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Barriers and facilitators to implementation of VA home-based primary care on American Indian reservations: a qualitative multi-case study

Overview of attention for article published in Implementation Science, September 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)

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11 tweeters


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89 Mendeley
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Barriers and facilitators to implementation of VA home-based primary care on American Indian reservations: a qualitative multi-case study
Published in
Implementation Science, September 2017
DOI 10.1186/s13012-017-0632-6
Pubmed ID

B. Josea Kramer, Sarah D. Cote, Diane I. Lee, Beth Creekmur, Debra Saliba


Veterans Health Affairs (VA) home-based primary care (HBPC) is an evidence-based interdisciplinary approach to non-institutional long-term care that was developed in urban settings to provide longitudinal care for vulnerable older patients. Under the authority of a Memorandum of Understanding between VA and Indian Health Service (IHS) to improve access to healthcare, 14 VA medical centers (VAMC) independently initiated plans to expand HBPC programs to rural American Indian reservations and 12 VAMC successfully implemented programs. The purpose of this study is to describe barriers and facilitators to implementation in rural Native communities with the aim of informing planners and policy-makers for future program expansions. A qualitative comparative case study approach was used, treating each of the 14 VAMC as a case. Using the Consolidated Framework for Implementation Research (CFIR) to inform an open-ended interview guide, telephone interviews (n = 37) were conducted with HBPC staff and clinicians and local/regional managers, who participated or oversaw implementation. The interviews were transcribed, coded, and then analyzed using CFIR domains and constructs to describe and compare experiences and to identify facilitators, barriers, and adaptations that emerged in common across VAMC and HBPC programs. There was considerable variation in local contexts across VAMC. Nevertheless, implementation was typically facilitated by key individuals who were able to build trust and faith in VA healthcare among American Indian communities. Policy promoted clinical collaboration but collaborations generally occurred on an ad hoc basis between VA and IHS clinicians to optimize patient resources. All programs required some adaptations to address barriers in rural areas, such as distances, caseloads, or delays in hiring additional clinicians. VA funding opportunities facilitated expansion and sustainment of these programs. Since program expansion is a responsibility of the HBPC program director, there is little sharing of lessons learned across VA facilities. Opportunities for shared learning would benefit federal healthcare organizations to expand other medical services to additional American Indian communities and other rural and underserved communities, as well as to coordinate with other healthcare organizations. The CFIR structure was an effective analytic tool to compare programs addressing multiple inner and outer settings.

Twitter Demographics

The data shown below were collected from the profiles of 11 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 89 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 13 15%
Researcher 11 12%
Student > Ph. D. Student 10 11%
Student > Doctoral Student 9 10%
Student > Bachelor 7 8%
Other 18 20%
Unknown 21 24%
Readers by discipline Count As %
Medicine and Dentistry 18 20%
Nursing and Health Professions 15 17%
Social Sciences 8 9%
Business, Management and Accounting 5 6%
Pharmacology, Toxicology and Pharmaceutical Science 4 4%
Other 13 15%
Unknown 26 29%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 November 2017.
All research outputs
of 20,640,204 outputs
Outputs from Implementation Science
of 1,671 outputs
Outputs of similar age
of 288,351 outputs
Outputs of similar age from Implementation Science
of 2 outputs
Altmetric has tracked 20,640,204 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,671 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.6. This one is in the 46th percentile – i.e., 46% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 288,351 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.