Literature DB >> 34363207

Factors affecting primary care implementation for older veterans with multimorbidity in Veterans Health Administration (VA).

Omonyêlé L Adjognon1, Marlena H Shin1, Melissa J A Steffen2,3,4, Jennifer Moye1,5,6, Samantha Solimeo2,3,4,7, Jennifer L Sullivan1,8.   

Abstract

OBJECTIVE: To identify factors affecting implementation of Geriatric Patient-Aligned Care Teams (GeriPACTs), a patient-centered medical home model for older adults with complex care needs including multiple chronic conditions (MCC), designed to provide them with comprehensive, managed, and coordinated primary care. DATA SOURCES: Qualitative data were collected from key informants at eight Veterans Health Administration Medical Centers geographically spread across the United States. STUDY
DESIGN: Guided by the Consolidated Framework for Implementation Research (CFIR), we collected prospective primary data through semi-structured interviews with GeriPACT team members (e.g., physicians, nurses, social workers, pharmacists), leaders (e.g., executive leaders, middle managers), and other staff referring to the program. DATA COLLECTION: We conducted in-person, semi-structured interviews with 134 key informants. Interviews were recorded with permission and professionally transcribed. Transcripts were coded in Nvivo 11. We used directed content analysis to identify key factors affecting GeriPACT implementation across sites. PRINCIPAL
FINDINGS: Five key factors affected GeriPACT implementation-five CFIR constructs within two CFIR domains. Within the intervention characteristics domain, two constructs emerged, namely, (1) the structure of the GeriPACT model and (2) design, quality, and packaging. Within the inner setting domain, we identified three constructs, namely, (1) available resources (e.g., staffing and space, and infrastructure and information technology), (2) leadership support and engagement, and (3) networks and communications including teamwork, communication, and coordination.
CONCLUSIONS: Older veterans with MCC have complex primary care needs requiring high levels of care management and coordination. Knowing what key factors affect GeriPACT implementation is critical. Study findings also contribute to the growing implementation science literature on applying CFIR to evaluate factors that affect program implementation, especially to aging research. Further studies on MCC-focused specialty primary care will help facilitate patient-centered care provision for older adults' complex health needs while also leveraging synergistic work across factors affecting implementation. Published 2021. This article is a U.S. Government work and is in the public domain in the USA.

Entities:  

Keywords:  implementation science; multiple chronic conditions; older person; patient-centered care; primary care; qualitative methods; veteran

Mesh:

Year:  2021        PMID: 34363207      PMCID: PMC8515219          DOI: 10.1111/1475-6773.13859

Source DB:  PubMed          Journal:  Health Serv Res        ISSN: 0017-9124            Impact factor:   3.734


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6.  Implementation of the Geriatric Patient-Aligned Care Team Model in the Veterans Health Administration (VA).

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7.  Identifying and overcoming implementation challenges: Experience of 59 noninstitutional long-term services and support pilot programs in the Veterans Health Administration.

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Review 8.  The global burden of multiple chronic conditions: A narrative review.

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10.  Factors affecting primary care implementation for older veterans with multimorbidity in Veterans Health Administration (VA).

Authors:  Omonyêlé L Adjognon; Marlena H Shin; Melissa J A Steffen; Jennifer Moye; Samantha Solimeo; Jennifer L Sullivan
Journal:  Health Serv Res       Date:  2021-08-27       Impact factor: 3.734

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3.  Factors affecting primary care implementation for older veterans with multimorbidity in Veterans Health Administration (VA).

Authors:  Omonyêlé L Adjognon; Marlena H Shin; Melissa J A Steffen; Jennifer Moye; Samantha Solimeo; Jennifer L Sullivan
Journal:  Health Serv Res       Date:  2021-08-27       Impact factor: 3.734

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