Automated conflict resolution between multiple clinical pathways:A technology report

Background The number of people in the UK with three or more long-term conditions continues to grow and the management of patients with co-morbidities is complex. In treating patients with multimorbidities, a fundamental problem is understanding and detecting points of conflict between different guidelines which to date has relied on individual clinicians collating disparate information. Objective We will develop a framework for modelling a diverse set of care pathways, and investigate how conflicts can be detected and resolved automatically. We will use this knowledge to develop a software tool for use by clinicians that can map guidelines, highlight root causes of conflict between these guidelines and suggest ways they might be resolved. Method Our work consists of three phases. First, we will accurately model clinical pathways for six of the most common chronic diseases; second, we will automatically identify and detect sources of conflict across the pathways and how they might be resolved. Third, we will present a case study to prove the validity of our approach using a team of clinicians to detect and resolve the conflicts in the treatment of a fictional patient with multiple common morbidities and compare their findings and recommendations with those derived automatically using our novel software. Discussion This paper describes the development of an important software-based method for identifying a conflict between clinical guidelines. Our findings will support clinicians treating patients with multimorbidity in both primary and secondary care settings

A Domain Specific Language for Expressing Model Matching

National audienceA matching strategy computes mappings between two models by executing a set of heuristics. In this paper, we introduce the AtlanMod Matching Language (AML), a Domain Specific Language (DSL) for expressing matching strategies. AML is based on the Model-Driven paradigm, i.e., it implements model matching strategies as chains of model transformations. A matching model transformation takes a set of models as input, and yields a mapping model as output. We present a compiler that takes AML programs and generates ATL (AtlanMod Transformation Language) and Apache Ant code. The ATL code instruments the matching model transformations, and the Ant code orchestrates their execution. We evaluate this implementation on two strategies including robust matching transformations from the literature

A logical approach for behavioural composition of scenario-based models

As modern systems become more complex, design approaches model different aspects of the system separately. When considering (intra and inter) system interactions, it is usual to model individual scenarios using UML’s sequence diagrams. Given a set of scenarios we then need to check whether these are consistent and can be combined for a better understanding of the overall behaviour. This paper addresses this by presenting a novel formal technique for composing behavioural models at the metamodel level through exact metamodel restriction (EMR). In our approach a sequence diagram can be completely described by a set of logical constraints at the metamodel level. When composing sequence diagrams we take the union of the sets of logical constraints for each diagram and additional behavioural constraints that describe the matching composition glue. A formal semantics for composition in accordance with the glue guides our model transformation to Alloy. Alloy’s fully automated constraint solver gives us the solution. Our technique has been implemented as an Eclipse plugin SD2Alloy.Postprin

A framework for automated conflict detection and resolution in medical guidelines

This research is supported by the MRC-funded UK Research and Innovation grant MR/S003819/1 and by EPSRC grant EP/M014290/1.Common chronic conditions are routinely treated following standardised procedures known as clinical guidelines. For patients suffering from two or more chronic conditions, known as multimorbidity, several guidelines have to be applied simultaneously, which may lead to severe adverse effects when the combined recommendations and prescribed medications are inconsistent or incomplete. This paper presents an automated formal framework to detect, highlight and resolve conflicts in the treatments used for patients with multimorbidities focusing on medications. The presented extended framework has a front-end which takes guidelines captured in a standard modelling language and returns the visualisation of the detected conflicts as well as suggested alternative treatments. Internally, the guidelines are transformed into formal models capturing the possible unfoldings of the guidelines. The back-end takes the formal models associated with multiple guidelines and checks their correctness with a theorem prover, and inherent inconsistencies with a constraint solver. Key to our approach is the use of an optimising constraint solver which enables us to search for the best solution that resolves/minimises conflicts according to medication efficacy and the degree of severity in case of harmful combinations, also taking into account their temporal overlapping. The approach is illustrated throughout with a real medical example.Publisher PDFPeer reviewe

Automated conflict resolution for patients with multiple morbidity being treated using more than one set of single condition clinical guidance: A case study

Background The number of people in the UK with two or more conditions continues to grow and their clinical management is complicated by the reliance on guidance focused on a single condition. This leaves individual clinicians responsible for collating disparate information from patient management systems and care recommendations to manually manage the contradictions that exist in the simultaneous treatment of various conditions. Methods/design We have devised a modelling language based on BPMN that allows us to create computer interpretable representations of single condition guidance and incorporate patient data to detect the points of conflict between multiple conditions based on their transformation to logical constraints. This has been used to develop a prototype clinical decision support tool that we can use to highlight the causes of conflict between them in three main areas: medication, lifestyle and well-being, and appointment bookings. Results The prototype tool was used to discern contradictions in the care recommendations of chronic obstructive pulmonary disease and osteoarthritis. These were presented to a panel of clinicians who confirmed that the tool produced clinically relevant alerts that can advise clinicians of the presence of conflicts between guidelines relating to both clashes in medication or lifestyle advice. Conclusions The need for supporting general practitioners in their treatment of patients remains and this proof of concept has demonstrated that by converting this guidance into computer-interpretable pathways we can use constraint solvers to readily identify clinically relevant points of conflict between critical elements of the pathway