James O E Pittman1,2,3,4, Borsika Rabin5,6,7, Erin Almklov5, Niloofar Afari5,8,9, Elizabeth Floto10, Eusebio Rodriguez9, Laurie Lindamer5,8,9,6. 1. VA Center of Excellence for Stress and Mental Health, 3350 La Jolla Village Dr., San Diego, CA, USA. james.pittman@va.gov. 2. Department of Psychiatry, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, USA. james.pittman@va.gov. 3. VA San Diego Healthcare System, 3350 La Jolla Village Dr., San Diego, CA, USA. james.pittman@va.gov. 4. UC San Diego Dissemination and Implementation Science Center, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, USA. james.pittman@va.gov. 5. VA Center of Excellence for Stress and Mental Health, 3350 La Jolla Village Dr., San Diego, CA, USA. 6. UC San Diego Dissemination and Implementation Science Center, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, USA. 7. Department of Family Medicine and Public Health, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, USA. 8. Department of Psychiatry, University of California San Diego, 9500 Gilman Dr., La Jolla, CA, USA. 9. VA San Diego Healthcare System, 3350 La Jolla Village Dr., San Diego, CA, USA. 10. VA Roseburg Health Care System, 913 NW Garden Valley Blvd, Roseburg, OR, USA.
Abstract
BACKGROUND: The Veterans Health Administration (VHA) developed a comprehensive mobile screening technology (eScreening) that provides customized and automated self-report health screening via mobile tablet for veterans seen in VHA settings. There is agreement about the value of health technology, but limited knowledge of how best to broadly implement and scale up health technologies. Quality improvement (QI) methods may offer solutions to overcome barriers related to broad scale implementation of technology in health systems. We aimed to develop a process guide for eScreening implementation in VHA clinics to automate self-report screening of mental health symptoms and psychosocial challenges. METHODS: This was a two-phase, mixed methods implementation project building on an adapted quality improvement method. In phase one, we adapted and conducted an RPIW to develop a generalizable process guide for eScreening implementation (eScreening Playbook). In phase two, we integrated the eScreening Playbook and RPIW with additional strategies of training and facilitation to create a multicomponent implementation strategy (MCIS) for eScreening. We then piloted the MCIS in two VHA sites. Quantitative eScreening pre-implementation survey data and qualitative implementation process "mini interviews" were collected from individuals at each of the two sites who participated in the implementation process. Survey data were characterized using descriptive statistics, and interview data were independently coded using a rapid qualitative analytic approach. RESULTS: Pilot data showed overall satisfaction and usefulness of our MCIS approach and identified some challenges, solutions, and potential adaptations across sites. Both sites used the components of the MCIS, but site 2 elected not to include the RPIW. Survey data revealed positive responses related to eScreening from staff at both sites. Interview data exposed implementation challenges related to the technology, support, and education at both sites. Workflow and staffing resource challenges were only reported by site 2. CONCLUSIONS: Our use of RPIW and other QI methods to both develop a playbook and an implementation strategy for eScreening has created a testable implementation process to employ automated, patient-facing assessment. The efficient collection and communication of patient information have the potential to greatly improve access to and quality of healthcare.
BACKGROUND: The Veterans Health Administration (VHA) developed a comprehensive mobile screening technology (eScreening) that provides customized and automated self-report health screening via mobile tablet for veterans seen in VHA settings. There is agreement about the value of health technology, but limited knowledge of how best to broadly implement and scale up health technologies. Quality improvement (QI) methods may offer solutions to overcome barriers related to broad scale implementation of technology in health systems. We aimed to develop a process guide for eScreening implementation in VHA clinics to automate self-report screening of mental health symptoms and psychosocial challenges. METHODS: This was a two-phase, mixed methods implementation project building on an adapted quality improvement method. In phase one, we adapted and conducted an RPIW to develop a generalizable process guide for eScreening implementation (eScreening Playbook). In phase two, we integrated the eScreening Playbook and RPIW with additional strategies of training and facilitation to create a multicomponent implementation strategy (MCIS) for eScreening. We then piloted the MCIS in two VHA sites. Quantitative eScreening pre-implementation survey data and qualitative implementation process "mini interviews" were collected from individuals at each of the two sites who participated in the implementation process. Survey data were characterized using descriptive statistics, and interview data were independently coded using a rapid qualitative analytic approach. RESULTS: Pilot data showed overall satisfaction and usefulness of our MCIS approach and identified some challenges, solutions, and potential adaptations across sites. Both sites used the components of the MCIS, but site 2 elected not to include the RPIW. Survey data revealed positive responses related to eScreening from staff at both sites. Interview data exposed implementation challenges related to the technology, support, and education at both sites. Workflow and staffing resource challenges were only reported by site 2. CONCLUSIONS: Our use of RPIW and other QI methods to both develop a playbook and an implementation strategy for eScreening has created a testable implementation process to employ automated, patient-facing assessment. The efficient collection and communication of patient information have the potential to greatly improve access to and quality of healthcare.
Authors: Amy M Kilbourne; Daniel Almirall; David E Goodrich; Zongshan Lai; Kristen M Abraham; Kristina M Nord; Nicholas W Bowersox Journal: Implement Sci Date: 2014-12-28 Impact factor: 7.327
Authors: Byron J Powell; Thomas J Waltz; Matthew J Chinman; Laura J Damschroder; Jeffrey L Smith; Monica M Matthieu; Enola K Proctor; JoAnn E Kirchner Journal: Implement Sci Date: 2015-02-12 Impact factor: 7.327
Authors: James O E Pittman; Niloofar Afari; Elizabeth Floto; Erin Almklov; Susan Conner; Borsika Rabin; Laurie Lindamer Journal: BMC Health Serv Res Date: 2019-08-28 Impact factor: 2.655