Moving the Bar, Even if you Can’t Move the Bed

Kimberly Pedram (Virginia Commonwealth University School of Medicine), Heather Masters (Virginia Commonwealth University School of Medicine), Kristin Miller (Virginia Commonwealth University School of Medicine), Kyle Jensen (Virginia Commonwealth University School of Medicine), Nargiza Kurbanova (Virginia Commonwealth University School of Medicine)

Background

Successful discharge planning starts at admission.  When admission occurs to a closed medical intensive care unit (MICU), discharge planning can be delayed until the patient transfers to a general floor.  This delay is exacerbated as a hospital’s occupancy rises, increasing the MICU boarding time for patients awaiting general bed availability.

Objectives

Our objective was to examine the difference in length of stay (LOS) and observed to expected length of stay (O:E LOS) before and after the implementation of an algorithm in which hospitalists assumed care of MICU patients awaiting transfer to the general medicine floor.

Methods

Our academic institution operates at a consistent state of full capacity; we created an algorithm to transfer care from the MICU service to a hospitalist team when a patient was deemed appropriate for transfer but there was no available bed. Patients on this “boarding” team were seen daily by a hospitalist and had the same access to care transition resources as a patient on the traditional general medicine units. These “boarding team” patients were either transferred to the general medicine unit as a bed became available or discharged from the MICU. Patients with identified floor beds at the time of transfer orders continued to be moved to a general medicine unit. Patient deaths were excluded. Mean LOS and O:E LOS for patients admitted to the MICU but discharged by a hospitalist were compared to patients who were directly transferred out of the MICU to a general medicine unit during the algorithm period. We used Student’s t-test to compare groups pre- and post- algorithm and multivariable linear regression for the difference-in-differences analyses.

Results

During the first six months of implementation of the algorithm, ICU “boarders” cared for by a hospitalist team had a mean LOS of 8.34 days and a mean O:E of 1.27 while patients discharged from the non-hospitalist teams had mean LOS of 11.12 days and O:E LOS of 1.51 (difference in LOS=2.22 days and O:E LOS=0.24).   Analysis of mean LOS and O:E LOS for the same six months in the year prior to the transfer algorithm showed no consistent difference between ICU patients discharged by the hospitalist or non-hospitalist teams. Using the Council of Teaching Hospitals 2017 report data, the intervention’s decrease in O:E LOS correlates to a 6-month savings of $689,232. Using an average LOS of 6.4 days, approximately 65 more patients could be admitted (increased revenue of $976,950 per internal benchmarking).

Conclusion

Early transition of MICU patients to a hospitalist service showed significant improvement in mean LOS and O: E LOS as compared to the traditional model of keeping a patient under the MICU’s care until a non-ICU bed opens.

Implications for the Patient

These findings suggest another opportunity for hospitalists to support the operational mission when traditional resources (available beds on Hospital Medicine units) might not be available.

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