Estimating National and Regional Primary Care Spending in the Veterans Health Administration in 2022 Article Swipe
Jonathan Staloff
,
Karin Nelson
,
Ashok Reddy
,
Eric Gunnink
,
Edwin S. Wong
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3122/jabfm.2024.240463r1
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3122/jabfm.2024.240463r1
Primary care spending in the VHA in 2022 as a percentage of total medical expenditures was stable compared with prior estimates. In addition, our results show discordance in each VISN's spending quartile based on the metric utilized. This finding suggests that each metric may capture a different element of primary care spending.
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- OA Status
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All OpenAlex metadata
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Estimating National and Regional Primary Care Spending in the Veterans Health Administration in 2022Work title
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2025Year of publication
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2025-07-01Full publication date if available
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Jonathan Staloff, Karin Nelson, Ashok Reddy, Eric Gunnink, Edwin S. WongList of authors in order
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https://doi.org/10.3122/jabfm.2024.240463r1Publisher landing page
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https://www.jabfm.org/content/jabfp/early/2025/10/17/jabfm.2024.240463R1.full.pdfDirect link to full text PDF
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diamondOpen access status per OpenAlex
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https://www.jabfm.org/content/jabfp/early/2025/10/17/jabfm.2024.240463R1.full.pdfDirect OA link when available
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| abstract_inverted_index.each | 28, 41 |
| abstract_inverted_index.show | 25 |
| abstract_inverted_index.that | 40 |
| abstract_inverted_index.with | 18 |
| abstract_inverted_index.based | 32 |
| abstract_inverted_index.prior | 19 |
| abstract_inverted_index.total | 12 |
| abstract_inverted_index.VISN's | 29 |
| abstract_inverted_index.metric | 35, 42 |
| abstract_inverted_index.stable | 16 |
| abstract_inverted_index.Primary | 0 |
| abstract_inverted_index.capture | 44 |
| abstract_inverted_index.element | 47 |
| abstract_inverted_index.finding | 38 |
| abstract_inverted_index.medical | 13 |
| abstract_inverted_index.primary | 49 |
| abstract_inverted_index.results | 24 |
| abstract_inverted_index.compared | 17 |
| abstract_inverted_index.quartile | 31 |
| abstract_inverted_index.spending | 2, 30 |
| abstract_inverted_index.suggests | 39 |
| abstract_inverted_index.addition, | 22 |
| abstract_inverted_index.different | 46 |
| abstract_inverted_index.spending. | 51 |
| abstract_inverted_index.utilized. | 36 |
| abstract_inverted_index.estimates. | 20 |
| abstract_inverted_index.percentage | 10 |
| abstract_inverted_index.discordance | 26 |
| abstract_inverted_index.expenditures | 14 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| citation_normalized_percentile.value | 0.69171252 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |