Testing of a Patient-centered E-health Implementation Model in Addiction Treatment

Brief Summary

Detailed Description

Patient-centered e-health has failed to achieve its promise despite considerable consumer interest in technology and research supporting its potential. E-health adoption rates in healthcare are poor, with specialty substance use disorder (SUD) treatment having the lowest technology adoption rate of any sector. Implementation science can address this emerging gap in the e-health field by augmenting existing models, that explain organizational and individual e-health behaviors retrospectively, with prospective models that can guide implementation. The organizational planning discipline, with its decades of research, could provide a cross-disciplinary "jump start" to developing an e-health implementation model for health organizations. Henry Mintzberg, a respected pioneer in this field, describes 2 beneficial approaches to planning: the deliberate approach, which is grounded in pre-implementation planning, and the emergent approach that is grounded in adapting to the environment as the plan is implemented. The proposed e-health implementation model, called the Network for the Improvement of Addiction Treatment-Technology Implementation (NIATx-TI) Framework, incorporates both approaches. NIATx-TI was piloted in the Iowa Rural Health Information Technology Initiative (IRHIT) with 14 of Iowa's 105 SUD treatment sites and resulted in a 2-fold increase in patients receiving distance treatment. The framework's deliberate component includes using an organizational technology assessment and patient simulation. These tools identify and address assets and barriers to incorporate into the technology's implementation protocol. The framework's emergent component includes using a project team to uncover and prioritize implementation barriers as they arise, develop changes to address identified barriers, and monitor selected adoption measures, while receiving monthly coaching. This project, based in Iowa, will compare a control condition (using a typical product training approach to software implementation that includes user tutorials and instruction on administrative and clinical protocols, followed by access to on-line support) to the typical product training combined with NIATx-TI. While e-health spans many modalities and health disciplines, this project will focus on the implementing Addiction Comprehensive Health Enhancement Support System (A-CHESS), an evidence-based SUD treatment recovery app developed by our Center for a disease that affects 21.5 million and kills 136,000 Americans annually: substance use disorder. A mobile app was selected, as opposed to another e-health technology, because of the near ubiquitous daily use of mobile technology and because mobile e-health adoption requires supportive participation of both health centers and patients. In response to the COVID-19 pandemic, the study team added a study component focused on describing how patients are responding to receiving remote treatment (e.g., telehealth). The study team will also seek to understand how using A-CHESS mitigates COVID-19 associated anxiety and loneliness among those with substance use disorders.

Primary Outcomes

Secondary Outcomes

• Effectiveness of A-CHESS as Assessed by the Retention Rate of Eligible Participants.(Collected monthly during months 13 - 45)
• Adoption: Number of Days Each Counselor Used the A-CHESS(45 months)
• Adoption - The Percentage of Counselors Using A-CHESS Will be Assessed Via the Organizational Survey and A-CHESS Logs(Collected twice during study; starting M22 - 31 and M35-44)
• A-CHESS/NIATx Implementation Fidelity (Survey)(Collected twice during study; approx. M14 - 25 and M32 - 43)
• Organizational Readiness of Participating Organizations as Assessed by Organizational Change Manager (Survey)(Collected twice during study; approx. M14 - 25 and M32 - 43)
• Financial Resource Availability (Survey)(Collected twice during study; starting M22 - 31 and M35-44)
• Difference in Number of Admissions in Rural vs. Urban Location(Collected during months 7, 18, 30, and 42, month 42 reported)