Telemedicine and e-HealthVol. 28, No. 5 AbstractsFree AccessATA2022 Annual Conference & Expo May 1–3, 2022Boston, MassachusettsPublished Online:11 May 2022https://doi.org/10.1089/tmj.2022.29073.abstractsAboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail Jointly Provided by the University of Virginia School of Medicine, School of Nursing and American Telemedicine AssociationAccreditation & Designation Statement“In support of improving patient care, this activity has been planned and implemented by the American Telemedicine Association (ATA) and the University of Virginia School of Medicine and School of Nursing is jointly accredited by the Accreditation Council for Continuing Medical Education (ACCME), the Accreditation Council for Pharmacy Education (ACPE), and the American Nurses Credentialing Center (ANCC), to provide continuing education for the healthcare team.”AMA PRA CATEGORY 1 CREDITThe University of Virginia School of Medicine and School of Nursing designates this live virtual activity and enduring material, for a maximum of 8AMA PRA Category 1 Credits.™ Physicians should claim only the credit commensurate with the extent of their participation in the activity.ANCC CONTACT HOURSThe University of Virginia School of Medicine and School of Nursing awards 8 contact hours for nurses who participate in this educational activity and complete the post activity evaluation.MOC IISuccessful completion of this CME activity enables the participant to earn MOC points equivalent to the amount of CME credits claimed for the activity for a maximum of 8.0 MOC Part II (ABMS) points.“Successful completion of this CME activity, which includes participation in the evaluation component, enables the participant to earn up to 8.0 MOC points [and patient safety MOC credit] in the American Board of Internal Medicine's (ABIM) Maintenance of Certification (MOC) program. It is the CME activity provider's responsibility to submit participant completion information to ACCME for the purpose of granting ABIM MOC credit”.Oral Presentations1.Withdrawn2. ASSESSING THE EFFECT OF PAYMENT PARITY ON TELEHEALTH USAGE AT COMMUNITY HEALTH CENTERS DURING COVID‐19Jordan HerringFitzhugh Mullan Institute for Health Workforce EquityDescription: Monthly visit volumes for in‐person and telehealth visits are based on aggregated, de‐identified claims data from FAIR Health that are representative of community health center sites, and this is matched with state‐level designations of payment parity policies. Relationship between telehealth utilization and policy is studied.Abstract: The COVID‐19 pandemic presented health care providers the incentive to aggressively adopt telehealth usage to supplement their visit levels while minimizing in‐person contact. States quickly altered telehealth coverage and payment policies to ensure ongoing access to care and help prevent spread of the virus. This study examines the effect payment parity had on the likelihood community health centers (CHCs) offered telehealth services in the initial year of the pandemic. The main data source was aggregated, deidentified FAIR Health data on monthly CHC site level visit counts (in‐person and telehealth) for privately insured patients covering dates of service from March 2019 through June 2021. We conducted separate logistic regression models to predict whether CHC sites utilized telehealth during the same four‐month period (March through June) for 1) one year before the pandemic, 2) the immediate pandemic response, and 3) one year after the pandemic.Classification of Research: Regulatory & Policy ResearchResults: Use of telehealth by CHC sites for privately insured patients surged during the immediate four‐month period of the pandemic to approximately 61%, but tapered off to approximately 44% one year later. Parity of payment was associated with greater likelihood of using telehealth beyond the initial four‐month period of the pandemic (OR:1.762, p < 0.001). Additionally, greater broadband access was positively associated with telehealth usage while rurality of the CHC site locations was negatively associated.Conclusions: Paying the same amount for telehealth visits as in‐person visits appears to make telehealth a more sustainable option in community health centers. Investments in broadband infrastructure could also help increase use of telehealth, particularly in rural areas.3. ASSESSMENT OF PROVIDER DIAGNOSTIC ACCURACY WITH VIDEO TELEMEDICINE IN THE INTEGRATED MULTISPECIALTY PRACTICE AT MAYO CLINIC DURING THE COVID‐19 PANDEMICBart Demaerschalk, MD, Andrew Pines, Richard Butterfield, Jack Haglin, Tufia Haddad, James Yiannias, Christopher Colby, Sarvam TerKonda, Steve Ommen, Matthew Bushman, Troy Lokken, R Blegen, Mekenzie Hoff, Gregory Anthony, Jordan Coffey, Nan ZhangDiagnostic Accuracy of Telemedicine Utilized at Mayo Clinic Alix School of Medicine Study GroupDescription: There was a shift in patient volume from in‐person to video telemedicine visits during the COVID‐19 pandemic. Objective of this study was to determine the accuracy of provisional diagnoses established at a video telemedicine visit for patients presenting with a new clinical problem.Abstract: Design: Retrospective review of patients who underwent a video telemedicine consult followed by an in‐person outpatient visit for the same clinical problem in the same specialty within a 90‐day window. The provisional diagnosis made during the video telemedicine visit was compared to the reference standard diagnosis by two blinded, independent medical reviewers. A multivariate logistic regression model was used to determine factors significantly related to diagnostic accuracy.Setting: Mayo Clinic, U.S.A., a large academic integrated multi‐specialty healthcare institution, between March 24 and June 24, 2020Participants: Mayo Clinic patients residing in the U.S.A. without age restrictionExposure: New clinical problem assessed via video telemedicine visit to home utilizing Zoom Care Anyplace integrated into EpicMain Outcome: Accuracy of provisional diagnoses established over video telemedicine visits compared against a reference standard diagnosisMethod: ObservationalClassification of Research: Access to CareResults: There were 2393 subjects in the analysis. The median age of patients was 53 years, and 1381/2393 (57.7%) identified as female and 1012/2393 (42.3%) identified as male. Overall, the provisional diagnosis established over video telemedicine visit matched the in‐person reference standard diagnosis in 2080/2393 [86.9% (95% CI 85.6%‐88.3%)] of cases. Diagnostic accuracy by ICD 10 chapter ranged from 65% (95% CI 42%‐87%) for “Diseases of the Ear and Mastoid Process” to 97% (95% CI 95%‐99%) for “Neoplasms”. Diagnostic accuracy by medical specialty ranged from 77% (95% CI 65%‐90%) for Otorhinolaryngology to 96% (92%‐100%) for Psychiatry. Specialty care was found to be significantly more likely than primary care to result in video telemedicine diagnoses congruent with a subsequent in‐person visit (OR:1.69; 95% CI: 1.24, 2.30. p < .001).Conclusions: Video telemedicine visits yield a high degree of diagnostic accuracy for most new clinical concerns, although it is important to recognize when specific clinical circumstances may be associated with decreased diagnostic accuracy over video telemedicine and which patients may benefit from timely in‐person follow up.!Video telemedicine visits yield a high degree of diagnostic accuracy for most new clinical concerns, although it is important to recognize when specific clinical circumstances may be associated with decreased diagnostic accuracy over video telemedicine and which patients may benefit from timely in‐person follow up.4. ENDING INEQUITY IN HEALTHCARE ACCESS: A TELEHEALTH PRIORITYCynthia WilliamsUniversity of North FloridaDescription: Access to care was critical during COVID19 and will continue to be an integral part of healthcare delivery. This research study provides insight to mitigate inequity in healthcare access by examining inequities in access and recommending strategies to increase access to vulnerable groups.Abstract: The global COVID‐19 pandemic has propelled the use of technology for healthcare services delivery. Through legislative measures and reimbursement practices, we witnessed overwhelming support for telehealth services to facilitate access to care during COVID‐19. However, the support and use for telehealth services must accompany outcomes that contribute to equity in access. If today's society is to support public health and healthcare, equal access to telehealth resources must be a priority. To achieve health equity, technology‐based resources should be comprehensively addressed to ensure that all racial/ethnic groups have access to all platforms for care. The study objective is to examine the use of telehealth services among racial/ethnic minority groups before and during the pandemic. The COVID‐19 Research Database Consortium provided data for this study. The study period was March 2019 to December 2019 and March 2020 to December 2020. Electronic health records of patients in the Healthjump database were examined. We performed a retrospective study on three racial/ethnic groups: non‐Hispanic Whites, non‐Hispanic Blacks Americans, and Hispanics. We used Logistic Regression to examine the study objective.Method: DescriptiveClassification of Research: Access to CareResults: We examined 17.98 million unique visit records from March 2019 to December 2019 and 22.17 million records of March 2020 to December 2020 to investigate changes in telehealth utilization before and during the pandemic. Pre‐COVID and during COVID telehealth visits accounted for 8.33% and 11.08% of total visits, respectively, with a peak of 15.46% in April 2020. Pre‐COVID, the Hispanic group showed a significantly lower utilization rate (5.36%) than the non‐Hispanic White groups (8.39%, p‐value <0.01) and Blacks (22.11%; p‐value <0.01). During the pandemic, Hispanic Americans (p‐value <0.01) had an adjusted odds ratio of 0.62.Conclusions: The odds of using telehealth by Hispanic Americans were still significantly lower compared to Whites and Blacks during the pandemic. Despite the removal of regulatory and reimbursement barriers to telehealth, utilization trends were largely unchanged. By identifying subgroups who are not accessing telemedicine, we recommend strategies and policy interventions to educate and target minority groups to promote the use of telemedicine services.5. ENSURING EQUITY: LESSONS FROM COVID‐19 REMOTE PATIENT MONITORINGLulu WangMedStar HealthDescription: Remote patient monitoring (RPM) has evolved into a powerful tool for expanding care delivery. Here, we discuss lessons learned from implementing a large‐scale COVID‐19 RPM program. Which disparities in telehealth access are highlighted with RPM? How can we make RPM more accessible?Abstract: RPM filled an important care gap during COVID‐19. For some, RPM served as a primary point of access to the health care system. It allowed for early detection of disease progression and provided additional reassurance to patients safely recovering at home. However, RPM remains vulnerable to the same disparities that affect healthcare as a whole: differences in health literacy, technologic literacy, and availability of services. Over the course of 11 months, our hospital system enrolled over 2047 patients in a COVID‐19 RPM program – the largest to‐date to capture both physiologic and symptomatologic data. We included two populations that often experience limited access to RPM: participants without smartphones, and participants whose primary language is not English. These are the exact vulnerable populations for whom RPM may prove particularly valuable as a safety net.Method: DescriptiveClassification of Research: Access to CareResults: We referred 4163 patients and enrolled 2047 patients on the RPM platform. Of these, 120 did not own smartphones and 43 spoke a primary language other than English (including Spanish, Portuguese, and Thai). Participants without smartphones required additional time resources; the RPM team called patients individually to collect data, as patients were not able to upload vital signs via the default method (Bluetooth‐enabled pulse oximeter and phone app). For non‐English speaking patients, the app was available in Spanish. Any other communication between the RPM team and participant required the assistance of interpreter services.Conclusions: RPM has rapidly expanded our scope of clinical care delivery. As its utilization continues to grow, we should be cognizant of promoting equity. Inclusion criteria, platform selection, communication modality, and methods of data collection all significantly impact patient experience. If deployed conscientiously, RPM can be a powerful tool to fill existing holes in health care accessibility.6. EVALUATION OF THE GREEK NATIONAL TELEMEDICINE NETWORK SERVICES IN THE AEGEAN ARCHIPELAGOS, DURING THE YEARS 2016‐2018Alexandra Bargiota, Alexandros Sarpakis, Athanasios Argyriadis, Christos Roilos, Eleftherios Thireos, George E. Dafoulas, Georgios Koukoulas, Haralampos KaranikasUniversity of ThessalyDescription: The Greek Ministry of Health established the National Telemedicine Network (EDIT) in 2016, to cover, in the first stage, 43 sites of the 2nd Regional Health Authority, 30 of them remotely and 13 urban located in islands of Aegean Archipelagos. This study evaluated these services for the years 2016‐2018.Abstract: The methodology for the evaluation of the EDIT services was based on “The Model for ASsessment of Telemedicine applications (MAST). MAST is a multidisciplinary assessment, for telemedicine services, that comprise seven domains (1. Health problem and characteristics of the application 2. Safety 3. Clinical effectiveness 4. Patient perspectives 5. Economic aspects 6. Organisational aspects 7. Socio‐cultural, ethical and legal aspects), based on the Health Technology Assessment (HTA) domains in the EUnetHTA model. In this study evaluation included the domains 1, 2, 6,7, while the evaluation of domains 3,4, and 5 will be performed per pathology, in other studies. The analysis included qualitative research based on interviews with personnel, health professionals and involved stakeholders, plus quantitative research based on descriptive methodolgy. The evaluation was performed by the University of Thessaly based on the data (years 2016‐2018) that were provided by the 2nd Regional Health Authority. The asynchronous and synchronous telemedicine services of EDIT, include teleconsultations for 25 specialties, emergency telemedicine and tele‐training. The urban located sites also called “doctor's end‐point”, are equipped with the video conference system and receive the patient's vital signs measurements. The remote located sites also called “patient's end‐point”, are additionally equipped with medical devices for the patient's examination.Method: DescriptiveClassification of Research: Measurement Frameworks & ToolsResults: The number of tele‐consultations increased gradually per year of service (2016:248, 2017:303, 2018:1205). The majority of tele‐consultations included Telepsychiatry with children (2016:49.19%, 2017:64.68%, 2018:38.75%), Telepsychiatry with adults (2017:13.33%, 2018:33.52%) and Tele‐diabetology (2017:7.2%, 2018:15.51%). No safety incidences were reported and based on the Service‐Level Agreement all technical problems were solved within the agreed mean time between failures (MTBF) and the mean time to repair or mean time to recovery (MTTR). Legal framework for telemedicine services in Greece is based on law 66§16‐3984/2011, and Data Protection and Privacy on the European General Data Protection Directive (GDPR).Conclusions: The introduction of telemedicine services of EDIT was mostly deployed in the clinical pathologies that adopted a specific tele‐consultation clinical protocol. The deployment of telemedicine services of EDIT were not followed by organisational changes, including the referral procedures that did not include prior requests for tele‐consultation and no reimbursement has been introduced. Safety and Data Privacy issues were managed adequately.Acknowledgement: This research has been co‐financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH – CREATE – INNOVATE (project code: Τ2EDK‐00640).”7. FROM DISEASE‐CENTRIC TO HUMAN‐CENTRIC REMOTE PATIENT MONITORING: WHAT IS THE ROLE OF DATA QUALITY MANAGEMENT?Robab AbdolkhaniRMIT UniversityDescription: The use of various technologies in disconnected remote patient monitoring programs which capture a large volume of data in multiple formats and inconsistent ways under the patient' or carer's supervision outside the clinical environment significantly impact the quality of data. Best practice recommendations were developed to address this issue.Abstract: Remote Patient Monitoring (RPM) is a complex system of people, processes, and technologies that constantly interact to monitor various health conditions and provide a comprehensive picture of the patient's status. However, current RPM programs are not integrated; instead, each RPM is used for one health condition and captures data relevant to that condition. This approach is not responsive to the needs of people suffering from multimorbidity to provide holistic patient‐centred care. The result is that a patient might participate in multiple RPM programs and use various disconnected technologies and platforms that capture a large volume of data in various formats and inconsistent ways, which significantly impact the quality of data, especially that data are collected under the patient' or carer's supervision outside the clinical environment.This issue was addressed via PhD research that provided innovative best practice recommendations for data quality management in RPM programs. The developed and validated recommendations comprising 19 items across seven aspects of data quality: accessibility, accuracy, completeness, consistency, interpretability, relevancy, and timeliness. It aims to drive strategies to collect and manage high‐quality data to integrate data with confidence from different RPM programs, improve multimorbidity monitoring, and provide efficient patient‐centred care.Method: Survey/QualitativeClassification of Research: Quality ImprovementResults: A DQM guideline was developed via five qualitative studies. Stakeholders with experience in RPM were involved in interviews to identify DQM challenges and a workshop to co‐design solutions. The findings along with results from literature and policy review were interpreted to construct the guideline. It comprised 19 recommendations across PGHD accessibility, accuracy, completeness, consistency, interpretability, relevancy, and timeliness. It was then validated by international health informatics and health information management experts on its likely contribution to the safety and quality of care in RPM which gained consensus that the recommendations are essential to delivering safe and high‐quality RPM.Conclusions: The increasing proliferation of PGHD from health wearables in RPM requires a systematic approach to enable the reliability of these data for use in patient‐centred care.These best practices provide new insights on PGHD quality management as these data are collected outside the healthcare setting, and different stakeholders are involved in PGHD management outside the healthcare setting and inside it. Using these recommendations could guide the integration of different RPM and provide comprehensive data quality management practice. Also, they can increase stakeholders' awareness of PGHD quality and their potential roles and responsibilities to provide high‐quality data.8. HOW SHOULD WE BE INTERPRETING LANGUAGE IN TELEHEALTH CONSULTATIONS?S. Chan, MD, MBA; H. Tougas, MD; T. Shahrvini, BS; A. Gonzalez, MA; Reyes R. Chun, BA; Parish M. Burke, PhD; P. Yellowlees, MBBS, MDUC DavisDescription: Patients with Limited English Proficiency (LEP) frequently receive below standard care because of language communication difficulties. Medical interpreters are often in short supply and tend to lengthen the time and simplify the language of medical interviews. A combination of Automated Speech Recognition (ASR) and Automated Machine Translation (AMT) technologies have been developed as a method of artificial intelligence (AI) interpretation. We have applied these to Asynchronous Telepsychiatry consultations (ATP) as we believe AI‐interpretation may be a way of improving psychiatric interviews across languages compared with interviews mediated through human‐interpretation.Abstract: AMT and ASR technologies have been used and evaluated for the translation of health education materials and in general medical encounters, however, no known evaluation of mental health interviews exists. We performed two studies to firstly examine differences in patient's language when using interpreters compared with speaking to a same language interviewer, and then to assess the accuracy of ASR and AMT artificial intelligence translation engines by testing and comparing two major publicly available cloud services.In study 1 we used three recorded psychiatric interviews performed by bilingual clinician actors to compare the word error rate (WER) the and the accuracy rates of ASR transcript generation and AMT steps between the two translation enginesIn study 2, we used a convenience sample of recorded pairs of psychiatric interviews in 3 Spanish speaking patients, both interpreted and ATP, from a group of patients involved in a larger study examining translation and interpretation accuracy and patient preferences. The number of examples of figurative language (such as similes and metaphors), the translation accuracy of the figurative language and the patient word counts were compared, as proxies for interview complexity and volume.Method: ObservationalClassification of Research: Patient ExperienceResults: Google Translate was consistently more accurate and had less word errors than Microsoft Translator, and was similar in accuracy to in‐person translation accuracy rates reported in the literature. We found in the AI‐interpretation model that word counts were greater and that figurative language examples were more common but less accurately translated than in the human interpreter model.Conclusions: These are the first known studies conducted to evaluate human interpreted interviews as compared to the use of AMT and ASR for psychiatric interviews. The use of machine learning transcription and translation systems in psychiatry has great potential but the accuracy of such systems depends on which products are used. According to industry literature, the accuracy appears to be improving over time. The use of human interpreters led patients to simplify and shorten their language, potentially omitting information that would be important in a psychiatric interview. The best long‐term option, as ASR and AMT gradually become more accurate, would appear to be the automated process where patients are interviewed and recorded in their own language prior to AMT and ASR. This would lead to patients providing more detailed, richer and likely more clinically useful histories than with the current gold standard use of human interpreters. This novel approach to clinical interviews should eventually lead to a reduction in the health impact of language disparities in the mental health field.9. IMPLEMENTATION OF A COLLABORATIVE MODEL OF INTEGRATED MEDICAL AND BEHAVIORAL HEALTHCARE THAT PROVIDES CHRONIC DISEASE MANAGEMENT VIA TELEHEALTHBrian Clear, Rebekah Rollston, Sarah HowroydBicycle HealthDescription: This descriptive study presents a novel model of collaborative, integrated medical and behavioral healthcare that delivers technology‐enabled biopsychosocial treatment of opioid use disorder (OUD) via telehealth. This model has the potential to decrease stigma for persons seeking OUD treatment, as well as increase access to treatment in many geographic areas.Abstract: In 2020, the opioid epidemic in the United States claimed the lives of 186 people each day, a 26% increase from the year prior. Per 2018 National Survey on Drug Use and Health data, only 19.7% of persons interested in treatment for opioid use disorder (OUD) had actually accessed care through existing systems, while capacity for office‐based opioid treatment remained dramatically underutilized. The approach of training more providers to deliver medication for opioid use disorder (MOUD) through existing systems has not addressed this access gap effectively, and the need for a truly biopsychosocial model of care with a focus on reaching unengaged populations has become increasingly clear. This descriptive study will present a novel clinical model of collaborative, integrated medical and behavioral healthcare that delivers technology‐enabled biopsychosocial treatment of OUD via telehealth. This model of tele‐OUD treatment includes three primary pillars: patient‐centered care, including chronic disease management and behavioral health; creation of tech‐enabled systems and resources; and data‐driven decision‐making. The patient treatment journey will be detailed, which includes development of a personalized treatment plan with an addiction medicine licensed provider, use of the buprenorphine induction tool, pharmacy finder tool, and engagement with the integrated behavioral health team and care coordinators.Method: DescriptiveClassification of Research: Access to CareResults: This innovative, biopsychosocial model of tele‐OUD healthcare delivery has served more than 66% of the United States population across 23 states. Analysis of the Brief Addiction Monitor demonstrates decreased opioid use and risk, decreased health services utilization, increased protective factors, and increased quality of life measures among this telehealth patient population, as well as retention rates at 30, 60, and 90 days that are appreciably higher than the industry average.CConclusions: This novel clinical model of collaborative, integrated medical and behavioral healthcare that delivers technology‐enabled biopsychosocial treatment of OUD via telehealth has the potential to decrease stigma for persons seeking OUD treatment, as well as increase access to treatment in many geographic areas, with a special emphasis on buprenorphine deserts. This integrated, collaborative, and comprehensive approach can be utilized and adapted by other healthcare service providers to increase access to treatment for persons living with opioid use disorder.10. IMPLEMENTATION OF A NOVEL TELEHEALTH PATIENT ADVISORY COUNCILAlex Lynch‐Coffey, Jennifer Harris, Liza Hoffman, Rafael Caycho, Rebekah Rollston, Wynne GalloglyBicycle HealthDescription: This implementation study describes the development of a fully telehealth Patient Advisory Council in a healthcare organization that provides biopsychosocial treatment of opioid use disorder via telehealth. The challenges, iterations, and key learnings presented herein may serve as an example for other telehealth Patient Advisory Councils.Abstract: Patient Advisory Councils have recently become a standard of care within organizations that provide in‐person health services, as patient‐centered systems seek to include the unique and invaluable perspectives of patients in care delivery, quality improvement, and innovation efforts. This implementation study describes the development of a fully telehealth Patient Advisory Council in a healthcare organization that provides biopsychosocial treatment of opioid use disorder via telehealth. We describe challenges, as well as iterations of addressing each challenge, including the following: diverse patient recruitment; understanding of the stigma often attributed to patients with opioid use disorder and how this influences their involvement in healthcare, and advisory councils in particular; advisory council compliance with 42 CFR Part 2 and navigation of this extra consent step with advisory council patients; building trust in a remote environment; patient versus staff participation during meetings; and how to approach quality improvement work in a new Patient Advisory Council.Method: Implementation ScienceClassification of Research: Patient ExperienceResults: This fully telehealth Patient Advisory Council includes six patients and six staff members. Patients are diverse in age, gender, geography, and life experiences. Staff are represented from all patient‐facing roles within the healthcare organization. Key learnings address diverse patient recruitment, compliance with 42 CFR Part 2, building trust, developing mission and vision for the advisory council, and implementation of quality improvement work. Qualitative patient feedback regarding the Patient Advisory Council itself is a key result. Next steps include evaluation of quality improvement work and its impact on healthcare delivery and innovation.Concusions: This fully telehealth Patient Advisory Council is a forum for patients and staff to work together to improve healthcare service delivery, as well as direct community engagement and advocacy, ultimately with the goal to provide more equitable access to treatment for persons living with opioid use disorder. As a fully remote healthcare organization that serves patients living with opioid use disorder, this Patient Advisory Council is a novel concept. The challenges, iterations, and key learnings presented herein may serve as an example for other telehealth Patient Advisory Councils.11. IMPLEMENTATION OF AN AI‐ENHANCED DIGITAL STETHOSCOPE AT A COMMUNITY VALVULAR HEART DISEASE SCREENING PR