Patient wait times and care service times are key performance measures for care processes in hospitals. Managing the quality of care delivered by these processes in real-time is challenging. A key challenge is to correlate source medical events to infer the care process states that define patient wait times and care service times. Commercially available complex event processing engines do not have built in support for the concept of care process state. This makes it unnecessarily complex to define and maintain rules for inferring states from source medical events in a care process. Another challenge is how to present the data in a real-time BI dashboard and the underlying data model to use to support this BI dashboard. Data representation architecture can potentially lead to delays in processing and presenting the data in the BI dashboard. In this research, we have investigated the problem of real-time monitoring of care processes, performed a gap analysis of current information system support for it, researched and assessed available technologies, and shown how to most effectively leverage event driven and BI architectures when building information support for real-time monitoring of care processes. We introduce a state monitoring engine for inferring and managing states based on an application model for care process monitoring. A BI architecture is also leveraged for the data model to support the real-time data processing and reporting requirements of the application’s portal. The research is validated with a case study to create a real-time care process monitoring application for an Acute Coronary Syndrome (ACS) clinical pathway in collaboration with IBM and Osler hospital. The research methodology is based on design-oriented research.

Patient wait times and care service times are key performance measures for care processes in hospitals. Managing the quality of care delivered by these processes in real-time is challenging. A key challenge is to correlate source medical events to infer the care process states that define patient wait times and care service times. Commercially available complex event processing engines do not have built in support for the concept of care process state. This makes it unnecessarily complex to define and maintain rules for inferring states from source medical events in a care process. Another challenge is how to present the data in a real-time BI dashboard and the underlying data model to use to support this BI dashboard. Data representation architecture can potentially lead to delays in processing and presenting the data in the BI dashboard. In this research, we have investigated the problem of real-time monitoring of care processes, performed a gap analysis of current information system support for it, researched and assessed available technologies, and shown how to most effectively leverage event driven and BI architectures when building information support for real-time monitoring of care processes. We introduce a state monitoring engine for inferring and managing states based on an application model for care process monitoring. A BI architecture is also leveraged for the data model to support the real-time data processing and reporting requirements of the application’s portal. The research is validated with a case study to create a real-time care process monitoring application for an Acute Coronary Syndrome (ACS) clinical pathway in collaboration with IBM and Osler hospital. The research methodology is based on design-oriented research.

Reporting patient states is considered an important part of care process monitoring in the hospital to efficiently monitor how well the health care system is performing. Monitoring care processes with enough fine-grained detail to precisely track wait states and service states in order to reduce wait times and improve their quality of care are challenging. Business Process Management (BPM) technology is used to bring care processes online, but there is no clear methodology on how to integrate performance management into BPM tools in a systematic matter that is effective, and minimizes complications and development costs. This thesis proposes a BPM methodology for care process monitoring that structures how to integrate performance monitoring into BPM. The major contribution of this thesis includes a generic methodology for care processes monitoring that describes how to structure and instrument a business process model for systematic care process monitoring which includes support for handoff points between organizations where many wait-time bottlenecks occur. It also includes a prototype implementation based on an existing case study based on a real cardiology care process from an Ontario hospital. Our results are evaluated using three different prototypes based on this same care process. The research methodology for the thesis is based on Design-Science research.

Care process monitoring is important in healthcare domains to provide precise and detailed analytics on patients, providers, and resources participating in a care process and their status. These analytics are used to keep track of whether the quality of care goals set by healthcare organizations are satisfied and ensure that legislative and organizational guidelines are followed. The complexity of care process monitoring can vary depending on whether the care process takes place in a hospital or out in the community, and it can vary depending on the complexity of the information technology infrastructure that is in place to support the care process. A Care Process Monitoring Application (CPMA) is a software application which collects and integrates data from various sources while a care process is being provided, in order to provide performance reporting of metrics that are used to measure how well the performance goals and guidelines for the care process are being met. In our research, we have studied how CPMAs are built in order to improve the quality of their engineering. The significant challenge in this context is how to engineer a CPMA so that the engineering process is repeatable, produces a CPMA of consistent high quality, and requires less time, less effort and less complexity. This thesis proposes an application framework for care process monitoring that collects and integrates events from event sources, maintains the individual and aggregate states of the care process and populates a metrics data mart to support performance reporting. Our contributions are the following: a state-based application meta-model of care process monitoring, a care process monitoring architectural pattern, and finally, a behavior driven development methodology for CPMAs based on our meta-model and architectural pattern. Our results are validated through three different case studies in which we collaborated with two different health care organizations to build and deploy CPMAs for two different care processes (one hospital-based, the other community-based) in collaboration with healthcare clinicians and researchers.

Care process monitoring is important in healthcare domains to provide precise and detailed analytics on patients, providers, and resources participating in a care process and their status. These analytics are used to keep track of whether the quality of care goals set by healthcare organizations are satisfied and ensure that legislative and organizational guidelines are followed. The complexity of care process monitoring can vary depending on whether the care process takes place in a hospital or out in the community, and it can vary depending on the complexity of the information technology infrastructure that is in place to support the care process. A Care Process Monitoring Application (CPMA) is a software application which collects and integrates data from various sources while a care process is being provided, in order to provide performance reporting of metrics that are used to measure how well the performance goals and guidelines for the care process are being met. In our research, we have studied how CPMAs are built in order to improve the quality of their engineering. The significant challenge in this context is how to engineer a CPMA so that the engineering process is repeatable, produces a CPMA of consistent high quality, and requires less time, less effort and less complexity. This thesis proposes an application framework for care process monitoring that collects and integrates events from event sources, maintains the individual and aggregate states of the care process and populates a metrics data mart to support performance reporting. Our contributions are the following: a state-based application meta-model of care process monitoring, a care process monitoring architectural pattern, and finally, a behavior driven development methodology for CPMAs based on our meta-model and architectural pattern. Our results are validated through three different case studies in which we collaborated with two different health care organizations to build and deploy CPMAs for two different care processes (one hospital-based, the other community-based) in collaboration with healthcare clinicians and researchers.