TY - JOUR
T1 - A Multi-Faceted Strategy for Evidence Translation Reduces Healthcare Waiting Time
T2 - A Mixed Methods Study Using the RE-AIM Framework
AU - Harding, Katherine E.
AU - Lewis, Annie K.
AU - Snowdon, David A.
AU - Kent, Bridie
AU - Taylor, Nicholas F.
N1 - Funding Information:
Funding. Funding for this work was received from the National Health and Medical Research Council, Australia (GNT1076777) and the Victorian Department of Health and Human Services.
Publisher Copyright:
Copyright © 2021 Harding, Lewis, Snowdon, Kent and Taylor.
PY - 2021/3/23
Y1 - 2021/3/23
N2 - Background: Waiting lists are often thought to be inevitable in healthcare, but strategies that address patient flow by reducing complexity, combining triage with initial management, and/or actively managing the relationship between supply and demand can work. One such model, Specific Timely Appointments for Triage (STAT), brings these elements together and has been found in multiple trials to reduce waiting times by 30–40%. The next challenge is to translate this knowledge into practice. Method: A multi-faceted knowledge translation strategy, including workshops, resources, dissemination of research findings and a community of practice (CoP) was implemented. A mixed methods evaluation of the strategy was conducted based on the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework, drawing on an internal database and a survey of workshop and CoP participants. Results: Demonstrating reach, at July 2020 an internal database held details of 342 clinicians and managers from 64 health services who had participated in the workshop program (n = 308) and/or elected to join an online CoP (n = 227). 40 of 69 (58%) respondents to a survey of this population reported they had adopted the model, with some providing data demonstrating that the STAT model had been efficacious in reducing waiting time. Perceived barriers to implementation included an overwhelming existing waiting list, an imbalance between supply and demand and lack of resources. Conclusion: There is high quality evidence from trials that STAT reduces waiting time. Using the RE-AIM framework, this evaluation of a translation strategy demonstrates uptake of evidence to reduce waiting time in health services.
AB - Background: Waiting lists are often thought to be inevitable in healthcare, but strategies that address patient flow by reducing complexity, combining triage with initial management, and/or actively managing the relationship between supply and demand can work. One such model, Specific Timely Appointments for Triage (STAT), brings these elements together and has been found in multiple trials to reduce waiting times by 30–40%. The next challenge is to translate this knowledge into practice. Method: A multi-faceted knowledge translation strategy, including workshops, resources, dissemination of research findings and a community of practice (CoP) was implemented. A mixed methods evaluation of the strategy was conducted based on the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework, drawing on an internal database and a survey of workshop and CoP participants. Results: Demonstrating reach, at July 2020 an internal database held details of 342 clinicians and managers from 64 health services who had participated in the workshop program (n = 308) and/or elected to join an online CoP (n = 227). 40 of 69 (58%) respondents to a survey of this population reported they had adopted the model, with some providing data demonstrating that the STAT model had been efficacious in reducing waiting time. Perceived barriers to implementation included an overwhelming existing waiting list, an imbalance between supply and demand and lack of resources. Conclusion: There is high quality evidence from trials that STAT reduces waiting time. Using the RE-AIM framework, this evaluation of a translation strategy demonstrates uptake of evidence to reduce waiting time in health services.
KW - community
KW - implementation science
KW - outpatient
KW - REAIM
KW - research translation
KW - scheduling
KW - waiting
KW - waiting and queuing
UR - http://www.scopus.com/inward/record.url?scp=85169316475&partnerID=8YFLogxK
U2 - 10.3389/fresc.2021.638602
DO - 10.3389/fresc.2021.638602
M3 - Article
C2 - 36188815
AN - SCOPUS:85169316475
SN - 2673-6861
VL - 2
JO - Frontiers in Rehabilitation Sciences
JF - Frontiers in Rehabilitation Sciences
M1 - 638602
ER -