Agile Implementation: A Blueprint for Implementing Evidence-Based Healthcare Solutions

Malaz Boustani, Catherine A. Alder, Craig A. Solid

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

Objectives: To describe the essential components of an Agile Implementation (AI) process, which rapidly and effectively implements evidence-based healthcare solutions, and present a case study demonstrating its utility. Design: Case demonstration study. Setting: Integrated, safety net healthcare delivery system in Indianapolis. Participants: Interdisciplinary team of clinicians and administrators. Measurements: Reduction in dementia symptoms and caregiver burden; inpatient and outpatient care expenditures. Results: Implementation scientists were able to implement a collaborative care model for dementia care and sustain it for more than 9 years. The model was implemented and sustained by using the elements of the AI process: proactive surveillance and confirmation of clinical opportunities, selection of the right evidence-based healthcare solution, localization (i.e., tailoring to the local environment) of the selected solution, development of an evaluation plan and performance feedback loop, development of a minimally standardized operation manual, and updating such manual annually. Conclusion: The AI process provides an effective model to implement and sustain evidence-based healthcare solutions.

Original languageEnglish (US)
JournalJournal of the American Geriatrics Society
DOIs
StateAccepted/In press - Jan 1 2018

Fingerprint

Evidence-Based Practice
Dementia
Delivery of Health Care
Ambulatory Care
Health Expenditures
Administrative Personnel
Caregivers
Inpatients
Safety

Keywords

  • Agile implementation
  • Dementia
  • Evidence-based care

ASJC Scopus subject areas

  • Geriatrics and Gerontology

Cite this

Agile Implementation : A Blueprint for Implementing Evidence-Based Healthcare Solutions. / Boustani, Malaz; Alder, Catherine A.; Solid, Craig A.

In: Journal of the American Geriatrics Society, 01.01.2018.

Research output: Contribution to journalArticle

@article{f0f17f0d3c694fc2b9a46284186e1ac1,
title = "Agile Implementation: A Blueprint for Implementing Evidence-Based Healthcare Solutions",
abstract = "Objectives: To describe the essential components of an Agile Implementation (AI) process, which rapidly and effectively implements evidence-based healthcare solutions, and present a case study demonstrating its utility. Design: Case demonstration study. Setting: Integrated, safety net healthcare delivery system in Indianapolis. Participants: Interdisciplinary team of clinicians and administrators. Measurements: Reduction in dementia symptoms and caregiver burden; inpatient and outpatient care expenditures. Results: Implementation scientists were able to implement a collaborative care model for dementia care and sustain it for more than 9 years. The model was implemented and sustained by using the elements of the AI process: proactive surveillance and confirmation of clinical opportunities, selection of the right evidence-based healthcare solution, localization (i.e., tailoring to the local environment) of the selected solution, development of an evaluation plan and performance feedback loop, development of a minimally standardized operation manual, and updating such manual annually. Conclusion: The AI process provides an effective model to implement and sustain evidence-based healthcare solutions.",
keywords = "Agile implementation, Dementia, Evidence-based care",
author = "Malaz Boustani and Alder, {Catherine A.} and Solid, {Craig A.}",
year = "2018",
month = "1",
day = "1",
doi = "10.1111/jgs.15283",
language = "English (US)",
journal = "Journal of the American Geriatrics Society",
issn = "0002-8614",
publisher = "Wiley-Blackwell",

}

TY - JOUR

T1 - Agile Implementation

T2 - A Blueprint for Implementing Evidence-Based Healthcare Solutions

AU - Boustani, Malaz

AU - Alder, Catherine A.

AU - Solid, Craig A.

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Objectives: To describe the essential components of an Agile Implementation (AI) process, which rapidly and effectively implements evidence-based healthcare solutions, and present a case study demonstrating its utility. Design: Case demonstration study. Setting: Integrated, safety net healthcare delivery system in Indianapolis. Participants: Interdisciplinary team of clinicians and administrators. Measurements: Reduction in dementia symptoms and caregiver burden; inpatient and outpatient care expenditures. Results: Implementation scientists were able to implement a collaborative care model for dementia care and sustain it for more than 9 years. The model was implemented and sustained by using the elements of the AI process: proactive surveillance and confirmation of clinical opportunities, selection of the right evidence-based healthcare solution, localization (i.e., tailoring to the local environment) of the selected solution, development of an evaluation plan and performance feedback loop, development of a minimally standardized operation manual, and updating such manual annually. Conclusion: The AI process provides an effective model to implement and sustain evidence-based healthcare solutions.

AB - Objectives: To describe the essential components of an Agile Implementation (AI) process, which rapidly and effectively implements evidence-based healthcare solutions, and present a case study demonstrating its utility. Design: Case demonstration study. Setting: Integrated, safety net healthcare delivery system in Indianapolis. Participants: Interdisciplinary team of clinicians and administrators. Measurements: Reduction in dementia symptoms and caregiver burden; inpatient and outpatient care expenditures. Results: Implementation scientists were able to implement a collaborative care model for dementia care and sustain it for more than 9 years. The model was implemented and sustained by using the elements of the AI process: proactive surveillance and confirmation of clinical opportunities, selection of the right evidence-based healthcare solution, localization (i.e., tailoring to the local environment) of the selected solution, development of an evaluation plan and performance feedback loop, development of a minimally standardized operation manual, and updating such manual annually. Conclusion: The AI process provides an effective model to implement and sustain evidence-based healthcare solutions.

KW - Agile implementation

KW - Dementia

KW - Evidence-based care

UR - http://www.scopus.com/inward/record.url?scp=85043352745&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85043352745&partnerID=8YFLogxK

U2 - 10.1111/jgs.15283

DO - 10.1111/jgs.15283

M3 - Article

C2 - 29513360

AN - SCOPUS:85043352745

JO - Journal of the American Geriatrics Society

JF - Journal of the American Geriatrics Society

SN - 0002-8614

ER -