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This paper presents an approach to monitor healthcare workflows us-ing a logic-based formal method. We introduce a monitoring architecture with workflows and knowledge bases, and propose a logical language, FO-LTL-K, to express temporal and knowledge properties to be monitored. We formalize some of the norms for palliative care using the proposed l...
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... propose a monitoring architecture to check whether the actual healthcare prac- tice meets these norms. It has the following four components (Fig. 2): (1) a Workflow Management System (WfMS) which defines, creates and manages the execution of workflows through the use of a workflow engine able to interpret the process defini- tion and interact with workflow participants; (2) a Data Management System (DMS) which stores and retrieves the information that is produced by the execution ...
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Citations
... Ruan et al. [19], [20] specify an agent-based alarm system as properties in logic, verified against formally modeled palliative care therapeutics. They created their agent-based alarms using a subset of detailed palliative workflows, checked against norms set by palliative care providers using first order LTL based modeled checker [19]. ...
... Ruan et al. [19], [20] specify an agent-based alarm system as properties in logic, verified against formally modeled palliative care therapeutics. They created their agent-based alarms using a subset of detailed palliative workflows, checked against norms set by palliative care providers using first order LTL based modeled checker [19]. Our work captures much more than a subset of blood bank workflow; it details the vein-to-vein processes. ...
The need for transfusion blood increases each year. The Food and Drug Administration (FDA), the American Association of Blood Banks (AABB) and standardization bodies that hold jurisdiction in other countries continuously update blood transfusion safety mandates. Verifying blood bank processes for safety takes labor and time. We automate this verification process by modeling the workflows of the blood processing supply chain, extracting FDA and AABB requirements as Temporal Logic formulas and verifying that the workflows comply with the mandates. We also show how this process can seamlessly integrate into an Electronic Medical Record System.
... In [34] Ruan and MacCaull present an approach to monitor healthcare workflows using a logic-based formal method. To specify the system the authors have presented FO-LTL-K a logic fusion of first order LTL and description logic. ...
Recent efforts towards the Semantic Web have resulted in powerful languages such as Semantic Web Rule Language (SWRL) based on OWL-DL and RuleML. Rule languages and inference engines incorporate reasoning capabilities to Semantic Web application systems. In this paper we present an approach for the design and specification of ontology-driven multi-agent rule-based systems. We use the Maude rewriting system and its Linear Temporal Logic (LTL) model checking tool to verify response time guarantees for the target systems. We present TOVRBA, an extended version of a verification tool developed by the first author, for ontology-driven multi-agent rule-based systems which allows the designer to specify information about agents' interactions, behavior, and execution strategies at different levels of abstraction. TOVRBA generates an encoding of the system for the Maude LTL model checker, allowing properties of the system to be verified. We illustrate the use of the framework on a simple healthcare system.
... As this care delivery information can be recorded by the caregiver agents, the monitoring agent can check whether the actual healthcare practice meets the norms of practice and remind the healthcare provider(s) when necessary. We plan to use the logic-based framework that we proposed in [10] to monitor above-mentioned information. The ideas are, in brief, (1) to build linear-time models of the health status and care delivery information, then (2) to express the specifications to be monitored in the logical language we proposed, called FO-LTL-K, which is a combination of a first-order linear temporal language and a description logic language, (3) to use the monitoring agent to check whether the specifications hold in the models; the results of the checking are then used to generate reminders and alerts. ...
... We have studied the model checking complexity and algorithm in [10]. • to realize agent-based scheduling. ...
In this paper, we propose the use of an agent-based architecture to enhance workflow system capacity to support interprofessional, patient-centred palliative care delivery. This paper outlines the concept of palliative care and describes how agents can be used to assist care providers to address the needs of the patient and family. Our architecture is illustrated in a diagram and the agents are described in terms of the services they provide, and the dependencies among them. The dependencies determine the information flow, which facilitates the communication and collaboration among the patient and care providers.
In this paper, we propose the use of an agent-based architecture to enhance workflow system capacity to support interprofessional, patient-centred palliative care delivery. This paper outlines the concept of palliative care and describes how agents can be used to assist care providers to address the needs of the patient and family. Agents are described in terms of the services they provide, and the dependencies among them (which determine the information flow, facilitating the communication and collaboration among the patient and care providers). We present how this architecture integrates with a healthcare workflow system and discuss the issues of work assignment, scheduling and monitoring. © 2011 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.
Healthcare workflows (careflows) involve complex, distributive processes with a high degree of variability. There are ubiquitous communication and enormous data and knowledge management requirements and the processes involve complex timing requirements, and are safety critical. Designing these processes and managing their performance is difficult and error-prone. Using verification techniques such as model checking, which are mathematical methods of proving correctness, we can reduce errors by ensuring that process designs satisfy their specifications. We describe a prototype next generation multithreaded model checker to reason about processes in careflows, sensitive to patient preferences and the goals of the careteam using a timed temporal logic extended with modalities of beliefs, desires, and intentions. Copyright © 2011 John Wiley & Sons, Ltd.
