Evidence-based assessment/Step 2: Benchmark base rates for issues

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Preparation: Benchmarking Base Rates

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Overview

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This section gathers several different sources for external base rates. These provide a way of comparing our local clinical practice to what we would expect to find in other clinical settings.

It is not easy to find good external rates. We will go through a range of sources, including epidemiological studies, clinical epidemiological studies, surveillance studies such as those done by the Centers for Disease Control and Prevention, and meta-analyses of results from different clinics. We will mention the strengths and limitations of each type of source. We conclude with a set of options for testing whether differences in one setting are "statistically significantly" different from another.

External Sources

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Epidemiological Studies

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Epidemiological studies are meant to provide the most accurate snapshot of how common different issues are in the general population. Here are some well-known examples of such studies:

  • Costello et al. (1996)[1]
  • Costello et al. (2003)[2]
  • Merikangas et al. (2010)[3]
  • Merikangas et al. (2010)[4]

Clinical Epidemiological Studies

Surveillance Studies

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The Centers for Disease Control and Prevention does annual surveys to track. Post-marketing surveillance is also a way of trying to detect when treatments have unintended consequences. The "Black Box" warning on antidepressant medications, stating that there might be an association between them and increased suicidal ideation, was based on this type of surveillance data.


Meta-analyses

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The following studies are examples of meta-analyses that focus on epidemiological studies:

  • Rettew et al. (2009)[5], which compares agreement of diagnoses made from clinical evaluations
  • Van Meter et al. (2011)[6], which focuses epidemiological studies of pediatric bipolar disorder.
  • Polanczyk et al. (2014)[7], which focuses on the prevalence estimates of ADHD.
  • Costello et al. (2006)[8], which is focuses on epidemiology of child and adolescent psychiatric disorders.



Comparing Rates at One Setting to Another

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Rationale

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Steps to put into practice

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Annotated bibliography

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Tables and figures

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We have several working tables that pull together rates from different sources.

One combines results from several major US epidemiological studies with rates from the Rettew et al. (2009) meta-analysis of clinical diagnoses as usual (DAU) and rates from structured diagnostic interviews (SDIs) at the same clinics. A version of this table also includes surveillance rates gathered by SAMHSA, which are striking in how differently they are organized. [This is the table that is currently on MECCA; but need to add back the SAMHSA column]

Another table is a work in progress, gathering rates of disorders to match up with the table of contents for one of the updated handbooks. [This is the long version of the table for Hunsley & Mash in the first version of Youngstrom & Van Meter; need to make an archival version]

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References

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  1. Costello, E. J., Angold, A., Burns, B. J., Stangl, D. K., Tweed, D. L., Erkanli, A., & Worthman, C. M. (1996). The Great Smoky Mountains Study of youth: Goals, design, methods, and the prevalence of DSM-III-R disorders. Archives of General Psychiatry, 53, 1129-1136.
  2.  Costello, E. J., Mustillo, S., Erkanli, A., Keeler, G., & Angold, A. (2003). Prevalence and Development of Psychiatric Disorders in Childhood and Adolescence. Archives of General Psychiatry, 60, 837-844. Retrieved from http://archpsyc.ama-assn.org/cgi/content/abstract/60/8/837
  3. Merikangas, K. R., He, J. P., Brody, D., Fisher, P. W., Bourdon, K., & Koretz, D. S. (2010). Prevalence and treatment of mental disorders among US children in the 2001-2004 NHANES. Pediatrics, 125, 75-81. doi:10.1542/peds.2008-2598
  4. Merikangas, K. R., He, J. P., Burstein, M., Swanson, S. A., Avenevoli, S., Cui, L., . . . Swendsen, J. (2010). Lifetime prevalence of mental disorders in U.S. adolescents: results from the National Comorbidity Survey Replication--Adolescent Supplement (NCS-A). Journal of the American Academy of Child & Adolescent Psychiatry, 49, 980-989. doi:10.1016/j.jaac.2010.05.017
  5. Rettew, D. C., Lynch, A. D., Achenbach, T. M., Dumenci, L., & Ivanova, M. Y. (2009). Meta-analyses of agreement between diagnoses made from clinical evaluations and standardized diagnostic interviews. International Journal of Methods in Psychiatric Research, 18, 169-184. doi:10.1002/mpr.289
  6. Van Meter, A., Moreira, A. L., & Youngstrom, E. A. (2011). Meta-analysis of epidemiological studies of pediatric bipolar disorder. Journal of Clinical Psychiatry, 72, 1250-1256. doi:10.4088/JCP.10m06290
  7. Polanczyk, G. V., Willcutt, E. G., Salum, G. A., Kieling, C., & Rohde, L. A. (2014). ADHD prevalence estimates across three decades: an updated systematic review and meta-regression analysis. Int J Epidemiol. doi:10.1093/ije/dyt261
  8. Costello, E. J., Foley, D. L., & Angold, A. (2006). 10-year research update review: the epidemiology of child and adolescent psychiatric disorders: II. Developmental epidemiology. Journal of the American Academy of Child and Adolescent Psychiatry, 45, 8-25. Retrieved from http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16327577