Levels of Telehealth Use, Perceived Usefulness, and Ease of Use in Behavioral Healthcare Organizations After the COVID-19 Pandemic.

The use of telehealth in behavioral healthcare increased significantly since the start of the COVID-19 pandemic and remains high even as a return to in-person care is now feasible. The use of telehealth is a promising strategy to increase access to behavioral healthcare for underserved and all populations. Identifying opportunities to improve the provision of telehealth is vital to ensuring access. An online survey about the current use of, and attitudes toward, telehealth was conducted by five Mental Health Technology Transfer Center (MHTTC) regional centers and the MHTTC Network Coordinating Office. The national MHTTC network provides training and technical assistance, to support the behavioral health workforce to implement evidence-based treatments. Three hundred and sixty-five respondents from 43 states and Puerto Rico participated. The majority of respondents were clinical providers (69.3%). Nearly all (n = 311) respondents reported providing at least one telehealth service at their organization, but the number and type of services varied substantially. Respondents had positive views of both video-based and phone-based services, but most had some preference for video-based telehealth services. Other services, including text message reminders, medication services, and mobile apps for treatment or recovery, were offered via telehealth by ~ 50% or fewer of respondents' organizations. Many organizations have areas where they could expand their telehealth use, allowing them to extend the reach of their services and increase access for populations that experience barriers to service access, though organizational barriers may still prevent this.

Patient Preferences for Mobile Health Applications to Support Recovery.

INTRODUCTION: Smartphone apps to support individuals in recovery from substance use disorders (SUDs) are increasingly available. Although many people with SUDs express interest in recovery support apps, few try them or use them long-term. Strategies like gamification and contingency management are increasingly being considered to sustain engagement. This study sought to describe features of a recovery support app called the Addiction version of the Comprehensive Health Enhancement Support System (A-CHESS) that are most used by individuals in SUD recovery and what makes individuals more likely to use these apps. METHODS: A total of 202 people with A-CHESS accounts completed an online survey assessing their experiences using A-CHESS between April and June 2021. We described app features reported to be most beneficial for managing anxiety, loneliness, and isolation during COVID-19; reasons for not using A-CHESS; and suggested app features for future recovery support apps. RESULTS: Respondents had a mean age of 41 years, 85% were White, and 61% were female. Respondents reported that app features related to messaging (ie, open discussion boards and private messaging) and informational or motivational resources were the most useful for managing isolation, anxiety, and loneliness. Reasons for not using A-CHESS were not knowing how to use the app and the app not being part of a personalized treatment plan. The most common suggested components for future apps were rewards for meeting goals and a support meeting locator. CONCLUSIONS: Ensuring that health apps are intuitive and include features that appeal to patients and educating patients about features apps already include that help them meet goals may enhance engagement with recovery apps.

Opening the "black box" of organizational coaching for implementation.

BACKGROUND: Organizational coaching to promote the implementation of evidence-informed interventions is becoming more popular in healthcare organizations. In order to open the "black box" of coaching for implementation, we first developed, then tested the rigor and utility of a model of coaching for implementation. METHODS: Interviews with nine experienced coaches were conducted and inductively coded to develop a model of coaching for implementation. Later, forty coaching calls with behavioral health organizations in Ohio, Wisconsin, and Florida were analyzed with directed content analysis using a priori codes based on this model. RESULTS: The coaching work that occurred during these calls aligned closely with the model of coaching for implementation developed by our team. Most coaching work was devoted to building capacity; almost as much work focused on building relationships. Very little coaching work was dedicated to building sustainability. Use of tools for organizational change and implementation remained relatively consistent across all coaching periods. CONCLUSION: Understanding what occurs during a successful coaching intervention will improve the effectiveness of coaching as an implementation strategy. Future research should focus on which processes and patterns make coaching more likely to promote specific implementation outcomes.

Implementation of Smartphone Systems to Improve Quality of Life for People With Substance Use Disorder: Interim Report on a Randomized Controlled Trial.

BACKGROUND: Researchers have conducted numerous studies seeking to understand how to improve the implementation of changes in health care organizations, but less focus has been given to applying lessons already learned from implementation science. Finding innovative ways to apply these findings efficiently and consistently will improve current research on implementation strategies and allow organizations utilizing these techniques to make changes more effectively. OBJECTIVE: This research aims to compare a practical implementation approach that uses principles from prior implementation studies to more traditional ways of implementing change. METHODS: A total of 43 addiction treatment sites in Iowa were randomly assigned to 2 different implementation strategies in a randomized comparative effectiveness trial studying the implementation of an eHealth substance use disorder treatment technology. One strategy used an adaptation of the Network for the Improvement of Addiction Treatment (NIATx) improvement approach, while the other used a traditional product training model. This paper discusses lessons learned about implementation. RESULTS: This midterm report indicates that use of the NIATx approach appears to be leading to improved outcomes on several measures, including initial and sustained use of new technology by both counselors and patients. Additionally, this research indicates that seamlessly integrating organizational changes into existing workflows and using coaching to overcome hurdles and assess progress are important to improve implementation projects. CONCLUSIONS: At this interim point in the study, it appears that the use of the NIATx improvement process leads to better outcomes in implementation of changes within health care organizations. Moreover, some strategies used in this improvement process are particularly useful and should be drawn on more heavily in future implementation efforts. TRIAL REGISTRATION: ClinicalTrials.gov NCT03954184; https://clinicaltrials.gov/ct2/show/NCT03954184.

Clinician Perspectives on Barriers and Facilitators to Implementing e-Health Technology in Substance Use Disorder (SUD) Treatment Facilities.

BACKGROUND: Substance use disorders (SUDs) in the United States cause many preventable deaths each year. Finding effective ways to manage SUDs is vital to improving outcomes for individuals seeking treatment. This has increased interest in using e-health technologies in behavioral healthcare settings. This research is part of a larger study evaluating the efficacy of the NIATx coaching intervention for implementing RISE Iowa, an e-health patient recovery app, in SUD treatment organizations and seeks to examine clinician perspectives of the barriers and facilitators to its implementation. METHOD: Semi-structured qualitative interviews were conducted with 13 clinicians from 9 different intervention sites involved in the study. RESULTS: Major barriers to implementing e-health technology include inability to access the technology, lack of time for both patients and clinicians, and a perceived lack of patient motivation to make changes. Facilitators to implementation include collaboration with other staff using e-health technology and integrating technology use into typical workflows. CONCLUSIONS: Implementation of e-health technology in SUD treatment will require integrating the technology into clinical workflows and improving patient access to the technology.