Authors:
Lisa V. Ibañez, Sabine Scott, Wendy L. Stone
University of Washington affiliated authors are displayed in bold.
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Published: May 2021
Lisa V. Ibañez, Sabine Scott, Wendy L. Stone
University of Washington affiliated authors are displayed in bold.
Published: May 2021
Emily M. Godfrey, Anna E. Fiastro, Elizabeth A. Jacob-Files, Francine M. Coeytaux, Elisa S. Wells, Molly R. Ruben, Sajal S. Sanan, & Ian M. Bennett
University of Washington affiliated authors are displayed in bold.
Published: April 2021
Emily R. Haines, Alex Dopp, Aaron R. Lyon, Holly O. Witteman, Miriam Bender, Gratianne Vaisson, Danielle Hitch, & Sarah Birken
University of Washington affiliated authors are displayed in bold.
Published: April 2021
Attempting to implement evidence-based practices in contexts for which they are not well suited may compromise their fidelity and effectiveness or burden users (e.g., patients, providers, healthcare organizations) with elaborate strategies intended to force implementation. To improve the fit between evidence-based practices and contexts, implementation science experts have called for methods for adapting evidence-based practices and contexts and tailoring implementation strategies; yet, methods for considering the dynamic interplay among evidence-based practices, contexts, and implementation strategies remain lacking. We argue that harmonizing the three can be facilitated by user-centered design, an iterative and highly stakeholder-engaged set of principles and methods.
This paper presents a case example in which we used a three-phase user-centered design process to design and plan to implement a care coordination intervention for young adults with cancer. Specifically, we used usability testing to redesign and augment an existing patient-reported outcome measure that served as the basis for our intervention to optimize its usability and usefulness, ethnographic contextual inquiry to prepare the context (i.e., a comprehensive cancer center) to promote receptivity to implementation, and iterative prototyping workshops with a multidisciplinary design team to design the care coordination intervention and anticipate implementation strategies needed to enhance contextual fit.
Our user-centered design process resulted in the Young Adult Needs Assessment and Service Bridge (NA-SB), including a patient-reported outcome measure and a collection of referral pathways that are triggered by the needs young adults report, as well as implementation guidance. By ensuring NA-SB directly responded to features of users and context, we designed NA-SB for implementation, potentially minimizing the strategies needed to address misalignment that may have otherwise existed. Furthermore, we designed NA-SB for scale-up; by engaging users from other cancer programs across the country to identify points of contextual variation which would require flexibility in delivery, we created a tool intended to accommodate diverse contexts.
User-centered design can help maximize usability and usefulness when designing evidence-based practices, preparing contexts, and informing implementation strategies—in effect, harmonizing evidence-based practices, contexts, and implementation strategies to promote implementation and effectiveness.
**This abstract is posted with permission under the Creative Commons Attribution 4.0 International License**
Yih-Ing Hser, Allison J. Ober, Alex R. Dopp, Chunqing Lin, Katie P. Osterhage, Sarah E. Clingan, Larissa J. Mooney, Megan E. Curtis, Lisa A. Marsch, Bethany McLeman, Emily Hichborn, Laurie S. Lester, Laura-Mae Baldwin, Yanping Liu, Petra Jacobs, & Andrew J. Saxon
University of Washington affiliated authors are displayed in bold.
Published: April 2021
Telemedicine (TM) enabled by digital health technologies to provide medical services has been considered a key solution to increasing health care access in rural communities. With the immediate need for remote care due to the COVID-19 pandemic, many health care systems have rapidly incorporated digital technologies to support the delivery of remote care options, including medication treatment for individuals with opioid use disorder (OUD). In responding to the opioid crisis and the COVID-19 pandemic, public health officials and scientific communities strongly support and advocate for greater use of TM-based medication treatment for opioid use disorder (MOUD) to improve access to care and have suggested that broad use of TM during the pandemic should be sustained.
Nevertheless, research on the implementation and effectiveness of TM-based MOUD has been limited. To address this knowledge gap, the National Drug Abuse Treatment Clinical Trials Network (CTN) funded (via the NIH HEAL Initiative) a study on Rural Expansion of Medication Treatment for Opioid Use Disorder (Rural MOUD; CTN-0102) to investigate the implementation and effectiveness of adding TM-based MOUD to rural primary care for expanding access to MOUD. In preparation for this large-scale, randomized controlled trial incorporating TM in rural primary care, a feasibility study is being conducted to develop and pilot test implementation procedures.
In this commentary, we share some of our experiences, which include several challenges, during the initial two-month period of the feasibility study phase. While these challenges could be due, at least in part, to adjusting to the COVID-19 pandemic and new workflows to accommodate the study, they are notable and could have a substantial impact on the larger, planned pragmatic trial and on TM-based MOUD more broadly. Challenges include low rates of identification of risk for OUD from screening, low rates of referral to TM, digital device and internet access issues, workflow and capacity barriers, and insurance coverage. These challenges also highlight the lack of empirical guidance for best TM practice and quality remote care models.
With TM expanding rapidly, understanding implementation and demonstrating what TM approaches are effective are critical for ensuring the best care for persons with OUD.
**This abstract is posted with permission under the Creative Commons Attribution 4.0 International License**
Elizabeth A. Baker, Stephanie K. Brewer, Julie Sarno Owens, Clayton R. Cook, & Aaron R. Lyon
University of Washington affiliated authors are displayed in bold.
Published: April 2021
John M. Inadomi, Rachel B. Issaka, & Beverly B. Green
University of Washington affiliated authors are displayed in bold.
Published: April 2021
Justin D. Smith, Cady Berkel, Allison J. Carroll, Emily Fu, Kevin J. Grimm, Anne M. Mauricio, Jenna Rudo-Stern, Emily Winslow, Thomas J. Dishion, Neil Jordan, David C. Atkins, Shrikanth S. Narayanan, Carlos Gallo, Meg M. Bruening, Charlton Wilson, Farah Lokey, & Kristen Samaddar
University of Washington affiliated authors are displayed in bold.
Published: March 2021
Stephanie Staras, Justin S. Tauscher, Natalie Rich, Esaa Samarah, Lindsay A. Thompson, Michelle M. Vinson, Michael J. Muszynski, & Elizabeth A. Shenkman
University of Washington affiliated authors are displayed in bold.
Published: March 2021
eHealth apps often fail to improve clinical outcomes due to poor integration with clinical workflow—the sequence and personnel needed to undertake a series of tasks for clinical care. Our central thesis is that eHealth interventions will be more effective if the clinical workflow is studied and taken into consideration for intervention implementation. This paper aims to provide an introductory tutorial on when and how to use a clinical workflow analysis to guide the implementation of eHealth interventions. The tutorial includes a step-by-step guide to conducting a clinical workflow analysis in planning for eHealth implementation.
We began with a description of why a clinical workflow analysis is best completed before the implementation of eHealth interventions. Next, we described 4 steps needed to perform the clinical workflow analysis: the identification of discrete workflow components, workflow assessment, triangulation, and the stakeholder proposal of intervention implementation. Finally, we presented a case study of a clinical workflow analysis, which was conducted during patient visits of patients aged 11 or 12 years from 4 diverse pediatric or family medicine clinics to plan the implementation of a tablet-based app for adolescent vaccination.
Investigators planning the implementation of new eHealth interventions in health care settings can use the presented steps to assess clinical workflow, thereby maximizing the match of their intervention with the clinical workflow. Conducting a prospective workflow study allows for evidence-based planning, identifying potential pitfalls, and increasing stakeholder buy-in and engagement. This tutorial should aid investigators in increasing the successful implementation of eHealth interventions.
**This abstract is posted with permission under the Creative Commons Attribution 4.0 International License**
Margaret E. Crane, Katherine E. Phillips, Colleen A. Maxwell, Lesley A. Norris, Lara S. Rifkin, Jacob M. Blank, Samantha D. Sorid, Kendra L. Read, Anna J. Swan, Philip C. Kendall & Hannah E. Frank
University of Washington affiliated authors are displayed in bold.
Published: March 2021
Sara J. Becker, Bryan R. Garner, Bryan J. Hartzler
University of Washington affiliated authors are displayed in bold.
Published: March 2021