OBJECTIVE: We sought to determine the accuracy of administrative data for identifying mental health service provision in primary care. STUDY DESIGN: This was a chart abstraction study measuring agreement between billing data and clinical data on the binary variable "mental health visit." Data were collected from the charts and billing records of 5 academic family practice clinics in Toronto, Ontario (1999 to 2000). Billing claims (n = 952) were selected from the billings for all visits by a stratified random sampling technique. A blinded data abstractor reviewed the clinical charts and assigned diagnostic codes for each patient visit associated with the selected claims. Any visit with at least 1 abstracted mental health diagnostic code was defined as a mental health visit. The test characteristics of 4 administrative measures of mental health service provision, based on different combinations of billing codes, were calculated. RESULTS: The accuracy of the administrative data was 86.8% when compared with clinical data. The sensitivity of the 4 administrative measures ranged from 22.3% to 80.7%. The specificity ranged from 97.0% to 99.5%. CONCLUSIONS: This is the first study to establish the performance of administrative data in measuring mental health service provision in a primary care setting. In our setting, broadly defined administrative measures of mental health have excellent specificity and adequate sensitivity for exploring and understanding mental health service utilization.
OBJECTIVE: We sought to determine the accuracy of administrative data for identifying mental health service provision in primary care. STUDY DESIGN: This was a chart abstraction study measuring agreement between billing data and clinical data on the binary variable "mental health visit." Data were collected from the charts and billing records of 5 academic family practice clinics in Toronto, Ontario (1999 to 2000). Billing claims (n = 952) were selected from the billings for all visits by a stratified random sampling technique. A blinded data abstractor reviewed the clinical charts and assigned diagnostic codes for each patient visit associated with the selected claims. Any visit with at least 1 abstracted mental health diagnostic code was defined as a mental health visit. The test characteristics of 4 administrative measures of mental health service provision, based on different combinations of billing codes, were calculated. RESULTS: The accuracy of the administrative data was 86.8% when compared with clinical data. The sensitivity of the 4 administrative measures ranged from 22.3% to 80.7%. The specificity ranged from 97.0% to 99.5%. CONCLUSIONS: This is the first study to establish the performance of administrative data in measuring mental health service provision in a primary care setting. In our setting, broadly defined administrative measures of mental health have excellent specificity and adequate sensitivity for exploring and understanding mental health service utilization.
Authors: Michelle Greiver; Jan Barnsley; Richard H Glazier; Rahim Moineddin; Bart J Harvey Journal: Can Fam Physician Date: 2011-10 Impact factor: 3.275
Authors: Paul Kurdyak; Juveria Zaheer; André Carvalho; Claire de Oliveira; Michael Lebenbaum; Andrew S Wilton; Mark Fefergrad; Vicky Stergiopoulos; Benoit H Mulsant Journal: CMAJ Open Date: 2020-03-10
Authors: Christopher Lo; Andrew Calzavara; Paul Kurdyak; Lisa Barbera; Frances Shepherd; Camilla Zimmermann; Malcolm J Moore; Gary Rodin Journal: Can Fam Physician Date: 2013-03 Impact factor: 3.275