TY - JOUR
T1 - Evaluating the impact of optimization algorithms for patient transits dispatching using discrete event simulation
AU - Furian, N.
AU - O'Sullivan, M.
AU - Walker, C.
AU - Vössner, S.
PY - 2018/12/1
Y1 - 2018/12/1
N2 - The on-time completion of patient transits can be identified as a bottleneck for the efficiency of health care services in major New Zealand hospitals. Delayed transits of patients between wards and treatment or diagnostic facilities lead to increasing waiting times at clinics and inefficient resource utilization (e.g. surgery teams) as appointment times are not met. Patient transits are carried out by orderlies, but in some cases require the assistance of a nurse. Ad-hoc dispatching of staff members, nurses and orderlies, to transits has been identified as one major source for delays currently observed in the system. To address this issue we present automated, optimized dispatching algorithms for staff members performing those transits. To develop these algorithms, a network formulation of the problem is introduced that is strongly related to classical vehicle routing problem with semi-soft time windows. However, the need to synchronize the routes of staff members of different types (nurses and orderlies) adds a whole new layer of complexity to the problem, as routes cannot be assessed independently. We present a set of algorithms with varying complexity, ranging from simple heuristics to the use of critical path methods to combine mixed integer formulations for the separated orderly and nurse problems. To address a transit service's stochasticity, volatility and the resulting need for constant re-optimization, we embed the optimization algorithms in a discrete event simulation to evaluate their performance under realistic circumstances.
AB - The on-time completion of patient transits can be identified as a bottleneck for the efficiency of health care services in major New Zealand hospitals. Delayed transits of patients between wards and treatment or diagnostic facilities lead to increasing waiting times at clinics and inefficient resource utilization (e.g. surgery teams) as appointment times are not met. Patient transits are carried out by orderlies, but in some cases require the assistance of a nurse. Ad-hoc dispatching of staff members, nurses and orderlies, to transits has been identified as one major source for delays currently observed in the system. To address this issue we present automated, optimized dispatching algorithms for staff members performing those transits. To develop these algorithms, a network formulation of the problem is introduced that is strongly related to classical vehicle routing problem with semi-soft time windows. However, the need to synchronize the routes of staff members of different types (nurses and orderlies) adds a whole new layer of complexity to the problem, as routes cannot be assessed independently. We present a set of algorithms with varying complexity, ranging from simple heuristics to the use of critical path methods to combine mixed integer formulations for the separated orderly and nurse problems. To address a transit service's stochasticity, volatility and the resulting need for constant re-optimization, we embed the optimization algorithms in a discrete event simulation to evaluate their performance under realistic circumstances.
KW - Column generation
KW - Discrete event simulation
KW - Limited subsequences
KW - Meta-heuristics
KW - Patient transit
KW - Vehicle routing
UR - http://www.scopus.com/inward/record.url?scp=85045565668&partnerID=8YFLogxK
U2 - 10.1016/j.orhc.2018.03.008
DO - 10.1016/j.orhc.2018.03.008
M3 - Article
AN - SCOPUS:85045565668
SN - 2211-6923
VL - 19
SP - 134
EP - 155
JO - Operations Research for Health Care
JF - Operations Research for Health Care
ER -