Burnout and Turnover Among Veterans Health Administration Primary Care Providers From Fiscal Years 2017–2021 Article Swipe
Eric Apaydin
,
Caroline Yoo
,
Susan E. Stockdale
,
Nicholas Jackson
,
Elizabeth M. Yano
,
Karin M. Nelson
,
David C. Mohr
,
Danielle E. Rose
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1097/mlr.0000000000002087
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1097/mlr.0000000000002087
Objectives: We examined how individual-level turnover among Veterans Health Administration primary care providers (PCPs) from fiscal years 2017 to 2021 was associated with health care system-level burnout and turnover intent. Background: Burnout among PCPs has been well documented in recent studies, but less is known about the potential relationship between burnout and turnover. Methods: We identified a national cohort of 6444 PCPs (physicians, nurse practitioners, and physician assistants) in 129 Veterans Health Administration health care systems in the first quarter of fiscal year 2017 and tracked their employment status for 20 quarters. PCP employment data on turnover were linked to annual health care system-level employee survey data on burnout, turnover intent, and other covariates. We performed logistic regression to estimate the impact of health care system-level burnout and turnover intent on individual PCP turnover, controlling for individual and health care system-level covariates and adjusting for clustering at the health care system level. Results: Median health care system-level burnout ranged from 42.5% to 52.0% annually, and turnover among PCPs ranged from 6.3% to 8.4% (mean = 7.0%; SD = 0.9%). Separation from employment was higher among employees at health care systems with the highest burnout (odds ratio =1.14; 95% CI = 1.01–1.29) and turnover intent (OR = 1.18; 95% CI = 1.03–1.35). Conclusions: PCPs in health care systems with high burnout are more likely to separate from employment. Policymakers and administrators seeking to improve retention should consider system-level interventions to address organizational drivers of burnout.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1097/mlr.0000000000002087
- OA Status
- green
- Cited By
- 3
- References
- 52
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4404262249
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4404262249Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1097/mlr.0000000000002087Digital Object Identifier
- Title
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Burnout and Turnover Among Veterans Health Administration Primary Care Providers From Fiscal Years 2017–2021Work title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-10-28Full publication date if available
- Authors
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Eric Apaydin, Caroline Yoo, Susan E. Stockdale, Nicholas Jackson, Elizabeth M. Yano, Karin M. Nelson, David C. Mohr, Danielle E. RoseList of authors in order
- Landing page
-
https://doi.org/10.1097/mlr.0000000000002087Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://www.ncbi.nlm.nih.gov/pmc/articles/11888842Direct OA link when available
- Concepts
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Burnout, Veterans Affairs, Medicine, Health care, Logistic regression, Psychological intervention, Turnover, Family medicine, Odds ratio, Nursing, Internal medicine, Clinical psychology, Management, Economic growth, EconomicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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3Total citation count in OpenAlex
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2025: 3Per-year citation counts (last 5 years)
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52Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.were | 97 |
| abstract_inverted_index.with | 22, 190, 217 |
| abstract_inverted_index.year | 82 |
| abstract_inverted_index.(mean | 173 |
| abstract_inverted_index.(odds | 194 |
| abstract_inverted_index.1.18; | 206 |
| abstract_inverted_index.42.5% | 160 |
| abstract_inverted_index.52.0% | 162 |
| abstract_inverted_index.7.0%; | 175 |
| abstract_inverted_index.about | 45 |
| abstract_inverted_index.among | 6, 32, 166, 184 |
| abstract_inverted_index.first | 78 |
| abstract_inverted_index.known | 44 |
| abstract_inverted_index.nurse | 63 |
| abstract_inverted_index.other | 112 |
| abstract_inverted_index.ratio | 195 |
| abstract_inverted_index.their | 86 |
| abstract_inverted_index.years | 16 |
| abstract_inverted_index.(PCPs) | 13 |
| abstract_inverted_index.0.9%). | 178 |
| abstract_inverted_index.=1.14; | 196 |
| abstract_inverted_index.Health | 8, 71 |
| abstract_inverted_index.Median | 153 |
| abstract_inverted_index.annual | 100 |
| abstract_inverted_index.cohort | 58 |
| abstract_inverted_index.fiscal | 15, 81 |
| abstract_inverted_index.health | 23, 73, 101, 123, 138, 148, 154, 187, 214 |
| abstract_inverted_index.higher | 183 |
| abstract_inverted_index.impact | 121 |
| abstract_inverted_index.intent | 129, 203 |
| abstract_inverted_index.level. | 151 |
| abstract_inverted_index.likely | 222 |
| abstract_inverted_index.linked | 98 |
| abstract_inverted_index.ranged | 158, 168 |
| abstract_inverted_index.recent | 39 |
| abstract_inverted_index.should | 234 |
| abstract_inverted_index.status | 88 |
| abstract_inverted_index.survey | 105 |
| abstract_inverted_index.system | 150 |
| abstract_inverted_index.Burnout | 31 |
| abstract_inverted_index.address | 239 |
| abstract_inverted_index.between | 49 |
| abstract_inverted_index.burnout | 26, 50, 126, 157, 193, 219 |
| abstract_inverted_index.drivers | 241 |
| abstract_inverted_index.highest | 192 |
| abstract_inverted_index.improve | 232 |
| abstract_inverted_index.intent, | 110 |
| abstract_inverted_index.intent. | 29 |
| abstract_inverted_index.primary | 10 |
| abstract_inverted_index.quarter | 79 |
| abstract_inverted_index.seeking | 230 |
| abstract_inverted_index.systems | 75, 189, 216 |
| abstract_inverted_index.tracked | 85 |
| abstract_inverted_index.Methods: | 53 |
| abstract_inverted_index.Results: | 152 |
| abstract_inverted_index.Veterans | 7, 70 |
| abstract_inverted_index.burnout, | 108 |
| abstract_inverted_index.burnout. | 243 |
| abstract_inverted_index.consider | 235 |
| abstract_inverted_index.employee | 104 |
| abstract_inverted_index.estimate | 119 |
| abstract_inverted_index.examined | 2 |
| abstract_inverted_index.logistic | 116 |
| abstract_inverted_index.national | 57 |
| abstract_inverted_index.separate | 224 |
| abstract_inverted_index.studies, | 40 |
| abstract_inverted_index.turnover | 5, 28, 96, 109, 128, 165, 202 |
| abstract_inverted_index.adjusting | 143 |
| abstract_inverted_index.annually, | 163 |
| abstract_inverted_index.employees | 185 |
| abstract_inverted_index.performed | 115 |
| abstract_inverted_index.physician | 66 |
| abstract_inverted_index.potential | 47 |
| abstract_inverted_index.providers | 12 |
| abstract_inverted_index.quarters. | 91 |
| abstract_inverted_index.retention | 233 |
| abstract_inverted_index.turnover, | 133 |
| abstract_inverted_index.turnover. | 52 |
| abstract_inverted_index.Separation | 179 |
| abstract_inverted_index.associated | 21 |
| abstract_inverted_index.clustering | 145 |
| abstract_inverted_index.covariates | 141 |
| abstract_inverted_index.documented | 37 |
| abstract_inverted_index.employment | 87, 93, 181 |
| abstract_inverted_index.identified | 55 |
| abstract_inverted_index.individual | 131, 136 |
| abstract_inverted_index.regression | 117 |
| abstract_inverted_index.Background: | 30 |
| abstract_inverted_index.Objectives: | 0 |
| abstract_inverted_index.assistants) | 67 |
| abstract_inverted_index.controlling | 134 |
| abstract_inverted_index.covariates. | 113 |
| abstract_inverted_index.employment. | 226 |
| abstract_inverted_index.(physicians, | 62 |
| abstract_inverted_index.1.01–1.29) | 200 |
| abstract_inverted_index.Conclusions: | 211 |
| abstract_inverted_index.Policymakers | 227 |
| abstract_inverted_index.relationship | 48 |
| abstract_inverted_index.system-level | 25, 103, 125, 140, 156, 236 |
| abstract_inverted_index.1.03–1.35). | 210 |
| abstract_inverted_index.interventions | 237 |
| abstract_inverted_index.Administration | 9, 72 |
| abstract_inverted_index.administrators | 229 |
| abstract_inverted_index.organizational | 240 |
| abstract_inverted_index.practitioners, | 64 |
| abstract_inverted_index.individual-level | 4 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 96 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 8 |
| citation_normalized_percentile.value | 0.92814631 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |