PaperChain: A Collaborative Healthcare System Grounded in Field Study Work

In this extended abstract we summarise our recent experiences of designing and deploying PaperChain, a system to support real-time information sharing in healthcare work. A guiding principle has been the development of a deep understanding of the work as the foundation for effective system design. We summarise the field work that motivated the development of PaperChain, some of the key findings and the resulting system. We briefly reflect on the benefits gained from undertaking substantial HCI work in the design of a healthcare system

New hardware platforms for healthcare consultations

Innovative hardware platforms such as Mobile Clinical Assistants and tabletop computers are emerging that have the potential to significantly impact the interaction between clinician and patient. This position paper describes the results of interviews undertaken with General Practitioners as part of an experimental study to explore how innovative hardware platforms impact patient-clinician communication. We reflect on the lessons learnt from the study, both in terms of the implications for the design of such studies and possible directions for the introduction of new hardware technologies into healthcare consultations

A Novel Approach to Improve the Planning of Adaptive and Interactive Sessions for the treatment of Major Depression

[EN] Human Computer Interaction (HCI) is a research field which aims to improve the relationship between users and interactive computer systems. A main objective of this research area is to make the user experience more pleasant and efficient, minimizing the barrier between the users' cognition of what they want to accomplish and the computer's understanding of the user's tasks, by means of userfriendly, useful and usable designs. A bad HCI design is one of the main reasons behind user rejection of computer-based applications, which in turn produces loss of productivity and economy in industrial environments. In the eHealth domain, user rejection of computer-based systems is a major barrier to exploiting the maximum benefit from those applications developed to support the treatment of diseases, and in the worst cases a poor design in these systems may cause deterioration in the clinical condition of the patient. Thus, a high level of personalisation of the system according to users' needs is extremely important, making it easy to use and contributing to the system's efficacy, which in turn facilitates the empowerment of the target users. Ideally, the content offered through the interactive sessions in these applications should be continuously assessed and adapted to the changing condition of the patient. A good HCI design and development can improve the acceptance of these applications and contribute to promoting better adherence levels to the treatment, preventing the patient from further relapses. In this work, we present a mechanism to provide personalised and adaptive daily interactive sessions focused on the treatment of patients with Major Depression. These sessions are able to automatically adapt the content and length of the sessions to obtain personalised and varied sessions in order to encourage the continuous and long-term use of the system. The tailored adaptation of session content is supported by decision-making processes based on: (i) clinical requirements; (ii) the patient's historical data; and (iii) current responses from the patient. We have evaluated our system through two different methodologies: the first one performing a set of simulations producing different sessions from changing input conditions, in order to assess different levels of adaptability and variability of the session content offered by the system. The second evaluation process involved a set of patients who used the system for 14 to 28 days and answered a questionnaire to provide feedback about the perceived level of adaptability and variability produced by the system. The obtained results in both evaluations indicated good levels of adaptability and variability in the content of the sessions according to the input conditions.E. Fuster Garcia acknowledges the financial support from the "Torres Quevedo" program (Spanish Ministry of Economy and Competitiveness) co-funded by the European Social Fund (PTQ-12-05693), and the financial support from the Universitat Politecnica de Valencia under the Grant "Ayudas Para la Contratacion de Doctores para el Acceso al Sistema Espanol de Ciencia, Tecnologia e Innovacion" (PAID-10-14).Bresó Guardado, A.; Martínez Miranda, JC.; Fuster García, E.; García Gómez, JM. (2016). A Novel Approach to Improve the Planning of Adaptive and Interactive Sessions for the treatment of Major Depression. International Journal of Human-Computer Studies. 87:80-91. https://doi.org/10.1016/j.ijhcs.2015.11.003S80918

Front Pharmacol

Pharmacovigilance consists in monitoring and preventing the occurrence of adverse drug reactions. This activity can be time-consuming because it requires the collection of both patient and medication information. In this paper, we present two visualization and data mining applications to make this task easier for the practitioner. These tools have been developed and tested using the biomedical data warehouse eHOP (Hospital Biomedical Data Warehouse) of the Rennes University Hospital Centre. The first application is a tool to visualize the patient electronic health record in the form of a timeline. All patient data is collected and displayed chronologically. The usability test of the timeline has been very positive (SUS score: 82.5) and the tool is now available for practitioners in their daily practice. The second application is a tool to visualize and search the sequences of a patient cohort. The visual interface allow user to quickly visualize sequences. A query builder allows user to search for sequences in relation with a reference sequence, such as a prescription sequence followed by an abnormal biological value. The sequences are then visually aligned with this reference sequence and ranked by similarity. The GSP (Generalized Sequential Pattern) and Apriori algorithms allow us to display a summary of the sequences list by searching for common sequences and associations. The tool was tested on a use case which consisted in detection of inappropriate drug administration. Compared to a random order, we showed this ranking system saved the practitioner time in this task (to analyze one sequence, 3.49 +/- 3.54 vs. 2.26 +/- 2.86 s, p = 0.0003). These two visualization and data mining applications will help the daily practice of pharmacovigilance

QOC-E: A mediating representation to support the development of shared rationale and integration of Human Factors advice

Designing and manufacturing medical devices is a complex and specialist effort. Throughout the process, there is an opportunity to consult across those involved in various aspects of development (for example Human Factors (HF), Human Computer Interaction (HCI), Design and Manufacture). Developers report difficulties in this area, speaking of isolated team members and organizational / cultural barriers. We illustrate the use of a mediating representation (Questions, Options, Criteria and Evidence – QOC-E) that promotes shared reasoning and can be used to capture design rationale. Application is demonstrated using an illustrative example involving the specification of a number entry mechanism. The benefits of the QOC scheme include making tacit reasoning explicit, articulation of trade-offs, traceability, allowing compartmentalization of the design and avoidance of fixation in any one particular area. Downsides include the fact that the representation may require prohibitive amounts of effort to maintain or fail to scale to large or complex systems. These issues are discussed and directions for further investigation outlined

Generic data processing & analysis architecture of a personal health system to manage daily interactive sessions in patients with major depression

[EN] The World Health Organization (WHO) considers Major Unipolar Depression as a significant cause of disability worldwide (globally, more than 350 million people of all ages suffer from depression). This common mental disorder spends many economic and clinical resources and it is sometimes responsible for patient suicides. The work presented in this Master Thesis document describes the design and implementation of a generic Data Processing & Analysis module which has been included within the Personal Health System developed in the Help4Mood Research European Project [FP7 ICT-248765]. The aim of Help4Mood is to develop a computational distributed system to support the treatment of people with Major Depression in the community. It is focused on reducing depressive symptoms, improving functioning, and preventing the recurrence of symptoms in the future. The developed Data Processing & Analysis module is the mechanism responsible of: i) The analysis of the objective and subjective inputs received from the user; ii) The inference of clinical concepts and the production of a set of activities to be suggested by the system during the treatment of depression; iii) The planning of the most appropriate interactive sessions based on the inferred activities; iv) The generation of adequate emotional responses represented in the Help4Mood¿s Virtual Agent to better engages the patient with the use of the system and to facilitate a better adherence to the treatment process; and v) The summarization of the relevant clinical information about the progress of the patient every week. The results of this work suggests that the generic Data Processing & Analysis module is useful for managing flexible and personalised sessions in the treatment of the depression, and it is able to be adapted to other clinical domains. It provides a systematic framework for data collection, processing and analysis which improves the continuous monitoring and treatment of the patients. Additionally, our module improves the communication between patients and clinicians by facilitating the joint reflexion about the evolution and improvements in wellbeing at the different stages of the treatment[ES] La Organización Mundial de la Salud (OMS) considera la Depresión Mayor Unipolar como una causa significativa de discapacidad mundial (más de 350 millones de personas de todas las edades padecen depresión). Esta común enfermedad mental consume muchos recursos económicos y clínicos y en ocasiones es responsable de suicidios de pacientes. El trabajo presentado en esta Tesina de Máster describe el diseño y la implementación de un módulo genérico de Procesado y Análisis de Datos, el cual ha sido incluido en el Sistema Personal de Salud desarrollado en el proyecto de investigación Europeo Help4Mood [FP7 ICT-248765]. El propósito de Help4Mood es el desarrollo de un sistema computacional distribuido que de soporte al tratamiento de personas con Depresión Mayor. Se centra en la reducir los síntomas de la depresión, mejorar el funcionamiento, y en prevenir la futura reaparición de los síntomas. El módulo de Procesado y Análisis de Datos desarrollado es el responsable de: i) El análisis de los datos objetivos y subjetivos recibidos por parte del usuario del sistema; ii) La inferencia de conceptos clínicos y la producción de un conjunto de actividades que serán propuestas por el sistema durante el tratamiento de la depresión; iii) La planificación de la sesión interactiva más apropiada basada en las actividades inferidas; iv) La generación de una respuesta emocional adecuada que el Agente Virtual de Help4Mood muestre para lograr una mayor participación de los usuarios en el uso del sistema y una mejor adherencia al proceso del tratamiento; y v) El resumen de la información clínica relevante sobre el progreso semanal del paciente. Los resultados de este trabajo sugieren que el módulo genérico de Procesado y Análisis de Datos es útil para la gestión flexible y personalizada de sesiones diarias para el tratamiento de la Depresión, además podría ser adaptada a otros dominios clínicos. Este módulo proporciona un marco sistemático para la recopilación, procesamiento y análisis que permite mejorar el control continuo y el tratamiento de los pacientes. Adicionalmente, nuestro módulo mejora la comunicación entre los pacientes y los médicos, facilitando la reflexión conjunta sobre la evolución y las mejoras en el bienestar en las diferentes etapas del tratamiento.Bresó Guardado, A. (2013). Generic data processing & analysis architecture of a personal health system to manage daily interactive sessions in patients with major depression. http://hdl.handle.net/10251/39155Archivo delegad

Think! Interactive Systems Need Safety Locks

This paper uses a simple analogy. A gun is designed to shoot bullets, but it is obvious that accidentally shooting is a danger one should avoid if at all possible. Thus guns have safety locks, which aim to protect users and bystanders. Interactive computer systems sometimes accidentally do bad things too, but something like “safety locks” are not often enough implemented to help protect users or bystanders from harm. Worse, user interfaces often behave quite unpredictably with erroneous input — rather than blocking errors and requiring the user to correct them. This is a bit like guns that misbehave. Computers and computers embedded in everyday devices are not always as dangerous as guns, although there are many cases where they can be as dangerous. Medical devices may give patients undetected overdoses. In-car entertainment devices, like radios, may, through their badly-designed user interfaces, cause a driver to have an accident. A slip in a spreadsheet may be the first step towards an organisation going bankrupt. And so on. The solution should include better design, including the concept of safety locks, that block some forms of user error