2012
DOI: 10.1089/pop.2011.0084
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Using Administrative Databases in the Surveillance of Depressive Disorders—Case Definitions

Abstract: The objective of this study was to assess the usefulness of provincial administrative databases in carrying out surveillance on depressive disorders. Electronic medical records (EMRs) at 3 family practice clinics in St. John's, NL, Canada, were audited; 253 depressive disorder cases and 257 patients not diagnosed with a depressive disorder were selected. The EMR served as the "gold standard," which then was compared to these same patients investigated through the use of various case definitions applied against… Show more

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Cited by 44 publications
(48 citation statements)
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“…Our primary outcomes of interest were anxiety and depression diagnoses, defined as one or more inpatient or two or more outpatient diagnoses on separate dates in the year before or after the index date. These criteria were conservatively modified from a previously validated claims‐based definition to require diagnoses to occur in 1 year instead of 2 years to better assess clinical status around the time of surgery . Anxiety and depression diagnosis codes for outcome classification are included in Appendix in the online Supporting Information.…”
Section: Methodsmentioning
confidence: 99%
“…Our primary outcomes of interest were anxiety and depression diagnoses, defined as one or more inpatient or two or more outpatient diagnoses on separate dates in the year before or after the index date. These criteria were conservatively modified from a previously validated claims‐based definition to require diagnoses to occur in 1 year instead of 2 years to better assess clinical status around the time of surgery . Anxiety and depression diagnosis codes for outcome classification are included in Appendix in the online Supporting Information.…”
Section: Methodsmentioning
confidence: 99%
“…Psychiatric comorbidities were collected from the problem list in the EMR. The limitations of a medical chart review as the source of the variable of “psychiatric diagnosis” are well established (Alaghehbandan et al, 2012; Fiest et al, 2014; Iezzoni, 1990; Noyes et al, 2011). First, psychiatric comorbidities are a heterogeneous group of diseases.…”
Section: Methodsmentioning
confidence: 99%
“…We included emerging adults between the ages of 16 and 25 years, inclusive, presenting for services between 1 April 2009 and 31 March 2015, and meeting at least one of the following diagnostic criteria: an inpatient hospitalization with a primary discharge diagnosis of a mood or anxiety disorder or at least two physician billing claims in OHIP or emergency department visits with a diagnostic code for a mood or anxiety disorder in any 12-month period (Supporting Information File S1). This algorithm has been shown to have a positive predictive value greater than 90% in health administrative datasets (Alaghehbandan, Macdonald, Barrett, Collins, & Chen, 2012;Solberg, Engebretson, Sperl-Hillen, Hroscikoski, & O'Connor, 2006). We excluded those with an invalid identification number, missing age, sex or postal code (for area rural/income data) and those with a history of nonaffective psychotic disorder prior to the index date.…”
Section: Cohort Creationmentioning
confidence: 99%