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Defining and validating chronic diseases

This served to standardise judgement before the 1000 record review.

Overall, the case definition and algorithm yielded strong sensitivity and specificity metrics and was found valid for use in research in CPCSSN primary-care practices.Our algorithm performed better in identifying patients up to 17 years of age.Previous research in Canada has also demonstrated the effectiveness of using algorithm-defined cases to identify patients with other chronic conditions using data from EMRs. found an EMR-based algorithm to identify multiple sclerosis performed well (91.5% sensitivity and 100% specificity) and could be used as an accurate tool in primary-care settings.These studies utilised a similar process whereby original patient charts were audited by primary-care physicians to determine whether patients had any of the CPCSSN indexed conditions and then compared with a CPCSSN case definition diagnosis.However, ours is the first study to use CPCSSN records rather than original EMR charts to validate a disease diagnosis.As there is no standard definition of the type, severity, or frequency of symptoms, the diagnosis of asthma in young children is challenging.Family physicians’ electronic medical records (EMRs) provide a rich source of clinical data that can be used in chronic disease surveillance and in determining the effectiveness of disease prevention and management interventions.However, the use of EMR data to identify paediatric patients with asthma cannot be successful without first confirming that a definition and case-finding diagnostic algorithm is valid.The Canadian Primary Care Sentinel Surveillance Network (CPCSSN) has developed a process that enables data from 12 different EMR databases to be extracted, cleaned and merged into a single primary-care data set.In Canada, the majority of studies validating a diagnosis of childhood asthma have focused on identifying patients with asthma using administrative and prescription data Our algorithm yielded higher specificity and lower sensitivity when compared with a case validation for children with asthma that utilised a single diagnosis code from primary-care administrative data in Ontario, Canada (sensitivity of 91.4% and specificity of 82.9%).tested the accuracy of an EMR-based search algorithm to identify patients over age 16 years with asthma and found a sensitivity and specificity of 90.2% and 83.9%, respectively, using their best search strategy.


  1. Validating the 8 CPCSSN Case Definitions for Chronic Disease Surveillance in a Primary Care Database of Electronic Health Records. Tyler Williamson, PhD,1.

  2. Full-Text Paper PDF Defining and Validating Chronic Diseases An Administrative Data Approach – An Update with ICD-10-CA.

  3. Apr 20, 2016. Keywords Catalog, chronic conditions, chronic disease, definition. using the definitions, and further validation and ongoing adjustment of the.

  4. Oct 19, 2011. AbstractBackground. Administrative data are commonly used for surveillance of chronic medical conditions. The purpose of this study was to.

  5. Nov 24, 2016. Overall, the case definition and algorithm yielded strong sensitivity and. Validating the 8 CPCSSN case definitions for chronic disease.

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