MitCon: Automated Conflict Resolution in Clinical Pathways
We are applying methods from business process modelling and software design to improve the treatment of patients suffering multiple concurrent clinical conditions (multimorbidity). This is a collaboration between the School of Computer Science and the Institute of Applied Health Research at the University of Birmingham, and the School of Computer Science at the University of St. Andrews.
This project is funded by the EPSRC. The project team at Birmingham are Mark Lee, Ian Litchfield, Ruth Backman, Phil Weber, Behzad Bordbar and Bosco Ferreira. Our parallel project MiMMS - Mixed Methods Multimorbidity Study "seeks to identify challenges GPs and hospital consultants face when managing patients with several chronic conditions" to lay the groundwork for the successful implementation of tools developed on the MitCon project.
May 2018: Our paper on process mining patient drug prescription pathways in primary care is to be presented at the IEEE International Conference on Healthcare Informatics (ICHI) in New York in June.
I. Litchfield, C. Hoye, D. Shukla, R. Backman, A. Turner, M. Lee, P. Weber. Can process mining automatically describe care pathways of patients with long-term conditions in UK primary care? A study protocol. BMJ Open, 2018 [in press].
R. Backman, P. Weber, A. M. Turner, M. G. Lee and I. Litchfield. Assessing the extent of drug interactions amongst patients with multimorbidity in primary and secondary care in the West Midlands (UK): A study protocol for the Mixed Methods Multimorbidity Study (MiMMS). BMJ Open, 7(9):e016713 (8 pages), 2017. (HTTP, DOI).
P. Weber, J. B. F. Filho, B. Bordbar, M. Lee, I. Litchfield and R. Backman. Automated Conflict Detection Between Medical Care Pathways, Journal of Software: Evolution and Process, Special Issue: Software Engineering for Connected Health, in press, 2017 (PDF).
Refereed Conference Papers
P. Weber, R. Backman, I. Litchfield and M. Lee. A Process Mining and Text Analysis Approach to Analyse the Extent of Polypharmacy in Medical Prescribing. Accepted to the 6th International Conference on Healthcare Informatics (ICHI 2018), New York, NY, USA, 2018.
I. Litchfield, A. Turner, R. Backman, P. Weber and M. Lee. Automated Conflict Resolution between multiple Clinical Pathways: An Aid for Family Practitioners, 45th North American Primary Care Research Group (NAPCRG) Annual Meeting, Montreal, Quebec, 2017 (Poster PDF).
P. Weber, J. B. F. Filho, B. Bordbar, M. Lee, I. Litchfield and R. Backman. Automated Conflict Detection Between Medical Care Pathways, In N. Carroll, C. Kuziemsky and I. Richardson (Eds.), Software Engineering for Connected Health (Journal First Session), Proc. International Conference on Software and System Process (ICSSP), Paris, France, 2017. (DOI, slides).
I. Litchfield, J. Bowles, B. Bordbar, A. Turner, R. Backman, P. Weber, M. Caminati and M. Lee. Automated Conflict Resolution between multiple Clinical Pathways: An Aid for Family Practitioners, 3rd West Midlands Health Informatics Network (WIN) Conference, Warwick, UK, 2017 (Poster PDF).
I. Litchfield, J. Bowles, B. Bordbar, A. Turner, R. Backman, P. Weber, M. Caminati and M. Lee. Automated Conflict Resolution between multiple Clinical Pathways: An Aid for Family Practitioners, 44th North American Primary Care Research Group (NAPCRG) Annual Meeting, Colorado Springs, USA, 2016 (Poster PDF).
By 2018, it is estimated that the number of people in the UK with three or more long-term conditions, also known as multimorbidity, will have grown from 1.9 million to 2.9 million. Various chronic diseases develop simultaneously in response to common risk factors such as smoking, diet, ageing and inactivity. The four most common chronic diseases are cancer, chronic obstructive pulmonary disease (COPD), coronary heart disease and diabetes. A recent study found that over 97% of patients with moderate to severe COPD had at least one concomitant chronic disease.
In clinical settings processes are complex and are influenced by a number of social, technical and organisational factors. This complexity can result in variation in how physicians practice, appropriate care is documented, and healthcare costs managed. To reduce inconsistencies, clinical guidelines have emerged based on the best existing evidence, with the aim to support clinical staff and improve the quality of healthcare. Current guidelines almost entirely focus on single conditions. As a result, applying multiple guidelines to a patient may potentially result in conflicting recommendations for care.
In software system design and development, we create computer systems capable to support diverse interactions between the environment/users and the system. These interactions often reflect different and possibly conflicting viewpoints, such as those presented by different users or stakeholders. Although software system specification and patient care guidelines seem different, inherently they have something in common. In both cases we have procedures and executions of (partially) ordered sequence of actions (aka activities or tasks) called "traces of execution" in computer science or "pathways" in clinical practice. In the case of computer-based systems, actions are carried out by users or computers (more specifically individual components or objects in the system). In the case of care guidelines, actions are carried out by physicians, patients and carers. In both cases, conflict may arise when individual executions and pathways are incompatible. In this project, we investigate automated methods of detection of conflicts in clinical pathways for multimorbidities and develop solutions that resolve them.