The n -by- T Target Discharge Strategy for Inpatient Units

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Abstract

Background. Ineffective inpatient discharge planning often causes discharge delays and upstream boarding. While an optimal discharge strategy that works across all units at a hospital is likely difficult to identify and implement, a strategy that provides a reasonable target to the discharge team appears feasible. Methods. We used observational and retrospective data from an inpatient trauma unit at a Level 2 trauma center in the Midwest US. Our proposed novel n-by-T strategy - discharge n patients by the Tth hour - was evaluated using a validated simulation model. Outcome measures included 2 measures: time-based (mean discharge completion and upstream boarding times) and capacity-based (increase in annual inpatient and upstream bed hours). Data from the pilot implementation of a 2-by-12 strategy at the unit was obtained and analyzed. Results. The model suggested that the 1-by-T and 2-by-T strategies could advance the mean completion times by over 1.38 and 2.72 h, respectively (for 10 AM ≤ T ≤ noon, occupancy rate = 85%); the corresponding mean boarding time reductions were nearly 11% and 15%. These strategies could increase the availability of annual inpatient and upstream bed hours by at least 2,469 and 500, respectively. At 100% occupancy rate, the hospital-favored 2-by-12 strategy reduced the mean boarding time by 26.1%. A pilot implementation of the 2-by-12 strategy at the unit corroborated with the model findings: a 1.98-h advancement in completion times (P<0.0001) and a 14.5% reduction in boarding times (P = 0.027). Conclusion. Target discharge strategies, such as the n-by-T, can help substantially reduce discharge lateness and upstream boarding, especially during high unit occupancy. To sustain implementation, necessary commitment from the unit staff and physicians is vital, and may require some training.

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Parikh, P. J., Ballester, N., Ramsey, K., Kong, N., & Pook, N. (2017). The n -by- T Target Discharge Strategy for Inpatient Units. Medical Decision Making, 37(5), 534–543. https://doi.org/10.1177/0272989X17691735

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