Conflict resolution in clinical treatments

Dissertação de mestrado integrado em Engenharia InformáticaCurrently, in the health area, there is a need for systems that provide support for the decision of health professionals through specific recommendations for each patient based on Clinical Practice Guidelines (CPGs) for automatic interpretation. CPGs are documents that have enormous importance in the daily life of health professionals, playing a key role in reducing variations in medical practice, improving the quality of health care, and reducing health care costs. These documents reflect knowledge about how best to diagnose and treat diseases in the form of a list of clinical recommendations. However, there may be conflicts and interactions in the application of these clinical recommendations, that which in their maximum exponent may impair the patient’s clinical condition. These conflicts are transported to decision support systems, creating the need to develop computational methods to solve these same conflicts. In the case of multimorbid patients, this resolution of conflicts can be very problematic because these patients suffer from several pathologies at the same time, and that the use of a drug for one particular pathology may have a detrimental effect on the application of another drug in another pathology. Therefore, the objective of this dissertation topic is the determination of conflicts and interactions between drugs and the determination of these same alternatives.Atualmente na área da saúde, existe uma necessidade de existirem sistemas que forneçam apoio à decisão dos profissionais de saúde através de recomendações específicas para cada paciente com base em protocolos clínicos para interpretação automática. Os protocolos clínicos são documentos que têm enorme importância no dia-a-dia dos profissionais de saúde, desempenhando um papel fundamental na redução das variações na prática médica, na melhoria da qualidade dos cuidados de saúde e na redução dos custos de saúde. Estes documentos reflectem o conhecimento sobre a melhor forma de diagnosticar e tratar doenças na forma de uma lista de recomendações clínicas. Contudo, podem existir conflitos e interações na aplicação destas recomendações clínicas, que no seu expoente máximo poderão levar a um agravamento do estado clínico do paciente, nomeadamente no caso da aplicação de diferentes fármacos. Estes conflitos são transportados para os sistemas de apoio à decisão, criando a necessidade de desenvolver métodos computacionais de resolução destes mesmos conflitos. No caso dos pacientes multimórbidos esta resolução de conflitos pode ser bastante problemática devido ao facto destes pacientes sofrerem de várias patologias ao mesmo tempo, e que a utilização de um fármaco para uma determinada patologia possa vir a ter um efeito nocivo na aplicação de outro fármaco noutra patologia. Sendo assim, o objetivo deste tema de dissertação é a determinação dos conflitos e interações entre fármacos e a determinação dessas mesmas alternativas

Towards a framework for comparing functionalities of multimorbidity clinical decision support: A literature-based feature set and benchmark cases.

Multimorbidity, the coexistence of two or more health conditions, has become more prevalent as mortality rates in many countries have declined and their populations have aged. Multimorbidity presents significant difficulties for Clinical Decision Support Systems (CDSS), particularly in cases where recommendations from relevant clinical guidelines offer conflicting advice. A number of research groups are developing computer-interpretable guideline (CIG) modeling formalisms that integrate recommendations from multiple Clinical Practice Guidelines (CPGs) for knowledge-based multimorbidity decision support. In this paper we describe work towards the development of a framework for comparing the different approaches to multimorbidity CIG-based clinical decision support (MGCDS). We present (1) a set of features for MGCDS, which were derived using a literature review and evaluated by physicians using a survey, and (2) a set of benchmarking case studies, which illustrate the clinical application of these features. This work represents the first necessary step in a broader research program aimed at the development of a benchmark framework that allows for standardized and comparable MGCDS evaluations, which will facilitate the assessment of functionalities of MGCDS, as well as highlight important gaps in the state-of-the-art. We also outline our future work on developing the framework, specifically, (3) a standard for reporting MGCDS solutions for the benchmark case studies, and (4) criteria for evaluating these MGCDS solutions. We plan to conduct a large-scale comparison study of existing MGCDS based on the comparative framework

The use of computer-interpretable clinical guidelines to manage care complexities of patients with multimorbid conditions : a review

Clinical practice guidelines (CPGs) document evidence-based information and recommendations on treatment and management of conditions. CPGs usually focus on management of a single condition; however, in many cases a patient will be at the centre of multiple health conditions (multimorbidity). Multiple CPGs need to be followed in parallel, each managing a separate condition, which often results in instructions that may interact with each other, such as conflicts in medication. Furthermore, the impetus to deliver customised care based on patient-specific information, results in the need to be able to offer guidelines in an integrated manner, identifying and managing their interactions. In recent years, CPGs have been formatted as computer-interpretable guidelines (CIGs). This enables developing CIG-driven clinical decision support systems (CDSSs), which allow the development of IT applications that contribute to the systematic and reliable management of multiple guidelines. This study focuses on understanding the use of CIG-based CDSSs, in order to manage care complexities of patients with multimorbidity. The literature between 2011 and 2017 is reviewed, which covers: (a) the challenges and barriers in the care of multimorbid patients, (b) the role of CIGs in CDSS augmented delivery of care, and (c) the approaches to alleviating care complexities of multimorbid patients. Generating integrated care plans, detecting and resolving adverse interactions between treatments and medications, dealing with temporal constraints in care steps, supporting patient-caregiver shared decision making and maintaining the continuity of care are some of the approaches that are enabled using a CIG-based CDSS

The Friendly Health Issue Network to Support Computer-Assisted Education for Clinical Reasoning in Multimorbidity Patients

Clinical reasoning in multimorbidity conditions asks for the ability to anticipate the possible evolutions of the overall health state of a patient and to identify the interactions among the concurrent health issues and their treatments. The HIN (Health Issue Network) approach, as Petri Nets-based formal language, is introduced as capable of providing a novel perspective to facilitate the acquisition of such competencies, graphically representing the network among a set of health issues (HIs) that affect a person throughout their life, and describing how HIs evolve over time. The need to provide a more immediate user-oriented interface has led to the development of f-HIN (friendly HIN), a lighter version based on the same mathematical properties as HIN, from which stems in turn the f-HINe (friendly HIN extracted) model, used to represent networks related to either real patients’ clinical experiences extracted from electronic health records, or from teacher-designed realistic clinical histories. Such models have also been designed to be embedded in a software learning environment that allows drawing a f-HIN diagram, checking for its format correctness, as well as designing clinical exercises for the learners, including their computer-assisted assessment. The present paper aims at introducing and discussing the f-HIN/f-HINe models and their educational use. It also introduces the main features of the software learning environment it was built upon, pointing out its importance to: (i) help medical teachers in designing and representing the context of a learning outcome; and (ii) handle the complex history of a multimorbidity patient, to be conveyed in Case-Based Learning (CBL) exercises

SERIES: eHealth in primary care. Part 1: Concepts, conditions and challenges.

Primary care is challenged to provide high quality, accessible and affordable care for an increasingly ageing, complex, and multimorbid population. To counter these challenges, primary care professionals need to take up new and innovative practices, including eHealth. eHealth applications hold the promise to overcome some difficulties encountered in the care of people with complex medical and social needs in primary care. However, many unanswered questions regarding (cost) effectiveness, integration with healthcare, and acceptability to patients, caregivers, and professionals remain to be elucidated. What conditions need to be met? What challenges need to be overcome? What downsides must be dealt with? This first paper in a series on eHealth in primary care introduces basic concepts and examines opportunities for the uptake of eHealth in primary care. We illustrate that although the potential of eHealth in primary care is high, several conditions need to be met to ensure that safe and high-quality eHealth is developed for and implemented in primary care. eHealth research needs to be optimized; ensuring evidence-based eHealth is available. Blended care, i.e. combining face-to-face care with remote options, personalized to the individual patient should be considered. Stakeholders need to be involved in the development and implementation of eHealth via co-creation processes, and design should be mindful of vulnerable groups and eHealth illiteracy. Furthermore, a global perspective on eHealth should be adopted, and eHealth ethics, patients' safety and privacy considered.Published versio

Empowering people to help speak up about safety in primary care: Using codesign to involve patients and professionals in developing new interventions for patients with multimorbidity.

BACKGROUND: Multimorbidity, defined as the presence of two or more long-term conditions, is increasingly common in primary care, and patients with multimorbidity may face particular barriers to quality of care and increased safety risks due to the complexity of managing multiple conditions. Consistent with calls to directly involve service users in improving care, we aimed to use design materials to codesign new interventions to improve safety in primary care. DESIGN: We drew on two established methods-accelerated experience-based codesign and the future workshop approach. We synthesized design materials based on research into the patient experience of safety and multimorbidity in primary care to enable both patients, service users and carers, and primary health-care professionals to propose interventions to improve care. RESULTS: Both patients and professionals prioritized polypharmacy as a threat to safety. Their recommendations for supportive interventions were consistent with Burden of Treatment theory, emphasizing the limited capacity of patients with multimorbidity and the need for services to proactively offer support to reduce the burden of managing complex treatment regimes. DISCUSSION & CONCLUSIONS: The process was feasible and acceptable to participants, who valued the opportunity to jointly propose new interventions. The iterative workshop approach enabled the research team to better explore and refine the suggestions of attendees. Final recommendations included the need for accessible reminders to support medication adherence and medication reviews for particularly vulnerable patients conducted with pharmacists within GP practices

Improving GPs' knowledge of the benefits and harms of treatment to support decision making in multimorbidity: qualitative research and co-design of a novel electronic information resource

Background General practitioners (GPs) regularly prescribe prolonged treatments for long-term conditions. However, GPs may benefit from further understanding of the absolute benefits and harms of these treatments, enhancing their ability to engage in shared decision-making and manage multimorbidity and polypharmacy. Aim To produce and evaluate a website to provide information on the benefits and harms of treatments for long-term conditions in a way that can be understood by GPs and potentially integrated into their practice. Methods The study consisted of three parts. First, a qualitative interview study and framework analysis with GPs exploring their attitudes to and understanding of the quantitative benefits and harms of treatments. Second, a participatory co-design process to design the website, coupled with a pragmatic approach to evidence collation to provide clinical content. Finally, an exploratory evaluation study of the website using online focus groups. Results The interview study reported findings on GPs’ understanding of quantitative information on the benefits and harms of treatments which informed the co-design research. The co-design research resulted in the creation of a website, www.gpevidence.org, which presents complex scientific information on treatment effect sizes and the nature and quality of the relevant clinical evidence. The evaluation study showed that participating GPs were able to understand the clinical information on GP Evidence, and that in hypothetical scenarios this might change their prescribing practice. Some participants found some information confusing. There was limited evidence that this new information could be integrated into complex decision-making for multimorbidity and polypharmacy. Conclusion The aim of producing a website able to deliver information on the benefits and harms of treatments for long-term conditions to GPs was achieved. Further research is needed to evaluate the effect of GP Evidence in real-world practice

Healthier and Independent Living of the Elderly: Interoperability in a Cross-Project Pilot

The ageing of the population creates new heterogeneous challenges for age-friendly living. The progressive decline in physical and cognitive skills tends to prevent elderly people from performing basic instrumental activities of daily living and there is a growing interest in technology for aging support. Digital health today can be exercised by anyone owning a smartphone and parameters such as heart rate, step counts, calorie intake, sleep quality, can be collected and used not only to monitor and improve the individual’s health condition but also to prevent illnesses. However, for the benefits of e-health to take place, digital health data, either Electronic Health Records (EHR) or sensor data from the IoMT, must be shared, maintaining privacy and security requirements but unlocking the potential for research an innovation throughout EU. This paper demonstrates the added value of such interoperability requirements, and a form of accomplishing them through a cross-project pilot

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