Elena Tànfani

A model to prioritize access to elective surgery on the basis of clinical urgency and waiting time

BackgroundPrioritization of waiting lists for elective surgery represents a major issue in public systems in view of the fact that patients often suffer from consequences of long waiting times. In addition, administrative and standardized data on waiting lists are generally lacking in Italy, where no detailed national reports are available. This is true although since 2002 the National Government has defined implicit Urgency-Related Groups (URGs) associated with Maximum Time Before Treatment (MTBT), similar to the Australian classification. The aim of this paper is to propose a model to manage waiting lists and prioritize admissions to elective surgery.MethodsIn 2001, the Italian Ministry of Health funded the Surgical Waiting List Info System (SWALIS) project, with the aim of experimenting solutions for managing elective surgery waiting lists. The project was split into two phases. In the first project phase, ten surgical units in the largest hospital of the Liguria Region were involved in the design of a pre-admission process model. The model was embedded in a Web based software, adopting Italian URGs with minor modifications. The SWALIS pre-admission process was based on the following steps: 1) urgency assessment into URGs; 2) correspondent assignment of a pre-set MTBT; 3) real time prioritization of every referral on the list, according to urgency and waiting time. In the second project phase a prospective descriptive study was performed, when a single general surgery unit was selected as the deployment and test bed, managing all registrations from March 2004 to March 2007 (1809 ordinary and 597 day cases). From August 2005, once the SWALIS model had been modified, waiting lists were monitored and analyzed, measuring the impact of the model by a set of performance indexes (average waiting time, length of the waiting list) and Appropriate Performance Index (API).ResultsThe SWALIS pre-admission model was used for all registrations in the test period, fully covering the case mix of the patients referred to surgery. The software produced real time data and advanced parameters, providing patients and users useful tools to manage waiting lists and to schedule hospital admissions with ease and efficiency. The model protected patients from horizontal and vertical inequities, while positive changes in API were observed in the latest period, meaning that more patients were treated within their MTBT.ConclusionThe SWALIS model achieves the purpose of providing useful data to monitor waiting lists appropriately. It allows homogeneous and standardized prioritization, enhancing transparency, efficiency and equity. Due to its applicability, it might represent a pragmatic approach towards surgical waiting lists, useful in both clinical practice and strategic resource management.

A decomposition heuristics for the container ship stowage problem

In this paper we face the problem of stowing a containership, referred to as the Master Bay Plan Problem (MBPP); this problem is difficult to solve due to its combinatorial nature and the constraints related to both the ship and the containers. We present a decomposition approach that allows us to assign a priori the bays of a containership to the set of containers to be loaded according to their final destination, such that different portions of the ship are independently considered for the stowage. Then, we find the optimal solution of each subset of bays by using a 0/1 Linear Programming model. Finally, we check the global ship stability of the overall stowage plan and look for its feasibility by using an exchange algorithm which is based on local search techniques. The validation of the proposed approach is performed with some real life test cases.

A pre-assignment heuristic algorithm for the Master Surgical Schedule Problem (MSSP)

In this paper a 0–1 linear programming model and a solution heuristic algorithm are developed in order to solve the so-called Master Surgical Schedule Problem (MSSP). Given a hospital department made up of different surgical units (i.e. wards) sharing a given number of Operating Rooms (ORs), the problem herein addressed is determining the assignment among wards and ORs during a given planning horizon, together with the subset of patients to be operated on during each day. Different resource constraints related to operating block time length, maximum OR overtime allowable by collective labour agreement and legislation, patient length of stay (LOS), available OR equipment, number of surgeons, number of stay and ICU beds, are considered. Firstly, a 0–1 linear programming model intended to minimise a cost function based upon a priority score, that takes into proper account both the waiting time and the urgency status of each patient, is developed. Successively, an heuristic algorithm that enables us to embody some pre-assignment rules to solve this NP-hard combinatorial optimisation problem, is presented. In particular, we force the assignment of each patient to a subset of days depending on his/her expected length of stay in order to allow closing some stay areas during the weekend and hence reducing overall hospitalisation cost of the department. The results of an extensive computational experimentation aimed at showing the algorithm efficiency in terms of computational time and solution effectiveness are given and analysed.

A two level metaheuristic for the operating room scheduling and assignment problem

Given a surgery department comprising several specialties that share a fixed number of operating rooms and post-surgery beds, we study the joint operating room (OR) planning and advanced scheduling problem. More specifically, we consider the problem of determining, over a one week planning horizon, the allocation of OR time blocks to specialties together with the subsets of patients to be scheduled within each time block. The aim of this paper is to extend and generalize existing approaches for the joint OR planning and scheduling problem. First, by allowing schedules that include patients requiring weekend stay beds which was not the case previously. Second, by tackling simultaneously both the OR planning and patient scheduling decision levels, instead of taking them into account in successive phases. To achieve this, we exploit the inherent hierarchy between the two decision levels, i.e.,the fact that the assignment decisions of OR time blocks to surgical specialties directly affect those regarding the scheduling of patients, but not the reverse. The objective function used in this study is an extension of an existing one. It seeks to optimize both patient utility (by reducing waiting time costs) and hospital utility (by reducing production costs measured in terms of the number of weekend stay beds required by the surgery planning). 0-1 linear programming formulations exploiting the stated hierarchy are proposed and used to derive a formal proof that the problem is NP-hard. A two level metaheuristic is then developed for solving the problem and its effectiveness is demonstrated through extensive numerical experiments carried out on a large set of instances based on real data.

A 3D-BPP approach for optimising stowage plans and terminal productivity

Abstract This paper addresses the problem of determining stowage plans for containers in a ship, that is the so-called master bay plan problem (MBPP). MBPP is NP-complete [Botter, R.C., Brinati, M.A., 1992. Stowage container planning: A model for getting an optimal solution. IFIP Transactions B (Applications in Technology) B-5, 217–229; Avriel, M., Penn, M., Shpirer, N., 2000. Container ship stowage problem: Complexity and connection to the colouring of circle graphs. Discrete Applied Mathematics 103, 271–279]. We present a heuristic method for solving MBPP based on its relation with the three-dimensional bin packing problem (3D-BPP), where items are containers and the only bin is the ship . We look for stowage plans that take into a proper account structural and operational constraints, related to both the containers and the ship, and maximise some important terminal performance indexes, such as the effective and mean net crane productivity. Our aim is to evaluate how stowage plans can influence the performance of the quay. A validation of the proposed approach with some test cases related to containership docks at the port of Genoa (Italy) is given. The results of real instances of the problem and the comparison with a validated heuristic for MBPP, show the effectiveness of the proposed approach in producing stowage plans that minimise the total loading time and allow an efficient use of the quay equipment.

Assigning surgery cases to operating rooms: A vns approach for leveling ward beds occupancies

Abstract This paper deals with the problem of scheduling over a given planning horizon a set of elective surgery patients into a set of available operating room block times. The aim is to level the post-surgery ward bed occupancies during the days, thus allowing a smooth workload in the ward and, as a consequence, an improved quality of care provided to patients. Exploiting the flexibility of the Variable Neighbourhood Search, we provide a general solution framework which we show could be easily adapted to different operative contexts.

A Robust Optimization Approach for the Operating Room Planning Problem with Uncertain Surgery Duration

This paper deals with the Surgical Case Assignment Problem (SCAP) taking into account the variability pertaining patient surgery duration. In particular, given a surgery waiting list, a set of Operating Room (OR) blocks and a planning horizon, the decision herein addressed is to determine the subset of patients to be scheduled in the considered time horizon and their assignment to the available OR block times. The aim is to minimize a penalty associated to waiting time, urgency and tardiness of patients. We propose a robust optimization approach for the SCAP with uncertain surgery duration, which allows to exploit the potentialities of a mathematical programming model without the necessity of generating scenarios. Tests on a set of real-based instances are carried on in order to evaluate the solutions obtained solving different versions of the problem. Besides the value of the penalty objective function, the solution quality is also evaluated with regards to the number of patients operated and their tardiness. Furthermore, assuming lognormal distribution for the surgery times, we use a set of randomly generated scenarios in order to assess the performance of the proposed solutions in terms of OR utilization rate and number of cancelled patients.

A simulation-based modeling framework to deal with clinical pathways

In this paper we focus our attention on the analysis and management of Clinical Pathways (CPs) in health care systems. From an operational point of view, the CP is “the path” followed by a patient with a given pathology through the health-care system. We start by a global vision and propose a modeling framework based on a discrete event simulation model to identify the critical activities and scarce resources that represent the process bottlenecks both from a patient-centered and facility-centered point of view. Moreover, we face the challenging problem of integrating simulation and optimization in order to put together the capability of the simulation in the scenario analysis (“what-if” analysis) and in describing the dynamics of the system considered and the decisional strength of the optimization, i.e., the “what-best” analysis. The framework is applied to a case study for the thyroid surgical treatment.

Improving surgery department performance via simulation and optimization

The production process inside a hospital surgery department is made up of three distinct main sub-processes: waiting list management, operating theatre planning and scheduling, stay area sizing and organization. Overall department performance depends on how these sub-processes are managed as well as they are integrated. In the literature, they are mainly treated separately recurring to two approaches: optimization or simulation. The complexity of the system often makes the optimization models intractable, whereas simulation seems to be preferred because of its ability to evaluate what if scenarios. The novelty of this paper is to propose an integrated approach to deal with the described issues. The approach is integrated under two points of view: firstly, because it concerns all the three sub-processes together, i.e. from the moment the patient enters the system to the moment it is discharged, and, secondly, because it utilizes both the methods, i.e. simulation and optimization. The proposed holistic integrated approach can be used as a decision support tool to compare alternative operative scenarios by means of a complete set of performance indexes, regarding all the different sub-processes. The framework has been applied to the analysis of a surgical department of a university public hospital sited in Genova (Italy).

Improving the performance of surgery-based clinical pathways: a simulation-optimization approach

This paper aims to improve the performance of clinical processes using clinical pathways (CPs). The specific goal of this research is to develop a decision support tool, based on a simulation-optimization approach, which identify the proper adjustment and alignment of resources to achieve better performance for both the patients and the health-care facility. When multiple perspectives are present in a decision problem, critical issues arise and often require the balancing of goals. In our approach, meeting patients’ clinical needs in a timely manner, and to avoid worsening of clinical conditions, we assess the level of appropriate resources. The simulation-optimization model seeks and evaluates alternative resource configurations aimed at balancing the two main objectives—meeting patient needs and optimal utilization of beds and operating rooms.Using primary data collected at a Department of Surgery of a public hospital located in Genoa, Italy. The simulation-optimization modelling approach in this study has been applied to evaluate the thyroid surgical treatment together with the other surgery-based CPs. The low rate of bed utilization and the long elective waiting lists of the specialty under study indicates that the wards were oversized while the operating room capacity was the bottleneck of the system. The model enables hospital managers determine which objective has to be given priority, as well as the corresponding opportunity costs.