Identification of Child Survivors of Sex Trafficking From Electronic Health Records: An Artificial Intelligence Guided Approach.

Survivors of child sex trafficking (SCST) experience high rates of adverse health outcomes. Amidst the duration of their victimization, survivors regularly seek healthcare yet fail to be identified. This study sought to utilize artificial intelligence (AI) to identify SCST and describe the elements of their healthcare presentation. An AI-supported keyword search was conducted to identify SCST within the electronic medical records (EMR) of ∼1.5 million patients at a large midwestern pediatric hospital. Descriptive analyses were used to evaluate associated diagnoses and clinical presentation. A sex trafficking-related keyword was identified in .18% of patient charts. Among this cohort, the most common associated diagnostic codes were for Confirmed Sexual/Physical Assault; Trauma and Stress-Related Disorders; Depressive Disorders; Anxiety Disorders; and Suicidal Ideation. Our findings are consistent with the myriad of known adverse physical and psychological outcomes among SCST and illuminate the future potential of AI technology to improve screening and research efforts surrounding all aspects of this vulnerable population.

Pediatric Outpatient Occupational Therapy: Transitioning From In-Person Services to Telehealth.

The COVID-19 pandemic necessitated rapid adoption of telehealth for outpatient pediatric occupational therapy practice. The dose of therapy may have varied across diagnostic and geographical groups despite efforts to ensure access for all patients. The objective of the study was to describe the visit length of outpatient pediatric occupational therapy practice for three diagnostic groups at one institution both during and prior to the COVID-19 pandemic. Retrospective review of electronic health records for two time periods using both practitioner-entered and telecommunications data. Data were analyzed using descriptive statistics and generalized linear mixed model. Prior to the pandemic, average treatment length did not vary by primary diagnosis. During the pandemic, average visit length varied by primary diagnosis, with feeding disorder (FD) visits significantly shorter than cerebral palsy (CP) and autism spectrum disorder (ASD) visits. During the pandemic, visit length was associated with rurality for the whole sample and for patients with ASD and CP, but not FD. Patients with FD may have been seen for shorter durations during telehealth visits. The technology gap may affect services for patients living in rural communities.

Rapid Development of a Telehealth Patient Satisfaction Survey Using a Multi-Stakeholder Approach.

Introduction: The COVID-19 pandemic has hastened the adoption of telehealth and the drastic shift to an unfamiliar process may impose significant impact to the quality-of-care delivery. Many providers are interested in understanding the quality of their telehealth services from the patients' experience. Materials and Methods: A telehealth patient satisfaction survey (TPSS) was developed by using an iterative stakeholder-centered design approach, incorporating elements from validated telemedicine and customer service survey instruments, and meeting the operational needs and constraints. A cross-sectional study design was employed to collect survey responses from patients and families of a large pediatric hospital. Finally, we performed exploratory factor analysis (EFA) to extract latent constructs and factor loadings of the survey items to further explain relationships. Results: A 22-item TPSS closely matched the existing in-person patient satisfaction survey and mapped to a revised SERVPERF conceptual model that was proposed by the interdisciplinary committee. Survey was implemented in the HIPAA-compliant online platform REDCap® with survey link embedded in an automated Epic MyChart (Verona, WI) visit follow-up message. In total, 2,394 survey responses were collected between July 7, 2020, and September 2, 2020. EFA revealed three constructs (with factor loadings >0.30): admission process, perceived quality of services, and telehealth satisfaction. Conclusions: We reported the development of TPSS that met the operational needs of compatibility with existing data and possible comparison to in-person survey. The survey is short and yet covers both the clinical experience and telehealth usability, with acceptable survey validity.

Measuring Telehealth Visit Length and Schedule Adherence Using Videoconferencing Data.

Background: The ability to measure clinical visit length is critical for operational efficiency, patient experience, and accurate billing. Despite the unprecedented surge in telehealth use in 2020, studies on visit length and schedule adherence in the telehealth setting are nonexistent in the literature. This article aims to demonstrate the use of videoconferencing data to measure telehealth visit length and schedule adherence. Materials and Methods: We used data from telehealth video visits at four clinical specialties at Nationwide Children's Hospital, including behavioral health (BH), speech pathology (SP), physical therapy/occupational therapy (PT/OT), and primary care (PC). We combined videoconferencing timestamp data with visit scheduling data to calculate the total visit length, examination length, and patient wait times. We also assessed schedule adherence, including patient on-time performance, examination on-time performance, provider schedule deviations, and schedule length deviations. Results: The analyses included a total of 175,876 telehealth video visits. On average, children with BH appointments spent a total of 57.2 min for each visit, followed by PT/OT (50.8 min), SP (42.1 min), and PC (25.0 min). The average patient wait times were 4.1 min (BH), 2.7 min (PT/OT), 2.8 min (SP), and 3.1 min (PC). The average examination lengths were 48.8 min (BH), 44.5 min (PT/OT), 34.9 min (SP), and 16.6 min (PC). Regardless of clinical specialty, actual examination lengths of most visits were shorter than the scheduled lengths, except that appointments scheduled for 15 min tended to run overtime. Conclusions: Videoconferencing data provide a low-cost, accurate, and readily available resource for measuring telehealth visit length and schedule adherence.

Challenges in creating an opt-in biobank with a registrar-based consent process and a commercial EHR.

Residual clinical samples represent a very appealing source of biomaterial for translational and clinical research. We describe the implementation of an opt-in biobank, with consent being obtained at the time of registration and the decision stored in our electronic health record, Epic. Information on that decision, along with laboratory data, is transferred to an application that signals to biobank staff whether a given sample can be kept for research. Investigators can search for samples using our i2b2 data warehouse. Patient participation has been overwhelmingly positive and much higher than anticipated. Over 86% of patients provided consent and almost 83% requested to be notified of any incidental research findings. In 6 months, we obtained decisions from over 18 000 patients and processed 8000 blood samples for storage in our research biobank. However, commercial electronic health records like Epic lack key functionality required by a registrar-based consent process, although workarounds exist.