Automated generation of patient-tailored electronic care pathways by translating computer-interpretable guidelines into hierarchical task networks

Abstract

Objective: This paper describes a methodology which enables computer-aided support for the planning, visualization and execution of personalized patient treatments in a specific healthcare process, taking into account complex temporal constraints and the allocation of institutional resources. To this end, a translation from a time-annotated computerinterpretable guideline (CIG) model of a clinical protocol into a temporal hierarchical task network (HTN) planning domain is presented.Methods and Material: The proposed method uses a knowledge-driven reasoning process to translate knowledge previously described in a CIG into a corresponding HTN Planning and Scheduling domain, taking advantage of HTNs known ability to i) dynamically cope with temporal and resource constraints, and ii) automatically generate customized plans. The proposed method, focusing on the representation of temporal knowledge and based on the identification of workflow and temporal patterns in a CIG, makes it possible to automatically generate time-annotated and resource-based care pathways tailored to the needs of any possible patient profile.Results: The proposed translation is illustrated through a case study based on a 70 pages long clinical protocol to manage Hodgkin's disease, developed by the Spanish Society of Pediatric Oncology. We show that an HTN planning domain can be generated from the corresponding specification of the protocol in the Asbru language, providing a running example of this translation. Furthermore, the correctness of the translation is checked and also the management of ten di↵erent types of temporal patterns represented in the protocol. By interpreting the automatically generated domain with a state-of-art HTN planner, a time-annotated care pathway is automatically obtained, customized for the patient's and institutional needs. The generated care pathway can then be used by clinicians to plan and manage the patients long-term care.Conclusion: The described methodology makes it possible to automatically generate patient-tailored care pathways, leveraging an incremental knowledge-driven engineering process that starts from the expert knowledge of medical professionals. The presented approach makes the most of the strengths inherent in both CIG languages and HTN planning and scheduling techniques: for the former, knowledge acquisition and representation of the original clinical protocol, and for the latter, knowledge reasoning capabilities and an ability to deal with complex temporal and resource constraints. Moreover, the proposed approach provides immediate access to technologies such as business process management (BPM) tools, which are increasingly being used to support healthcare processes.

Knowledge-Driven Adaptive Execution of Care Pathways Based on Continuous Planning Techniques

“…Moreover, information about already performed care tasks is also embedded in the VMR, to avoid their repetition when adapting a pathway, as we will see next. The extraction of a patienttailored Care Pathway from these elements following an HTN planning process has already been explained in previous works [6,7]. In this sense, our work extends that approach with adaptive execution capabilities.…”

“…Previous works of our group shows that HTN planning is an enabling technology for the representation of clinical guidelines and the generation of treatment plans [6], and also how Computer Interpretable Guidelines (CIGs) can be translated into HTN planning domains so patient-tailored care pathways can be extracted from them [7]. The work here presented adds adaptive execution capabilities for the care pathways.…”

“…Though we set the focus on the execution of care pathways, there are common points because of the guideline adherence of the patient-tailored care pathways here treated. In this sense, our approach has all the elements needed to encode a guideline [6,7] and adds execution capabilities to care pathways that adhere to so-encoded guidelines.…”

“…The dynamic generation of patient-tailored care pathways is based on a knowledge-driven, temporal hierarchical planning process described in [6,7]. This planning process receives as inputs the expert knowledge model which encodes guideline recommendations, a starting date for the pathway and context data accomplishing the UML specification of the context model.…”

“…This process takes as inputs both an HTN-based formal representation of a clinical guideline and data extracted from a Virtual Medical Record (VMR) which includes patient and resource information. This HTN formalism has already been proved to be an enabling technology for representing clinical guidelines and generating patient-tailored care pathways from them [6,7]. It takes into account the specific patient features and observation values for generating a patient-centric and individualized care pathway, which is one of the challenges to be confronted in the Healthcare area since each patient constitutes an unique case [2].…”