Telemedicine and Office-Based Care for Behavioral and Psychiatric Conditions During the COVID-19 Pandemic in the United States
Notice bibliographique
Résumé
Letters17 November 2020Telemedicine and Office-Based Care for Behavioral and Psychiatric Conditions During the COVID-19 Pandemic in the United StatesFREEOmar Mansour, MHS, Matthew Tajanlangit, James Heyward, MPH, Ramin Mojtabai, MD, PhD, G. Caleb Alexander, MD, MSOmar Mansour, MHSMonument Analytics, Baltimore, Maryland, Matthew Tajanlangit, James Heyward, MPHCenter for Drug Safety and Effectiveness, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, Ramin Mojtabai, MD, PhDCenter for Drug Safety and Effectiveness, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, G. Caleb Alexander, MD, MSCenter for Drug Safety and Effectiveness, Johns Hopkins Bloomberg School of Public Health, and Johns Hopkins Medicine, Baltimore, MarylandAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/M20-6243 SectionsAboutVisual AbstractPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail Background: The coronavirus disease 2019 (COVID-19) pandemic has had far-reaching effects on health care delivery in the United States, ranging from postponement of elective care (1) to increases in the use of telemedicine (2). However, little is known about how the pandemic has affected the treatment of behavioral and psychiatric conditions.Objective: To characterize quarterly telemedicine and office-based visits from the first quarter of 2018 (2018Q1) through the second quarter of 2020 (2020Q2).Methods and Findings: We used IQVIA's National Disease and Therapeutic Index—a proprietary, 2-stage, stratified (by specialty and geographic area), nationally representative audit of ambulatory care in the United States—to characterize quarterly telemedicine and office-based visits from 2018Q1 through 2020Q2. Telemedicine visits included those taking place by telephone as well as through web-based platforms. The National Disease and Therapeutic Index involves approximately 4800 physicians who use an electronic form to record details of all patient contacts during 2 consecutive workdays per quarter and generates more than 350 000 annual contact records. Reporting days are randomly assigned to ensure that all workdays in a report period are covered; Saturdays, Sundays, and holidays are assigned as reporting days to physicians practicing on those days. We restricted our analyses to primary care and psychiatric visits and focused on care for 6 of the most prevalent behavioral and psychiatric conditions in the United States: anxiety, depression, overactivity, bipolar disorder, insomnia, and opioid use disorder (3).Total visits across settings for the 6 conditions decreased from an average of 15.9 million during the first quarter of 2018 and 2019 (2018/2019Q1) to 13.0 million in 2020Q1 (percentage change, −18%) before increasing to 15.8 million in 2020Q2, which is near the 2018/2019Q2 average of 15.7 million (Figure and Table). Office-based visits decreased from an average quarterly volume of 15.5 million before 2020 to 11.9 million in 2020Q1 and 5.3 million in 2020Q2. During the same period, telemedicine visits accounted for fewer than 3% of visits before 2020 (approximately 0.4 million), 9% during 2020Q1 (1.1 million), and 66% during 2020Q2 (10.5 million). Generally, there were no significant variations in patients' sex or race/ethnicity during the same period; however, patients who had telemedicine visits were younger, especially in 2020Q2. Most visits were subsequent rather than new visits, even after the shift to telemedicine starting in 2020 (Figure), suggesting that telemedicine served primarily to accommodate persons already established in care.Figure. Quarterly trends in telemedicine and office-based visits for behavioral and psychiatric conditions in the United States, 2018–2020 (n = 16 067 unweighted total visits).Source: IQVIA's National Disease and Therapeutic Index, 2018–2020, based on a sampling frame of more than 500 000 physicians from the American Medical Association and the American Osteopathic Association master lists. Estimates are weighted based on survey weights provided by the National Disease and Therapeutic Index. Conditions were defined on the basis of having International Classification of Diseases, Ninth Revision codes listed from a visit. Data were based on primary care (family practice, general practice, geriatrics, internal medicine, and pediatrics) and psychiatrist visits. Q = quarter. Download figure Download PowerPoint Table. Telemedicine and Office-Based Visits for Behavioral and Psychiatric Conditions in the United States During the First Two Quarters of 2018–2020 (n = 9540 Unweighted Total Visits)From 2018/2019Q1 to 2020Q1, there were decreases of 17% to 31% in office-based visits across the 6 conditions (Figure and Table). Office-based visits decreased further, by 49% (opioid use disorder) to 73% (bipolar disorder), between 2018/2019Q2 and 2020Q2. By contrast, telemedicine visits increased by 55% (bipolar disorder) to 360% (overactivity) between 2018/2019Q1 and 2020Q1 and by 1620% (insomnia) to 8061% (overactivity) between 2018/2019Q2 and 2020Q2.Discussion: The COVID-19 pandemic has been associated with large decreases in office-based visits for behavioral and psychiatric conditions, although by 2020Q2 these had been offset by large increases in telemedicine visits among the conditions examined. Given concerns about the potential deleterious effects of the pandemic on the behavioral and psychiatric needs of vulnerable populations as well as the implementation of policies to mitigate such harms (4), the increases in telemedicine visits are noteworthy. However, further work is needed to establish how effectively telemedicine can reduce logistic and social barriers to mental health care. It is also unclear if the increases we note are sufficient to address the increased prevalence of depressive and anxiety symptoms as a result of the COVID-19 pandemic (5).Despite our analyses' insights, they provide a snapshot of dynamic processes and, like all surveys, may be prone to measurement error and bias. These limitations notwithstanding, our findings suggest profound shifts in care patterns for common behavioral and psychiatric illnesses in the United States and underscore the importance of further work to assess how different treatment settings, including the delivery of care through telemedicine platforms, may affect patients' experiences and health outcomes.References1. Cutler D. How will COVID-19 affect the health care economy? JAMA Forum. 9 April 2020. Accessed at https://jamanetwork.com/channels/health-forum/fullarticle/2764547 on 2 June 2020. Google Scholar2. Alexander GC, Tajanlangit M, Heyward J, et al. Use and content of primary care office-based vs telemedicine care visits during the COVID-19 pandemic in the US. JAMA Netw Open. 2020;3:e2021476. [PMID: 33006622] doi: 10.1001/jamanetworkopen.2020.21476 CrossrefMedlineGoogle Scholar3. Ashman JJ, Rui P, Okeyode T. Characteristics of office-based physician visits, 2016. NCHS Data Brief. 2019:1-8. [PMID: 30707670] MedlineGoogle Scholar4. Alexander GC, Stoller KB, Haffajee RL, et al. An epidemic in the midst of a pandemic: opioid use disorder and COVID-19 [Editorial]. Ann Intern Med. 2020;173:57-8. doi: 10.7326/M20-1141 LinkGoogle Scholar5. Amsalem D, Dixon LB, Neria Y. The coronavirus disease 2019 (COVID-19) outbreak and mental health: current risks and recommended actions. JAMA Psychiatry. 2020. [PMID: 32579160] doi:10.1001/jamapsychiatry.2020.1730 Google Scholar Comments 0 Comments Sign In to Submit A Comment Author, Article, and Disclosure InformationAuthors: Omar Mansour, MHS; Matthew Tajanlangit; James Heyward, MPH; Ramin Mojtabai, MD, PhD; G. Caleb Alexander, MD, MSAffiliations: Monument Analytics, Baltimore, MarylandCenter for Drug Safety and Effectiveness, Johns Hopkins Bloomberg School of Public Health, Baltimore, MarylandCenter for Drug Safety and Effectiveness, Johns Hopkins Bloomberg School of Public Health, and Johns Hopkins Medicine, Baltimore, MarylandDisclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M20-6243.Reproducible Research Statement: Study protocol and data set: Not available. Statistical code: Available from Dr. Alexander (e-mail, galexan9@jhmi.edu).Corresponding Author: G. Caleb Alexander, MD, MS, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, W6035, Baltimore, MD 21205; e-mail, galexan9@jhmi.edu.This article was published at Annals.org on 17 November 2020. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetails Metrics Cited byImpact of the COVID-19 pandemic on treatment for mental health needs: a perspective on service use patterns and expenditures from commercial medical claims dataImproving measurement-based care implementation in adult ambulatory psychiatry: a virtual focus group interview with multidisciplinary healthcare professionalsPrevalence and Predictors of Multimodal Treatment Among U.S. Adults Newly Diagnosed With ADHDDemographic Predictors of Telehealth Use for Integrated Psychological Services in Primary Care During the COVID-19 PandemicA Pilot Study of Brief, Stepped Behavioral Activation for Primary Care Patients with Depressive SymptomsPersonalized Mobile Health for Elderly Home Care: A Systematic Review of Benefits and ChallengesKey implementation factors in telemedicine-delivered medications for opioid use disorder: a scoping review informed by normalisation process theoryEffects of the Affordable Care Act Medicaid Expansions on Mental Health During the COVID-19 Pandemic in 2020-2021Telemedicine to Manage ADHDAppropriateness of Telemedicine Versus In-Person Care: A Qualitative Exploration of Psychiatrists’ Decision MakingTelemedicine services for living kidney donation: A US survey of multidisciplinary providersBehavioral activation for live-in migrant home care workers and care recipients in Israel: a pilot studyChanges and Inequities in Adult Mental Health–Related Emergency Department Visits During the COVID-19 Pandemic in the USUtilization of Physician-Based Mental Health Care Services Among Children and Adolescents Before and During the COVID-19 Pandemic in Ontario, CanadaTrends and Disparities in the Use of Telehealth Among Injured Workers During the COVID-19 PandemicExperience of using telemedicine technologies in healthcare systems of foreign countries and the Russian Federation: systematic reviewKnowing Well, Being Well: well-being born of understanding: Shifts in Health Behaviors Amid the COVID-19 PandemicOpportunities to Integrate Mobile App–Based Interventions Into Mental Health and Substance Use Disorder Treatment Services in the Wake of COVID-19Changes in Short-term, Long-term, and Preventive Care Delivery in US Office-Based and Telemedicine Visits During the COVID-19 PandemicIncreasing Cybercrime Since the Pandemic: Concerns for Psychiatry March 2021Volume 174, Issue 3 Page: 428-430 Keywords Anxiety Bipolar disorder COVID-19 Disclosure Insomnia Opioid use disorder Prevention, policy, and public health Primary care Psychiatry and mental health Telemedicine ePublished: 17 November 2020 Issue Published: March 2021 Copyright & PermissionsCopyright © 2020 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».