The few touch digital diabetes diary : user-involved design of mobile self-help tools for peoplewith diabetes

Paper number 2, 4, 5 and 7 are not available in Munin, due to publishers' restrictions: 2. Årsand E, and Demiris G.: "User-Centered Methods for Designing Patient-Centric Self-Help Tools", Informatics for Health and Social Care, 2008 Vol. 33, No. 3, Pages 158-169 (Informa Healthcare). Available at http://dx.doi.org/10.1080/17538150802457562 4. Årsand E, Olsen OA, Varmedal R, Mortensen W, and Hartvigsen G.: "A System for Monitoring Physical Activity Data Among People with Type 2 Diabetes", pages 173-178 in S.K. Andersen, et.al. (eds.) "eHealth Beyond the Horizon - Get IT There", Proceedings of MIE2008, Studies in Health Technology and Informatics, Volume 136, May 2008, ISBN: 978-1-58603-864-9 5. Årsand E, Tufano JT, Ralston J, and Hjortdahl P.: "Designing Mobile Dietary Management Support Technologies for People with Diabetes", Journal of Telemedicine and Telecare, 2008 Volume 14, Number 7, Pp. 329-332 (Royal Society of Medicine Press). Available at http://dx.doi.org/10.1258/jtt.2008.007001 7. Årsand E, Walseth OA, Andersson N, Fernando R, Granberg O, Bellika JG, and Hartvigsen G.: "Using Blood Glucose Data as an Indicator for Epidemic Disease Outbreaks", pages 199-204 in R. Engelbrecht et.al. (eds.): "Connecting Medical Informatics and Bio-Informatics", Proceedings of MIE2005, Studies in Health Technology and Informatics, Volume 116, August 2005, ISBN: 978-1-58603-549-5. Check availabilityParadoxically, the technological revolution that has created a vast health problem due to a drastic change in lifestyle also holds great potential for individuals to take better care of their own health. The first consequence is not addressed in this dissertation, but the second represents the focus of the work presented, namely utilizing ICT to support self-management of individual health challenges. As long as only 35% of the patients in Norway achieve the International Diabetes Federation‟s goal for blood glucose (HbA1c), actions and activities to improve blood glucose control and related factors are needed. The presented work focuses on the development and integration of alternative sensor systems for blood glucose and physical activity, and a fast and effortless method for recording food habits. Various user-interface concepts running on a mobile terminal constitute a digital diabetes diary, and the total concept is referred to as the “Few Touch application”. The overall aim of this PhD project is to generate knowledge about how a mobile tool can be designed for supporting lifestyle changes among people with diabetes. Applying technologies and methods from the informatics field has contributed to improved insight into this issue. Conversely, addressing the concrete use cases for people with diabetes has resulted in the achievement of ICT designs that have been appreciated by the cohorts involved. Cooperation with three different groups of patients with diabetes over several years and various methods and theories founded in computer science, medical informatics, and telemedicine have been combined in design and research on patient-oriented aids. The blood glucose Bluetooth adapter, the step counter, and the nutrition habit registration system that have been developed were all novel and to my knowledge unique designs at the time they were first tested, and this still applies to the latter two. Whether it can be claimed that the total concept presented, the Few Touch application, will increase quality of life, is up to future research and large-scale tests of the system to answer. However, results from the Type 2 diabetes half-year study showed that several of the participants did adjust their medication, food habits and/or physical activity due to use of the application

Advising patients on selecting trustful apps for diabetes self-care

BACKGROUND: There has been a dramatic increase in mobile apps for diabetes self-care. However, their quality is not guaranteed and patients do not have the appropriate tools for careful evaluation. OBJECTIVE: This work aims to propose a tool to help patients with diabetes select an appropriate app for self-care. METHODS: After identifying the conceptual framework of diabetes self-care, we searched Apple US app store and reviewed diabetes self-care apps, considering both generic and diabetes-specific features. Based on an existing tool for representing the benefits and weaknesses of medical apps, we created the pictorial identification schema/Diabetes Self-care tool, which specifically identified medical apps in the diabetes domain. RESULTS: Of the 952 apps retrieved, 67 were for diabetes self-care, while 26 were excluded because they were not updated in the last 12 months. Of the remaining 41, none cost more than 15 USD, and 36 implemented manual data entry. Basic features (data logging, data representation, and data delivery) were implemented in almost all apps, whereas advanced features (e.g., insulin calculator) were implemented in a small percentage of apps. The pictorial identification schema for diabetes was completed by one patient and one software developer for 13 apps. Both users highlighted weaknesses related to the functionalities offered and to their interface, but the patient focused on usability, whereas the software developer focused on technical implementation. CONCLUSIONS: The Pictorial Identification Schema/Diabetes Self-care is a promising graphical tool for perceiving the weaknesses and benefits of a diabetes self-care app that includes multiple user profile perspectives

mHealth: opportunities and challenges for diabetes intervention research

Background: Traditionally, health intervention evaluations provide long-term evidence of efficacy and safety via validated protocols, following a positivist paradigm, or approach, to research. However, modern mobile health (mHealth) technologies develop too quickly and outside of medical regulation, making it challenging for health research to keep pace. Objective: This thesis explored and tested how research can incorporate mHealth approaches and resources to evaluate mHealth interventions comprehensively, which follows the pragmatism paradigm. The works described herein were part of a larger project that designed, developed, and tested a data-sharing system between patients and their healthcare providers (HCPs) during diabetes consultations. Methods: The pragmatism paradigm underpins the mixed-methods, multi-phase design approach to exploring this overall objective. The following methods were performed using a sequential exploratory strategy. First, co-design workshops invited individuals with diabetes and HCPs to design an mHealth data-sharing system. Next, a scoping literature review identified research practices for evaluating mHealth interventions to-date. Then, app usage-logs, collected from a previous longitudinal study, were analyzed to explore how much additional information they could provide about patients’ self-management. Finally, a mixed-method study was designed to test the feasibility of combining both traditional and mHealth approaches and resources to evaluate an intervention. Results: Using the pragmatist paradigm as a scaffolding, these works provide evidence of how research can provide more comprehensive knowledge about mHealth interventions for diabetes care and self-management. Nine individuals with diabetes and six HCPs participated in the co-design workshops. Feedback included how a data-sharing system should work between patients and providers. The literature review identified how both traditional and mHealth-based approaches (n=15 methods, n=21 measures) were used together to evaluate mHealth interventions. Usage-log analysis revealed that changes in Glycosylated haemoglobin (HbA1c) differed between groups organized by usage patterns and duration of use of mHealth. The mixed-method study demonstrated how to collect comprehensive and complementary information when combining traditional and mHealth-centered approaches and resources. Conclusion: Traditional positivist approaches and resources are not adequate, on their own, to comprehensively understand the impact of mHealth interventions. The presented studies demonstrate that it is both feasible and prudent to combine traditional research with mHealth approaches, such as analyzing usage-logs, arranging co-design workshops, and other patient-centered methods in a pragmatist approach to produce comprehensive evidence of mHealth’s impacts on both patients and HCPs

State-of-the-art and User Requirements of Blood Glucose Measurement: Devices, Software and Services.

Diabetes on jatkuvasti yleistyvä sairaus, joka vaatii yleisesti säännölliset verensokerin omamittaukset. Tämä Diplomityö tutkii verensokerimittauksen nykytilaa ja käyttäjätarpeita.. Erityisesti työ keskittyy verensokerimittareihin, verensokerimittauksen apuohjelmiin, sekä diabeteksen hoitosuosituksiin ja -käytäntöihin. Diplomityössä käsittellään lisäksi laadukkaan verensokerimittauksen määrittelyä Nykytilan analyysi perustuu valtaosin kirjallisuustutkimuksiin. Käyttäjätarpeiden kartoitus perustuu puolistrukturoituihin haastatteluihin. Haastatteluaineisto pohjautuu 8:aan haastatteluun, jossa haastateltiin kolmen eri käyttäjäryhmä edustajia: lääkäreitä, hoitajia ja diabeetikoita. Näiden käyttäjäryhmien käyttäjätarpeet ovat hyvin yhteneviä. Nykyiset verensokerimittauksen laitteet ja palvelut vastaavat hyvälaatuisen verensokerihallinnan vähimmäisvaatimuksiin. Nykyiset laitteet ja palvelut eivät vastaa Diplomityön esittelemiä vaativampia käyttäjätarpeita. Laitteiden ja palveluiden tulisi ola nykyistä kokonaisvaltaisempia ja integroituneita. Yksi verensokerimittauksen suurimmista haasteista on potilaan motivaatio mittausten laadukkaaseen läpivientiin. Potilaan motivaatioon vaikuttavien tekijöiden selvittäminen on yksi mielenkiintoinen jatkotutkimuksen aihe.Diabetes is an increasingly common illness that often requires regular measurement of Blood Glucose (BG). This Thesis discusses the state-of-the-art and user requirements of BG measurement, focusing on: BG meters, diabetes management software, and diabetes treatment guidelines and practices. Additionally, BG measurement quality definitions are discussed. The discussion on the state-of-the-art presented is primarily based on literature research. The requirements study is based on the results of a semi-structured interview of 8 subjects. The requirements of three user groups are discussed, i.e. doctors, nurses and diabetics. The requirements of the user groups are significantly similar. The current supply of BG measuring devices and services provides the bare minimum required for good quality BG measurement. The more advanced requirements elicited in this Thesis are mostly not met. The BG measuring devices and services are thus required to be more comprehensive and integrated. One of the key issues with BG measurement is motivating the diabetics to perform good quality measurements. Interesting topics for further research include the factors affecting patients’ motivation

HOLMeS: eHealth in the Big Data and Deep Learning Era

Now, data collection and analysis are becoming more and more important in a variety of application domains, as long as novel technologies advance. At the same time, we are experiencing a growing need for human–machine interaction with expert systems, pushing research toward new knowledge representation models and interaction paradigms. In particular, in the last few years, eHealth—which usually indicates all the healthcare practices supported by electronic elaboration and remote communications—calls for the availability of a smart environment and big computational resources able to offer more and more advanced analytics and new human–computer interaction paradigms. The aim of this paper is to introduce the HOLMeS (health online medical suggestions) system: A particular big data platform aiming at supporting several eHealth applications. As its main novelty/functionality, HOLMeS exploits a machine learning algorithm, deployed on a cluster-computing environment, in order to provide medical suggestions via both chat-bot and web-app modules, especially for prevention aims. The chat-bot, opportunely trained by leveraging a deep learning approach, helps to overcome the limitations of a cold interaction between users and software, exhibiting a more human-like behavior. The obtained results demonstrate the effectiveness of the machine learning algorithms, showing an area under ROC (receiver operating characteristic) curve (AUC) of 74.65% when some first-level features are used to assess the occurrence of different chronic diseases within specific prevention pathways. When disease-specific features are added, HOLMeS shows an AUC of 86.78%, achieving a greater effectiveness in supporting clinical decisions

Development and evaluation of a microservice-based virtual assistant for chronic patients support

Los asistentes virtuales (también conocidos como chatbots) son programas que interactúan con los usuarios simulando una conversación humana a través de mensajes de texto o de voz. Los asistentes virtuales destinados al cuidado de la salud ofrecen servicios, herramientas, asesoramiento, ayuda, soporte y gestión de diferentes enfermedades. Los usuarios de este tipo de asistente virtual pueden ser, por ejemplo, pacientes, cuidadores y profesionales sanitarios, los cuales poseen diferentes necesidades y requerimientos. Los pacientes con enfermedades crónicas podrían beneficiarse de los asistentes virtuales que se encargan de realizar seguimientos de su condición, proporcionar información específica, fomentar la adherencia a la medicación, etc. Para realizar estas funciones, los asistentes virtuales necesitan una arquitectura de software adecuada. Esta tesis doctoral propone el diseño de una arquitectura específica para el desarrollo de asistentes virtuales destinados a proporcionar soporte a pacientes crónicos. Hoy en día, las personas interactúan entre sí diariamente utilizando plataformas de mensajería. Para alinear este tipo de interacción con la arquitectura del asistente virtual, proponemos el uso de plataformas de mensajería para la interacción asistente virtual-paciente, prestando especial atención a las cuestiones de seguridad y privacidad (es decir, el uso de plataformas de mensajería seguras con cifrado de extremo a extremo).Los asistentes virtuales pueden implementar sistemas conversacionales para que la interacción con los pacientes sea más natural. Los sistemas conversacionales en escenarios de atención médica complejos, como la gestión de enfermedades, deben ser capaces de poder comprender oraciones complejas utilizadas durante la interacción. La adaptación de nuevos métodos con el procesamiento de lenguaje natural (NLP, por su nombre en inglés, Natural Language Processing) puede aportar una mejora a la arquitectura del asistente virtual. Los word embeddings (incrustación de palabras) se han utilizado ampliamente en NLP como entrada en las redes neuronales. Tales word embeddings pueden ayudar a comprender el objetivo final y las palabras clave en una oración. Por ello, en esta tesis estudiamos el impacto de diferentes word embeddings entrenados con corpus generales y específicos utilizando el entendimiento del lenguaje natural conjunto (Joint NLU, por su nombre en inglés, Joint Natural Language Understanding) en el dominio de la medicación en español. Los datos para entrenar el modelo NLU conjunto se generan usando plantillas. Dicho modelo se utiliza para la detección de intenciones, así como para el slot filling (llenado de ranuras). En este estudio comparamos word2vec y fastText como word embeddings y ELMo y BERT como modelos de lenguaje. Para entrenar los embeddings utilizamos tres corpus diferentes: los datos de entrenamiento generados para este escenario, la Wikipedia en español como dominio general y la base de datos de medicamentos en español como datos especializados. El mejor resultado se obtuvo con el modelo ELMo entrenado con Wikipedia en español.Dotamos al asistente virtual de capacidades de gestión de medicamentos basadas en NLP. En consecuencia, se analiza el impacto del etiquetado de slots y la longitud de los datos de entrenamiento en modelos NLU conjuntos para escenarios de gestión de medicamentos utilizando asistentes virtuales en español. En este estudio definimos las intenciones (propósitos de las oraciones) para escenarios centrados en la administración de medicamentos y dos tipos de etiquetas de slots. Para entrenar el modelo, generamos cuatro conjuntos de datos, combinando oraciones largas o cortas con slots largos o cortos. Para el análisis comparativo, elegimos seis modelos NLU conjuntos (SlotRefine, stack-propagation framework, SF-ID network, capsule-NLU, slot-gated modeling y joint SLU-LM) de la literatura existente. Tras el análisis competitivo, se observa que el mejor resultado se obtuvo utilizando oraciones y slots cortos. Nuestros resultados sugirieron que los modelos NLU conjuntos entrenados con slots cortos produjeron mejores resultados que aquellos entrenados con slots largos para la tarea de slot filling.En definitiva, proponemos una arquitectura de microservicios genérica válida para cualquier tipo de gestión de enfermedades crónicas. El prototipo genérico ofrece un asistente virtual operativo para gestionar información básica y servir de base para futuras ampliaciones. Además, en esta tesis presentamos dos prototipos especializados con el objetivo de mostrar cómo esta nueva arquitectura permite cambiar, añadir o mejorar diferentes partes del asistente virtual de forma dinámica y flexible. El primer prototipo especializado tiene como objetivo ayudar en la gestión de la medicación del paciente. Este prototipo se encargará de recordar la ingesta de medicamentos a través de la creación de una comunidad de apoyo donde los pacientes, cuidadores y profesionales sanitarios interactúen con herramientas y servicios útiles ofrecidos por el asistente virtual. La implementación del segundo prototipo especializado está diseñada para una enfermedad crónica específica, la psoriasis. Este prototipo ofrece teleconsulta y almacenamiento de fotografías.Por último, esta tesis tiene como objetivo validar la eficacia del asistente virtual integrado en las plataformas de mensajería, destinado al cuidado de la salud. Por ello, esta tesis incluye la evaluación de los dos prototipos especializados. El primer estudio tiene como objetivo mejorar la adherencia a la medicación en pacientes con diabetes mellitus tipo 2 comórbida y trastorno depresivo. Para ello, se diseñó y posteriormente se realizó un estudio piloto de nueve meses. En el estudio analizamos la Tasa de Posesión de Medicamentos (MPR, por su nombre en inglés, Medication Possession Ratio), obtuvimos la puntuación del Cuestionario sobre la Salud del Paciente (PHQ-9, por su nombre en inglés, Patient Health Questionnaire) y medimos el nivel de hemoglobina glicosilada (HbA1c), en los pacientes antes y después del estudio. También realizamos entrevistas a todos los participantes. Un total de trece pacientes y cinco enfermeras utilizaron y evaluaron el asistente virtual propuesto. Los resultados mostraron que, en promedio, la adherencia a la medicación de los pacientes mejoró. El segundo estudio tiene como objetivo evaluar un año de uso entre el asistente virtual y pacientes con psoriasis y dermatólogos, y el impacto en su calidad de vida. Para ello se diseñó y realizó un estudio prospectivo de un año de duración con pacientes con psoriasis y dermatólogos. Para medir la mejora en la calidad de vida, en este estudio analizamos los cuestionarios de Calidad de Vida de los Pacientes con Psoriasis (PSOLIFE, por su nombre en inglés, Psoriasis Quality of Life) y el Índice de Calidad de Vida en Dermatología (DLQI, por su nombre en inglés, Dermatology Life Quality Index). Además, realizamos encuestas a todos los participantes y obtuvimos el número de consultas médicas realizadas a través del asistente virtual. Se incluyeron en el estudio un total de 34 participantes (30 pacientes diagnosticados con psoriasis moderada-grave y cuatro profesionales sanitarios). Los resultados mostraron que, en promedio, la calidad de vida mejoró.<br /