Prevalence and Epidemiology of Diabetes in Canadian Primary Care Practices: A Report from the Canadian Primary Care Sentinel Surveillance Network

2014 ◽  
Vol 38 (3) ◽  
pp. 179-185 ◽  
Author(s):  
Michelle Greiver ◽  
Tyler Williamson ◽  
David Barber ◽  
Richard Birtwhistle ◽  
Babak Aliarzadeh ◽  
...  
Keyword(s):  
Primary Care ◽  
Sentinel Surveillance ◽  
Surveillance Network ◽  
Care Practices ◽  
Primary Care Practices

scholarly journals Creation of a Case Definition to Identify People Living with HIV using Canadian Primary Care Sentinel Surveillance Network data

2020 ◽  
Author(s):  
Sarah Elizabeth Boyd ◽  
Tao Chen ◽  
Jillian Blackmore ◽  
Marissa Becker ◽  
Claire Kendall ◽  
...  
Keyword(s):  
Primary Care ◽  
Case Definition ◽  
Sentinel Surveillance ◽  
Hiv Care ◽  
Future Research ◽  
People Living With Hiv ◽  
Internal Reference ◽  
Surveillance Network ◽  
Primary Care Practices ◽  
Living With Hiv

Abstract Background: HIV care that has been predominantly specialty based can often be managed in primary care settings. The Canadian Primary Care Sentinel Surveillance Network (CPCSSN) database is a rich source of electronic medical records of primary care practices. A case definition for HIV using CPCSSN allows the examination of epidemiology and healthcare utilization of people living with HIV (PLHIV) whose records are in this database and assists us to better understand the primary care of PLHIV. The objective of this study was to develop a case definition for HIV applicable to the CPCSSN database. Methods: Electronic medical record data from CPCSSN was used to develop a retrospective cohort between 2009 and 2017. We identified all possible records of PLHIV in the CPCSSN dataset based on the presence of HIV codes, keywords and medications. Multiple combination of codes, keywords and medications were analyzed to see which resulted in the most accurate definition of PLHIV. To assess the validity, we linked the data to external references (a Newfoundland and Labrador (NL) PLHIV cohort and Nine Circles HIV clinic in Manitoba) and an internal reference (a random sample of the CPCSSN database which was reviewed by two experts to confirm HIV status). Results: We found that the presence of an HIV keyword along with either an ICD code or taking 3 or more HIV medications concurrently was the most accurate algorithm for predicting PLHIV with a sensitivity of 95%, 97.9% and 88.9%, specificity of 63.5%, 100% and 100% for the NL PLHIV cohort, Nine Circles HIV clinic data and internal reference, respectively. Conclusion: To our knowledge, this is the first study to develop an algorithm for identifying people with HIV applicable to the Canadian Primary Care Sentinel Surveillance Network database. This algorithm-based case definition will support future research investigating the utilization of primary healthcare by PLHIV and facilitate improvements in primary care for PLHIV.

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