A novel framework for predicting patients at risk of readmission

Uncertainty in decision-making for patients’ risk of re-admission arises due to non-uniform data and lack of knowledge in health system variables. The knowledge of the impact of risk factors will provide clinicians better decision-making and in reducing the number of patients admitted to the hospital. Traditional approaches are not capable to account for the uncertain nature of risk of hospital re-admissions. More problems arise due to large amount of uncertain information. Patients can be at high, medium or low risk of re-admission, and these strata have ill-defined boundaries. We believe that our model that adapts fuzzy regression method will start a novel approach to handle uncertain data, uncertain relationships between health system variables and the risk of re-admission. Because of nature of ill-defined boundaries of risk bands, this approach does allow the clinicians to target individuals at boundaries. Targeting individuals at boundaries and providing them proper care may provide some ability to move patients from high risk to low risk band. In developing this algorithm, we aimed to help potential users to assess the patients for various risk score thresholds and avoid readmission of high risk patients with proper interventions. A model for predicting patients at high risk of re-admission will enable interventions to be targeted before costs have been incurred and health status have deteriorated. A risk score cut off level would flag patients and result in net savings where intervention costs are much higher per patient. Preventing hospital re-admissions is important for patients, and our algorithm may also impact hospital income.

Business Process Modelling based on formal temporal theory with an application to hospital patient flows

Existing Workflow Management Systems (WFMSs) follow a pragmatic approach. They often use a proprietary modelling language with an intuitive graphical layout. However the underlying semantics lack a formal foundation. As a consequence, analysis issues, such as proving correctness i.e. soundness and completeness, and reliable execution are not supported at design level. This project will be using an applied ontology approach by formally defining key terms such as process, sub-process, action/task based on formal temporal theory. Current business process modelling (BPM) standards such as Business Process Modelling Notation (BPMN) and Unified Modelling Language (UML) Activity Diagram (AD) model their constructs with no logical basis. This investigation will contribute to the research and industry by providing a framework that will provide grounding for BPM to reason and represent a correct business process (BP). This is missing in the current BPM domain, and may result in reduction of the design costs and avert the burden of redundant terms used by the current standards. A graphical tool will be introduced which will implement the formal ontology defined in the framework. This new tool can be used both as a modelling tool and at the same time will serve the purpose of validating the model. This research will also fill the existing gap by providing a unified graphical representation to represent a BP in a logically consistent manner for the mainstream modelling standards in the fields of business and IT. A case study will be conducted to analyse a catalogue of existing ‘patient pathways’ i.e. processes, of King’s College Hospital NHS Trust including current performance statistics. Following the application of the framework, a mapping will be conducted, and new performance statistics will be collected. A cost/benefits analysis report will be produced comparing the results of the two approaches.

A general framework for Business Process Modelling (BPM) based on Formal Temporal Theory with an application to Hospital Patient flows

Existing Workflow Management Systems (WFMSs) follow a pragmatic approach. They often use a proprietary modelling language with an intuitive graphical layout. However the underlying semantics lack a formal foundation. As a consequence, analysis issues, such as proving correctness i.e. soundness and completeness, and reliable execution are not supported at design level. This project will be using an applied ontology approach by formally defining key terms such as process, sub-process, action/task based on formal temporal theory. Current business process modelling (BPM) standards such as Business Process Modelling Notation (BPMN) and Unified Modelling Language (UML) Activity Diagram (AD) model their constructs with no logical basis. This investigation will contribute to the research and industry by providing a framework that will provide grounding for BPM to reason and represent a correct business process (BP). This is missing in the current BPM domain, and may result in reduction of the design costs and avert the burden of redundant terms used by the current standards. A graphical tool will be introduced which will implement the formal ontology defined in the framework. This new tool can be used both as a modelling tool and at the same time will serve the purpose of validating the model. This research will also fill the existing gap by providing a unified graphical representation to represent a BP in a logically consistent manner for the mainstream modelling standards in the fields of business and IT. A case study will be conducted to analyse a catalogue of existing ‘patient pathways’ i.e. processes, of King’s College Hospital NHS Trust including current performance statistics. Following the application of the framework, a mapping will be conducted, and new performance statistics will be collected. A cost/benefits analysis report will be produced comparing the results of the two approaches.