Healthcare Process Support: Achievements, Challenges, Current Research

Healthcare organizations are facing the challenge of delivering high-quality services to their patients at affordable costs. To tackle this challenge, the Medical Informatics community targets at formalisms for developing decision-support systems (DSSs) based on clinical guidelines. At the same time, business process management (BPM) enables IT support for healthcare processes, e.g., based on workflow technology. By integrating aspects from these two fields, promising perspectives for achieving better healthcare process support arise. The perspectives and limitations of IT support for healthcare processes provided the focus of three Workshops on Process-oriented Information Systems (ProHealth). These were held in conjunction with the International Conference on Business Process Management in 2007-2009. The ProHealth workshops provided a forum wherein challenges, paradigms, and tools for optimized process support in healthcare were debated. Following the success of these workshops, this special issue on process support in healthcare provides extended papers by research groups who contributed multiple times to the ProHealth workshop series. These works address issues pertaining to healthcare process modeling, process-aware healthcare information system, workflow management in healthcare, IT support for guideline implementation and medical decision support, flexibility in healthcare processes, process interoperability in healthcare and healthcare standards, clinical semantics of healthcare processes, healthcare process patterns, best practices for designing healthcare processes, and healthcare process validation, verification, and evaluation

Performance Analysis of Emergency Room Episodes Through Process Mining

The performance analysis of Emergency Room episodes is aimed at providing decision makers with knowledge that allows them to decrease waiting times, reduce patient congestion, and improve the quality of care provided. In this case study, Process Mining is used to determine which activities, sub-processes, interactions, and characteristics of episodes explain why some episodes have a longer duration. The employed method and the results obtained are described in detail to serve as a guide for future performance analysis in this domain. It was discovered that the main cause of the increment in the episode duration is the occurrence of a loop between the Examination and Treatment sub-processes. It was also found out that as the episode severity increases, the number of repetitions of the Examination–Treatment loop increases as well. Moreover, the episodes in which this loop is more common are those that lead to Hospitalization as discharge destination. These findings might help to reduce the occurrence of this loop, in turn lowering the episode duration and, consequently, providing faster attention to more patients

Process-aware information system development for the healthcare domain : consistency, reliability and effectiveness

Optimal support for complex healthcare processes cannot be provided by a single out-of-the-box Process-Aware Information System and necessitates the construction of customized applications based on these systems. In order to allow for the seamless integration of the new technology into the existing operational processes of a healthcare organization, ensuring the correct operation and reliability of the developed system are of the utmost importance. This paper proposes an approach in which the same model is used for specifying, developing, testing and validating the operational performance of a new system. The benefits of using the same model for different purposes are decreased potential for loss of user requirements and increased confidence in reliability and correct operation of the resultant system before its deployment. This approach has been applied to a schedule-based workflow system developed for the AMC hospital in Amsterdam

Process-aware information system development for the healthcare domain : consistency, reliability and effectiveness

Optimal support for complex healthcare processes cannot be provided by a single out-of-the-box Process-Aware Information System and necessitates the construction of customized applications based on these systems. In order to allow for the seamless integration of the new technology into the existing operational processes of a healthcare organization, ensuring the correct operation and reliability of the developed system are of the utmost importance. This paper proposes an approach in which the same model is used for specifying, developing, testing and validating the operational performance of a new system. The benefits of using the same model for different purposes are decreased potential for loss of user requirements and increased confidence in reliability and correct operation of the resultant system before its deployment. This approach has been applied to a schedule-based workflow system developed for the AMC hospital in Amsterdam

Adaptive Time- and Process-Aware Information Systems

For the digitized enterprise the proper handling of the temporal aspects of its business processes is vital. Delivery times, appointments and deadlines must be met, processing times and durations be monitored, and optimization objectives shall be pursued. However, contemporary Process-Aware Information Systems (PAISs)--the go-to solution for the computer-aided support of business processes—still lack a sophisticated support of the time perspective. Hence, there is a high demand for a more profound support of temporal aspects in PAISs. Accordingly, both the specification and the operational support of temporal aspects constitute fundamental challenges for the further development and dissemination of PAISs. The aim of this thesis is to propose a framework for supporting the time perspective of business processes in PAISs. As PAISs enable the design, execution and evolution of business processes, the designated framework must support these three fundamental phases of the process life cycle. The ATAPIS framework proposed by this thesis essentially comprises three major com-ponents. First, a universal and comprehensive set of time patterns is provided. Respective time patterns represent temporal concepts commonly found in business processes and are based on empirical evidence. In particular, they provide a universal and comprehensive set of notions for describing temporal aspects in business processes. Moreover, a precise formal semantics for each of the time patterns is provided based on an in-depth analysis of a large set of real-world use cases. Respective formal semantics enable the proper integration of the time patterns into PAISs. In turn, the latter will allow for the specification of time-aware process schemas. Second, a generic framework for implementing the time patterns based on their formal semantics is developed. The framework and its techniques enable the verification of time-aware process schemas regarding their temporal consistency, i. e., their ability to be successfully executed without violating any of their temporal constraints. Subsequently, the framework is extended to consider advanced aspects like the contingent nature of activity durations and alternative execution paths as well. Moreover, an algorithm as well as techniques for executing and monitoring time-aware process instances in PAISs is provided. Based on the presented concepts, it becomes possible to ensure that a time-aware process instance may be executed without violating any of its temporal constraints. Third, a set of change operations for dynamically modifying time-aware process instances during run time is suggested. Respective change operations ensure that a modified time-aware process instance remains temporally consistent after the respective modification. Moreover, to reduce the complexity involved when applying multiple change operations a sophisticated approximation-based technique is presented. Overall, the developed change operations allow providing the flexibility required by business processes in practice. Altogether, the ATAPIS framework provides fundamental concepts, techniques and algorithms for integrating the time perspective into PAISs. As beauty of this framework the specification, execution and evolution of business processes is supported by an integrated approach

Exploring the use of routine healthcare data through process mining to inform the management of musculoskeletal diseases

Healthcare informatics can help address some of the challenges faced by both healthcare providers and patients. The medical domain is characterised by inherently complex and intricate issues, data can often be of poor quality and novel techniques are required. Process mining is a discipline that uses techniques to extract insights from event data, generated during the execution of processes. It has had good results in various branches of medical science but applications to musculoskeletal diseases remain largely unexplored. This research commenced with a review of the healthcare and technical literature and applied a variety of process mining techniques in order to investigate approaches to the healthcare plans of patients with musculoskeletal conditions. The analysis involved three datasets from: 1) a private hospital in Boston, US, where data was used to create disease trajectory models. Results suggest the method may be of interest to healthcare researchers, as it enables a more rapid modelling and visualisation; 2) a mobile healthcare application for patients receiving physiotherapy in Sheffield, UK, where data was used to identify possible indicators for health outcomes. After evaluation of the results, it was found that the indicators identified may be down to chance; and 3) the population of Wales to explore knee pain surgery pathways. Results suggest that process mining is an effective technique. This work demonstrates how routine healthcare data can be analysed using process mining techniques to provide insights that may benefit patients suffering with musculoskeletal conditions. This thesis explores how strict criteria for analysis can be performed. The work is intended to expand the breadth of process mining methods available to the data science community and has contributed by making recommendations for service utilisation within physiotherapy at Sheffield Hospital and helped to define a roadmap for a leading healthcare software company