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

Abstract

Objective: The objective of this study was to assess the validity of electronic medical records-based diagnostic algorithms for 5 chronic conditions.Methods: A retrospective validation study using primary chart abstraction. A standardized abstraction form was developed to ascertain diagnoses of diabetes, hypertension, osteoarthritis, chronic obstructive pulmonary disease, and depression. Information about billing, laboratory tests, notes, specialist and hospital reports, and physiologic data was collected. An age-stratified random sample of 350 patient charts was selected from Kingston, Ontario, Canada. Approximately 90% of those charts were allocated to people aged >60 years.Results: Three hundred thirteen patient records were included in the study. Patients' mean age was 68 years and 52% were women. High interrater reliability was indicated by 92% complete agreement and a statistic of 89.3%. The sensitivities of algorithms were 100% (diabetes), 83% (hypertension), 45% (osteoarthritis), 41% (chronic obstructive pulmonary disease), and 39% (depression). The lowest specificity was 97%, for depression. The positive predictive value ranged from 79% (depression) to 100%, and the negative predictive value ranged from 68% (osteoarthritis) to 100%. Chronic diseases constitute a major burden of illness in Canada and around the world. Recent estimates suggest that 46% of adult Canadians suffer from one or more of 7 common chronic diseases. 1Of these conditions, 6 million Canadians are affected with hypertension, 2 2 million with diabetes, 3 1.2 million with major depression, 4 Ͼ750,000adults with chronic obstructive pulmonary disease (COPD), 5 and 3 million with osteoarthritis. 6Currently available information on chronic diseases at the national level is derived from databases such as hospital discharge summaries, disease-specific registries, and population health surveys. These sources have significant limitations, such as the inability to capture data on conditions that do not lead to hospitalizations and the unreliability of self-reported surveys.7 A large validation study of the Discharge At the Canadian provincial level, billing for physician services may provide a source of data, but it is limited in the depth of information because administrative data are created for financial management rather than research purposes.10 When compared against a clinical research database, administrative data had only 20% agreement. 11Primary care databases constitute another source of data on chronic conditions. For instance, people with one or more chronic conditions accounted for 51% of family physician encounters, 12 suggesting that comprehensive clinical records collected by primary care physicians could be a rich resource for researchers and policymakers. The benefit of using primary care databases is that they provide prospective and systematic collection of clinically verified data that can be comprehensive for studying a variety of important outcomes. 13The Canadian Primary Care Sentinel Surveillance Network (CPCSSN) is one...

Disparities in Electronic Health Record Patient Portal Use in Nephrology Clinics

“…Insurance status was categorized as private, Medicare, medical assistance/ Medicaid, or self-pay. Comorbidities were determined on the basis of their presence on the patient's problem list, as a billing diagnosis on two outpatient encounters, or active use of a specified medication (Supplemental Table 1) (7,37,(39)(40)(41)(42)(43)(44)(45)(46)(47). The university-affiliated health system mandates that providers enter all prescriptions electronically and maintain an up-to-date medication list.…”

“…HTN was identified on the basis of two outpatient billing diagnoses, a problem list diagnosis, or the use of an antihypertensive medication (37)(38)(39)(41)(42)(43)(44). For patients with a diagnosis of HTN, all recorded office BP values from the cohort period were abstracted from the EHR.…”

Prevalence and management of osteoarthritis in primary care: an epidemiologic cohort study from the Canadian Primary Care Sentinel Surveillance Network

“…20 We included patients identified as having osteoarthritis, based on CPCSSN case criteria, at any point in their available EMR record in our analysis and compared their data with those from patients without a diagnosis of osteoarthritis. 14,15 A diagnosis of osteoarthritis in CPCSSN includes osteoarthritis and allied disorders, as well as spondylosis and allied disorders such as ankylosing vertebral hyperostosis. The diagnosis excludes intervertebral disc disorders, ankylosing spondylitis and other inflammatory spondylopathies and spinal stenosis.…”

“…We have developed validated case definitions for 8 chronic conditions, including the diagnosis of osteoarthritis, which takes into account prescribed medications, billing codes, laboratory tests and multiple diagnostic codes from the International Classification of Diseases, 9th revision (clinical modification) (ICD-9) to find cases. 15,16 CPCSSN is a primary care network comprising 11 practicebased research networks in 7 Canadian provinces and 1 territory. The network extracts patient data from 12 different EMR vendor products.…”

Chronic obstructive pulmonary disease in primary care: an epidemiologic cohort study from the Canadian Primary Care Sentinel Surveillance Network

“…Case-finding algorithms have been established for 8 chronic diseases, including COPD, and validated against chart abstraction and physician identification of cases. [15][16][17] For COPD, the algorithms of the Canadian Primary Care Sentinel Surveillance Network have a sensitivity of 82% and specificity of 97%. 16 Details of the case definitions and algorithms used are available on the network's website (cpcssn.ca/research-resources/case-definitions).…”