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Research ArticleOriginal Research

Validation of the Diagnostic Algorithms for 5 Chronic Conditions in the Canadian Primary Care Sentinel Surveillance Network (CPCSSN): A Kingston Practice-based Research Network (PBRN) Report

Amjed Kadhim-Saleh, Michael Green, Tyler Williamson, Duncan Hunter and Richard Birtwhistle
The Journal of the American Board of Family Medicine March 2013, 26 (2) 159-167; DOI: https://doi.org/10.3122/jabfm.2013.02.120183
Amjed Kadhim-Saleh
From the Departments of Community Health and Epidemiology (AK-S, MG, DH) and Family Medicine (MG, DH, TW, RB), Queen's University, Kingston, Ontario, Canada.
BHSc, MSc
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Michael Green
From the Departments of Community Health and Epidemiology (AK-S, MG, DH) and Family Medicine (MG, DH, TW, RB), Queen's University, Kingston, Ontario, Canada.
MD, MPH
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Tyler Williamson
From the Departments of Community Health and Epidemiology (AK-S, MG, DH) and Family Medicine (MG, DH, TW, RB), Queen's University, Kingston, Ontario, Canada.
PhD
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Duncan Hunter
From the Departments of Community Health and Epidemiology (AK-S, MG, DH) and Family Medicine (MG, DH, TW, RB), Queen's University, Kingston, Ontario, Canada.
PhD
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Richard Birtwhistle
From the Departments of Community Health and Epidemiology (AK-S, MG, DH) and Family Medicine (MG, DH, TW, RB), Queen's University, Kingston, Ontario, Canada.
MD, MSc
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    Figure 1.

    A visual representation of the study design. Computerized data collected through the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) will be compared against the gold standard (primary chart abstraction). For each index condition, a CPCSSN protocol algorithm was used to determine whether a patient had the disease. In contrast, prespecified criteria were used in chart abstraction to identify the presence or absence of index conditions. The level of concordance will be compared between the 2 data sources.

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    Figure 2.

    Data flow from physician's office to Canadian Primary Care Sentinel Surveillance Network's (CPCSSN′s) central repository site. At stage 1, the data are entered into the electronic medical record. At this stage, there is a possibility of nondocumentation that can result either from the patient not reporting the condition (or being unaware of it) or physician failure to document the condition in the chart. At stage 2, CPCSSN extracts data from the local sites. At this stage, certain data, including physician notes, hospital and specialist reports, imaging reports, past medical and social history, certain questionnaires (eg, depression screening), procedures, and imaging reports, are not extracted by CPCSSN. These data were only available through the manual chart abstraction. At stage 2 patient identifying information is removed to ensure privacy. At stage 3 cleaned and transformed data is uploaded to the central database.

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    Table 1. Demographics of Patients Included in The Study Sample from the Kingston Practice-Based Research Network
    DemographicsCount (n = 313)
    Male150 (48)
    Female163 (52)
    Age, yr
        ≥60282 (90)
        <6031 (10)
    Chronic conditions
        Diabetes53 (17)
        Hypertension181 (58)
        Osteoarthritis144 (46)
        COPD29 (9)
        Depression66 (21)
    Number of chronic conditions
        At least 1 of 5250 (80)
        294 (30)
        337 (12)
        417 (5)
    • Values provided as n (%).

    • COPD, chronic obstructive pulmonary disease.

    • View popup
    Table 2. Validation Results of the Case-Finding Diagnostic Algorithm for the 5 Chronic Conditions
    ConditionChart+ CPCSSN+Chart-CPCSSN+Chart+ CPCSSN-Chart-CPCSSN-Sensitivity (95% CI)Specificity (95% CI)PPV (95% CI)NPV (95% CI)
    Diabetes5330257100% (92–100)99% (96–100)95% (83–100)100% (98–100)
    Hypertension15033112983% (75–89)98% (93–100)98% (94–100)81% (72–88)
    Osteoarthritis6507916945% (35–55)100% (97–100)100% (93–100)68% (61–75)
    COPD1231728141% (20–65)99% (97–100)80% (46–99)94% (90–97)
    Depression2674024039% (25–55)97% (94–99)79% (57–94)86% (80–90)
    • CI, confidence interval; COPD, chronic obstructive pulmonary disease; CPCSSN, Canadian Primary Care Sentinel Surveillance Network; NPV, negative predictive value; PPV, positive predictive value.

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The Journal of the American Board of Family     Medicine: 26 (2)
The Journal of the American Board of Family Medicine
Vol. 26, Issue 2
March-April 2013
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Validation of the Diagnostic Algorithms for 5 Chronic Conditions in the Canadian Primary Care Sentinel Surveillance Network (CPCSSN): A Kingston Practice-based Research Network (PBRN) Report
Amjed Kadhim-Saleh, Michael Green, Tyler Williamson, Duncan Hunter, Richard Birtwhistle
The Journal of the American Board of Family Medicine Mar 2013, 26 (2) 159-167; DOI: 10.3122/jabfm.2013.02.120183

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Validation of the Diagnostic Algorithms for 5 Chronic Conditions in the Canadian Primary Care Sentinel Surveillance Network (CPCSSN): A Kingston Practice-based Research Network (PBRN) Report
Amjed Kadhim-Saleh, Michael Green, Tyler Williamson, Duncan Hunter, Richard Birtwhistle
The Journal of the American Board of Family Medicine Mar 2013, 26 (2) 159-167; DOI: 10.3122/jabfm.2013.02.120183
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