Paolo Landa

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.

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.

Vaccinating Italian infants with a new multicomponent vaccine (Bexsero®) against meningococcal B disease: A cost-effectiveness analysis

ABSTRACT The European Medicines Agency has approved a multicomponent serogroup B meningococcal vaccine (Bexsero®) for use in individuals of 2 months of age and older. A cost-effectiveness analysis (CEA) from the societal and Italian National Health Service perspectives was performed in order to evaluate the impact of vaccinating Italian infants less than 1 y of age with Bexsero®, as opposed to non-vaccination. The analysis was carried out by means of Excel Version 2011 and the TreeAge Pro® software Version 2012. Two basal scenarios that differed in terms of disease incidence (official and estimated data to correct for underreporting) were considered. In the basal scenarios, we considered a primary vaccination cycle with 4 doses (at 2, 4, 6 and 12 months of age) and 1 booster dose at the age of 11 y, the societal perspective and no cost for death. Sensitivity analyses were carried out in which crucial variables were changed over probable ranges. In Italy, on the basis of official data on disease incidence, vaccination with Bexsero® could prevent 82.97 cases and 5.61 deaths in each birth cohort, while these figures proved to be three times higher on considering the estimated incidence. The results of the CEA showed that the Incremental Cost Effectiveness Ratio (ICER) per QALY was €109,762 in the basal scenario if official data on disease incidence are considered and €26,599 if estimated data are considered. The tornado diagram indicated that the most influential factor on ICER was the incidence of disease. The probability of sequelae, the cost of the vaccine and vaccine effectiveness also had an impact. Our results suggest that vaccinating infants in Italy with Bexsero® has the ability to significantly reduce meningococcal disease and, if the probable underestimation of disease incidence is considered, routine vaccination is advisable.

A Discrete Event Simulation model to support bed management

In recent years, due to the overcrowding of Emergency Department (ED) and the growing concern in reducing the number of inpatient ward beds, it has become crucial to improve the capacity planning and control activities, which manage the patient flows from EDs to hospital wards. Bed Management has a key role in this context. This study starts by a collaboration with the Local Health Government (LHG) of the Liguria region aimed at studying the impact of supporting bed management with some operational strategies without increasing the bed capacity. A large amount of data was collected over a one-year period at public hospital in Genova and a preliminary observational analysis was conducted to get the main information about the flow of emergency and elective patients from ED to inpatient wards. A Discrete Event Simulation (DES) model has been then developed in order to represent the real system. A scenarios analysis is proposed to assess the best strategy to improve the system performance without increasing bed capacity, by simply synchronizing bed supply and demand. The model can be used as a decision support tool to optimise the use of the available resources as well as to improve the quality of the patient pathway inside the hospital.

Community-based rehabilitation training after stroke: results of a pilot randomised controlled trial (ReTrain) investigating acceptability and feasibility

Objectives To assess acceptability and feasibility of trial processes and the Rehabilitation Training (ReTrain) intervention including an assessment of intervention fidelity. Design A two-group, assessor-blinded, randomised controlled trial with parallel mixed methods process and economic evaluations. Setting Community settings across two sites in Devon. Participants Eligible participants were: 18 years old or over, with a diagnosis of stroke and with self-reported mobility issues, no contraindications to physical activity, discharged from National Health Service or any other formal rehabilitation programme at least 1 month before, willing to be randomised to either control or ReTrain and attend the training venue, possessing cognitive capacity and communication ability sufficient to participate. Participants were individually randomised (1:1) via a computer-generated randomisation sequence minimised for time since stroke and level of functional disability. Only outcome assessors independent of the research team were blinded to group allocation. Interventions ReTrain comprised (1) an introductory one-to-one session; (2) ten, twice-weekly group classes with up to two trainers and eight clients; (3) a closing one-to-one session, followed by three drop-in sessions over the subsequent 3 months. Participants received a bespoke home-based training programme. All participants received treatment as usual. The control group received an exercise after stroke advice booklet. Outcome measures Candidate primary outcomes included functional mobility and physical activity. Results Forty-five participants were randomised (ReTrain=23; Control=22); data were available from 40 participants at 6 months of follow-up (ReTrain=21; Control=19) and 41 at 9 months of follow-up (ReTrain=21; Control=20). We demonstrated ability to recruit and retain participants. Participants were not burdened by the requirements of the study. We were able to calculate sample estimates for candidate primary outcomes and test procedures for process and health economic evaluations. Conclusions All objectives were fulfilled and indicated that a definitive trial of ReTrain is feasible and acceptable. Trial registration number NCT02429180; Results.

Multiobjective bed management considering emergency and elective patient flows

In recent years, hospitals have increasingly been faced with a growing proportion of their inpatient work coming from the fluctuating and unpredictable demand of emergency admissions. The opportunity to move emergency patients who have been selected for admission out of the emergency department (ED) is linked to the ability of the hospital network to actually admit them. The latter is, in turn, correlated to the availability of inpatient beds in the hospital wards, which are shared resources between elective and emergency patients. Due to the overcrowding of EDs and the growing concern regarding reducing the number of inpatient ward beds, it is thus becoming crucial to improve the bed capacity planning and the management of emergency and elective patient admissions. In this direction, greater coordination and communication among the different healthcare providers involved in the pathway flows is required, and the so-called “bed management” function plays a key role. This study starts with collaboration with the local health government (LHG) of the Liguria region aimed at studying the hospital bed management function. A large quantity of data records have been collected during one year of activity to obtain information related to the flow of emergency and elective patient pathways. A medium-sized hospital located in the city of Genova has been chosen as a case study, and a discrete event simulation model has been developed to reproduce the multiple patient flows involved in the system. Multiobjective optimization analysis has been performed to choose the best bed allocations considering both operational and tactical decisions characterized by various trade-offs among alternative conflicting objectives. The model can be used to help decision makers find a representative set of Pareto-optimal solutions and quantify trade-offs when satisfying different objectives.

Managing Emergent Patient Flow to Inpatient Wards: A Discrete Event Simulation Approach

In recent years, a growing proportion of patients flowing through inpatient hospital wards come from Emergency Departments (EDs). Because of ED overcrowding and the reduction of hospital beds, it is becoming crucial to improve the management of emergent patient flows to be admitted into inpatient wards. This study evaluates the impact and potential of introducing the so-called Bed Management function in a large city’s health district. Thanks to the collaboration with the Local Health Authority of the Liguria region, an observational analysis was conducted based on data collected over a 1-year period to develop a discrete event simulation model. The model has been utilised to evaluate several bed management strategies. Two scenarios at a tactical level, i.e. the opening of a discharge room and blocking elective arrivals, have also been simulated. The effects of such scenarios have been compared with respect to a set of performance metrics, such as waiting times, misallocated patients, trolleys in EDs, and inpatient bed occupancy rates.

System Dynamics Modelling of Emergent and Elective Patient Flows

This paper introduces a tool to assess the impact of organizational strategies that are intended to allocate inpatient beds amongst emergent and elective flows inside a hospital. The tool, based on a System Dynamics model, is able to reproduce the entire system and the relationship between the various flows. In the absence of corrective strategies, an exogenous increase in the rate of arrivals at the Emergency Department (e.g., in winter) can trigger a reinforcing loop increasing elective waits and further overcrowding emergency rooms. The model can be used to discover the best strategies aimed at managing bed capacity between emergent and elective flows. Some preliminary results are given in the context of a public hospital located in Genova (Italy).

Singing for people with aphasia (SPA): a protocol for a pilot randomised controlled trial of a group singing intervention to improve well-being

Introduction The singing for people with aphasia (SPA) intervention aims to improve quality of life and well-being for people with poststroke aphasia. A definitive randomised controlled trial (RCT) is required to assess the clinical and cost effectiveness of SPA. The purpose of this pilot study is to assess the feasibility of such a definitive trial and inform its design. Methods and analysis A two-group, assessor-blinded, randomised controlled external pilot trial with parallel mixed methods process evaluation and economic evaluation. Forty-eight participants discharged from clinical speech and language therapy will be individually randomised 1:1 to SPA (10 group sessions plus a resource booklet) or control (resource booklet only). Outcome assessment at baseline, 3 and 6 months postrandomisation include: ICEpop CAPability measure for adults, Stroke and Aphasia Quality of Life, EQ-5D-5L, modified Reintegration into Normal Living Index, Communication Outcome After Stroke, Very Short Version of the Minnesota Aphasia Test, Service Receipt Inventory and Care Related Quality of Life. Feasibility, acceptability and process outcomes include recruitment and retention rates, with measurement burden and trial experiences being explored in qualitative interviews (15 participants, 2 music facilitators and 2 music champions). Analyses include: descriptive statistics, with 95% CIs where appropriate; qualitative themes; intervention fidelity from videos and session checklists; rehearsal of health economic analysis. Ethics and dissemination NHS National Research Ethics Service and the Health Research Authority confirmed approval in April 2017; recruitment commenced in June 2017. Outputs will include: pilot data to inform whether to proceed to a definitive RCT and support a funding application; finalised intervention manual for multicentre replication of SPA; presentations at conferences, public involvement events; internationally recognised peer reviewed journal publications, open access sources and media releases. Trial registration number NCT03076736.

A Comparative Study for Cost-Utility Analysis Methods: An Application to a Case Study on Multicomponent Vaccine against Meningococcal B Disease.

The aim of this study is to explore and compare the results of application of three different modelling techniques used to perform Cost-utility Analysis in Health Economics and Health Technology Assessment (HTA). The three modelling techniques described are Decision Tree, Markov model and Discrete Event Simulation. For each of these modelling techniques was evaluated the introduction of a multicomponent serogroup B meningococcal vaccine. The preliminary cost-utility analysis herein developed considers societal perspective, and evaluates the impact of vaccination on Italian infants less than one year of age. The models validation and the Incremental Cost-Effectiveness Ratio (ICER) resulting from each technique are reported, in preliminary results each modelling technique gives different ICER, depending on the modelling technique.