Digital Health for the Opioid Crisis: A Historical Analysis of NIH Funding from 2013 to 2017

Prior to the COVID-19 crisis, the opioid crisis was the major public health challenge ravaging economies and communities across the United States. Digital health offered new ways to reach, diagnose, and treat individuals with opioid use disorders. Federal research funding usually reflects the nation’s research priorities and shapes the direction of innovation. We reviewed funded projects by the National Institute on Drug Abuse (NIDA) from 2013 to 2017, a period leading to the substantial increase in federal funding and the launch of the $500M HEAL (Helping End Addiction Long-TermSM) initiative in 2018. We presented our viewpoint of the research landscape of the digital health development for the opioid crisis. Overall, there was a gradual increase in NIDA grant funding for technology in the opioid crisis and the percentage of NIDA technology awards funding new projects had nearly doubled in that period. We categorize the types of applications and potential challenges in five emerging technology categories: electronic health, mobile health, virtual reality, artificial intelligence, and biosensor. Diversification of funding in these categories offers the promise of more innovation in new technologies to combat the opioid epidemic.

Associations of Telehealth Care Delivery with Pediatric Health Care Provider Well-Being.

BACKGROUND: The rapid, large-scale deployment of new health technologies can introduce challenges to clinicians who are already under stress. The novel coronavirus disease 19 (COVID-19) pandemic transformed health care in the United States to include a telehealth model of care delivery. Clarifying paths through which telehealth technology use is associated with change in provider well-being and interest in sustaining virtual care delivery can inform planning and optimization efforts. OBJECTIVE: This study aimed to characterize provider-reported changes in well-being and daily work associated with the pandemic-accelerated expansion of telehealth and assess the relationship of provider perceptions of telehealth effectiveness, efficiency, and work-life balance with desire for future telehealth. METHODS: A cross-sectional survey study was conducted October through November 2020, 6 months after the outbreak of COVID-19 at three children's hospitals. Factor analysis and structural equation modeling (SEM) were used to examine telehealth factors associated with reported change in well-being and desire for future telehealth. RESULTS: A total of 947 nontrainee physicians, advanced practice providers, and psychologists were surveyed. Of them, 502 (53.0%) providers responded and 467 (49.3%) met inclusion criteria of telehealth use during the study period. Of these, 325 (69.6%) were female, 301 (65.6%) were physicians, and 220 (47.1%) were medical subspecialists. Providers were 4.77 times as likely (95% confidence interval [CI]: 3.29-7.06) to report improved versus worsened well-being associated with telehealth. Also, 95.5% of providers (95% CI: 93.2-97.2%) wish to continue performing telehealth postpandemic. Our model explains 66% of the variance in telehealth-attributed provider well-being and 59% of the variance for future telehealth preference and suggests telehealth resources significantly influence provider-perceived telehealth care effectiveness which in turn significantly influences provider well-being and desire to perform telehealth. CONCLUSION: Telehealth has potential to promote provider well-being; telehealth-related changes in provider well-being are associated with both provider-perceived effectiveness of telemedicine for patients and adequacy of telehealth resources.

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.

Identifying the Factors Influencing Patients' Telehealth Visit Satisfaction: Survey Validation Through a Structural Equation Modeling Approach.

Introduction: The COVID-19 pandemic accelerated the adoption of telehealth as an alternative to in-person hospital visits. To understand the factors impacting the quality of telehealth services, there is a need for validated survey instruments and conceptual frameworks. The objective of this study is to validate a telehealth patient satisfaction survey by structural equation modeling (SEM) and determine the relationship between the factors in the proposed telehealth patient satisfaction model (TPSM). Methods: We conducted a cross-sectional survey of pediatric patients and families receiving care from a comprehensive pediatric hospital in the Midwest between September 2020 and January 2021. In total, 2,039 usable responses were collected. We used an SEM approach by performing confirmatory factor analysis with Diagonally Weighted Least Squares modeling and Partial Least Squares-Path Modeling to establish the structural validity and examined the relationships among the constructs of "Admission Process" (AP), "Perceived Quality of Service" (PQS), and "Telehealth Satisfaction" (TS). Results: Participants were predominantly White (75%) and English-speaking (95%) parents (85%) of patients (mean age of patients was 10.2 years old). The survey responses were collected from patients visiting 43 department specialties, whereas 50% were behavioral and occupational therapy patients. The structural model showed that the admission process (AP) had a strong positive impact on perceived quality of service (PQS) (p = 0.67, t = 36.1, p < 0.001). The PQS had a strong positive impact on telehealth satisfaction (TS) (p = 0.66, t = 31.8, p < 0.001). The AP had a low positive direct impact on TS (p = 0.16, t = 7.46, p < 0.05). Overall, AP and PQS explained 61% variances (R2) of TS. Conclusions: We validated a newly proposed TS assessment model by using SEM. The TPSM will inform researchers to better understand the influencing factors in TS and help health care systems to improve telehealth patient satisfaction through a validated model.