2011
DOI: 10.1080/19488300.2011.628638
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A stochastic dynamic program for the single-day surgery scheduling problem

Abstract: The scheduling of individual surgical patients has received extensive treatment in the literature, but this paper is the first to propose a model that simultaneously captures the roles of block schedules, block release dates, and request queue policies in the dynamic evolution of the schedule for a single day in an operating room suite. The model is formulated as a stochastic dynamic program and theoretical results are obtained for a single room version. These results demonstrate that optimal request queue dec… Show more

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Cited by 15 publications
(5 citation statements)
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“…This indicates that having a very large number of cases on the RQ should not force the OR manager to place more of them. Table 1 shows the optimal thresholds for SDSSP1 across a range of different input scenarios for an OR schedule that has a capacity of four cases (for the complete input data, see Herring 2010). Recall that the thresholds reflect how much space to save on the OR schedule for future primary cases, so higher thresholds lead to fewer RQ cases being scheduled.…”
Section: The Special Case Of Unit Durationsmentioning
confidence: 99%
See 3 more Smart Citations
“…This indicates that having a very large number of cases on the RQ should not force the OR manager to place more of them. Table 1 shows the optimal thresholds for SDSSP1 across a range of different input scenarios for an OR schedule that has a capacity of four cases (for the complete input data, see Herring 2010). Recall that the thresholds reflect how much space to save on the OR schedule for future primary cases, so higher thresholds lead to fewer RQ cases being scheduled.…”
Section: The Special Case Of Unit Durationsmentioning
confidence: 99%
“…For more details on the specific algorithm used to find the optimal thresholds, see the proof of the threshold optimality claim in Herring (2010). The first three methods, which are based on the observed behavior for specific problem scenarios, should work well for some problems and poorly for others.…”
Section: Threshold Determinationmentioning
confidence: 99%
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“…Although there were traces of the interactions between systems thinking and healthcare back in the 1950s, it is only recently that the field has started to discuss these possibilities [Anderson and McDaniel, ; Murray and Berwick, ; Proctor et al., ; Ben‐Tzion Karsh and Alper, ; Wu et al., ; Omachonu and Einspruch, ; Kopach‐Konrad et al., ; Wickramasinghe et al., ; Rouse, ; Rouse and Cortese, ; Ross and Bidanda, ]. A new journal has been recently started [Fowler et al., ] in 2011 with applications ranging from scheduling [Mobasher et al., ; Herring and Herrmann, ; Pérez et al., ; Turkcan et al., ; Koeleman and Koole, ; Huang, Hancock, and Herrin, ; Lin et al., ; Mancilla and Storer, ; Claudio et al., ; Ewen and Mönch, ; Alaeddini et al., ], to reducing errors [Alvarado et al., ], improving hospital outpatient flow [Marmor et al., ; Peck et al., ], improving emergency room operations [Kaner et al., ], and improving patient safety [Rivera and Karsh, ].…”
Section: Background Conceptsmentioning
confidence: 99%