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

SAFE-FLOW : a systematic approach for safety analysis of clinical workflows

The increasing use of technology in delivering clinical services brings substantial benefits to the healthcare industry. At the same time, it introduces potential new complications to clinical workflows that generate new risks and hazards with the potential to affect patients’ safety. These workflows are safety critical and can have a damaging impact on all the involved parties if they fail.Due to the large number of processes included in the delivery of a clinical service, it can be difficult to determine the individuals or the processes that are responsible for adverse events. Using methodological approaches and automated tools to carry out an analysis of the workflow can help in determining the origins of potential adverse events and consequently help in avoiding preventable errors. There is a scarcity of studies addressing this problem; this was a partial motivation for this thesis.The main aim of the research is to demonstrate the potential value of computer science based dependability approaches to healthcare and in particular, the appropriateness and benefits of these dependability approaches to overall clinical workflows. A particular focus is to show that model-based safety analysis techniques can be usefully applied to such areas and then to evaluate this application.This thesis develops the SAFE-FLOW approach for safety analysis of clinical workflows in order to establish the relevance of such application. SAFE-FLOW detailed steps and guidelines for its application are explained. Then, SAFE-FLOW is applied to a case study and is systematically evaluated. The proposed evaluation design provides a generic evaluation strategy that can be used to evaluate the adoption of safety analysis methods in healthcare.It is concluded that safety of clinical workflows can be significantly improved by performing safety analysis on workflow models. The evaluation results show that SAFE-FLOW is feasible and it has the potential to provide various benefits; it provides a mechanism for a systematic identification of both adverse events and safeguards, which is helpful in terms of identifying the causes of possible adverse events before they happen and can assist in the design of workflows to avoid such occurrences. The clear definition of the workflow including its processes and tasks provides a valuable opportunity for formulation of safety improvement strategies

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

A modular, open-source information extraction framework for identifying clinical concepts and processes of care in clinical narratives

In this thesis, a synthesis is presented of the knowledge models required by clinical informa- tion systems that provide decision support for longitudinal processes of care. Qualitative research techniques and thematic analysis are novelly applied to a systematic review of the literature on the challenges in implementing such systems, leading to the development of an original conceptual framework. The thesis demonstrates how these process-oriented systems make use of a knowledge base derived from workflow models and clinical guidelines, and argues that one of the major barriers to implementation is the need to extract explicit and implicit information from diverse resources in order to construct the knowledge base. Moreover, concepts in both the knowledge base and in the electronic health record (EHR) must be mapped to a common ontological model. However, the majority of clinical guideline information remains in text form, and much of the useful clinical information residing in the EHR resides in the free text fields of progress notes and laboratory reports. In this thesis, it is shown how natural language processing and information extraction techniques provide a means to identify and formalise the knowledge components required by the knowledge base. Original contributions are made in the development of lexico-syntactic patterns and the use of external domain knowledge resources to tackle a variety of information extraction tasks in the clinical domain, such as recognition of clinical concepts, events, temporal relations, term disambiguation and abbreviation expansion. Methods are developed for adapting existing tools and resources in the biomedical domain to the processing of clinical texts, and approaches to improving the scalability of these tools are proposed and evalu- ated. These tools and techniques are then combined in the creation of a novel approach to identifying processes of care in the clinical narrative. It is demonstrated that resolution of coreferential and anaphoric relations as narratively and temporally ordered chains provides a means to extract linked narrative events and processes of care from clinical notes. Coreference performance in discharge summaries and progress notes is largely dependent on correct identification of protagonist chains (patient, clinician, family relation), pronominal resolution, and string matching that takes account of experiencer, temporal, spatial, and anatomical context; whereas for laboratory reports additional, external domain knowledge is required. The types of external knowledge and their effects on system performance are identified and evaluated. Results are compared against existing systems for solving these tasks and are found to improve on them, or to approach the performance of recently reported, state-of-the- art systems. Software artefacts developed in this research have been made available as open-source components within the General Architecture for Text Engineering framework

The remodelling of patient care pathway for e-health

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The interdependencies within the health care system are seldom taken into account prior to implementation of e-health projects, and there tends to be little change management as part of the plan. Our proposal offers a systems analysis model that gives e-health a framework to consider and manage the introduction, changes and outcomes. This research describes the use of a modified Patient Care Pathway as a method to design and implement e-health projects, presenting as a case study the pre-implementation phase of a teleradiology project in rural Thailand. The proposal is that a modified version of Patient Care Pathways can be used as a prospective design model for e-health services. The method adopts systems engineering principles and applies a ―whole systems approach‖ thereby providing a much richer schematic representation of the patient care pathway illustrating both the patient‘s journey through the system and also the information flow. Our method was applied to the design of a new teleradiology service that was to be established in Thailand, to connect GP‘s in a rural hospital to the radiology department in a tertiary hospital with a further connection to a specialist radiologist in a medical school in Bangkok. By comparing the pre-implementation Patient Care Pathway with the proposed pathway using the teleradiology, a systems analysis model was developed to identify critical points in the system and identify and anticipate how the system would support the changes in clinical practices. The method produced a valuable framework to better understand and thereby manage the implications of change prior to implementation of an e-health project

A service oriented architecture to implement clinical guidelines for evidence-based medical practice

Health information technology (HIT) has been identified as the fundamental driver to streamline the healthcare delivery processes to improve care quality and reduce operational costs. Of the many facets of HIT is Clinical Decision Support (CDS) which provides the physician with patient-specific inferences, intelligently filtered and organized, at appropriate times. This research has been conducted to develop an agile solution to Clinical Decision Support at the point of care in a healthcare setting as a potential solution to the challenges of interoperability and the complexity of possible solutions. The capabilities of Business Process Management (BPM) and Workflow Management systems are leveraged to support a Service Oriented Architecture development approach for ensuring evidence based medical practice. The aim of this study is to present an architecture solution that is based on SOA principles and embeds clinical guidelines within a healthcare setting. Since the solution is designed to implement real life healthcare scenarios, it essentially supports evidence-based clinical guidelines that are liable to change over a period of time. The thesis is divided into four parts. The first part consists of an Introduction to the study and a background to existing approaches for development and integration of Clinical Decision Support Systems. The second part focuses on the development of a Clinical Decision Support Framework based on Service Oriented Architecture. The CDS Framework is composed of standards based open source technologies including JBoss SwitchYard (enterprise service bus), rule-based CDS enabled by JBoss Drools, process modelling using Business Process Modelling and Notation. To ensure interoperability among various components, healthcare standards by HL7 and OMG are implemented. The third part provides implementation of this CDS Framework in healthcare scenarios. Two scenarios are concerned with the medical practice for diagnosis and early intervention (Chronic Obstructive Pulmonary Disease and Lung Cancer), one case study for Genetic data enablement of CDS systems (New born screening for Cystic Fibrosis) and the last case study is about using BPM techniques for managing healthcare organizational perspectives including human interaction with automated clinical workflows. The last part concludes the research with contributions in design and architecture of CDS systems. This thesis has primarily adopted the Design Science Research Methodology for Information Systems. Additionally, Business Process Management Life Cycle, Agile Business Rules Development methodology and Pattern-Based Cycle for E-Workflow Design for individual case studies are used. Using evidence-based clinical guidelines published by UK’s National Institute of Health and Care Excellence, the integration of latest research in clinical practice has been employed in the automated workflows. The case studies implemented using the CDS Framework are evaluated against implementation requirements, conformance to SOA principles and response time using load testing strategy. For a healthcare organization to achieve its strategic goals in administrative and clinical practice, this research has provided a standards based integration solution in the field of clinical decision support. A SOA based CDS can serve as a potential solution to complexities in IT interventions as the core data and business logic functions are loosely coupled from the presentation. Additionally, the results of this this research can serve as an exemplar for other industrial domains requiring rapid response to evolving business processes

Modeling Business Process Variability

This master thesis presents research findings on business process variability modeling. Its main goal is to analyze inherent problems of business process variability and solve them simply, innovatively and effectively. To achieve this goal, process variability is defined by analyzing scientific literature, its main problems identified and is illustrated using a healthcare running example: process variability is classified into process variability within the domain space and over time. These two forms of process variability respectively lead to process variability modeling and process model evolution problems. After defining the main problems inherent to process variability, the focus of this research project is defined: solving process variability modeling problems. First current business process modeling languages are evaluated to assess the effectiveness of their respective modeling concepts when modeling process variability, using a newly created set of evaluation criteria and the healthcare running example. The following business process modeling languages are evaluated: Event driven process chains (EPC), the Business Process Modeling Notation (BPMN) and Configurable EPC (C-EPC). Business process variability modeling and Software product line engineering have similar problems. Therefore the variability modeling concepts developed by software product line engineering are analyzed. Feature diagrams and software configuration management are the main variability management concepts provided by software product line engineering. To apply these variability management concepts to model process variability meant combining them with existing business modeling languages. Riebisch feature diagrams are combined with C-EPC to form Feature-EPC. Applying software configuration management, meant merging Change Oriented Versioning with basic EPC to create COV-EPC, and merging the Proteus Configuration Language with basic EPC to design PCL-EPC. Finally these newly created business process modeling languages are also evaluated using the newly designed evaluation criteria and the healthcare running example. EPC or BPMN are not suited to model business process variability within the domain space. C-EPC provide explicit means to model business process variability, however the process models tend to get big very fast. Furthermore the syntax, the contextual constraints and the semantics of the configuration requirements and guidelines used to configure the C-EPC process models are unclear. Feature-EPC improve C-EPC with domain modeling capability and clearly defined configuration rules: their syntax, contextual constraints and semantics have been clearly defined using a context free grammar in Backus-Naur form. Furthermore, consistent combinations of features and configuration rules are ensured using respectively constraints and a conflict resolution algorithm. However, Feature-EPC and C-EPC suffer from the same weakness: large configurable process models. In COV-EPC and PCL-EPC the problem of large configurable process models is solved. COV-EPC ensures consistent combinations of options and configuration rules using respectively validities and a conflict resolution algorithm. PCL-EPC guarantees consistent combinations of process fragments by means of a PCL specification

Ensuring patients privacy in a cryptographic-based-electronic health records using bio-cryptography

Several recent works have proposed and implemented cryptography as a means to preserve privacy and security of patients health data. Nevertheless, the weakest point of electronic health record (EHR) systems that relied on these cryptographic schemes is key management. Thus, this paper presents the development of privacy and security system for cryptography-based-EHR by taking advantage of the uniqueness of fingerprint and iris characteristic features to secure cryptographic keys in a bio-cryptography framework. The results of the system evaluation showed significant improvements in terms of time efficiency of this approach to cryptographic-based-EHR. Both the fuzzy vault and fuzzy commitment demonstrated false acceptance rate (FAR) of 0%, which reduces the likelihood of imposters gaining successful access to the keys protecting patients protected health information. This result also justifies the feasibility of implementing fuzzy key binding scheme in real applications, especially fuzzy vault which demonstrated a better performance during key reconstruction