ArticlePharmacoepidemiology and drug safety2018
Assessing the accuracy of using diagnostic codes from administrative data to infer antidepressant treatment indications: a validation study.
Article in Pharmacoepidemiology and drug safety, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 11 citations in OpenAlex.
- Initiation of SGLT2 Inhibitors Versus DPP-4 Inhibitors in Metformin Users and Risk of Incident Depression: A Nationwide, Claims-Based Active-Comparator New-User Study.Diabetes, obesity & metabolism · 2026Article
- Socioeconomic burden of adult attention deficit/hyperactivity disorder in Japan: a nationwide cross-sectional observational study.BMC psychiatry · 2026Observational
- Mental Health Diagnoses are Not Associated With Indicators of Lower Quality Pain Care in Electronic Health Records of a National Sample of Veterans Treated in Veterans Health Administration Primary Care Settings.The journal of pain · 2023Article
- Comparing Relapse Rates in Real-World Patients with Schizophrenia Who Were Adequately versus Not Adequately Treated with Paliperidone Palmitate Once-Monthly Injections Before Transitioning to Once-Every-3-Months Injections.Neuropsychiatric disease and treatment · 2022Article
- Article
- Who diagnosed and prescribed what? Using provider details to inform observational research.Pharmacoepidemiology and drug safety · 2018Article
- Assessing the accuracy of using diagnostic codes from administrative data to infer antidepressant treatment indications: a validation study.Pharmacoepidemiology and drug safety · 2018Article
- Derivation and validation of a multivariable model to predict when primary care physicians prescribe antidepressants for indications other than depression.Clinical epidemiology · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
purposeTo assess the accuracy of using diagnostic codes from administrative data to infer treatment indications for antidepressants prescribed in primary care.
methodsValidation study of administrative diagnostic codes for 13 plausible indications for antidepressants compared with physician-documented treatment indications from an indication-based electronic prescribing system in Quebec, Canada. The analysis included all antidepressant prescriptions written by primary care physicians between January 1, 2003 and December 31, 2012 using the electronic prescribing system. Patient prescribed antidepressants were linked to physician claims and hospitalization data to obtain all diagnoses recorded in the past year.
resultsDiagnostic codes had poor sensitivity for all treatment indications, ranging from a high of only 31.2% (95% CI, 26.8%-35.9%) for anxiety/stress disorders to as low as 1.3% (95% CI, 0.0%-5.2%) for sexual dysfunction. Sensitivity was notably worse among older patients and patients with more chronic comorbidities. Physician claims data were a better source of diagnostic codes for antidepressant treatment indications than hospitalization data.
conclusionsAdministrative diagnostic codes are poor proxies for antidepressant treatment indications. Future work should determine whether the use of other variables in administrative data besides diagnostic codes can improve the ability to predict antidepressant treatment indications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.