimarycaredataadescriptionofthecanadianprimarycaresentinelsurveillancenetworkdatacaptureextractionandprocessinginalberta
AT quanh achievingqualityprimarycaredataadescriptionofthecanadianprimarycaresentinelsurveillancenetworkdatacaptureextractionandprocessinginalberta
AT williamsont achievingqualityprimarycaredataadescriptionofthecanadianprimarycaresentinelsurveillancenetworkdatacaptureextractionandprocessinginalberta