Including patient-generated health data in electronic health records – a solution for CGM-data

Patients with diabetes and health personnel do not have an optimal way of interacting. Health personnel must use multiple ICT systems, such as third-party companies’ services, to access health-related data from diverse vendors’ CGM platforms and Electronic Health Record (EHR). Furthermore, other health-related data like physical activities, quality of life or well-being is often discussed but rarely stored inside the EHR system. We propose a future-proof architecture for diabetes medical consultation using the HL7 Fast Healthcare Interoperability Resources (FHIR) standard

Information and communication technology-based interventions for chronic diseases consultation: Scoping review

Background: Medical consultations are often critical meetings between patients and health personnel to provide treatment, health-management advice, and exchange of information, especially for people living with chronic diseases. The adoption of patient-operated Information and Communication Technologies (ICTs) allows the patients to actively participate in their consultation and treatment. The consultation can be divided into three different phases: before, during, and after the meeting. The difference is identified by the activities in preparation (before), the meeting, conducted either physically or in other forms of non-face-to-face interaction (during), and the follow-up activities after the meeting (after). Consultations can be supported by various ICT-based interventions, often referred to as eHealth, mHealth, telehealth, or telemedicine. Nevertheless, the use of ICTs in healthcare settings is often accompanied by security and privacy challenges due to the sensitive nature of health information and the regulatory requirements associated with storing and processing sensitive information. Objective: This scoping review aims to map the existing knowledge and identify gaps in research about ICT-based interventions for chronic diseases consultations. The review objective is guided by three research questions: (1) which ICTs are used by people with chronic diseases, health personnel, and others before, during, and after consultations; (2) which type of information is managed by these ICTs; and (3) how are security and privacy issues addressed? Methods: We performed a literature search in ACM, IEEE, PubMed, Scopus, and Web of Science and included primary studies published between January 2015 and June 2020 that used ICT before, during, and/or after a consultation for chronic diseases. This review presents and discusses the findings from the included publications structured around the three research questions. Results: Twenty-four studies met the inclusion criteria. Only five studies reported the use of ICTs in all three phases: before, during, and after consultations. The main ICTs identified were smartphone applications, webbased portals, cloud-based infrastructures, and electronic health record systems. Different devices like sensors and wearable devices were used in 23 studies to gather diverse information. Regarding the type of information managed by these ICTs, we identified nine categories: physiological data, treatment information, medical history, consultation media like images or videos, laboratory results, reminders, lifestyle parameters, symptoms, and patient identification. Security issues were addressed in 20 studies, while only eight of the included studies addressed privacy issues. Conclusions: This scoping review highlights the potential for a new model of consultation for patients with chronic diseases. Furthermore, it emphasizes the possibilities for consultations besides physical and remote meetings

Privacy Concerns Related to Data Sharing for European Diabetes Devices

Background: Individuals with diabetes rely on medical equipment (eg, continuous glucose monitoring (CGM), hybrid closed-loop systems) and mobile applications to manage their condition, providing valuable data to health care providers. Data sharing from this equipment is regulated via Terms of Service (ToS) and Privacy Policy documents. The introduction of the Medical Devices Regulation (MDR) and In Vitro Diagnostic Medical Devices Regulation (IVDR) in the European Union has established updated rules for medical devices, including software. Objective: This study examines how data sharing is regulated by the ToS and Privacy Policy documents of approved diabetes medical equipment and associated software. It focuses on the equipment approved by the Norwegian Regional Health Authorities. Methods: A document analysis was conducted on the ToS and Privacy Policy documents of diabetes medical equipment and software applications approved in Norway. Results: The analysis identified 11 medical equipment and 12 software applications used for diabetes data transfer and analysis in Norway. Only 3 medical equipment (OmniPod Dash, Accu-Chek Insight, and Accu-Chek Solo) were registered in the European Database on Medical Devices (EUDAMED) database, whereas none of their respective software applications were registered. Compliance with General Data Protection Regulation (GDPR) security requirements varied, with some software relying on adequacy decisions (8/12), whereas others did not (4/12). Conclusions: The study highlights the dominance of non-European Economic Area (EEA) companies in medical device technology development. It also identifies the lack of registration for medical equipment and software in the EUDAMED database, which is currently not mandatory. These findings underscore the need for further attention to ensure regulatory compliance and improve data-sharing practices in the context of diabetes management

The House of Carbs: Personalized Carbohydrate Dispenser for People with Diabetes

Patients with diabetes are often worried about having low blood glucose because of the unpleasant feeling and possible dangerous situations this can lead to. This can make patients consume more carbohydrates than necessary. Ad-hoc carbohydrate estimation and dosing by the patients can be unreliable and may produce unwanted periods of high blood glucose. In this paper we present a system that automatically estimates and dispenses the amount of juice (or similar) according to the current patients’ blood glucose values. The system is remotely accessible and customizable from a chatbot, exploits sensors and actuators to dispense the necessary amount of liquid carbohydrates. It relies on a cloud solution (Nightscout) to acquire the patient’s blood glucose values, which are constantly updated thanks to a commercial wearable continuous glucose monitor (CGM)

Towards a New Model for Chronic Disease Consultations

Medical consultations for chronic diseases form an arena to provide information from health personnel to patients. This information is necessary for patients to understand how to deal with the possible lifelong symptoms and needed self-management activities. The amount of patient-generated health data is increasing. Today’s patients gather an increasing amount of personalised health-related information. Meanwhile, the health personnel get more patients to care for and fewer resources. This paper summarises information and communication technologies possibilities for improved diabetes consultations. It aims to inform how the medical consultation for chronic diseases needs to change drastically to meet today and future’s challenges

Methods and Evaluation Criteria for Apps and Digital Interventions for Diabetes Self-Management: Systematic Review

Background: There is growing evidence that apps and digital interventions have a positive impact on diabetes self-management. Standard self-management for patients with diabetes could therefore be supplemented by apps and digital interventions to increase patients’ skills. Several initiatives, models, and frameworks suggest how health apps and digital interventions could be evaluated, but there are few standards for this. And although there are many methods for evaluating apps and digital interventions, a more specific approach might be needed for assessing digital diabetes self-management interventions. Objective: This review aims to identify which methods and criteria are used to evaluate apps and digital interventions for diabetes self-management, and to describe how patients were involved in these evaluations. Methods: We searched CINAHL, EMBASE, MEDLINE, and Web of Science for articles published from 2015 that referred to the evaluation of apps and digital interventions for diabetes self-management and involved patients in the evaluation. We then conducted a narrative qualitative synthesis of the findings, structured around the included studies’ quality, methods of evaluation, and evaluation criteria. Results: Of 1681 articles identified, 31 fulfilled the inclusion criteria. A total of 7 articles were considered of high confidence in the evidence. Apps were the most commonly used platform for diabetes self-management (18/31, 58%), and type 2 diabetes (T2D) was the targeted health condition most studies focused on (12/31, 38%). Questionnaires, interviews, and user-group meetings were the most common methods of evaluation. Furthermore, the most evaluated criteria for apps and digital diabetes self-management interventions were cognitive impact, clinical impact, and usability. Feasibility and security and privacy were not evaluated by studies considered of high confidence in the evidence. Conclusions: There were few studies with high confidence in the evidence that involved patients in the evaluation of apps and digital interventions for diabetes self-management. Additional evaluation criteria, such as sustainability and interoperability, should be focused on more in future studies to provide a better understanding of the effects and potential of apps and digital interventions for diabetes self-management

Crystal clustering in magmas: Insights from HP–HT experiments

International audienceWe have studied by high-resolution X-ray Computed Tomography the effect of crystal clustering on the Shape-Preferred Orientation (SPO) development in synthetic magmas experimentally deformed at 300 MPa and 475–550°C. A fully connected solid network that could potentially induce the onset of yield strength is not achieved in these suspensions containing 16 vol% of crystals. The alumina grain population exhibits a glomeroporphyritic texture made of isolated grains (59.6%) and clusters of touching grains (40.4%). The SPO of the sub-population of isolated grains exhibits foliation and lineation, which are closely parallel to the plane and direction of shear, respectively. The SPO of clustered grains has little influence overall shape fabric. The angular relationships between the average foliation and cluster elongation provide a good indicator of the shear sense. Finally, we highlight the strain partitioning between nearly non-deformed large clusters acting as rigid glomerocrysts and highly sheared zones in low concentrated suspensions

Criteria for Assessing and Recommending Digital Diabetes Tools: A Delphi Study

Diabetes self-management, an integral part of diabetes care, can be improved with the help of digital self-management tools such as apps, sensors, websites, and social media. The study objective was to reach a consensus on the criteria required to assess and recommend digital diabetes self-management tools targeting those with diabetes in Norway. Healthcare professionals working with diabetes care from all health regions in Norway were recruited to participate in a three-round Delphi study. In all rounds, the panellists rated criteria identified in a systematic review and interviews on a scale from 0-10, with the option to provide comments. On a scale of 0:not important to 10:extremely important, the highest rated criteria for assessing and recommending digital diabetes self-management tools were “Usability” and “Information quality”, respectively. For assessing apps, “Security and privacy” was one of the lowest rated criteria. Having access to a list of criteria for assessing and recommending digital self-management tools can help diabetes care stakeholders to make informed choices in recommending and choosing suitable apps, websites, and social media for self-management. Future work on quality assessment of digital health tools should place emphasis on security and privacy compliance, to enable diabetes care stakeholders focus on other relevant criteria to recommend or choose and use such tools

Do diabetes mHealth and online interventions evaluate what is important for users?

Research often presents patient needs from perceptions of healthcare professionals and researchers. Today, patients can formulate tailored questions and seek solutions for what they need to self-manage in many ways. We aimed to compare reported outcomes of mHealth and online intervention studies for diabetes selfmanagement to patient-reported needs, from a systematic review and a literature review respectively. Although we found similarities between the reported outcomes and the patient-reported needs, research has yet to meet all patient needs. Comprehensive methods for development and testing of interventions should be explored to meet the specific needs of patients

Measuring the effects of sharing mHealth data during diabetes consultations: a mixed-method study protocol

Background: There is rising demand for health care’s limited resources. Mobile health (mHealth) could be a solution, especially for those with chronic illnesses such as diabetes. mHealth can increases patients’ options to self-manage their health, improving their health knowledge, engagement, and capacity to contribute to their own care decisions. However, there are few solutions for sharing and presenting patients’ mHealth data with health care providers (HCPs) in a mutually understandable way, which limits the potential of shared decision making. Objective: Through a six-month mixed method feasibility study in Norway, we aim to explore the impacts that a system for sharing patient-gathered data from mHealth devices has on patients and HCPs during diabetes consultations. Methods: Patients with diabetes will be recruited through their HCPs. Participants will use the Diabetes Diary mobile phone app to register and review diabetes self-management data and share these data during diabetes consultations using the FullFlow data-sharing system. The primary outcome is the feasibility of the system, which includes HCP impressions and expectations (prestudy survey), usability (System Usability Scale), functionalities used and data shared during consultations, and study-end focus group meetings. Secondary outcomes include a change in the therapeutic relationship, patient empowerment and wellness, health parameters (HbA1c and blood pressure), and the patients’ own app-registered health measures (blood glucose, medication, physical activity, diet, and weight). We will compare measures taken at baseline and at six months, as well as data continuously gathered from the app. Analysis will aim to explain which measures have changed and how and why they have changed during the intervention. Results: The Full Flow project is funded for 2016 to 2020 by the Research Council of Norway (number 247974/O70). We approached 14 general practitioner clinics (expecting to recruit 1-2 general practitioners per clinic) and two hospitals (expecting to recruit 2-3 nurses per hospital). By recruiting through the HCPs, we expect to recruit 74 patients with type 2 and 33 patients with type 1 diabetes. Between November 2018 and July 2019, we recruited eight patients and 15 HCPs. During 2020, we aim to analyze and publish the results of the collected data from our patient and HCP participants. Conclusions: We expect to better understand what is needed to be able to share data. This includes potential benefits that sharing patient-gathered data during consultations will have on patients and HCPs, both individually and together. By measuring these impacts, we will be able to present the possibilities and challenges related to a system for sharing mHealth data for future interventions and practice. Results will also demonstrate what needs to be done to make this collaboration between HCPs and patients successful and subsequently further improve patients’ health and engagement in their care