Temporal similarity measures for querying clinical workflows

Combi, Carlo; Gozzi, Matteo; Oliboni, Barbara; Juárez, José M.; Marín, Rafael Luis Hernández

doi:10.1016/j.artmed.2008.07.013

Cited by 41 publications

(23 citation statements)

References 18 publications

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“…For general process, the workflow models, Business Process Management and clinical processes management have been successfully introduced in the hospital organisation [16,20]. More specific clinical processes, such as surgery process models [18] or clinical temporal workflows [9] have also been considered. However, all the mentioned models are composed of a-priori-known interrelated sets of activities, that is, a model valid for different patients.…”

Section: Related Workmentioning

confidence: 99%

Computing Problem Oriented Medical Records

Juárez

Gomariz

2012

Knowledge Representation for Health-Care

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Abstract. Problem Oriented Medical Record (POMR) is a medical record approach that provides a quick and structured acquisition of the patient's history. POMR, unlike classical health records, focuses on patient's problems, their evolution, and the relations between the clinical events. This approach provides the physician a view of the patients' history as an orderly process to solve their problems, giving the opportunity to make explicit hypotheses and clinical decisions. Most efforts regarding POMR focus on the implementation of information systems as an alternative of classical health records. Results reveal that POMR information systems provide a better organisation of patients' information but unsuitable mechanisms to perform other basic issues (e.g. administrative reports).Due to its features, POMR can help to bridge the gap between the traditional clinical information process and knowledge management. Despite the potential advantages of POMR, only few efforts have been done to exploit its capacities as a knowledge representation model and a further automatic reasoning. In this work, we propose the Problem Flow, a computational model based on the POMR. This proposal has a double objective: (1) to make explicit the knowledge included in the POMR for reasoning purposes and (2) to allow the coexistence between classical health records and the POMR. We also present PLOW, a knowledge acquisition tool which supports the proposed model. We illustrate its application in the Intensive Care Unit domain.

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Section: Related Workmentioning

confidence: 99%

Computing Problem Oriented Medical Records

Juárez

Gomariz

2012

Knowledge Representation for Health-Care

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“…Work by van der Aalst et al [6] proposes an approach (based on Petri nets) to allow the ability to distinguish between marginally different and completely different processes. Work looking for temporal similarity using ad hoc temporal constraint networks, has been reported in [2]. Other approaches include the use of fuzzy logic [19] or linear temporal logic expressions [9].…”

Section: A Process Semanticsmentioning

confidence: 99%

“…These too can be described using general business process notations [4]- [6]. Deploying process models in the medical domain in practise requires flexible interpretations of those models [2], [4], [6]- [9] .…”

Section: Introductionmentioning

confidence: 99%

UTP Semantics for Shared-State, Concurrent, Context-Sensitive Process Models

Butterfield

Mjeda

Noll

2016

2016 10th International Symposium on Theoretical Aspects of Software Engineering (TASE)

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Abstract-Process Modelling Language (PML) is a notation for describing software development and business processes. It takes the form of a shared-state concurrent imperative language describing tasks as activities that require resources to start and provide resources when they complete. Its syntax covers sequential composition, parallelism, iteration and choice, but without explicit iteration and choice conditions. It is intended to support a range of context-sensitive interpretations, from a rough guide for intended behaviour, to being very prescriptive about the order in which tasks must occur. We are using Unifying Theories of Programming (UTP) to model this range of semantic interpretations, with formal links between them, typically of the nature of a refinement. We address a number of challenges that arise when trying to develop a compositional semantics for PML and its shared-state concurrent underpinnings, most notably in how UTP observations need to distinguish between dynamic state-changes and static context parameters. The formal semantics are intended as the basis for tool support for process analysis, with applications in the healthcare domain, covering such areas as healthcare pathways and software development and certification processes for medical device software. c IEEE 2016 http://doi.ieeecomputersociety

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“…Some research exists that analyzes process variation in healthcare based on similarity measures between CPs (e.g. Huang et al 2013;Combi et al 2009). This is different to our work since we will allow for variations in CPs while filtering out non-significant ones.…”

Section: Medical- Data-driven Clinical Pathway and Process Miningmentioning

confidence: 99%

Improving hospital layout planning through clinical pathway mining

Arnolds

Gärtner

2017

Ann Oper Res

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Clinical pathways (CPs) are standardized, typically evidence-based health care processes. They define the set and sequence of procedures such as diagnostics, surgical and therapy activities applied to patients. This study examines the value of data-driven CP mining for strategic healthcare management. When assigning specialties to locations within hospitals-for new hospital buildings or reconstruction works-the future CPs should be known to effectively minimize distances traveled by patients. The challenge is to dovetail the prediction of uncertain CPs with hospital layout planning. We approach this problem in three stages: In the first stage, we extend a machine learning algorithm based on probabilistic finite state automata (PFSA) to learn significant CPs from data captured in hospital information systems. In that stage, each significant CP is associated with a transition probability. A unique feature of our approach is that we can generalize the data and include those CPs which have not been observed in the data but which are likely to be followed by future patients according to the pathway probabilities obtained from the PFSA. At the same time, rare and non-significant CPs are filtered out. In the second stage, we present a mathematical model that allows us to perform hospital layout planning decisions based on the CPs, their probabilities and expert knowledge. In the third stage, we evaluate our approach based on different performance measures. Our case study results based on real-world hospital data reveal that using our CP mining approach, distances traveled by patients can be reduced substantially as compared to using a baseline method. In a second case study, when using our approach for reconstructing a hospital and incorporating expert knowledge into the planning, existing layouts can be improved. B Daniel Gartner

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Temporal similarity measures for querying clinical workflows

Cited by 41 publications

References 18 publications

Computing Problem Oriented Medical Records

Computing Problem Oriented Medical Records

UTP Semantics for Shared-State, Concurrent, Context-Sensitive Process Models

Improving hospital layout planning through clinical pathway mining

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