Economic burden of attention-deficit/hyperactivity disorder among adults in the United States: a societal perspective
Notice bibliographique
Résumé
BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is associated with substantial clinical burden as individuals transition to adulthood, including higher rates of comorbidities, mortality, incarceration, and psychiatric hospitalizations than in individuals without ADHD. These higher rates likely contribute to substantial economic burden as well. OBJECTIVE: To provide a comprehensive evaluation of the economic burden associated with ADHD in the US adult population. METHODS: Direct health care costs were obtained by using claims data from the IBM MarketScan Research Databases (January 1, 2017, through December 31, 2018). Direct non–health care costs and indirect costs were estimated on the basis of the literature and government publications. Excess costs incurred by adults with ADHD during 2018 were evaluated from a societal perspective; per-patient costs were extrapolated to the national level. RESULTS: An estimated 8.7 million adults live with ADHD in the United States, resulting in a total societal excess cost attributable to ADHD of $122.8 billion ($14,092 per adult). Excess costs of unemployment ($66.8 billion; 54.4%) comprised the largest proportion of the total, followed by productivity loss ($28.8 billion; 23.4%) and health care services ($14.3 billion; 11.6%). CONCLUSIONS: ADHD in adults is associated with substantial economic burden. DISCLOSURES: This study was funded by Otsuka Pharmaceutical Development & Commercialization, Inc. (Otsuka). The study sponsor contributed to and approved the study design, participated in the interpretation of data, and reviewed and approved the manuscript. Schein is an employee of Otsuka. Gagnon-Sanschagrin, Davidson, Kinkead, Cloutier, Guérin, and Lefebvre are employees of Analysis Group, Inc., a consulting company that provided paid consulting services to Otsuka to develop and conduct this study and write the manuscript. Adler has received research support from Shire/Takeda, Sunovion, and Otsuka; consulting fees from Bracket, Shire/Takeda, Sunovion, Otsuka, the State University of New York (SUNY), the National Football League (NFL), and Major League Baseball (MLB); and royalty payments (as inventor) from New York University (NYU) for license of adult ADHD scales and training materials. Childress has received research support from Allergan, Takeda/Shire, Emalex, Akili, Ironshore, Arbor, Aevi Genomic Medicine, Neos Therapeutics, Otsuka, Pfizer, Purdue, Rhodes, Sunovion, Tris, KemPharm, Supernus, and the US Food and Drug Administration; was on the advisory board of Takeda/Shire, Akili, Arbor, Cingulate, Ironshore, Neos Therapeutics, Otsuka, Pfizer, Purdue, Adlon, Rhodes, Sunovion, Tris, Supernus, and Corium; received consulting fees from Arbor, Ironshore, Neos Therapeutics, Purdue, Rhodes, Sunovion, Tris, KemPharm, Supernus, Corium, Jazz, and Tulex Pharma; received speaker fees from Takeda/Shire, Arbor, Ironshore, Neos Therapeutics, Pfizer, Tris, and Supernus; and received writing support from Takeda/Shire, Arbor, Ironshore, Neos Therapeutics, Pfizer, Purdue, Rhodes, Sunovion, and Tris. Part of the material in this study was presented as a poster at the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) 2021 Virtual Meeting; May 17-20, 2021.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».