Whitney L Mills1, Camilla B Pimentel2, A Lynn Snow3, Rebecca S Allen4, Nancy J Wewiorski5, Jennifer A Palmer6, Valerie Clark5, Therasia M Roland5, Sarah E McDannold7, Christine W Hartmann7. 1. Center for Innovation in Long-Term Services and Supports, Providence Veterans Affairs Medical Center, Providence, RI; Department of Health Services, Policy, and Practice, School of Public Health, Brown University, Providence, RI. Electronic address: whitney.mills@va.gov. 2. New England Geriatric Research Education and Clinical Center, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA; Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA. 3. Tuscaloosa Veterans Affairs Medical Center, Tuscaloosa, AL; Alabama Research Institute on Aging and the Department of Psychology, the University of Alabama, Tuscaloosa, AL. 4. Alabama Research Institute on Aging and the Department of Psychology, the University of Alabama, Tuscaloosa, AL. 5. Center for Healthcare Organization and Implementation Research, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA. 6. Institute for Aging Research, Hebrew SeniorLife, Roslindale, MA. 7. Center for Healthcare Organization and Implementation Research, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA; Department of Health Law, Policy and Management, School of Public Health, Boston University, Boston, MA.
Abstract
OBJECTIVES: Quality improvement (QI) may be a promising approach for staff to improve the quality of care in nursing homes. However, little is known about the challenges and facilitators to implementing QI interventions in nursing homes. This study examines staff perspectives on the implementation process. DESIGN: We conducted semistructured interviews with staff involved in implementing an evidence-based QI intervention ("LOCK") to improve interactions between residents and staff through targeted staff behavior change. The LOCK intervention consists of 4 practices: (1) Learn from the bright spots, (2) Observe, (3) Collaborate in huddles, and (4) Keep it bite sized. SETTING AND PARTICIPANTS: We interviewed staff members in 6 Veterans Health Administration nursing homes [ie, Community Living Centers (CLCs)] via opportunistic and snowball sampling. MEASURES: The semistructured interviews were grounded in the Capability, Opportunity, Motivation, Behavior (COM-B) model of behavior change and covered staff experience, challenges, facilitators, and lessons learned during the implementation process. The interviews were analyzed using thematic content analysis. RESULTS: Overall, staff accepted the intervention and appreciated the focus on the positives. Challenges fell largely within the categories of capability and opportunity and included difficulty finding time to complete intervention activities, inability to interpret data reports, need for ongoing training, and misunderstanding of study goals. Facilitators were largely within the motivation category, including incentives for participation, reinforcement of desired behavior, feasibility of intervention activities, and use of data to quantify improvements. CONCLUSIONS/IMPLICATIONS: As QI programs become more common in nursing homes, it is critical that interventions are tailored for this unique setting. We identified barriers and facilitators of our intervention's implementation and learned that no challenge was insurmountable or derailed the implementation of LOCK. This ability of frontline staff to overcome implementation challenges may be attributed to LOCK's inherently motivational features. Future nursing home QI interventions should consider including built-in motivational components. Published by Elsevier Inc.
OBJECTIVES: Quality improvement (QI) may be a promising approach for staff to improve the quality of care in nursing homes. However, little is known about the challenges and facilitators to implementing QI interventions in nursing homes. This study examines staff perspectives on the implementation process. DESIGN: We conducted semistructured interviews with staff involved in implementing an evidence-based QI intervention ("LOCK") to improve interactions between residents and staff through targeted staff behavior change. The LOCK intervention consists of 4 practices: (1) Learn from the bright spots, (2) Observe, (3) Collaborate in huddles, and (4) Keep it bite sized. SETTING AND PARTICIPANTS: We interviewed staff members in 6 Veterans Health Administration nursing homes [ie, Community Living Centers (CLCs)] via opportunistic and snowball sampling. MEASURES: The semistructured interviews were grounded in the Capability, Opportunity, Motivation, Behavior (COM-B) model of behavior change and covered staff experience, challenges, facilitators, and lessons learned during the implementation process. The interviews were analyzed using thematic content analysis. RESULTS: Overall, staff accepted the intervention and appreciated the focus on the positives. Challenges fell largely within the categories of capability and opportunity and included difficulty finding time to complete intervention activities, inability to interpret data reports, need for ongoing training, and misunderstanding of study goals. Facilitators were largely within the motivation category, including incentives for participation, reinforcement of desired behavior, feasibility of intervention activities, and use of data to quantify improvements. CONCLUSIONS/IMPLICATIONS: As QI programs become more common in nursing homes, it is critical that interventions are tailored for this unique setting. We identified barriers and facilitators of our intervention's implementation and learned that no challenge was insurmountable or derailed the implementation of LOCK. This ability of frontline staff to overcome implementation challenges may be attributed to LOCK's inherently motivational features. Future nursing home QI interventions should consider including built-in motivational components. Published by Elsevier Inc.
Authors: Gregory L Alexander; Andrew Georgiou; Kevin Doughty; Andrew Hornblow; Anne Livingstone; Michelle Dougherty; Stephen Jacobs; Malcolm J Fisk Journal: Int J Med Inform Date: 2020-01-24 Impact factor: 4.046
Authors: Guy Peryer; Sarah Kelly; Jessica Blake; Jennifer K Burton; Lisa Irvine; Andy Cowan; Gizdem Akdur; Anne Killett; Sarah L Brand; Massirfufulay Kpehe Musa; Julienne Meyer; Adam L Gordon; Claire Goodman Journal: Age Ageing Date: 2022-03-01 Impact factor: 10.668