Advance Care Planning Bundle: Using Technical and Adaptive Solutions to Promote Goal Concordant Care.

Advanced care planning Goal Concordant Care Quality Improvement Technical and Adaptive Framework

Journal

Journal of pain and symptom management
ISSN: 1873-6513
Titre abrégé: J Pain Symptom Manage
Pays: United States
ID NLM: 8605836

Informations de publication

Date de publication:
20 Sep 2024
Historique:
received: 27 05 2024
revised: 22 08 2024
accepted: 08 09 2024
medline: 23 9 2024
pubmed: 23 9 2024
entrez: 22 9 2024
Statut: aheadofprint

Résumé

Advance Care Planning (ACP) is critical to achieve goal-aligned care for patients. However, optimal implementation requires complex coordination and alignment across a healthcare system. A survey of rapid response providers assessed usefulness of the ACP quality improvement bundle and perceptions of use and adherence. We implemented a bundle of advance care planning tools and interventions using the technical-adaptive framework. These included orders, documentation templates and processes, and standard education. Ninety-three rapid response providers completed the survey. 80.5% reported that overall, these quality improvement efforts have been very helpful or somewhat helpful in improving their ability to provide care consistent with the patient's goals. Implementation of technical and adaptive tools as a bundle for Advance Care Planning shows promise to improve and sustain goal-aligned care. Quality Improvement in ACP is a complex, iterative process involving both structural change and behavioral adaptation.

Sections du résumé

BACKGROUND BACKGROUND
Advance Care Planning (ACP) is critical to achieve goal-aligned care for patients. However, optimal implementation requires complex coordination and alignment across a healthcare system.
MEASURES METHODS
A survey of rapid response providers assessed usefulness of the ACP quality improvement bundle and perceptions of use and adherence.
INTERVENTION METHODS
We implemented a bundle of advance care planning tools and interventions using the technical-adaptive framework. These included orders, documentation templates and processes, and standard education.
OUTCOMES RESULTS
Ninety-three rapid response providers completed the survey. 80.5% reported that overall, these quality improvement efforts have been very helpful or somewhat helpful in improving their ability to provide care consistent with the patient's goals.
CONCLUSIONS/LESSONS LEARNED CONCLUSIONS
Implementation of technical and adaptive tools as a bundle for Advance Care Planning shows promise to improve and sustain goal-aligned care. Quality Improvement in ACP is a complex, iterative process involving both structural change and behavioral adaptation.

Identifiants

pubmed: 39307373
pii: S0885-3924(24)01009-1
doi: 10.1016/j.jpainsymman.2024.09.014
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024. Published by Elsevier Inc.

Déclaration de conflit d'intérêts

Conflict of Interest Statement Dr. Porter-Williamson is a former member of the EPIC Palliative Care Advisory Board and Dr. Kalender-Rich received payment for Henderson Lecture at the University of Nebraska. Dr. Kalendar-Rich is also a Geriatrics Specialty Board Member through ABIM.

Auteurs

Sara Brigham (S)

Division of Palliative Medicine, University of Kansas School of Medicine, Kansas City, KS, USA. Electronic address: sara.n.brigham@gmail.com.

Lori Olson (L)

Division of Palliative Medicine, University of Kansas School of Medicine, Kansas City, KS, USA.

Jessica Kalender-Rich (J)

Division of Geriatric Medicine, University of Kansas School of Medicine, Kansas City, KS, USA; Landon Center on Aging, University of Kansas Medical Center, Kansas City, KS, USA.

Ben Skoch (B)

Division of Palliative Medicine, University of Kansas School of Medicine, Kansas City, KS, USA.

Joanna Veazey Brooks (JV)

Division of Palliative Medicine, University of Kansas School of Medicine, Kansas City, KS, USA; Department of Population Health, Kansas City, KS, USA; University of Kansas Cancer Center, Kansas City, KS, USA.

Casey Pickering (C)

The University of Kansas Health System, Kansas City, KS, USA.

Dustin Pierce (D)

The University of Kansas Health System, Kansas City, KS, USA.

Angella Herrman (A)

System Informatics, The University of Kansas Health System, Kansas City, KS, USA.

Maritza Campos (M)

System Informatics, The University of Kansas Health System, Kansas City, KS, USA.

Randa Hallock (R)

System Informatics, The University of Kansas Health System, Kansas City, KS, USA.

Karin Porter-Williamson (K)

Division of Palliative Medicine, University of Kansas School of Medicine, Kansas City, KS, USA.

Classifications MeSH