Cited by 156Medical Coding and Health InformationMental Health Treatment and AccessReliability and Agreement in Measurement

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Validation of a case definition for depression in administrative data against primary chart data as a reference standard

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Abstract

BACKGROUND: Because the collection of mental health information through interviews is expensive and time consuming, interest in using population-based administrative health data to conduct research on depression has increased. However, there is concern that misclassification of disease diagnosis in the underlying data might bias the results. Our objective was to determine the validity of International Classification of Disease (ICD)-9 and ICD-10 administrative health data case definitions for depression using review of family physician (FP) charts as the reference standard. METHODS: Trained chart reviewers reviewed 3362 randomly selected charts from years 2001 and 2004 at 64 FP clinics in Alberta (AB) and British Columbia (BC), Canada. Depression was defined as presence of either: 1) documentation of major depressive episode, or 2) documentation of specific antidepressant medication prescription plus recorded depressed mood. The charts were linked to administrative data (hospital discharge abstracts and physician claims data) using personal health numbers. Validity indices were estimated for six administrative data definitions of depression using three years of administrative data. RESULTS: Depression prevalence by chart review was 15.9-19.2% depending on year, region, and province. An ICD administrative data definition of '2 depression claims with depression ICD codes within a one-year window OR 1 discharge abstract data (DAD) depression diagnosis' had the highest overall validity, with estimates being 61.4% for sensitivity, 94.3% for specificity, 69.7% for positive predictive value, and 92.0% for negative predictive value. Stratification of the validity parameters for this case definition showed that sensitivity was fairly consistent across groups, however the positive predictive value was significantly higher in 2004 data compared to 2001 data (78.8 and 59.6%, respectively), and in AB data compared to BC data (79.8 and 61.7%, respectively). CONCLUSIONS: Sensitivity of the case definition is often moderate, and specificity is often high, possibly due to undercoding of depression. Limitations to this study include the use of FP charts data as the reference standard, given the potential for missed or incorrect depression diagnoses. These results suggest that that administrative data can be used as a source of information for both research and surveillance purposes, while remaining aware of these limitations.

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Crossref · 10.1186/s12888-018-1990-6

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  • The MDD definition (at least two MDD-ICD codes at least a year apart) is aligned with prior recommendations for MDD studies using EHR data.

    “These criteria are aligned with prior recommendations for MDD studies using EHR data. 9”

    From Antidepressant exposure and long‐term dementia risk in a nationwide retrospective study on US veterans with midlife major depressive disorder (2024) · cites this paper as [9]

    The Methods and Results define the preferred rule as two depression claims within a one-year window, or one hospital discharge diagnosis—not two ICD codes at least a year apart. The paper studies depression in administrative data and does not present the claimed rule as a recommendation for MDD studies using EHR data. Page numbers are not provided in our copy. (LLM, conf=0.88)

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  • The specific ICD-code-based definitions used for MDD and AD/ADRD were validated or used in multiple previous studies.

    “However, the specific ICD-codebased definitions we used were validated or used in multiple previous studies for MDD 9 and AD/ADRD. 12-14”

    From Antidepressant exposure and long‐term dementia risk in a nationwide retrospective study on US veterans with midlife major depressive disorder (2024) · cites this paper as [9]

    The Methods section lists ICD-9-CM and ICD-10 codes used to define depression, and the Results section validates an administrative-data case definition against physician charts. The paper does not validate a definition specific to major depressive disorder (MDD), and the citing sentence does not provide its exact codes for comparison. The AD/ADRD portion is attributed to other citations, not this paper. (LLM, conf=0.84)

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Citations

Cites

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Research works printed but not linked: 19

  1. Craven MA, Bland R. Depression in primary care: current and future challenges. Can J Psychiatry. 2013;58(8):442–8. · DOI
  2. Cepoiu M, McCusker J, Cole MG, Sewitch M, Belzile E, Ciampi A. Recognition of depression by non-psychiatric physicians—a systematic literature review and meta-analysis. J Gen Intern Med. 2008;23(1):25–36. · DOI
  3. Smolders M, Laurant M, Verhaak P, Prins M, van Marwijk H, Penninx B, Wensing M, Grol R. Adherence to evidence-based guidelines for depression and anxiety disorders is associated with recording of the diagnosis. Gen Hosp Psychiatry. 2009;31(5):460–9. · DOI
  4. Mitchell AJ, Vaze A, Rao S. Clinical diagnosis of depression in primary care: a meta-analysis. Lancet. 2009;374(9690):609–19. · DOI · Paper page
  5. Cadarette SM, Wong L. An introduction to health care administrative data. The Canadian journal of hospital pharmacy. 2014;68(3):232–7.
  6. Chen G, Khan N, Walker R, Quan H. Validating ICD coding algorithms for diabetes mellitus from administrative data. Diabetes Res Clin Pract. 2010;89(2):189–95. · DOI
  7. Ronksley PE, Tonelli M, Quan H, Manns BJ, James MT, Clement FM, Samuel S, Quinn RR, Ravani P, Brar SS. Validating a case definition for chronic kidney disease using administrative data. Nephrology Dialysis Transplantation. 2012;27(5):1826–31. · DOI
  8. Reid AY, Germaine-Smith CS, Liu M, Sadiq S, Quan H, Wiebe S, Faris P, Dean S, Jetté N. Development and validation of a case definition for epilepsy for use with administrative health data. Epilepsy Res. 2012;102(3):173–9. · DOI
  9. Hinds A, Lix LM, Smith M, Quan H, Sanmartin C. Quality of administrative health databases in Canada: a scoping review. Can J Public Health. 2016;107(1):56–61. · DOI
  10. Fiest KM, Jette N, Quan H, St Germaine-Smith C, Metcalfe A, Patten SB, Beck CA. Systematic review and assessment of validated case definitions for depression in administrative data. BMC Psychiatry. 2014;14:289. · DOI
  11. Quan H, Sundararajan V, Halfon P, Fong A, Burnand B, Luthi J-C, Saunders LD, Beck CA, Feasby TE, Ghali WA. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care. 2005:1130–9. · DOI · Paper page
  12. Cunningham CT, Cai P, Topps D, Svenson LW, Jetté N, Quan H. Mining rich health data from Canadian physician claims: features and face validity. BMC research notes. 2014;7(1):682. · DOI
  13. Peng M, Southern DA, Williamson T, Quan H. Under-coding of secondary conditions in coded hospital health data: impact of co-existing conditions, death status and number of codes in a record. Health informatics journal. 2016;1460458216647089:260–7.
  14. Canuto A, Gkinis G, DiGiorgio S, Arpone F, Herrmann FR, Weber K. Agreement between physicians and liaison psychiatrists on depression in old age patients of a general hospital: influence of symptom severity, age and personality. Aging Ment Health. 2015;20:1–7.
  15. Seekles WM, Cuijpers P, Van de Ven P, Penninx B, Verhaak PFM, Beekman ATF, Van Straten A. Personality and perceived need for mental health care among primary care patients. J Affect Disord. 2012;136(3):666–74. · DOI
  16. Hunt KA, Weber EJ, Showstack JA, Colby DC, Callaham ML. Characteristics of frequent users of emergency departments. Ann Emerg Med. 2006;48(1):1–8. · DOI
  17. Byrne M, Murphy AW, Plunkett PK, McGee HM, Murray A, Bury G. Frequent attenders to an emergency department: a study of primary health care use, medical profile, and psychosocial characteristics. Ann Emerg Med. 2003;41(3):309–18. · DOI
  18. Powell H, Lim LLY, Heller RF. Accuracy of administrative data to assess comorbidity in patients with heart disease: an Australian perspective. J Clin Epidemiol. 2001;54(7):687–93. · DOI
  19. Lix L, Yogendran M, Burchill C, Metge C, McKeen N, Moore D, Bond R. Defining and validating chronic diseases: an administrative data approach. Winnipeg: Manitoba Centre for Health Policy; 2006.

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Metadata

Authors
Doktorchik, C., Patten, S., Eastwood, C., Peng, M., Chen, G., Beck, C. A., Jetté, N., Williamson, T., & Quan, H.
Affiliations
University of Calgary (CA)
Corresponding author
Doktorchik, Chelsea
Venue
BMC Psychiatry
Published
2019-01-07
Volume
19
Issue
1
Pages
9-9
ISSN
1471-244X (ISSN-L)
OpenAlex
W2941590297
Cited by
156
References
4
Citations by year
2026: 20 · 2025: 19 · 2024: 27 · 2023: 22 · 2022: 19 · 2021: 19 · 2020: 18 · 2019: 12
FWCI
13.76
Type
journal article
Language
en
Open access
Locations
  • BMC Psychiatry (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, other-oa)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Libraries and Cultural Resources (University of Calgary) (submittedVersion)
Topics
  • Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
  • Health Sciences › Medicine › Psychiatry and Mental health › Mental Health Treatment and Access
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Reliability and Agreement in Measurement
Keywords
depression, case definition validation, administrative health data, ICD-9, ICD-10, medical records review, major depressive episode, antidepressant prescribing, depression prevalence, hospital discharge abstracts, diagnostic misclassification
MeSH terms
Adult, Aged, Alberta, British Columbia, Major Depressive Disorder, Female, Humans, Male, Medical Records, Middle Aged, Patient Discharge, Random Allocation, Reference Standards, Prevalence, Databases, Factual, International Classification of Diseases

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