OBJECTIVE: The objective of this study is to provide a comprehensive estimate of the cost of ADHD by consider ing the healthcare and work loss costs of persons with ADHD, as well as those costs imposed on their family members. METHODS: Excess per capita healthcare (medical and prescription drug) and work loss (disability and work absence) costs of treated ADHD patients (ages 7 years-44 years) and their family members (under 65 years of age) were calculated using administrative claims data from a single large company; work loss costs are from disability data or imputed for medically related work loss days. Excess costs are the additional costs of patients and their family members over and above those of comparable control individuals. The excess costs of untreated individuals with ADHD and their family members were also estimated. All per capita costs were extrapolated using published prevalence and treatment rates and population data; the prevalence of persons with ADHD was based upon the literature. RESULTS: The total excess cost of ADHD in the US in 2000 was $31.6 billion. Of this total, $1.6 billion was for the ADHD treatment of patients, $12.1 billion was for all other healthcare costs of persons with ADHD, $14.2 billion was for all other healthcare costs of family members of persons with ADHD, and $3.7 billion was for the work loss cost of adults with ADHD and adult family members of persons with ADHD. CONCLUSION: The annual cost of ADHD in the US is substantial. Both treated and untreated persons with ADHD, as well as their family members, impose consider able economic burdens on the healthcare system as a result of this condition. While these first estimates of the cost of ADHD to the nation are suggestive of its substantial economic burden, future research needs to refine and build on this analysis, particularly in the context of a model to control for related co-morbidities. Similarly, since these results are based on data from a single company for the period 1996-1998, the analysis should be validated with more representative, current data.
OBJECTIVE: The objective of this study is to provide a comprehensive estimate of the cost of ADHD by consider ing the healthcare and work loss costs of persons with ADHD, as well as those costs imposed on their family members. METHODS: Excess per capita healthcare (medical and prescription drug) and work loss (disability and work absence) costs of treated ADHDpatients (ages 7 years-44 years) and their family members (under 65 years of age) were calculated using administrative claims data from a single large company; work loss costs are from disability data or imputed for medically related work loss days. Excess costs are the additional costs of patients and their family members over and above those of comparable control individuals. The excess costs of untreated individuals with ADHD and their family members were also estimated. All per capita costs were extrapolated using published prevalence and treatment rates and population data; the prevalence of persons with ADHD was based upon the literature. RESULTS: The total excess cost of ADHD in the US in 2000 was $31.6 billion. Of this total, $1.6 billion was for the ADHD treatment of patients, $12.1 billion was for all other healthcare costs of persons with ADHD, $14.2 billion was for all other healthcare costs of family members of persons with ADHD, and $3.7 billion was for the work loss cost of adults with ADHD and adult family members of persons with ADHD. CONCLUSION: The annual cost of ADHD in the US is substantial. Both treated and untreated persons with ADHD, as well as their family members, impose consider able economic burdens on the healthcare system as a result of this condition. While these first estimates of the cost of ADHD to the nation are suggestive of its substantial economic burden, future research needs to refine and build on this analysis, particularly in the context of a model to control for related co-morbidities. Similarly, since these results are based on data from a single company for the period 1996-1998, the analysis should be validated with more representative, current data.
Authors: Jessica C Agnew-Blais; Guilherme V Polanczyk; Andrea Danese; Jasmin Wertz; Terrie E Moffitt; Louise Arseneault Journal: Br J Psychiatry Date: 2018-06-29 Impact factor: 9.319
Authors: Anne W Riley; Lisa M Lyman; Georg Spiel; Manfred Döpfner; Maria J Lorenzo; Stephen J Ralston Journal: Eur Child Adolesc Psychiatry Date: 2006-12 Impact factor: 4.785
Authors: Andreas J Fallgatter; Ann-Christine Ehlis; Thomas Dresler; Andreas Reif; Christian P Jacob; Mauricio Arcos-Burgos; Maximilian Muenke; Klaus-Peter Lesch Journal: Eur Neuropsychopharmacol Date: 2012-12-12 Impact factor: 4.600
Authors: Sandra J J Kooij; Susanne Bejerot; Andrew Blackwell; Herve Caci; Miquel Casas-Brugué; Pieter J Carpentier; Dan Edvinsson; John Fayyad; Karin Foeken; Michael Fitzgerald; Veronique Gaillac; Ylva Ginsberg; Chantal Henry; Johanna Krause; Michael B Lensing; Iris Manor; Helmut Niederhofer; Carlos Nunes-Filipe; Martin D Ohlmeier; Pierre Oswald; Stefano Pallanti; Artemios Pehlivanidis; Josep A Ramos-Quiroga; Maria Rastam; Doris Ryffel-Rawak; Steven Stes; Philip Asherson Journal: BMC Psychiatry Date: 2010-09-03 Impact factor: 3.630