A Computer-Interpretable Version of the AACE, AME, ETA Medical Guidelines for Clinical Practice for the Diagnosis and Management of Thyroid Nodules.

OBJECTIVE: Clinical practice guidelines (CPGs) could have a more consistent and meaningful impact on clinician behavior if they were delivered as electronic algorithms that provide patient-specific advice during patient-physician encounters. We developed a computer-interpretable algorithm for U.S. and European users for the purpose of diagnosis and management of thyroid nodules that is based on the "AACE, AME, ETA Medical Guidelines for Clinical Practice for the Diagnosis and Management of Thyroid Nodules," a narrative, evidence-based CPG. METHODS: We initially employed the guideline-modeling language GuideLine Interchange Format, version 3, known as GLIF3, which emphasizes the organization of a care algorithm into a flowchart. The flowchart specified the sequence of tasks required to evaluate a patient with a thyroid nodule. PROforma, a second guideline-modeling language, was then employed to work with data that are not necessarily obtained in a rigid flowchart sequence. Tallis-a user-friendly web-based "enactment tool"- was then used as the "execution engine" (computer program). This tool records and displays tasks that are done and prompts users to perform the next indicated steps. The development process was iteratively performed by clinical experts and knowledge engineers. RESULTS: We developed an interactive web-based electronic algorithm that is based on a narrative CPG. This algorithm can be used in a variety of regions, countries, and resource-specific settings. CONCLUSION: Electronic guidelines provide patient-specific decision support that could standardize care and potentially improve the quality of care. The "demonstrator" electronic thyroid nodule guideline that we describe in this report is available at http://demos.deontics.com/trace-review-app (username: reviewer; password: tnodule1). The demonstrator must be more extensively "trialed" before it is recommended for routine use.

The Case Manager: An Agent Controlling the Activation of Knowledge Sources in a FHIR-Based Distributed Reasoning Environment.

BACKGROUND: Within the CAPABLE project the authors developed a multi-agent system that relies on a distributed architecture. The system provides cancer patients with coaching advice and supports their clinicians with suitable decisions based on clinical guidelines. OBJECTIVES: As in many multi-agent systems we needed to coordinate the activities of all agents involved. Moreover, since the agents share a common blackboard where all patients' data are stored, we also needed to implement a mechanism for the prompt notification of each agent upon addition of new information potentially triggering its activation. METHODS: The communication needs have been investigated and modeled using the HL7-FHIR (Health Level 7-Fast Healthcare Interoperability Resources) standard to ensure proper semantic interoperability among agents. Then a syntax rooted in the FHIR search framework has been defined for representing the conditions to be monitored on the system blackboard for activating each agent. RESULTS: The Case Manager (CM) has been implemented as a dedicated component playing the role of an orchestrator directing the behavior of all agents involved. Agents dynamically inform the CM about the conditions to be monitored on the blackboard, using the syntax we developed. The CM then notifies each agent whenever any condition of interest occurs. The functionalities of the CM and other actors have been validated using simulated scenarios mimicking the ones that will be faced during pilot studies and in production. CONCLUSION: The CM proved to be a key facilitator for properly achieving the required behavior of our multi-agent system. The proposed architecture may also be leveraged in many clinical contexts for integrating separate legacy services, turning them into a consistent telemedicine framework and enabling application reusability.

An eHealth App (CAPABLE) Providing Symptom Monitoring, Well-Being Interventions, and Educational Material for Patients With Melanoma Treated With Immune Checkpoint Inhibitors: Protocol for an Exploratory Intervention Trial.

BACKGROUND: Since treatment with immune checkpoint inhibitors (ICIs) is becoming standard therapy for patients with high-risk and advanced melanoma, an increasing number of patients experience treatment-related adverse events such as fatigue. Until now, studies have demonstrated the benefits of using eHealth tools to provide either symptom monitoring or interventions to reduce treatment-related symptoms such as fatigue. However, an eHealth tool that facilitates the combination of both symptom monitoring and symptom management in patients with melanoma treated with ICIs is still needed. OBJECTIVE: In this pilot study, we will explore the use of the CAPABLE (Cancer Patients Better Life Experience) app in providing symptom monitoring, education, and well-being interventions on health-related quality of life (HRQoL) outcomes such as fatigue and physical functioning, as well as patients' acceptance and usability of using CAPABLE. METHODS: This prospective, exploratory pilot study will examine changes in fatigue over time in 36 patients with stage III or IV melanoma during treatment with ICI using CAPABLE (a smartphone app and multisensory smartwatch). This cohort will be compared to a prospectively collected cohort of patients with melanoma treated with standard ICI therapy. CAPABLE will be used for a minimum of 3 and a maximum of 6 months. The primary endpoint in this study is the change in fatigue between baseline and 3 and 6 months after the start of treatment. Secondary end points include HRQoL outcomes, usability, and feasibility parameters. RESULTS: Study inclusion started in April 2023 and is currently ongoing. CONCLUSIONS: This pilot study will explore the effect, usability, and feasibility of CAPABLE in patients with melanoma during treatment with ICI. Adding the CAPABLE system to active treatment is hypothesized to decrease fatigue in patients with high-risk and advanced melanoma during treatment with ICIs compared to a control group receiving standard care. The Medical Ethics Committee NedMec (Amsterdam, The Netherlands) granted ethical approval for this study (reference number 22-981/NL81970.000.22). TRIAL REGISTRATION: ClinicalTrials.gov NCT05827289; https://clinicaltrials.gov/study/NCT05827289. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/49252.

Argumentation logic for the flexible enactment of goal-based medical guidelines.

UNLABELLED: RESEARCH PURPOSE: We have designed a prototype clinical workflow system that allows the specification and enactment of medical guidelines in terms of clinical goals to be achieved, maintained or avoided depending on the patient's disease and treatment evolution. The prototype includes: (1) an argumentation-based decision support system which can be used both to represent medical decisions within guidelines, and to dynamically choose the most suitable plans to achieve clinical goals, and (2) mechanisms to specify a health organization's facilities and health workers skills and roles, which can be taken into account during the decision process in order to improve quality of care. RESULTS: The framework has been fully implemented in the COGENT formal modeling system. The prototype has been evaluated implementing a hypertension guideline. CONCLUSIONS: The framework has shown flexibility and adaptability in (1) advising and tailoring health care based on a health organization's resources and a patient's particular medical condition, (2) delegating health care, and (3) replanning when unexpected situations arise.

The Case Manager: Driving Medical Reasoning in a Distributed Environment for Home Patient Monitoring.

The CAPABLE project has been funded by the EU Horizon 2020 Programme over the years 2020-24 to support home care. A system is being designed and implemented supporting remote monitoring and virtual coaching for cancer patients. The system is based on a distributed modular architecture involving many components encapsulating various knowledge. The Case Manager has been designed as a separate component with the aim of coordinating the problem solving strategies. A first version of the Case Manager has been released and used by the components in a prototypical scenario shown at the first project review.

A goal-oriented framework for specifying clinical guidelines and handling medical errors.

Computer-interpretable guidelines (CIGs) aim to improve patient care and reduce medical errors. Although CIGs implement evidence-based recommendations they cannot prevent exceptional behavior from happening. To address this problem we developed a framework that can monitor, detect, and handle exceptions that occur during normal CIG execution and can potentially prevent them from developing into medical errors. Our framework enables specifying the goals of a guideline and linking them with recommended tasks that could satisfy the goals. Exceptions are linked with goals that manage them, which can be realized by tasks or plans. To achieve a link between the tasks, plans, goals, monitored effects, and exceptions, our definition of goals and exceptions is state-based. We demonstrate our approach using a generic plan for management of a chronic disease and a particular instantiation for hypertension management.

Interactive decision support for risk management: a qualitative evaluation in cancer genetic counselling sessions.

Genetic counselling for inherited susceptibility to cancer involves communication of a significant amount of information about possible consequences of different interventions. This study explores counsellors' attitudes to computer software designed to aid this process. Eight genetic counsellors used the software with actors playing patients. Clinicians' rating of expected patient satisfaction, content, accuracy, timeliness, format, overall value, ease of use, effect on the patient-provider relationship and effect on clinician's performance were evaluated via qualitative and quantitative analysis of interviews, training tasks and questionnaires. Most counsellors found the software effective. Concerns related to possible impact on consultation dynamics and content. Participants suggested countering these through appropriate new counselling skills and selective use of the computer. The REACT software could provide effective support for genetic risk management counselling.

Goal-based design pattern for delegation of work in health care teams.

We show how a domain and language independent design pattern, defined as networks of tasks and goals, can be used to formally specify the transfer of responsibility and accountability when tasks are delegated in healthcare teams. The pattern is general enough to be applied unchanged across a broad range of different healthcare situations.

Serial order and consonant-vowel structure in a graphemic output buffer model.

We review features of the spelling errors of dysgraphic patients with "Graphemic Buffer Disorder" (GBD). We argue that the errors made by such patients suggest the breakdown of a system used to generate serial order in the output stages of spelling production, and we develop a model for this system based on an existing theory of sequential behaviour--"Competitive Queuing." We show that constraints on response categories may be straightforwardly applied during sequence production in such a model, and this enables us to account for the preservation of consonant-vowel status in the spelling errors of GBD patients. When the sequence generation process is disrupted by the addition of random noise the model shows the major features of GBD. The results are compared in detail against data from a number of patients.

A canonical theory of dynamic decision-making.

Decision-making behavior is studied in many very different fields, from medicine and economics to psychology and neuroscience, with major contributions from mathematics and statistics, computer science, AI, and other technical disciplines. However the conceptualization of what decision-making is and methods for studying it vary greatly and this has resulted in fragmentation of the field. A theory that can accommodate various perspectives may facilitate interdisciplinary working. We present such a theory in which decision-making is articulated as a set of canonical functions that are sufficiently general to accommodate diverse viewpoints, yet sufficiently precise that they can be instantiated in different ways for specific theoretical or practical purposes. The canons cover the whole decision cycle, from the framing of a decision based on the goals, beliefs, and background knowledge of the decision-maker to the formulation of decision options, establishing preferences over them, and making commitments. Commitments can lead to the initiation of new decisions and any step in the cycle can incorporate reasoning about previous decisions and the rationales for them, and lead to revising or abandoning existing commitments. The theory situates decision-making with respect to other high-level cognitive capabilities like problem solving, planning, and collaborative decision-making. The canonical approach is assessed in three domains: cognitive and neuropsychology, artificial intelligence, and decision engineering.

A formal approach to the analysis of clinical computer-interpretable guideline modeling languages.

OBJECTIVE: To develop proof strategies to formally study the expressiveness of workflow-based languages, and to investigate their applicability to clinical computer-interpretable guideline (CIG) modeling languages. METHOD: We propose two strategies for studying the expressiveness of workflow-based languages based on a standard set of workflow patterns expressed as Petri nets (PNs) and notions of congruence and bisimilarity from process calculus. Proof that a PN-based pattern P can be expressed in a language L can be carried out semi-automatically. Proof that a language L cannot provide the behavior specified by a PNP requires proof by exhaustion based on analysis of cases and cannot be performed automatically. The proof strategies are generic but we exemplify their use with a particular CIG modeling language, PROforma. To illustrate the method we evaluate the expressiveness of PROforma against three standard workflow patterns and compare our results with a previous similar but informal comparison. RESULTS: We show that the two proof strategies are effective in evaluating a CIG modeling language against standard workflow patterns. We find that using the proposed formal techniques we obtain different results to a comparable previously published but less formal study. We discuss the utility of these analyses as the basis for principled extensions to CIG modeling languages. Additionally we explain how the same proof strategies can be reused to prove the satisfaction of patterns expressed in the declarative language CIGDec. CONCLUSION: The proof strategies we propose are useful tools for analysing the expressiveness of CIG modeling languages. This study provides good evidence of the benefits of applying formal methods of proof over semi-formal ones.

Comparing semi-automatic systems for recruitment of patients to clinical trials.

OBJECTIVES: (i) To review contributions and limitations of decision support systems for automatic recruitment of patients to clinical trials (Clinical Trial Recruitment Support Systems, CTRSS). (ii) To characterize the important features of this domain, the main classes of approach that have been used, and their advantages and disadvantages. (iii) To assess the effectiveness and potential of such systems in improving trial recruitment rates. DATA SOURCES: A systematic MESH keyword-based search of Pubmed, Embase, and Scholar Google for relevant CTRSS publications from January 1st 1998 to August 31st 2009 yielded 73 references, from which 33 relevant papers describing 28 distinct studies were chosen for review, based on their report of a novel decision support system for trial recruitment which reused already available patient data. METHOD: The reviewed papers were classified using a modified version of an existing taxonomy for clinical decision support systems, using 10 axes relevant to the trial recruitment domain. RESULTS: It proved possible and useful to characterize CTRSS on a relatively small number of dimensions and a number of clear trends emerge from the study. Only nine papers reported a useful evaluation of the effectiveness of the system in terms of trial pre-inclusion or enrolment rate. While all the systems reviewed re-use structured and coded patient data none attempts the more difficult task of using unstructured patient notes to pre-screen for trial inclusion. Few studies address acceptance of systems by clinicians, or integration into clinical workflow, and there is little evidence of use of interoperability standards. CONCLUSIONS: System design, scope, and assessment methodology vary significantly between papers, making it difficult to establish the impact of different approaches on recruitment rate. It is clear, however, that the pre-screening phase of trial recruitment is the most effective part of the process to address with CTRSS, that clinical workflow integration and clinician acceptance are critical for this class of decision support, and that the current trends in this field are towards generalization and scalability.

Patterns for collaborative work in health care teams.

OBJECTIVE: The problem of designing and managing teams of workers that can collaborate working together towards common goals is a challenging one. Incomplete or ambiguous specification of responsibilities and accountabilities, lack of continuity in teams working in shifts, inefficient organization of teams due to lack of information about workers' competences and lack of clarity to determine if the work is delegated or assigned are examples of important problems related to collaborative work in healthcare teams. Here we address these problems by specifying goal-based patterns for abstracting the delegation and assignment of services. The proposed patterns should provide generic and reusable solutions and be flexible enough to be customizable at run time to the particular context of execution. Most importantly the patterns should support a mechanism for detecting abnormal events (exceptions) and for transferring responsibility and accountability for recovering from exceptions to the appropriate actor. METHOD: To provide a generic solution to the problematic issues arising from collaborative work in teams of health workers we start from definitions of standard terms relevant for team work: competence, responsibility, and accountability. We make explicit the properties satisfied by service assignment and delegation in terms of competences, responsibilities, and accountability in normal scenarios and abnormal situations that require the enactment of recovery strategies. Based on these definitions we specify (1) a basic terminology, (2) design patterns for service assignment and delegation (with and without supervision), and (3) an exception manager for detecting and recovering from exceptions. We use a formal framework to specify design patterns and exceptions. RESULTS: We have proved using Owicki-Gries Theory that the proposed patterns satisfy the properties that characterize service assignment and delegation in terms of competence, responsibility and accountability in normal and abnormal (exceptional) scenarios. We show that although abstract, the proposed patterns can be instantiated in an executable COGENT prototype, and can be mapped into the Tallis tool that enacts PROforma language specifications of medical guidelines. CONCLUSIONS: The proposed patterns are generic and abstract enough to capture the normal and abnormal scenarios of assignment and delegation of tasks in collaborative work in health care teams.

Towards a unified process model for graphemic buffer disorder and deep dysgraphia.

Models based on the competitive queuing (CQ) approach can explain many of the effects on dysgraphic patients' spelling attributed to disruption of the "graphemic output buffer". Situating such a model in the wider spelling system, however, raises the question of what happens when input to the buffer (e.g., from a semantic system) is degraded while the buffer remains intact. We present a preliminary exploration of predictions following from the CQ approach. We show that the CQ account of the graphemic buffer predicts and explains the finding that deep dysgraphic patients generally show features of graphemic buffer disorder, as disrupted input from a damaged semantic system has an inevitable effect upon the functioning of the buffer. The approach also explains the most salient differences between the two syndromes, which are seen as consequences of the difference between an intact sequence generation system operating on degraded input versus a damaged sequencing system operating on intact input.