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Measuring the Effects of Sharing Mobile Health Data During Diabetes Consultations: Protocol for a Mixed Method Study.

ABSTRACT: 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.

SUBMITTER: Bradway M

PROVIDER: S-EPMC7055770 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Measuring the Effects of Sharing Mobile Health Data During Diabetes Consultations: Protocol for a Mixed Method Study.

Bradway Meghan M Giordanengo Alain A Joakimsen Ragnar R Hansen Anne Helen AH Grøttland Astrid A Hartvigsen Gunnar G Randine Pietro P Årsand Eirik E

JMIR research protocols 20200210 2

<h4>Background</h4>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 understandab ...[more]

PMID: 32039818

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Project description:ObjectiveThe potential for data collected in general practice to be linked and used to address health system challenges of maintaining quality care, accessibility and safety, including pandemic support, has led to an increased interest in public acceptability of data sharing, however practitioners have rarely been asked to share their opinions on the topic. This paper attempts to gain an understanding of general practitioner's perceptions on sharing routinely collected data for the purposes of healthcare planning and research. It also compares findings with data sharing perceptions in an international context. MATERIALS AND METHODS: A mixed methods approach combining an initial online survey followed by face-to-face interviews (before and during COVID-19), designed to identify the barriers and facilitators to sharing data, were conducted on a cross sectional convenience sample of general practitioners across Western Australia (WA).ResultsEighty online surveys and ten face-to-face interviews with general practitioners were conducted from November 2020 - May 2021. Although respondents overwhelmingly identified the importance of population health research, their willingness to participate in data sharing programs was determined by a perception of trust associated with the organisation collecting and analysing shared data; a clearly defined purpose and process of collected data; including a governance structure providing confidence in the data sharing initiative simultaneously enabling a process of data sovereignty and autonomy.DiscussionResults indicate strong agreement around the importance of sharing patient's medical data for population and health research and planning. Concerns pertaining to lack of trust, governance and secondary use of data continue to be a setback to data sharing with implications for primary care business models being raised.ConclusionTo further increase general practitioner's confidence in sharing their clinical data, efforts should be directed towards implementing a robust data governance structure with an emphasis on transparency and representative stakeholder inclusion as well as identifying the role of government and government funded organisations, as well as building trust with the entities collecting and analysing the data.

Project description:Diabetes is a common chronic condition affecting the many spheres of individuals' lives. It can also lead to severe complications without continuous management. Accordingly, this paper describes a study protocol aimed at 1) determining the status and prevalence of diabetes complications in a Northwestern Ontario community; 2) exploring the internal (e.g., demographic and clinical variables) and external factors (e.g., access to services and resources) affecting diabetes outcomes (e.g., complications, emergency room visits, hospitalizations); 3) critically exploring how the social determinants of health affect self-management for individuals living with diabetes; and 4) identifying individuals' needs, concerns, and challenges to monitor and regulate diabetes. The study uses a cross-sectional design and a social constructivist approach based on qualitative data collection. The proposed study will include patients with type 1 and type 2 diabetes with or without diabetes complications who have been attending the Centre for Complex Diabetes Care (CCDC) in Thunder Bay, Ontario, Canada, since January 2019. Quantitative data related to diabetes complications and other outcomes, diabetes management, and demographic and clinical status will be retrieved from patients' charts using a data extraction form. Analyses of the quantitative data will include the prevalence of diabetes complications, rate of hospitalizations, and their associations with diabetes management, access to services, and social determinants of health. Additionally, interviews will occur with at least 10 participants with or without diabetes complications to understand their needs, concerns, and struggle to self-manage diabetes daily. The results of this study will generate evidence to support future research and policy on the development and implementation of an educational program to improve self-care management and outcomes for individuals living with diabetes and its complications in Northwestern Ontario.

Project description:ObjectivesHealth information sharing continues to play a crucial yet underappreciated role in humanitarian settings, to guide evidence-based disease prevention, detection and response. We conducted a mixed-methods study to investigate and analyse existing approaches and practices to health information sharing across humanitarian settings over the past 20 years.SettingWe sought to identify studies from any self-described humanitarian setting worldwide, and also targeted experts familiar with refugee settings, specifically long-term camps in Kenya, Jordan and Bangladesh, for key informant interviews.ParticipantsThe systematic review did not directly involve participants. The identified reports were largely retrospective and observational, and focused on populations affected by humanitarian crises worldwide. Participants in the key informant interviews were experts with either broad geographical expertise or direct experience in refugee camp settings.Primary and secondary outcome measuresOur study was qualitative, and both the systematic review and analysis of key informant interview responses focused on identifying themes related to barriers, tools and recommendations used between stakeholders to share health information, with a particular emphasis on infectious disease and surveillance data.ResultsWe identified logistical challenges, difficulties with data collection and a lack of health information sharing frameworks as the most significant barriers to health information sharing. The most important tools to health information sharing included the use of third-party technologies for data collection and standardisation, formalised health information sharing frameworks, establishment of multilevel coordination mechanisms and leadership initiatives which prioritised the sharing of health information.ConclusionsWe conclude that health information sharing can be strengthened in humanitarian settings with improvements to existing frameworks, coordination and leadership tools, in addition to promotion of health information communication. Furthermore, specific recommendations for improving health information sharing should be pursued according to the nature of the humanitarian setting and the efficacy of the health system present.

Project description:BACKGROUND:The diagnosis and management of bipolar disorder are limited by the absence of available biomarkers. Patients with bipolar disorder frequently present with mood instability even during remission, which is likely associated with the risk of relapse, impaired functioning, and suicidal behavior, indicating that the illness is active. OBJECTIVE:This research protocol aimed to investigate the correlations between clinically rated mood symptoms and mood/behavioral data automatically collected using the Toi Même app in patients with bipolar disorder presenting with different mood episodes. This study also aimed to assess the feasibility of this app for self-monitoring subjective and objective mood/behavior parameters in those patients. METHODS:This open-label, nonrandomized trial will enroll 93 (31 depressive, 31 euthymic, and 31 hypomanic) adults diagnosed with bipolar disorder type I/II (Diagnostic and Statistical Manual of Mental Disorders, 5th edition criteria) and owning an iPhone. Clinical evaluations will be performed by psychiatrists at the baseline and after 2 weeks, 1 month, 2 months, and 3 months during the follow-up. Rather than only accessing the daily mood symptoms, the Toi Même app also integrates ecological momentary assessments through 2 gamified tests to assess cognition speed (QUiCKBRAIN) and affective responses (PLAYiMOTIONS) in real-life contexts, continuously measures daily motor activities (eg, number of steps, distance) using the smartphone's motion sensors, and performs a comprehensive weekly assessment. RESULTS:Recruitment began in April 2018 and the completion of the study is estimated to be in December 2021. As of April 2019, 25 participants were enrolled in the study. The first results are expected to be submitted for publication in 2020. This project has been funded by the Perception and Memory Unit of the Pasteur Institute (Paris) and it has received the final ethical/research approvals in April 2018 (ID-RCB: 2017-A02450-53). CONCLUSIONS:Our results will add to the evidence of exploring other alternatives toward a more integrated approach in the management of bipolar disorder, including digital phenotyping, to develop an ethical and clinically meaningful framework for investigating, diagnosing, and treating individuals at risk of developing bipolar disorder or currently experiencing bipolar disorder. Further prospective studies on the validity of automatically generated smartphone data are needed for better understanding the longitudinal pattern of mood instability in bipolar disorder as well as to establish the reliability, efficacy, and cost-effectiveness of such an app intervention for patients with bipolar disorder. TRIAL REGISTRATION:ClinicalTrials.gov NCT03508427; https://clinicaltrials.gov/ct2/show/NCT03508427. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID):DERR1-10.2196/18818.

Project description:BACKGROUND:Self-management is integral for control of type 2 diabetes mellitus (T2DM). Patient self-management is improved when they receive real-time information on their health status and behaviors and ongoing facilitation from health professionals. However, timely information for these behaviors is notably absent in the health care system. Providing real-time data could help improve patient understanding of the dynamics of their illness and assist clinicians in developing targeted approaches to improve health outcomes and in delivering personalized care when and where it is most needed. Mobile technologies (eg, wearables, apps, and connected scales) have the potential to make these patient-provider interactions a reality. What strategies might best help patients overcome self-management challenges using self-generated diabetes-related data? How might clinicians effectively guide patient self-management with the advantage of real-time data? OBJECTIVE:This study aims to describe the protocol for an ongoing study (June 2016-May 2019) that examines trajectories of symptoms, health behaviors, and associated challenges among individuals with T2DM utilizing multiple mobile technologies, including a wireless body scale, wireless glucometer, and a wrist-worn accelerometer over a 6-month period. METHODS:We are conducting an explanatory sequential mixed methods study of 60 patients with T2DM recruited from a primary care clinic. Patients were asked to track relevant clinical data for 6 months using a wireless body scale, wireless glucometer, a wrist-worn accelerometer, and a medication adherence text message (short message service, SMS) survey. Data generated from the devices were then analyzed and visualized. A subset of patients is currently being interviewed to discuss their challenges and successes in diabetes self-management, and they are being shown visualizations of their own data. Following the data collection period, we will conduct interviews with study clinicians to explore ways in which they might collaborate with patients. RESULTS:This study has received regulatory approval. Patient enrollment ongoing with a sample size of 60 patients is complete, and up to 20 clinicians will be enrolled. At the patient level, data collection is complete, but data analysis is pending. At the clinician level, data collection is currently ongoing. CONCLUSIONS:This study seeks to expand the use of mobile technologies to generate real-time data to enhance self-management strategies. It also seeks to obtain both patient and provider perspectives on using real-time data to develop algorithms for software that will facilitate real-time self-management strategies. We expect that the findings of this study will offer important insight into how to support patients and providers using real-time data to manage a complex chronic illness. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID):DERR1-10.2196/13517.

Project description:INTRODUCTION:Mental health issues appear as a growing problem in modern societies and tend to be more frequent in big cities. Where increased evidence exists for positive links between nature and mental health, associations between urban environment characteristics and mental health are still not well understood. These associations are highly complex and require an interdisciplinary and integrated research approach to cover the broad range of mitigating factors. This article presents the study protocol of a project called Nature Impact on Mental Health Distribution that aims to generate a comprehensive understanding of associations between mental health and the urban residential environment. METHODS AND ANALYSIS:Following a mixed-method approach, this project combines quantitative and qualitative research. In the quantitative part, we analyse among the Brussels urban population associations between the urban residential environment and mental health, taking respondents' socioeconomic status and physical health into account. Mental health is determined by the mental health indicators in the national Health Interview Survey (HIS). The urban residential environment is described by subjective indicators for the participant's dwelling and neighbourhood present in the HIS and objective indicators for buildings, network infrastructure and green environment developed for the purpose of this project. We assess the mediating role of physical activity, social life, noise and air pollution. In the qualitative part, we conduct walking interviews with Brussels residents to record their subjective well-being in association with their neighbourhood. In the validation part, results from these two approaches are triangulated and evaluated through interviews and focus groups with stakeholders of healthcare and urban planning sectors. ETHICS AND DISSEMINATION:The Privacy Commission of Belgium and ethical committee from University Hospital of Antwerp respectively approved quantitative database merging and qualitative interviewing. We will share project results with a wide audience including the scientific community, policy authorities and civil society through scientific and non-expert communication.

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Measuring the Effects of Sharing Mobile Health Data During Diabetes Consultations: Protocol for a Mixed Method Study.

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Measuring the Effects of Sharing Mobile Health Data During Diabetes Consultations: Protocol for a Mixed Method Study.

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