MétaCan
Menu
Back to cohort
Record W3100391753 · doi:10.7326/m20-6243

Telemedicine and Office-Based Care for Behavioral and Psychiatric Conditions During the COVID-19 Pandemic in the United States

2020· article· en· W3100391753 on OpenAlexaboutno aff
Omar Mansour, Matthew Tajanlangit, James Heyward, Ramin Mojtabai, G. Caleb Alexander

Bibliographic record

VenueAnnals of Internal Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsnot available
Fundersnot available
KeywordsTelemedicineMedicinePandemicPublic healthSpecialtyQuarter (Canadian coin)Family medicineHealth careTelehealthGerontologyPsychiatryCoronavirus disease 2019 (COVID-19)DiseaseNursingInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

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 ...

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.199
Threshold uncertainty score0.409

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.131
GPT teacher head0.451
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations32
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueAnnals of Internal MedicineSame topicTelemedicine and Telehealth ImplementationFrench-language works237,207