A multilevel integrative approach to hospital case mix and capacity planning.

Hospital case mix and capacity planning involves the decision making both on patient volumes that can be taken care of at a hospital and on resource requirements and capacity management. In this research, to advance both the hospital resource efficiency and the health care service level, a multilevel integrative approach to the planning problem is proposed on the basis of mathematical programming modeling and simulation analysis. It consists of three stages, namely the case mix planning phase, the master surgery scheduling phase and the operational performance evaluation phase. At the case mix planning phase, a hospital is assumed to choose the optimal patient mix and volume that can bring the maximum overall financial contribution under the given resource capacity. Then, in order to improve the patient service level potentially, the total expected bed shortage due to the variable length of stay of patients is minimized through reallocating the bed capacity and building balanced master surgery schedules at the master surgery scheduling phase. After that, the performance evaluation is carried out at the operational stage through simulation analysis, and a few effective operational policies are suggested and analyzed to enhance the trade-offs between resource efficiency and service level. The three stages are interacting and are combined in an iterative way to make sound decisions both on the patient case mix and on the resource allocation.Health care; Case mix and capacity planning; Master surgery schedule; Multilevel; Resource efficiency; Service level;

Assessing the performance of hospital capacity planning through simulation analysis

Hospital capacity planning at the tactical level produces the optimal patient case mix that can be taken care of at a hospital with the associated time-phased allocation of resources. However, different generated scenarios may result in dissimilar effects on the delivery of health care when variability comes into play. Therefore, it is important to evaluate the performance of capacity planning through simulation analysis. In our setting, the daily booked surgical inpatients are always operated on but possibly are misplaced in an alternative area for recovery because of a bed shortage in the suitable ward, while the bed shortage is the consequence of fluctuating lengths of stay of the patients. Patient misplacement is the chief performance indicator to reflect the service level. Two aspects are studied intensively in this paper. On the one hand, in order to reduce the bed shortage maximally, a few strategies are suggested when determining the capacity decisions. Then, the impacts of different strategies are compared on bed occupancy and patient misplacement. On the other hand, sensitivity analysis is carried out to check whether the number of patient misplacements can be reduced and whether the bed shortage phenomenon can be mitigated.status: publishe

A multilevel integrative approach to hospital case mix and capacity planning

Hospital case mix and capacity planning involves the decision making both on patient volumes that can be taken care of at a hospital and on resource requirements and capacity management. In this research, to advance both the hospital resource efficiency and the health care service level, a multilevel integrative approach to the planning problem is proposed on the basis of mathematical programming modeling and simulation analysis. It consists of three stages, namely the case mix planning phase, the master surgery scheduling phase and the operational performance evaluation phase. At the case mix planning phase, a hospital is assumed to choose the optimal patient mix and volume that can bring the maximum overall financial contribution under the given resource capacity. Then, in order to improve the patient service level potentially, the total expected bed shortage due to the variable length of stay of patients is minimized through reallocating the bed capacity and building balanced master surgery schedules at the master surgery scheduling phase. After that, the performance evaluation is carried out at the operational stage through simulation analysis, and a few effective operational policies are suggested and analyzed to enhance the trade-offs between resource efficiency and service level. The three stages are interacting and are combined in an iterative way to make sound decisions both on the patient case mix and on the resource allocation.status: publishe

A multilevel integrative approach to hospital case mix and capacity planning

Hospital case mix and capacity planning involves the decision making both on patient volumes that can be taken care of at a hospital and on resource requirements and capacity management. In this research, to advance both the hospital resource efficiency and the health care service level, a multilevel integrative approach to the planning problem is proposed on the basis of mathematical programming modeling and simulation analysis. It consists of three stages, namely the case mix planning phase, the master surgery scheduling phase and the operational performance evaluation phase. At the case mix planning phase, a hospital is assumed to choose the optimal patient mix and volume that can bring the maximum overall financial contribution under the given resource capacity. Then, in order to improve the patient service level potentially, the total expected bed shortage due to the variable length of stay of patients is minimized through reallocating the bed capacity and building balanced master surgery schedules at the master surgery scheduling phase. After that, the performance evaluation is carried out at the operational stage through simulation analysis, and a few effective operational policies are suggested and analyzed to enhance the trade-offs between resource efficiency and service level. The three stages are interacting and are combined in an iterative way to make sound decisions both on the patient case mix and on the resource allocation. © 2012 Elsevier Ltd.status: publishe

Operation Mechanisms of Flexible RF Silicon Thin Film Transistor under Bending Conditions

We fabricate a flexible silicon thin-film transistor (TFT) on a plastic substrate as a key component and representative example to analyze the major influencing factors of flexible devices under bending conditions. Experimental and two-dimensional device modeling results reveal that bending radius and device dimensions have a significant influence on the radio-frequency (RF) performance of the flexible silicon nanomembrane (SiNM) TFT under bending conditions. Carrier mobility and electric field extracted from the model, together with theoretical analysis, were employed to study the performance dependence and the operation mechanisms of the bended TFTs. The carrier mobility and electric field are increased monotonically with larger bending strains, which lead to better RF performance. They also showed a consistent change trend with different device parameters (e.g., gate length, oxide thickness). Flexible SiNM TFTs with a smaller gate length and a larger gate dielectric thickness are shown to have better RF performance robustness with bending strains. The analysis provides a guideline for the study of flexible electronics under bending conditions

Solving the case mix problem optimally by using branch-and-price algorithms

This paper describes a methodology for the case mix problem in the health care sector. Aiming at maximizing the overall financial contribution of the given resource capacity within a hospital, the case mix problem is formulated as an integer linear programming model to produce the optimal patient mix pattern together with its associated resource allocation scheme. In order to solve the huge integer program optimally, an efficient solution approach, branch-and-price, is proposed, developed and implemented in this research. When studied from the column generation perspective, the integer linear programming model can be formulated differently. According to different decomposition units, namely wards, surgeon groups and patient groups, three decomposition based reformulations are built respectively. Among them, the first two reformulations are suitable to be solved within the framework of branch-and-price, while this is not the case for the last one. Numerical experiments are carried out, and the computational results are presented and compared, which demonstrate that the branch-and-price approach outperforms the integer linear programming method significantly and that decomposition on wards performs much better than decomposition on surgeon groups both with respect to the solution quality and the computation speed.status: publishe

Solving the case mix problem optimally by using branch-and-price algorithms.

This paper describes a methodology for the case mix problem in the health care sector. Aiming at maximizing the overall financial contribution of the given resource capacity within a hospital, the case mix problem is formulated as an integer linear programming model to produce the optimal patient mix pattern together with its associated resource allocation scheme. In order to solve the huge integer program optimally, an efficient solution approach, branch-and-price, is proposed, developed and implemented in this research. When studied from the column generation perspective, the integer linear programming model can be formulated differently. According to different decomposition units, namely wards, surgeon groups and patient groups, three decomposition based reformulations are built respectively. Among them, the first two reformulations are suitable to be solved within the framework of branch-and-price, while this is not the case for the last one. Numerical experiments are carried out, and the computational results are presented and compared, which demonstrate that the branch-and-price approach outperforms the integer linear programming method significantly and that decomposition on wards performs much better than decomposition on surgeon groups both with respect to the solution quality and the computation speed.Patient case mix; Capacity planning; Integer linear programming; Branch-and-price approach;

High-Performance Flexible Single-Crystalline Silicon Nanomembrane Thin-Film Transistors with High‑<i>k</i> Nb₂O₅–Bi₂O₃–MgO Ceramics as Gate Dielectric on a Plastic Substrate

A novel method of fabricating flexible thin-film transistor based on single-crystalline Si nanomembrane (SiNM) with high-<i>k</i> Nb₂O₅–Bi₂O₃–MgO (BMN) ceramic gate dielectric on a plastic substrate is demonstrated in this paper. SiNMs are successfully transferred to a flexible polyethylene terephthalate substrate, which has been plated with indium-tin-oxide (ITO) conductive layer and high-<i>k</i> BMN ceramic gate dielectric layer by room-temperature magnetron sputtering. The BMN ceramic gate dielectric layer demonstrates as high as ∼109 dielectric constant, with only dozens of pA current leakage. The Si–BMN–ITO heterostructure has only ∼nA leakage current at the applied voltage of 3 V. The transistor is shown to work at a high current on/off ratio of above 10⁴, and the threshold voltage is ∼1.3 V, with over 200 cm²/(V s) effective channel electron mobility. Bending tests have been conducted and show that the flexible transistors have good tolerance on mechanical bending strains. These characteristics indicate that the flexible single-crystalline SiNM transistors with BMN ceramics as gate dielectric have great potential for applications in high-performance integrated flexible circuit