Personalized conciliation of clinical guidelines for comorbid patients through multi-agent planning

[EN] The conciliation of multiple single-disease guidelines for comorbid patients entails solving potential clinical interactions, discovering synergies in the diagnosis and the recommendations, and managing clinical equipoise situations. Personalized conciliation of multiple guidelines considering additionally patient preferences brings some further difficulties. Recently, several works have explored distinct techniques to come up with an automated process for the conciliation of clinical guidelines for comorbid patients but very little attention has been put in integrating the patient preferences into this process. In this work, a Multi-Agent Planning (MAP) framework that extends previous work on single-disease temporal Hierarchical Task Networks (HTN) is proposed for the automated conciliation of clinical guidelines with patient-centered preferences. Each agent encapsulates a single-disease Computer Interpretable Guideline (CIG) formalized as an HTN domain and conciliates the decision procedures that encode the clinical recommendations of its CIG with the decision procedures of the other agents' CIGs. During conciliation, drug-related interactions, scheduling constraints as well as redundant actions and multiple support interactions are solved by an automated planning process. Moreover, the simultaneous application of the patient preferences in multiple diseases may potentially bring about contradictory clinical decisions and more interactions. As a final step, the most adequate personalized treatment plan according to the patient preferences is selected by a Multi-Criteria Decision Making (MCDM) process. The MAP approach is tested on a case study that builds upon a simplified representation of two real clinical guidelines for Diabetes Mellitus and Arterial Hypertension.This work has been partially supported by Spanish Government Projects MINECO TIN2014-55637-C2-2-R and TIN2015-71618-R.Fernández-Olivares, J.; Onaindia De La Rivaherrera, E.; Castillo Vidal, L.; Jordán, J.; Cózar, J. (2019). Personalized conciliation of clinical guidelines for comorbid patients through multi-agent planning. Artificial Intelligence in Medicine. 96:167-186. https://doi.org/10.1016/j.artmed.2018.11.003S1671869

GLARE-SSCPM: an Intelligent System to Support the Treatment of Comorbid Patients

The development of software tools supporting physicians in the treatment of comorbid patients is a challenging goal and a hot topic in Medical Informatics and Artificial Intelligence. Computer Interpretable Guidelines (CIGs) are consolidated tools to support physicians with evidence-based recommendations in the treatment of patients affected by a specific disease. However, the applications of two or more CIGs on comorbid patients is critical, since dangerous interactions between (the effects of) actions from different CIGs may arise. GLARE-SSCPM is the first tool supporting, in an integrated way, (i) the knowledge-based detection of interactions, (ii) the management of the interactions, and (iii) the final merge of (part of) the CIGs operating on the patient. GLARE-SSCPM is characterized by being very supportive to physicians, providing them support for focusing, interaction detection, and for an hypothesize and test approach to manage the detected interactions. To achieve such goals, it provides advanced Artificial Intelligence techniques. Preliminary tests in the educational context, within the RoPHS project, have provided encouraging results

Temporal detection and analysis of guideline interactions

Background Clinical practice guidelines (CPGs) are assuming a major role in the medical area, to grant the quality of medical assistance, supporting physicians with evidence-based information of interventions in the treatment of single pathologies. The treatment of patients affected by multiple diseases (comorbid patients) is one of the main challenges for the modern healthcare. It requires the development of new methodologies, supporting physicians in the treatment of interactions between CPGs. Several approaches have started to face such a challenging problem. However, they suffer from a substantial limitation: they do not take into account the temporal dimension. Indeed, practically speaking, interactions occur in time. For instance, the effects of two actions taken from different guidelines may potentially conflict, but practical conflicts happen only if the times of execution of such actions are such that their effects overlap in time. Objectives We aim at devising a methodology to detect and analyse interactions between CPGs that considers the temporal dimension. Methods In this paper, we first extend our previous ontological model to deal with the fact that actions, goals, effects and interactions occur in time, and to model both qualitative and quantitative temporal constraints between them. Then, we identify different application scenarios, and, for each of them, we propose different types of facilities for user physicians, useful to support the temporal detection of interactions. Results We provide a modular approach in which different Artificial Intelligence temporal reasoning techniques, based on temporal constraint propagation, are widely exploited to provide users with such facilities. We applied our methodology to two cases of comorbidities, using simplified versions of CPGs. Conclusion We propose an innovative approach to the detection and analysis of interactions between CPGs considering different sources of temporal information (CPGs, ontological knowledge and execution logs), which is the first one in the literature that takes into account the temporal issues, and accounts for different application scenarios

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

MuCIGREF: multiple computer-interpretable guideline representation and execution framework for managing multimobidity care

Clinical Practice Guidelines (CPGs) supply evidence-based recommendations to healthcare professionals (HCPs) for the care of patients. Their use in clinical practice has many benefits for patients, HCPs and treating medical centres, such as enhancing the quality of care, and reducing unwanted care variations. However, there are many challenges limiting their implementations. Initially, CPGs predominantly consider a specific disease, and only few of them refer to multimorbidity (i.e. the presence of two or more health conditions in an individual) and they are not able to adapt to dynamic changes in patient health conditions. The manual management of guideline recommendations are also challenging since recommendations may adversely interact with each other due to their competing targets and/or they can be duplicated when multiple of them are concurrently applied to a multimorbid patient. These may result in undesired outcomes such as severe disability, increased hospitalisation costs and many others. Formalisation of CPGs into a Computer Interpretable Guideline (CIG) format, allows the guidelines to be interpreted and processed by computer applications, such as Clinical Decision Support Systems (CDSS). This enables provision of automated support to manage the limitations of guidelines. This thesis introduces a new approach for the problem of combining multiple concurrently implemented CIGs and their interrelations to manage multimorbidity care. MuCIGREF (Multiple Computer-Interpretable Guideline Representation and Execution Framework), is proposed whose specific objectives are to present (1) a novel multiple CIG representation language, MuCRL, where a generic ontology is developed to represent knowledge elements of CPGs and their interrelations, and to create the multimorbidity related associations between them. A systematic literature review is conducted to discover CPG representation requirements and gaps in multimorbidity care management. The ontology is built based on the synthesis of well-known ontology building lifecycle methodologies. Afterwards, the ontology is transformed to a metamodel to support the CIG execution phase; and (2) a novel real-time multiple CIG execution engine, MuCEE, where CIG models are dynamically combined to generate consistent and personalised care plans for multimorbid patients. MuCEE involves three modules as (i) CIG acquisition module, transfers CIGs to the personal care plan based on the patient’s health conditions and to supply CIG version control; (ii) parallel CIG execution module, combines concurrently implemented multiple CIGs by performing concurrency management, time-based synchronisation (e.g., multi-activity merging), modification, and timebased optimisation of clinical activities; and (iii) CIG verification module, checks missing information, and inconsistencies to support CIG execution phases. Rulebased execution algorithms are presented for each module. Afterwards, a set of verification and validation analyses are performed involving real-world multimorbidity cases studies and comparative analyses with existing works. The results show that the proposed framework can combine multiple CIGs and dynamically merge, optimise and modify multiple clinical activities of them involving patient data. This framework can be used to support HCPs in a CDSS setting to generate unified and personalised care recommendations for multimorbid patients while merging multiple guideline actions and eliminating care duplications to maintain their safety and supplying optimised health resource management, which may improve operational and cost efficiency in real world-cases, as well

Off-Label and Unlicensed Medicines' Related Problems in Paediatric In-Patients

Background: Current legislations such as paediatric investigation plan (PIP) require pharmaceutical companies seeking marketing authorisation for a new medicine to provide evidence of studies in paediatrics to justify the use of such medicine in this population. In spite of these legislations, there are still challenges with conduct of clinical trials in paediatrics; thus, there is lack of commercially available dosage forms appropriate for use in this population. Consequently, a good proportion of medicines used in treating paediatric patients are used in the unlicensed (UL) or off-label (OL) manner. Use of UL or OL medicines has been associated with higher safety incidents such as, adverse drug reactions (ADRs) than licensed medicines. ADRs are only a subset of medicine related problems (MRPs) associated with the use of medicines. Currently, no studies have explored all aspects of problems associated with the use of OL and UL medicines in paediatrics. Aim: To investigate the prevalence of the use of OL and UL medicines and problems associated with their use in paediatrics patients admitted to intensive care units of a Children’s Hospital. Method: A systematic literature review was carried out to identify problems that are associated with the use of OL and UL medicines. A retrospective review of case notes (n=194) of patients who were admitted to Paediatric Intensive Care Unit (PICU) was carried out at medical records units of the hospital. This was followed by a prospective review of case notes (n=147) of patients admitted to PICU. The last study involved a prospective review of case notes (n=87) admitted to Neonatal Intensive Care Unit (NICU); NICU had migrated to electronic prescribing at the time the study was carried out. Licensing status of medicines was determined using Summary of Product Characteristics of medicines. Definition and categories of MRPs were based on the Pharmaceutical Care Network Europe classification system version 6.2. Naranjo causality scale was used to identify the medicines that was associated with MRPs. Severity and preventability of identified MRPs were assessed using the National Patient Safety Agency categorisation for level of harm and Schumock and Thornton scale respectively. Data was analysed using computer programmes including Excel, Statistical Package for the Social Sciences and STATA. Results: In the retrospective study, 53% of the total number of patients developed at least one MRP and 8% (n=165/2000) of the total number of medicines were associated with MRPs. From the total number of MRPs, 43% were associated with licensed medicines, while 57% were associated with OL and/or UL medicines. Identified MRPs were mostly ADRs and treatment effectiveness problems (84% vs.16%). In the prospective PICU study, 66% of the total number of patients developed at least one MRP and 11% (n=178/1578) of prescribed medicines were associated with MRPs. From the total number of MRPs, 40.4% were associated with licensed medicines, while 59.6% were associated with OL and/or UL medicines. Among the identified MRPs, 83% were ADRs and 17% were treatment effectiveness problems. In the NICU study, 90% of the patients developed MRPs and 9% (n= 186/1978) of the total number of medicines were associated with MRPs. From the total number of MRPs, 55% were associated with licensed medicines, while 45% were associated with OL and/or UL medicines. All the identified MRPs were ADRs. Conclusion: This research is the first to investigate MRPs associated with the use of OL and UL medicines in paediatric in-patients. MRPs associated with the use of OL and UL medicines were higher than with the use of licensed medicines. Inclusion of paediatrics in clinical trials of new medicines is fundamental to reducing the use of OL and UL medicines and the problems associated with their use

Eye quietness and quiet eye in expert and novice golf performance: an electrooculographic analysis

Quiet eye (QE) is the final ocular fixation on the target of an action (e.g., the ball in golf putting). Camerabased eye-tracking studies have consistently found longer QE durations in experts than novices; however, mechanisms underlying QE are not known. To offer a new perspective we examined the feasibility of measuring the QE using electrooculography (EOG) and developed an index to assess ocular activity across time: eye quietness (EQ). Ten expert and ten novice golfers putted 60 balls to a 2.4 m distant hole. Horizontal EOG (2ms resolution) was recorded from two electrodes placed on the outer sides of the eyes. QE duration was measured using a EOG voltage threshold and comprised the sum of the pre-movement and post-movement initiation components. EQ was computed as the standard deviation of the EOG in 0.5 s bins from –4 to +2 s, relative to backswing initiation: lower values indicate less movement of the eyes, hence greater quietness. Finally, we measured club-ball address and swing durations. T-tests showed that total QE did not differ between groups (p = .31); however, experts had marginally shorter pre-movement QE (p = .08) and longer post-movement QE (p < .001) than novices. A group × time ANOVA revealed that experts had less EQ before backswing initiation and greater EQ after backswing initiation (p = .002). QE durations were inversely correlated with EQ from –1.5 to 1 s (rs = –.48 - –.90, ps = .03 - .001). Experts had longer swing durations than novices (p = .01) and, importantly, swing durations correlated positively with post-movement QE (r = .52, p = .02) and negatively with EQ from 0.5 to 1s (r = –.63, p = .003). This study demonstrates the feasibility of measuring ocular activity using EOG and validates EQ as an index of ocular activity. Its findings challenge the dominant perspective on QE and provide new evidence that expert-novice differences in ocular activity may reflect differences in the kinematics of how experts and novices execute skills

Contribution des facteurs de risque vasculaires dans le développement de troubles cognitifs et de démence dans la maladie de Parkinson idiopathique

Chez les aînés autrement en santé, les facteurs de risque vasculaires (FRV), tels que l’hypertension artérielle, le diabète sucré, l’hypercholestérolémie et le tabagisme, sont d’importants facteurs de risque pour les troubles cognitifs, les symptômes psychologiques et comportementaux ainsi que la démence. Néanmoins, il y a actuellement peu de connaissances quant aux conséquences des maladies cérébro-vasculaires et des FRV dans la maladie de Parkinson idiopathique (MP). Les troubles d’ordre neuropsychologique ont un impact considérable sur la qualité de vie des patients et de leurs proches et constituent un aspect important du tableau clinique de la MP. Par conséquent, il est crucial d’identifier les facteurs y prédisposant. Les FRV offrent plusieurs pistes d’interventions intéressantes, puisqu’ils peuvent être modifiés et traités. Ainsi, cette thèse avait pour objectifs principaux d’étudier si les FRV contribuaient aux troubles cognitifs et la démence associés à la MP, et dans l’affirmative, de préciser le profil neuropsychologique des patients MP présentant des FRV. La thèse se divise en six chapitres, chacun adressant un objectif particulier. Le Chapitre 1 introduit les principaux concepts de la problématique et présente les particularités de l’étude des conséquences neurocognitives des FRV dans le contexte spécifique de la MP. Le Chapitre 2 est une recension systématique des écrits qui a permis de faire état des connaissances actuelles sur la question, en plus de soulever les limites des études antérieures afin de guider les travaux subséquents de cette thèse doctorale. Le Chapitre 3 présente une analyse transversale incluant 139 patients MP et montre que la sévérité de l’histoire de tabagisme est associée à un fonctionnement cognitif global inférieur, même chez les patients ayant cessé de fumer, et ce, indépendamment de l’âge et du niveau d’éducation. Le Chapitre 4 présente une étude empirique basée sur la banque de données longitudinale du Parkinson’s Progression Markers Initiative (PPMI), et conclut que le nombre d’années avec un diagnostic d’hypertension artérielle ainsi qu’une pression différentielle élevée ont des effets délétères sur les mesures de mémoire épisodique et de fluidité verbale sémantique. Le Chapitre 5 détaille la dernière étude empirique de la thèse et expose les effets dommageables du fardeau vasculaire total sur les fonctions exécutives et la mémoire épisodique, à la fois dans un groupe de patients MP et un groupe de participants contrôles. Enfin, le Chapitre 6 se veut une synthèse, une mise à jour et une réflexion critique des résultats obtenus dans le cadre des travaux de cette thèse.Vascular risk factors (VRFs) such as hypertension, diabetes mellitus, hypercholesterolemia and smoking are important risk factors for cognitive impairment, psychiatric disorders and dementia in otherwise healthy older adults. However, there is little knowledge about the influence of cerebrovascular diseases and VRFs on cognition in idiopathic Parkinson's disease (PD). Cognitive impairment and dementia are an important part of the clinical presentation of PD and have a considerable impact on the quality of life of the patients and their caregivers. Therefore, it is crucial to identify potential risk factors for neuropsychological disorders in PD. VRFs offer many possibilities for intervention in clinical settings, since they can be modified and treated. Thus, the main objectives of this dissertation were to study whether VRFs contribute to cognitive impairment and dementia associated with PD, and if so, to specify the neuropsychological profile of MP patients with VRFs. The dissertation is divided into six chapters, each addressing a particular objective. Chapter 1 introduces the main concepts of the problem and presents the specific challenges of the study of the neurocognitive consequences of VRFs in the specific context of PD pathology and treatment. Chapter 2 is a systematic and critical review of the literature that presents the current knowledge on this issue, in addition to identifying and discussing the limits of the previous studies to guide the subsequent work of this dissertation. Chapter 3 presents a cross-sectional analysis including 139 PD patients that shows that the severity of smoking history is associated with lower global cognitive functioning, even in patients who quit smoking, and regardless of age and level of education. Chapter 4 presents an empirical study based on the longitudinal database of the Parkinson's Progression Markers Initiative (PPMI), and concludes that the number of years with a diagnosis of hypertension and high pulse pressure have deleterious effects on measures of episodic memory and semantic fluency. Chapter 5 presents the last empirical study of this dissertation and shows that a higher vascular burden is independently associated with worse performance on executive functions and episodic memory, both in a group of PD patients and a group of otherwise healthy controls. Finally, Chapter 6 presents a summary, an update and a critical discussion of the results obtained over the last five years

A Systems Analysis of Factors that Lead to the Successful Employment of People with a Disability

BACKGROUND: Disability Employment Services (DES) is the primary vehicle in Australia charged with promoting and supporting successful open employment opportunities for people with intellectual and developmental disabilities. This research examined the client consultant dynamic to see what factors were at play in promoting successful employment. METHOD: Research was undertaken using a Multiple Perspective Design that resides within the Interpretative Phenomenological Analysis methodology. Clients with a wide variety of ID/DD (n=24) and Employment Consultants (n=23) were interviewed using semi-structured interviews in small group settings. The data were analysed using Interpretative Phenomenological Analysis (IPA) that allowed for themes to be developed. RESULTS: The research highlighted five primary themes: Relationships, Processes, Compliance Driven Systems, Employers and the Environment. These themes provide a base to develop an understanding of some of the factors influencing employment outcomes amongst the client participant base and the disability employment consultants. The results highlighted disparities in perceived abilities, attitudes and a lack of understanding between the system participants. The results also highlighted the influence of ecology on employment outcomes and a high level of disequilibrium within the employment system and environment. IMPLICATIONS: The inability of the disability employment system to use known evidence-based processes that support clients with ID/DD and consultants has resulted in a system that lacks any real understanding of the client and consultant needs, placing primacy on compliance and system needs ahead of the stated purpose of the program which is to support people with a disability to gain and maintain meaningful employment consistent with their capacity and career aspirations. The research highlights the importance of relationships in creating real understanding of the client to supporting employment outcomes