Unwarranted variations modelling and analysis of healthcare services based on heterogeneous service data

There is a growing demand worldwide to increase the quality and productivity of healthcare services thereby increasing the value of the healthcare services delivered. To deal with these demands, increasingly importance is being placed on analysing and reducing unwarranted variations in healthcare services to achieve significant savings in healthcare expenditure. Unwarranted variations are defined as the variations in the utilisation of healthcare services that cannot be explained by variation in patient illness or patient preferences. Current modelling and simulation approaches for healthcare service efficiency and effectiveness improvements in hospitals do not utilise multiple types of heterogeneous service data such as qualitative information about hospital services and quantitative data such as historic system data, electronic patient records (EPR), and real time tracking data for analysing unwarranted variations in hospital. Consequently, due to the presence of large amount of unwarranted variations in the service delivery systems, service improvement efforts are often inadequate or ineffective. Therefore, there is urgent need to: (i) accurately and efficiently model complex care delivery services provided in hospital; (ii) develop integrated simulation model to analyse unwarranted variations on a care pathway of a hospitals; and, (iii) develop analytical and simulation models to analyse unwarranted variations from a care pathway. Current process modelling methods to represent healthcare services rely on simplified flowchart of patient flow obtained based on on-site observations and clinician workshops. However, gathering and documenting qualitative data from workshops is challenging. Furthermore, resulting models are insufficient in modelling important service interactions and hence the resulting models are often inaccurate. Therefore, a detailed and accurate process modelling methodology is proposed together with a systematic knowledge acquisition approach based on staff interviews. Traditional simulation models utilised simplified flow diagrams as an input together with the historic system data for analysing unwarranted variations on a care pathway. The resulting simulation models are often incomplete leading to oversimplified outputs from the conducted simulations. Therefore, an integrated simulation modelling approach is presented together with the capability to systematically use heterogeneous data to analyse unwarranted variations on service delivery process of a hospital. Maintaining and using care services pathway within hospitals to provide complex care to patients have challenges related to unwarranted variations from a care pathway. These variations from care pathway predominantly occur due ineffective decision making processes, unclear process steps, their interactions, conflicting performance measures for speciality units, and availability of resources. These variations from care pathway are largely unnecessary and lead to longer waiting times, delays, and lower productivity of care pathways. Therefore, methodologies for analysing unwarranted variations from a care pathway such as: (i) system variations (decision makers (roles) and decision making process); (ii) patient variations (patient diversion from care pathway); are discussed in this thesis. A system variations modelling methodology to model system variations in radiology based on real time tracking data is proposed. The methodology employs generalised concepts from graph theory to identify and represent system variations. In particular, edge coloured directed multi-graphs (ECDMs) are used to model system variations which are reflected in paths adopted by staff, i.e., sequence of rooms/areas traversed while delivering services. A pathway variations analysis (PVA) methodology is proposed which simulates patient diversions from the care pathway by modelling hospital operational parameters, assessing the accuracy of clinical decisions, and performance measures of speciality units involved in care pathway to suggest set-based solutions for reducing variations from care pathway. PVA employs the detailed service model of care pathway together with the electronic patient records (EPRs) and historic data. The main steps of the methodology are: (i) generate sample of patients for analysis; (ii) simulate patient diversions from care pathway; and, (iii) simulation analysis to suggest set-based solutions. The aforementioned unwarranted variations analysis approaches have been applied to Magnetic Resonance (MR) scanning process of radiology and stroke care pathway of a large UK hospital as a case study. Proposed improvement options contributed to achieve the performance target of stroke services

Simulation-based evaluation of an integrated planning and scheduling algorithm for maintenance projects

The field of maintenance project planning and scheduling is attracting increasing attention due to ever growing competition among manufacturing organisations. There is a lack of studies that has tackled all the aspects of maintenance project implementation such as costs, resources, down times, uncertainties, operational constraints, among others. Therefore, an approach which uses a unitary structuring method and discrete event simulation to integrate relevant data about the maintenance projects is proposed. The results of the evaluation, on a case from paper-pulp industry, have shown that the proposed approach is able to overcome most of the issues of maintenance planning and scheduling

Role activity diagram-based discrete event simulation model for healthcare service delivery processes

In case of healthcare systems, discrete event simulations are useful techniques to identify problematic process issues. However, currently available simulation models often use a simplified flow chart as an input which represents patient flow obtained from on on-site observations and interviews complemented with historic patient data. This is insufficient in modelling important interactions between clinical staff, equipment and patients causing the resultant models to be incomplete and unrealistic. This in turn leads to oversimplified outputs from any simulations. This paper presents a systematic methodology for the development of discrete event simulation model from process mapping model based on the Role Activity Diagram (RAD) notations. RAD allows complex collaborative healthcare service delivery processes to be modelled as roles, interactions, actions, and decision questions. The workflow simulation modelling methodology based on RADs includes: (i) development of RAD model of the service delivery process; (ii) data model for RAD based service delivery process; (iii) developing DES model based on RAD; and, (iv) adding dynamic attributes and validating DES model. The methodology is demonstrated through a case study of magnetic resonance (MR) scanning process of radiology department in a large hospital

Big data analytics and application for logistics and supply chain management

This special issue explores big data analytics and applications for logistics and supply chain management by examining novel methods, practices, and opportunities. The articles present and analyse a variety of opportunities to improve big data analytics and applications for logistics and supply chain management, such as those through exploring technology-driven tracking strategies, financial performance relations with data driven supply chains, and implementation issues and supply chain capability maturity with big data. This editorial note summarizes the discussions on the big data attributes, on effective practices for implementation, and on evaluation and implementation methods

Introducing algorithm portfolios to a class of vehicle routing and scheduling problem

The paper presents a comprehensive foundation and implementation of Algorithm Portfolios to solve Theater Distribution Vehicle Routing and Scheduling Problems (TDVRSP). In order to evaluate the performance of proposed approach, it has been applied to varying dimensions of theater distribution problem. In particular, eight random search metaheuristics embedded in four processors, packed to form different portfolios. Four basic algorithms- Genetic Algorithm (GA), Simulated Annealing (SA), Tabu Search (TS) and Artificial Immune System (AIS), as well as their group theoretic counterparts have been utilized. The proposed approach also takes care of platform dependence and helps evolving a robust solution pack. The portfolio concept is shown to be computationally advantageous and qualitatively competitive over the benchmark set of problems. The paper does not only provide modeling to TDVRSP, but also aids in developing a generic solution framework for other problems of its kind

MRI Evaluation of Carotid Cavernous Fistula – A Case Report

A carotid cavernous fistula is a rare condition and often difficult to diagnose. We herewith present a case of a female patient who presented with minimal proptosis in the right eye and occipital headache. Magnetic resonance imaging showed classical findings like arterialization of ophthalmic veins and tortuous prominent cavernous sinuses on right side. In such situations, magnetic resonance venography (MRV) plays a major role in the diagnosis and may reveal any cerebral thrombosis. We will be discussing the types of CCF and the MRV findings which help in the diagnosis as well as treatment planning

Malignant meningioma with intra- and extra-cranial extension: A case report

Meningioma is the most common intracranial benign neoplasm. The malignant transformation of this neoplasm is less frequent. Here, we report the case of a 77-year-old male patient who came to our department with a visible mass in the scalp for 1½ years. The mass was gradually increasing in size, soft in nature, not painful, and associated with the left-sided weakness. His multidetector computed tomography showed lesion which is having an intracranial component with the destruction of a vault with extracranial extension. This imaging modality gives a clear-cut picture of the extent of the lesion, nearby structures, and vascularity to give the surgeon proper guidance in two, three, and four dimensions

A rare neglected case of large leptomeningeal cyst: A case report

Leptomeningeal cysts are enlarging skull fractures that occur near post-traumatic encephalomalacia. The term cyst is usually a misnomer as it is not only a cyst but also an extension of encephalomalacia. They commonly occur after severe head trauma during the first 3 years of life (especially infancy) and almost never after 8 years of life. Herewith, we present a case of a 7-year-old female patient who presented to our hospital with left-sided weakness since 2 years and painless swelling over the scalp since 3 years giving past history of head trauma. Plain radiography, computed tomography, and magnetic resonance imaging were performed which showed classical findings of leptomeningeal cyst. We will be discussing about the causes and radiological findings which help in diagnosis as well as treatment planning