The Impact of a Novel Transfer Process on Patient Bed Days and Length of Stay: A Five-Year Comparative Study at the Mayo Clinic in Rochester and Mankato Quaternary and Tertiary Care Centers

Anwar Khedr, Esraa Hassan, Rida Asim, Muhammad Khuzzaim Khan (), Nikhil Duseja, Noura Attallah, Jennifer Mueller, Jamie Newman, Erica Loomis, Jennifer Bartelt, Syed Anjum Khan and Brian Bartlett
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Anwar Khedr: BronxCare Health System, Bronx, NY 10457, USA
Esraa Hassan: Mayo Clinic, Rochester, MN 55905, USA
Rida Asim: Department of Internal Medicine, Karachi Medical and Dental College, Karachi 74700, Pakistan
Muhammad Khuzzaim Khan: Department of Internal Medicine, Dow University of Health Sciences, Karachi 74200, Pakistan
Nikhil Duseja: Department of Internal Medicine, Karachi Medical and Dental College, Karachi 74700, Pakistan
Noura Attallah: Henry Ford Health System, Jackson, MI 49201, USA
Jennifer Mueller: Mayo Clinic, Rochester, MN 55905, USA
Jamie Newman: Mayo Clinic, Rochester, MN 55905, USA
Erica Loomis: Mayo Clinic, Rochester, MN 55905, USA
Jennifer Bartelt: Mayo Clinic, Rochester, MN 55905, USA
Syed Anjum Khan: Mayo Clinic, Rochester, MN 55905, USA
Brian Bartlett: Mayo Clinic, Rochester, MN 55905, USA

IJERPH, 2025, vol. 22, issue 6, 1-13

Abstract: Introduction: This study evaluated the impact of parallel-level patient transfers on bed utilization efficiency within the Mayo Clinic Health System in Southern Minnesota, focusing on optimizing resources across tertiary and critical access hospitals. Methods: A retrospective analysis of 179,066 Emergency Department visits (2018–2022) was conducted, with ~2% involving parallel-level transfers for observation or admission. Machine learning was utilized to identify patients suitable for parallel transfers based on demographics, comorbidities, and clinical factors. A Random Forest model with an AUROC of 0.87 guided transfer decisions. Saved patient days were calculated as the difference between the actual LOS and the benchmark LOS based on Diagnosis-Related Groups (DRGs). Generalized estimating equations analyzed length of stay (LOS) differences, adjusted for confounders, with 95% confidence intervals (CI). Statistical analyses were conducted using SPSS (v.26). Results: The mean patient age was 56 years (SD = 17.2), with 51.4% being female. Saved patient days increased from ~600 to 5200 days over the study period. Transferred patients had a 5.7% longer unadjusted LOS compared to non-transferred patients (95% CI: 2.9–8.6%, p < 0.001). After adjustment for demographics and comorbidities, the LOS difference was not significant (adjusted mean difference: 0.4%, 95% CI: −1.7–2.5%, p = 0.51). Conclusions: Parallel-level transfers increased saved patient days, reflecting enhanced resource utilization. However, the adjusted LOS differences were not significant, highlighting the need for robust transfer protocols and controlled studies to confirm these findings.

Keywords: parallel transfer; saved patient days; tertiary care centers; bed utilization efficiency (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2025
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