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• W4297310852 abstract "IntroductionWe report caregiver agreement to attend telehealth neurodevelopmental consultation during COVID-19, demographic differences in agreement, reasons families declined, and clinical access metrics before and during COVID-19.MethodData were gathered from telehealth referrals and consultations from April to July 2020. Schedulers documented agreement status and reasons for the decline. Wait time, lag time, and missed appointment rates were calculated to measure access.ResultsNinety-one percent agreed to attend telehealth consultation; 55% of those who declined preferred in-person services. There were no demographic differences between those who accepted, declined, or did not respond. The median wait time from referral to appointment was 60 days. Missed appointment rates were consistent with prepandemic rates.DiscussionFindings support literature suggesting patients are agreeable to telehealth. They diverged from evidence suggesting telehealth reduces missed appointments. Overall, results indicate telehealth is an acceptable alternative; however, further telehealth innovation is needed to address existing disparities. We report caregiver agreement to attend telehealth neurodevelopmental consultation during COVID-19, demographic differences in agreement, reasons families declined, and clinical access metrics before and during COVID-19. Data were gathered from telehealth referrals and consultations from April to July 2020. Schedulers documented agreement status and reasons for the decline. Wait time, lag time, and missed appointment rates were calculated to measure access. Ninety-one percent agreed to attend telehealth consultation; 55% of those who declined preferred in-person services. There were no demographic differences between those who accepted, declined, or did not respond. The median wait time from referral to appointment was 60 days. Missed appointment rates were consistent with prepandemic rates. Findings support literature suggesting patients are agreeable to telehealth. They diverged from evidence suggesting telehealth reduces missed appointments. Overall, results indicate telehealth is an acceptable alternative; however, further telehealth innovation is needed to address existing disparities. Before the COVID-19 pandemic, there was limited evidence to suggest that telehealth had the potential to increase access to needed services and decrease burdens for families of children with neurodevelopmental disabilities (Alfuraydan et al., 2020Alfuraydan M. Croxall J. Hurt L. Kerr M. Brophy S. Use of telehealth for facilitating the diagnostic assessment of autism spectrum disorder (ASD): A scoping review.PLOS ONE. 2020; 15e0236415Crossref PubMed Scopus (52) Google Scholar; Antezana et al., 2017Antezana L. Scarpa A. Valdespino A. Albright J. Richey J.A. Rural trends in diagnosis and services for autism spectrum disorder.Frontiers in Psychology. 2017; 8: 590Crossref PubMed Scopus (110) Google Scholar; Burke and Hall, 2015Burke B.L. Hall R.W. Section on Telehealth CareTelemedicine: Pediatric applications.Pediatrics. 2015; 136: e293-e308Crossref PubMed Scopus (256) Google Scholar; Soares and Langkamp, 2012Soares N.S. Langkamp D.L. Telehealth in developmental-behavioral pediatrics.Journal of Developmental and Behavioral Pediatrics. 2012; 33: 656-665Crossref PubMed Scopus (33) Google Scholar). Furthermore, small studies have demonstrated the feasibility, acceptability, and effectiveness of diagnostic and behavior intervention services delivered through telehealth (Bearss et al., 2018Bearss K. Burrell T.L. Challa S.A. Postorino V. Gillespie S.E. Crooks C. Scahill L. Feasibility of parent training via telehealth for children with autism spectrum disorder and disruptive behavior: A demonstration pilot.Journal of Autism and Developmental Disorders. 2018; 48: 1020-1030Crossref PubMed Scopus (84) Google Scholar; Juárez et al., 2018Juárez A.P. Weitlauf A.S. Nicholson A. Pasternak A. Broderick N. Hine J. Warren Z. Early identification of ASD through telemedicine: Potential value for underserved populations.Journal of Autism and Developmental Disorders. 2018; 48: 2601-2610Crossref PubMed Scopus (74) Google Scholar; Lindgren et al., 2020Lindgren S. Wacker D. Schieltz K. Suess A. Pelzel K. Kopelman T. O’Brien M. A randomized controlled trial of functional communication training via telehealth for young children with autism spectrum disorder.Journal of Autism and Developmental Disorders. 2020; 50: 4449-4462Crossref PubMed Scopus (49) Google Scholar; Reese et al., 2015Reese R.M. Jamison T.R. Braun M. Wendland M. Black W. Hadorn M. Prather C. Brief report: Use of interactive television in identifying autism in young children: Methodology and preliminary data.Journal of Autism and Developmental Disorders. 2015; 45: 1474-1482Crossref PubMed Scopus (21) Google Scholar; Stainbrook et al., 2019Stainbrook J.A. Weitlauf A.S. Juárez A.P. Taylor J.L. Hine J. Broderick N. Warren Z. Measuring the service system impact of a novel telediagnostic service program for young children with autism spectrum disorder.Autism. 2019; 23: 1051-1056Crossref PubMed Scopus (30) Google Scholar; Talbott et al., 2020Talbott M.R. Dufek S. Zwaigenbaum L. Bryson S. Brian J. Smith I.M. Rogers S.J. Brief Report: Preliminary feasibility of the TEDI: A novel parent-administered telehealth assessment for autism spectrum disorder symptoms in the first year of life.Journal of Autism and Developmental Disorders. 2020; 50: 3432-3439Crossref PubMed Scopus (27) Google Scholar). Although there was growing recognition of the potential benefits of telehealth, providers had been slow to implement this modality (Wallis et al., 2021Wallis K.E. Mulé C. Mittal S. Cerda N. Shaffer R. Scott A. Blum N.J Use of telehealth in fellowship-affiliated developmental behavioral pediatric practices during the COVID-19 pandemic.Journal of Developmental and Behavioral Pediatrics. 2021; 42: 314-321Crossref PubMed Scopus (18) Google Scholar) because of barriers including inconsistent reimbursement for services, limited access to the necessary technology, and the need for clinician training on telehealth technologies (Burke and Hall, 2015Burke B.L. Hall R.W. Section on Telehealth CareTelemedicine: Pediatric applications.Pediatrics. 2015; 136: e293-e308Crossref PubMed Scopus (256) Google Scholar; Iacono et al., 2016Iacono T. Dissanayake C. Trembath D. Hudry K. Erickson S. Spong J. Family and practitioner perspectives on telehealth for services to young children with autism.Studies in Health Technology and Informatics. 2016; 231: 63-73PubMed Google Scholar; Scott Kruse et al., 2018Scott Kruse C. Karem P. Shifflett K. Vegi L. Ravi K. Brooks M. Evaluating barriers to adopting telemedicine worldwide: A systematic review.Journal of Telemedicine and Telecare. 2018; 24: 4-12Crossref PubMed Scopus (738) Google Scholar). When COVID-19 made traditional diagnostic methods unsafe and inaccessible, social distancing requirements necessitated a rapid transition to telehealth for clinics worldwide. Since the onset of COVID-19, there has been a significant increase in evidence supporting telehealth models for neurodevelopmental evaluation (Alfuraydan et al., 2020Alfuraydan M. Croxall J. Hurt L. Kerr M. Brophy S. Use of telehealth for facilitating the diagnostic assessment of autism spectrum disorder (ASD): A scoping review.PLOS ONE. 2020; 15e0236415Crossref PubMed Scopus (52) Google Scholar; Thibodaux et al., 2021Thibodaux L.K. Breiger D. Bledsoe J. Sato J. Hilsman R. Paolozzi A. Teleneuropsychology: A model for clinical practice.Practice Innovations. 2021; 6: 189-198Crossref Google Scholar) as well as tools for remote evaluation of autism spectrum disorder (ASD; Berger et al., 2022Berger N.I. Wainer A.L. Kuhn J. Bearss K. Attar S. Carter A.S. Stone W.L. Characterizing available tools for synchronous virtual assessment of toddlers with suspected autism spectrum disorder: A brief report.Journal of Autism and Developmental Disorders. 2022; 52: 423-434Crossref PubMed Scopus (24) Google Scholar Corona et al., 2021Corona L.L. Weitlauf A.S. Hine J. Berman A. Miceli A. Nicholson A. Warren Z. Parent perceptions of caregiver-mediated telemedicine tools for assessing autism risk in toddlers.Journal of Autism and Developmental Disorders. 2021; 51: 476-486Crossref PubMed Scopus (44) Google Scholar; Wagner et al., 2021Wagner L. Corona L.L. Weitlauf A.S. Marsh K.L. Berman A.F. Broderick N.A. Warren Z. Use of the TELE-ASD-PEDS for autism evaluations in response to COVID-19: Preliminary outcomes and clinician acceptability.Journal of Autism and Developmental Disorders. 2021; 51: 3063-3072Crossref PubMed Scopus (63) Google Scholar. Research suggests that telehealth visits have been as effective as in-person visits for the screening and diagnosis of ASD (Alfuraydan et al., 2020Alfuraydan M. Croxall J. Hurt L. Kerr M. Brophy S. Use of telehealth for facilitating the diagnostic assessment of autism spectrum disorder (ASD): A scoping review.PLOS ONE. 2020; 15e0236415Crossref PubMed Scopus (52) Google Scholar; Ellison et al., 2021Ellison K.S. Guidry J. Picou P. Adenuga P. Davis 3rd, T.E. Telehealth and autism prior to and in the age of COVID-19: A systematic and critical review of the last decade.Clinical Child and Family Psychology Review. 2021; 24: 599-630Crossref PubMed Scopus (51) Google Scholar; Stavropoulos et al., 2022Stavropoulos K.K. Bolourian Y. Blacher J. A scoping review of telehealth diagnosis of autism spectrum disorder.PLOS ONE. 2022; 17e0263062Crossref Scopus (17) Google Scholar). In addition, clinicians and caregivers perceive the use of telehealth for neurodevelopmental evaluation as acceptable and satisfactory (Matthews et al., 2021Matthews N.L. Skepnek E. Mammen M.A. James J.S. Malligo A. Lyon A. Smith C.J. Feasibility and acceptability of a telehealth model for autism diagnostic evaluations in children, adolescents, and adults.Autism Research. 2021; 14: 2564-2579Crossref PubMed Scopus (12) Google Scholar; McNally Keehn et al., 2022McNally Keehn R. Enneking B. James C. Tang Q. Rouse M. Hines E. Etling A. Telehealth evaluation of pediatric neurodevelopmental disabilities during the COVID-19 pandemic: Clinician and caregiver perspectives.Journal of Developmental and Behavioral Pediatrics. 2022; 43: 262-272Crossref PubMed Scopus (7) Google Scholar). However, there continues to be a need for additional data on the feasibility and impact of service access. Evidence from primary care and other subspecialties suggests that the use of telehealth may reduce the rate of patients who do not arrive for or call to cancel their scheduled appointment (Drerup et al., 2021Drerup B. Espenschied J. Wiedemer J. Hamilton L. Reduced no-show rates and sustained patient satisfaction of telehealth during the COVID-19 pandemic.Telemedicine Journal and e-Health. 2021; 27: 1409-1415Crossref PubMed Scopus (48) Google Scholar; Franciosi et al., 2021Franciosi E.B. Tan A.J. Kassamali B. Leonard N. Zhou G. Krueger S. LaChance A. The impact of telehealth implementation on underserved populations and no-show rates by medical specialty during the COVID-19 pandemic.Telemedicine Journal and e-Health. 2021; 27: 874-880Crossref PubMed Scopus (30) Google Scholar; Muppavarapu et al., 2022Muppavarapu K. Saeed S.A. Jones K. Hurd O. Haley V. Study of impact of telehealth use on clinic “no show” rates at an academic practice.Psychiatric Quarterly. 2022; 93: 689-699Crossref PubMed Scopus (8) Google Scholar; Van Houten et al., 2021Van Houten L. Deegan K. Siemer M. Walsh S. A telehealth initiative to decrease no-show rates in a pediatric asthma mobile clinic.Journal of Pediatric Nursing. 2021; 59: 143-150Abstract Full Text Full Text PDF PubMed Scopus (11) Google Scholar). In a study of community-based appointments serving children and adults, Adepoju et al., 2022Adepoju O.E. Chae M. Liaw W. Angelocci T. Millard P. Matuk-Villazon O. Transition to telemedicine and its impact on missed appointments in community-based clinics.Annals of Medicine. 2022; 54: 98-107Crossref PubMed Scopus (13) Google Scholar found that use of telehealth reduced missed clinic visits for child and adult mental health services and general community health services for those in urban areas. Differences in show rates by race and ethnicity were consistent regardless of whether the appointment was completed in person or through telehealth (Adepoju et al., 2022Adepoju O.E. Chae M. Liaw W. Angelocci T. Millard P. Matuk-Villazon O. Transition to telemedicine and its impact on missed appointments in community-based clinics.Annals of Medicine. 2022; 54: 98-107Crossref PubMed Scopus (13) Google Scholar). Furthermore, there is mixed evidence regarding the efficacy and uptake of telehealth for reducing access barriers across race, ethnicity, and socioeconomic groups in the primary care setting (Alexander et al., 2020Alexander G.C. Tajanlangit M. Heyward J. Mansour O. Qato D.M. Stafford R.S. Use and content of primary care office-based vs telemedicine care visits during the COVID-19 pandemic in the US.JAMA Network Open. 2020; 3e2021476Crossref Scopus (246) Google Scholar; Cantor et al., 2021Cantor J.H. McBain R.K. Pera M.F. Bravata D.M. Whaley C.M. Who is (and is not) receiving telemedicine care during the COVID-19 pandemic.American Journal of Preventive Medicine. 2021; 61: 434-438Abstract Full Text Full Text PDF PubMed Scopus (81) Google Scholar; Reiners et al., 2019Reiners F. Sturm J. Bouw L.J.W. Wouters E.J.M. Sociodemographic factors influencing the use of ehealth in people with chronic diseases.International Journal of Environmental Research and Public Health. 2019; 16: 645Crossref PubMed Scopus (96) Google Scholar; Rodriguez et al., 2021Rodriguez J.A. Betancourt J.R. Sequist T.D. Ganguli I. Differences in the use of telephone and video telemedicine visits during the COVID-19 pandemic.American Journal of Managed Care. 2021; 27: 21-26Crossref PubMed Google Scholar; Weiner et al., 2021Weiner J.P. Bandeian S. Hatef E. Lans D. Liu A. Lemke K.W. In-person and telehealth ambulatory contacts and costs in a large US insured cohort before and during the COVID-19 pandemic.JAMA Network Open. 2021; 4e212618Crossref Scopus (84) Google Scholar). Although information regarding change in access metrics for patients with neurodevelopmental disabilities is limited, some evidence suggests that telehealth evaluation for children with ASD may decrease overall service costs and eliminate travel time (Juárez et al., 2018Juárez A.P. Weitlauf A.S. Nicholson A. Pasternak A. Broderick N. Hine J. Warren Z. Early identification of ASD through telemedicine: Potential value for underserved populations.Journal of Autism and Developmental Disorders. 2018; 48: 2601-2610Crossref PubMed Scopus (74) Google Scholar; Lindgren et al., 2016Lindgren S. Wacker D. Suess A. Schieltz K. Pelzel K. Kopelman T. Waldron D. Telehealth and autism: Treating challenging behavior at lower cost.Pediatrics. 2016; 137: S167-S175Crossref PubMed Scopus (218) Google Scholar). Furthermore, research on the impact of telehealth on waitlists or wait times, from referral to appointment, suggests that telehealth is associated with decreased numbers of patients waiting for subspecialty care (Gadenz et al., 2021Gadenz S.D. Basso J. de Oliviera P.R.B.P. Sperling S. Zuanazzi M.V.D. Oliveira G.G. de Faria Leao B. Telehealth to support referral management in a universal health system: A before-and-after study.BMC Health Services Research. 2021; 21: 1012Crossref PubMed Scopus (6) Google Scholar). For children with neurodevelopmental disabilities and their families, access to telehealth consultation services was associated with a reduction in the number of referrals made from rural areas to the tertiary care center (Stainbrook et al., 2019Stainbrook J.A. Weitlauf A.S. Juárez A.P. Taylor J.L. Hine J. Broderick N. Warren Z. Measuring the service system impact of a novel telediagnostic service program for young children with autism spectrum disorder.Autism. 2019; 23: 1051-1056Crossref PubMed Scopus (30) Google Scholar). COVID-19 has offered a unique opportunity to examine the utility of telehealth for serving children with neurodevelopmental disabilities and their families. However, gaps in the literature remain regarding who agrees to engage in telehealth consultation services, how demographic factors might impact acceptance, and how telehealth impacts metrics of service access. As such, the overall objective of this study was to examine caregiver agreement to engage in telehealth neurodevelopmental consultation during COVID-19 when in-person clinical services were suspended at a large outpatient neurodevelopmental evaluation clinic. In addition, we report on demographic differences between those who agree, decline, and are lost to follow-up after referral (i.e., did not respond to contact), reasons for which families declined a telehealth appointment, and clinical access metrics (i.e., wait time and rates of missed appointments) before and during the COVID-19 pandemic. Although research examining the feasibility and accuracy of telehealth neurodevelopmental consultation and evaluation is promising, understanding the reasons why caregivers accept or decline telehealth, how sociodemographic factors impact acceptability, and how telehealth impacts clinical access metrics has the potential to inform how telehealth service delivery models can improve care for children and families as well as the clinicians and institutions who serve them. Data were collected from an outpatient neurodevelopmental evaluation clinic within an academic medical center in the Midwestern United States. The interdisciplinary clinic is staffed by nine psychologists, two developmental-behavioral pediatricians, two speech/language pathologists, two social workers, and several affiliated trainees. Services are provided to patients ranging in age from 1 to 20 years with referral questions including ASD, developmental delay, speech-language delay, and behavioral concerns. The clinic serves patients from multiple neighboring Midwestern states, resulting in families traditionally traveling up to several hours for an appointment. Typical clinic volume before COVID-19 included approximately 4,500 referrals per year, with approximately 8,000 appointments (new and follow-up) offered. Sixty-six percent of patients seen in the clinic before COVID-19 used Medicaid insurance as their primary health plan. All patients referred to the clinic undergo an initial diagnostic consultation appointment. Initial appointment duration typically ranges between 90 and 120 min and is determined by the necessity for multiple disciplines. Interdisciplinary appointments are 120 min long and include a developmental-behavioral pediatrician and psychologist. A diagnostic consultation with a single discipline is scheduled for 90 min. During this consultation, providers conduct a clinical interview and developmental history with the patient's caregivers, obtain behavioral observations, and sometimes use a formal symptom inventory or observational screening tool. Usually, providers spend approximately 60–75 min completing a face-to-face interview and any symptom inventories, followed by 10–15 min synthesizing data, identifying resources and recommendations, and culminating with 15–45 min in face-to-face counseling with families. Typical “next steps” include further in-clinic evaluations or consultations (i.e., interdisciplinary or discipline-specific), treatment (provided by our clinic or an outside agency), and/or support via local resources and problem-specific recommendations. Before COVID-19, the clinic had piloted telehealth for follow-up care navigation services on a very limited basis. When stay-at-home orders were initiated in mid-March 2020, fewer than 10 telehealth visits had been conducted. The demand for continuity of care provided safely and socially distanced required a rapid transformation of clinic processes. Clinical services well-suited for a rapid transition to telehealth (e.g., initial diagnostic consultations) were prioritized while efforts were made to overcome barriers to conducting other services virtually. Telehealth appointment times remained the same for in-person services (i.e., 90 min for single discipline and 120 min for interdisciplinary). In lieu of traditional measures, providers identified and obtained training on alternative telehealth assessment measures (e.g., Tele-ASD-Peds; Corona et al., 2020Corona, L., Hine, J., Nicholson, A., Stone, C., Swanson, A., Wade, J., . . . Warren, Z. (2020). TELE-ASD-PEDS: A telemedicine-based ASD consultation tool for toddlers and young children. Retrieved from: https://vkc.vumc.org/vkc/triad/tele-asd-peds.Google Scholar). In addition to virtual observational tools, caregiver and teacher rating forms (e.g., Vineland Adaptive Behavior Scales [third edition]; Sparrow et al., 2016Sparrow S.S. Cicchetti D.V. Saulnier C.A. Vineland Adaptive Behavior Scales.3rd ed. Pearson, San Antonio, TX2016Google Scholar) used to supplement parent interviews were fully transitioned to remote electronic completion using publisher-provided platforms (e.g., Pearson Q-Global). Following the appointment, a written summary and recommendations were sent to families by secure e-mail, a final consultation report was provided to caregivers and the referring physician, and the opportunity for care navigation support from social work was provided as needed. Clinic staff and providers developed detailed educational guides, support tools, and processes for three primary groups: (1) providers, (2) staff members, and (3) families of referred children. Providers were trained on the use of the telehealth platform, administration of assessments (Wagner and Hine, 2020Wagner, L., & Hine, J. (2020). Telemedicine-based autism spectrum disorder assessment in toddlers. Retrieved from: https://vkc.vumc.org/vkc/triad/live-webinars/.Google Scholar), telehealth billing guidelines, virtual provision of documentation to the families, and compliance with state and national clinical guidelines. The administrative staff was trained on scheduling procedures and scripts to support families accessing telehealth consultations. A technology support hotline was established to assist families before and during the consultation if needed. In addition, providers and administrative staff collaborated to ensure families received timely clinical documentation following the diagnostic consultation. All patients referred to the clinic for consultation of developmental and/or behavioral concerns were eligible for a telehealth appointment during the study period. During the initial scheduling phone contact, the administrative team offered a telehealth consultation and informed the caregivers of the referred child that it was unknown when in-person appointments would resume. Those who declined telehealth were informed of their placement on a waitlist for an in-person consultation. For caregivers agreeing to be scheduled for a telehealth appointment, administrative staff verified that families had the required technology, including access to a mobile device with a camera (i.e., smartphone, tablet, or computer), the ability to download the application needed for the conferencing platform (i.e., Zoom Health), and appropriate Internet connection. Verbal and written instructions on accessing the virtual platform were provided and guidance on preparing for their diagnostic consultation appointment. This project was part of a larger research study on the implementation of telehealth for neurodevelopmental consultation and was approved by the university institutional review board. Data were collected for patients contacted to schedule a telehealth appointment between April and July 2020. Clinical schedulers used verbal scripts to contact the patient's caregiver to determine whether they were agreeable to a telehealth visit and their preferred platform (e.g., phone or virtual). Based on the conversation, data were gathered regarding whether the family agreed to the telehealth appointment, declined the telehealth appointment, and any reasons for declining were collected. Reasons for declining were categorized into the following: (1) do not have appropriate technology (i.e., video, Internet/data, reliable phone connection), (2) have other prioritized needs (i.e., food, safety), (3) concern about payment or insurance reimbursement, (4) prefer in-person appointment and would rather wait until this is available, or (5) other. If the scheduling team could not reach the family after two phone calls 48 hr apart and the family did not return the phone call during the study period, the patient was considered “lost to follow up.” Schedulers documented this information during phone calls through an online, secure data collection survey. In addition to this data, the patient's electronic medical records were reviewed to obtain child demographic information, including sex, date of birth, referral date and concern, and insurance information. Two measures of access were collected for the current study: (1) wait time (i.e., defined as the time from receipt of referral to appointment completion) and (2) lag time (i.e., defined as the time between when the patient is scheduled and when the appointment is completed). Because our hospital system collects lag time data, the research team was able to compare this metric between pre- and post-COVID-19. Data used to calculate both wait time and lag time were gathered from the electronic medical record. Missed appointments were defined as families who did not arrive for their scheduled appointment, called to cancel, or did not respond to a phone call from the provider to resolve any technological concerns. Study data were collected and managed using REDCap (Research Electronic Data Capture), a secure, web-based software platform to support data capture for research studies (Harris et al., 2009Harris P.A. Taylor R. Thielke R. Payne J. Gonzalez N. Conde J.G. Research Electronic Data Capture (REDCap) – A metadata-driven methodology and workflow process for providing translational research informatics support.Journal of Biomedical Informatics. 2009; 42: 377-381Crossref PubMed Scopus (25804) Google Scholar; Harris et al., 2019Harris P.A. Taylor R. Minor B.L. Elliott V. Fernandez M. O'Neal L. REDCap ConsortiumThe REDCap consortium: Building an international community of software platform partners.Journal of Biomedical Informatics. 2019; 95103208Crossref PubMed Scopus (7143) Google Scholar). Data analysis was performed with SAS version 9.4 (SAS Institute, Inc., Cary, NC). Descriptive statistics for continuous variables are presented as means and standard deviations, and descriptive statistics for categorical variables are presented as frequencies and percentages. Between-group analyses for continuous variables were conducted using a one-way analysis of variance, and between-group analyses for categorical variables were conducted using χ2 or Fisher's exact tests. The relationship between wait/lag time and demographic variables was examined using generalized linear mixed effect models with random effects to account for correlation within providers. A similar method was used to examine differences in demographic variables between those who attended their consultations and those who did not. Of note, for these analyses, children who were scheduled for a phone visit (n = 4) or required the use of an interpreter (n = 8) were excluded. Participants included 430 patients referred to our clinic and contacted for consultation scheduling between April–July 2020. Patients were, on average, 71 months of age (range 18–211 months). Sixty-nine percent (n = 296) of patients were male. Patient race/ethnicity was only available on a subset (n = 124) of the sample because of incomplete information in the patient's medical record. Of those for which data was available, 80% (n = 99) identified as White. Other races included Black or African American (11%, n = 14), more than one race (5%, n = 6), Asian (3%, n = 4), and other (1%, n = 1). Eighty-eight percent (n = 109) of patients identified as non-Hispanic/Latinx. Most common referral questions included ASD (50%; n = 213), developmental delay (18%; n = 78), and behavior problems (12%; n = 50). Other referral questions (20%; n = 89) included language/communication delay, attention deficit hyperactivity disorder, learning difficulties, and anxiety. Most patients (57%; n = 246) used Medicaid as their primary health insurance plan. For those patients for whom details regarding household income were available (n = 124), 35% reported an income less than $40,000, 29% reported between $40,000 and $74,999, and 29% reported $75,000 or more. See Table 1 for a detailed summary of demographic and referral information. For details regarding patient flow through the study, see Figure 1.Table 1Demographics of children identified for telehealth consultation (n = 430)Demographicsn%Gender Male29669.0 Female13331.0Insurance Medicaid24657.3 Private12428.9 No Insurance5913.8Race (n = 124) White9979.8 Black or African American1411.3 More than one race64.8 Asian43.2 Other10.8Ethnicity (n = 124) Not Hispanic or Latino10987.9 Hispanic or Latino118.9 Unknown43.2Household Income (n = 124) < $40,0004334.7 ≥ $75,0003629.0 $50,000–$59,9991411.3 $60,000–$74,999129.7 $40,000–$49,999108.1 Prefer not to answer97.3 Open table in a new tab Of the 430 children identified for telehealth consultation, 21% (n = 91) of families were lost to follow-up (i.e., did not respond to contact). Of those who did respond to contact (n = 339; 79%), most families (92%; n = 310) agreed to be scheduled for a telehealth consultation. Ninety-nine percent (n = 308) preferred to have a video visit over a phone consultation. Eleven percent (n = 29) declined to participate in a telehealth appointment. Of those w" @default.
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• W4297310852 title "Acceptability and Access Metrics for Telehealth Consultation of Pediatric Neurodevelopmental Disabilities During COVID-19" @default.
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• W4297310852 doi "https://doi.org/10.1016/j.pedhc.2022.08.008" @default.
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