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Ruske J, Castillo-Angeles M, Lamarre T, Salim A, Jenkins K, Rembetski BE, Kaafarani HMA, Herrera-Escobar JP, Sanchez SE. Patients Lost to Follow-up After Injury: Who are They and What are Their Long-Term Outcomes? J Surg Res 2024; 296:343-351. [PMID: 38306940 DOI: 10.1016/j.jss.2023.12.037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 12/08/2023] [Accepted: 12/30/2023] [Indexed: 02/04/2024]
Abstract
INTRODUCTION Trauma patients are at high risk for loss to follow-up (LTFU) after hospital discharge. We sought to identify risk factors for LTFU and investigate associations between LTFU and long-term health outcomes in the trauma population. METHODS Trauma patients with an Injury Severity Score ≥9 admitted to one of three Level-I trauma centers, 2015-2020, were surveyed via telephone 6 mo after injury. Univariate and multivariate analyses were performed to assess factors associated with LTFU and several long-term outcomes. RESULTS Of 3609 patients analyzed, 808 (22.4%) were LTFU. Patients LTFU were more likely to be male (71% versus 61%, P = 0.001), Black (22% versus 14%, P = 0.003), have high school or lower education (50% versus 42%, P = 0.003), be publicly insured (23% versus 13%, P < 0.001), have a penetrating injury (13% versus 8%, P = 0.006), have a shorter length of stay (3.64 d ± 4.09 versus 5.06 ± 5.99, P < 0.001), and be discharged home without assistance (79% versus 50%, P < 0.001). In multivariate analyses, patients who followed up were more likely to require assistance at home (6% versus 11%; odds ratio [OR] 2.23, 1.26-3.92, P = 0.005), have new functional limitations (11% versus 26%; OR 2.91, 1.97-4.31, P = < 0.001), have daily pain (30% versus 48%; OR 2.11, 1.54-2.88, P = < 0.001), and have more injury-related emergency department visits (7% versus 10%; OR 1.93, 1.15-3.22, P = 0.012). CONCLUSIONS Vulnerable populations are more likely to be LTFU after injury. Clinicians should be aware of potential racial and socioeconomic disparities in follow-up care after traumatic injury. Future studies investigating improvement strategies in follow-up care should be considered.
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Affiliation(s)
- Jack Ruske
- Boston University Chobanian and Avedisian School of Medicine, Boston, Massachusetts; Boston Medical Center, Boston, Massachusetts.
| | | | | | - Ali Salim
- Brigham and Women's Hospital, Boston, Massachusetts
| | - Kendall Jenkins
- Boston University Chobanian and Avedisian School of Medicine, Boston, Massachusetts; Boston Medical Center, Boston, Massachusetts
| | - Benjamin E Rembetski
- Boston University Chobanian and Avedisian School of Medicine, Boston, Massachusetts; Boston Medical Center, Boston, Massachusetts
| | | | | | - Sabrina E Sanchez
- Boston University Chobanian and Avedisian School of Medicine, Boston, Massachusetts; Boston Medical Center, Boston, Massachusetts
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Rubenstein LV, Curtis I, Wheat CL, Grembowski DE, Stockdale SE, Kaboli PJ, Yoon J, Felker BL, Reddy AS, Nelson KM. Learning from national implementation of the Veterans Affairs Clinical Resource Hub (CRH) program for improving access to care: protocol for a six year evaluation. BMC Health Serv Res 2023; 23:790. [PMID: 37488518 PMCID: PMC10367243 DOI: 10.1186/s12913-023-09799-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Accepted: 07/10/2023] [Indexed: 07/26/2023] Open
Abstract
BACKGROUND The Veterans Affairs (VA) Clinical Resource Hub (CRH) program aims to improve patient access to care by implementing time-limited, regionally based primary or mental health staffing support to cover local staffing vacancies. VA's Office of Primary Care (OPC) designed CRH to support more than 1000 geographically disparate VA outpatient sites, many of which are in rural areas, by providing virtual contingency clinical staffing for sites experiencing primary care and mental health staffing deficits. The subsequently funded CRH evaluation, carried out by the VA Primary Care Analytics Team (PCAT), partnered with CRH program leaders and evaluation stakeholders to develop a protocol for a six-year CRH evaluation. The objectives for developing the CRH evaluation protocol were to prospectively: 1) identify the outcomes CRH aimed to achieve, and the key program elements designed to achieve them; 2) specify evaluation designs and data collection approaches for assessing CRH progress and success; and 3) guide the activities of five geographically dispersed evaluation teams. METHODS The protocol documents a multi-method CRH program evaluation design with qualitative and quantitative elements. The evaluation's overall goal is to assess CRH's return on investment to the VA and Veterans at six years through synthesis of findings on program effectiveness. The evaluation includes both observational and quasi-experimental elements reflecting impacts at the national, regional, outpatient site, and patient levels. The protocol is based on program evaluation theory, implementation science frameworks, literature on contingency staffing, and iterative review and revision by both research and clinical operations partners. DISCUSSION Health systems increasingly seek to use data to guide management and decision-making for newly implemented clinical programs and policies. Approaches for planning evaluations to accomplish this goal, however, are not well-established. By publishing the protocol, we aim to increase the validity and usefulness of subsequent evaluation findings. We also aim to provide an example of a program evaluation protocol developed within a learning health systems partnership.
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Affiliation(s)
- Lisa V Rubenstein
- Evidence-Based Practice Center, RAND Corporation, Santa Monica, CA, USA.
- Geffen School of Medicine and Fielding School of Public Health at UCLA, Los Angeles, CA, USA.
| | - Idamay Curtis
- Primary Care Analytics Team, VA Puget Sound Healthcare System, Seattle, WA, USA
| | - Chelle L Wheat
- Primary Care Analytics Team, VA Puget Sound Healthcare System, Seattle, WA, USA
| | - David E Grembowski
- The Department of Health Systems and Population Health in the School of Public Health, University of Washington, Seattle, USA
| | - Susan E Stockdale
- VA HSR&D Center for the Study of Healthcare Innovation, Implementation, and Policy, VA Greater Los Angeles Healthcare System, Los Angeles, USA
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, USA
| | - Peter J Kaboli
- Center for Access and Delivery Research and Evaluation (CADRE), Iowa City VA Healthcare System, Iowa City, IA, USA
| | - Jean Yoon
- Health Economics Resource Center, VA Palo Alto Health Care System, Menlo Park, CA, USA
- Department of General Internal Medicine, UCSF School of Medicine, San Francisco, CA, USA
| | - Bradford L Felker
- Mental Health Service Line, VA Puget Sound Healthcare System, Seattle, WA, USA
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Ashok S Reddy
- Primary Care Analytics Team, VA Puget Sound Healthcare System, Seattle, WA, USA
- Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA
| | - Karin M Nelson
- Primary Care Analytics Team, VA Puget Sound Healthcare System, Seattle, WA, USA
- Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA
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