 Your new post is loading...
Your new post is loading...
C'est légal mais risqué pour les patients : deux tiers (64%) des applications de santé n'ont pas fait l'objet d'une évaluation scientifique avant d'être mises sur le marché.
Un groupe de chercheurs a développé un outil de notation des applications d'e-santé, le "Medical Digital Solution", qui a été testé sur 65 solutions. Seules 21% d'entre elles ont fait l'objet d'une étude randomisée avant d'être mise sur le marché. Un pourcentage faible étant donné que cette indication est indispensable pour envisager un remboursement par l'Assurance maladie.
Une majorité des applications utilisées dans le cadre du suivi médical, de télésurveillance notamment, n’ont pas fait l’objet d’études cliniques ad hoc avant leur mise sur le marché. Ce sont les…
The Digital Health Assessment Framework
PARIS (TICpharma) - L'application Odysight, développée par la start-up française Tilak Healthcare, montre une bonne adhésion des personnes de plus de 50 ans et il semble également y avoir un intérêt dans le dépistage de récidives exsudatives des oedèmes maculaires chez certains profils, selon deux études françaises présentées le 8 mai au congrès de la Société française d'ophtalmologie (SFO).
Background: Mobile health (mHealth) apps are revolutionizing the way clinicians and researchers monitor and manage the health of their participants. However, many studies using mHealth apps are hampered by substantial participant dropout or attrition, which may impact the representativeness of the sample and the effectiveness of the study. Therefore, it is imperative for researchers to understand what makes participants stay with mHealth apps or studies using mHealth apps. Objective: This study aimed to review the current peer-reviewed research literature to identify the notable factors and strategies used in adult participant engagement and retention. Methods: We conducted a systematic search of PubMed, MEDLINE, and PsycINFO databases for mHealth studies that evaluated and assessed issues or strategies to improve the engagement and retention of adults from 2015 to 2020. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Notable themes were identified and narratively compared among different studies. A binomial regression model was generated to examine the factors affecting retention. Results: Of the 389 identified studies, 62 (15.9%) were included in this review. Overall, most studies were partially successful in maintaining participant engagement. Factors related to particular elements of the app (eg, feedback, appropriate reminders, and in-app support from peers or coaches) and research strategies (eg, compensation and niche samples) that promote retention were identified. Factors that obstructed retention were also identified (eg, lack of support features, technical difficulties, and usefulness of the app). The regression model results showed that a participant is more likely to drop out than to be retained. Conclusions: Retaining participants is an omnipresent challenge in mHealth studies. The insights from this review can help inform future studies about the factors and strategies to improve participant retention.
The researchers found 20 of the 23 apps reviewed shared data with third parties. Only 16 displayed a privacy policy, and three collected data before consent.
Grâce au smartphone, un repérage précoce des troubles améliore les chances de progrès.
Germany, Belgium and France are trailblazers followed by Italy, Netherlands, Austria, Finland, Ireland, Luxembourg, Sweden, Denmark, and Switzerland.
In collaboration with its partners, the American Telemedicine Association has released an open framework to help clinicians and patients select and adopt high-quality digital health tools.
Artificial intelligence-powered smartphone diagnostic for skin cancer from Skin Analytics has been certified for use in UK
Background: Selecting and integrating health-related apps into patient care is impeded by the absence of objective guidelines for identifying high-quality apps from the many thousands now available.
Objective: This study aimed to evaluate the App Rating Inventory, which was developed by the Defense Health Agency’s Connected Health branch, to support clinical decisions regarding app selection and evaluate medical and behavioral apps.
Methods: To enhance the tool’s performance, eliminate item redundancy, reduce scoring system subjectivity, and ensure a broad application of App Rating Inventory–derived results, inventory development included 3 rounds of validation testing and 2 trial periods conducted over a 6-month interval. The development focused on content validity testing, dimensionality (ie, whether the tool’s criteria performed as operationalized), factor and commonality analysis, and interrater reliability (reliability scores improved from 0.62 to 0.95 over the course of development).
Results: The development phase culminated in a review of 248 apps for a total of 6944 data points and a final 28-item, 3-category app rating system. The App Rating Inventory produces scores for the following three categories: evidence (6 items), content (11 items), and customizability (11 items). The final (fourth) metric is the total score, which constitutes the sum of the 3 categories. All 28 items are weighted equally; no item is considered more (or less) important than any other item. As the scoring system is binary (either the app contains the feature or it does not), the ratings’ results are not dependent on a rater’s nuanced assessments.
Conclusions: Using predetermined search criteria, app ratings begin with an environmental scan of the App Store and Google Play. This first step in market research funnels hundreds of apps in a given disease category down to a manageable top 10 apps that are, thereafter, rated using the App Rating Inventory. The category and final scores derived from the rating system inform the clinician about whether an app is evidence informed and easy to use. Although a rating allows a clinician to make focused decisions about app selection in a context where thousands of apps are available, clinicians must weigh the following factors before integrating apps into a treatment plan: clinical presentation, patient engagement and preferences, available resources, and technology expertise.
Trial Registration:
|
[Courrier de l'Ouest] Deux médecins ont créé une application « Way4Good », qui vise à soutenir la santé mentale et le bien-être des jeunes angevins. Gratuite, elle concerne particulièrement les 11-25 ans.
Pour suivre l'évolution de sa santé, de nombreuses applis d'e-santé viennent en aide aux patients. Parfois sans même qu'une étude clinique pertinente ne viennent justifier leur commercialisation.
Le CHRU de Nancy a lancé en avril dernier, un module destiné aux urgentistes pour offrir une plus grande souplesse dans la gestion des lits d’urgence. Son objectif : leur permettre de repérer en un coup d’oeil, l’offre de lits disponible dans les autres services. Une solution plus qu’utile en cette période tendue au sein du service des urgences et de réanimation médicale du CHRU de Nancy
Lify Air a développé une solution et une application pour prévenir des allergies au pollen et faciliter la vie des personnes atteintes. Plusieurs territoires ont déjà adopté Live Pollen et les capteurs optiques capables de mesurer et identifier les particules dans l’air.
Via Rémy TESTON
100 percent of the 30 popular mHealth apps are vulnerable to API abuse that can allow unauthorized access to full patient records.
Mobile performance of popular mental health apps indicates overvaluation during the pandemic.
While some of the factors impacting patients’ adoption of mHealth tools may be hard to influence
They are rapidly becoming an important part of health care | Technology Quarterly
Background: Mobile health (mHealth) tools have emerged as a promising health care technology that may contribute to cost savings, better access to care, and enhanced clinical outcomes; however, it is important to ensure their acceptance and adoption to harness this potential. Patient adoption has been recognized as a key challenge that requires further exploration.
Objective: The aim of this review was to systematically investigate the literature to understand the factors affecting patients’ adoption of mHealth tools by considering sociotechnical factors (from technical, social, and health perspectives).
Methods: A structured search was completed following the participants, intervention, comparators, and outcomes framework. We searched the MEDLINE, PubMed, Cochrane Library, and SAGE databases for studies published between January 2011 and July 2021 in the English language, yielding 5873 results, of which 147 studies met the inclusion criteria. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and the Cochrane Handbook were followed to ensure a systematic process. Extracted data were analyzed using NVivo (QSR International), with thematic analysis and narrative synthesis of emergent themes.
Results: The technical factors affecting patients’ adoption of mHealth tools were categorized into six key themes, which in turn were divided into 20 subthemes: usefulness, ease of use, data-related, monetary factors, technical issues, and user experience. Health-related factors were categorized into six key themes: the disease or health condition, the care team’s role, health consciousness and literacy, health behavior, relation to other therapies, integration into patient journey, and the patients’ insurance status. Social and personal factors were divided into three key clusters: demographic factors, personal characteristics, and social and cultural aspects; these were divided into 19 subthemes, highlighting the importance of considering these factors when addressing potential barriers to mHealth adoption and how to overcome them.
Conclusions: This review builds on the growing body of research that investigates patients’ adoption of mHealth services and highlights the complexity of the factors affecting adoption, including personal, social, technical, organizational, and health care aspects. We recommend a more patient-centered approach by ensuring the tools’ fit into the overall patient journey and treatment plan, emphasizing inclusive design, and warranting comprehensive patient education and support. Moreover, empowering and mobilizing clinicians and care teams, addressing ethical data management issues, and focusing on health care policies may facilitate adoption.
Trial Registration:
Efelya édite une application mobile permettant aux personnes enceintes de suivre leur grossesse, selon leur profil de risque personnel.
Via Rémy TESTON
Background: Mobile health (mHealth) apps are revolutionizing the way clinicians and researchers monitor and manage the health of their participants. However, many studies using mHealth apps are hampered by substantial participant dropout or attrition, which may impact the representativeness of the sample and the effectiveness of the study. Therefore, it is imperative for researchers to understand what makes participants stay with mHealth apps or studies using mHealth apps. Objective: This study aimed to review the current peer-reviewed research literature to identify the notable factors and strategies used in adult participant engagement and retention. Methods: We conducted a systematic search of PubMed, MEDLINE, and PsycINFO databases for mHealth studies that evaluated and assessed issues or strategies to improve the engagement and retention of adults from 2015 to 2020. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Notable themes were identified and narratively compared among different studies. A binomial regression model was generated to examine the factors affecting retention. Results: Of the 389 identified studies, 62 (15.9%) were included in this review. Overall, most studies were partially successful in maintaining participant engagement. Factors related to particular elements of the app (eg, feedback, appropriate reminders, and in-app support from peers or coaches) and research strategies (eg, compensation and niche samples) that promote retention were identified. Factors that obstructed retention were also identified (eg, lack of support features, technical difficulties, and usefulness of the app). The regression model results showed that a participant is more likely to drop out than to be retained. Conclusions: Retaining participants is an omnipresent challenge in mHealth studies. The insights from this review can help inform future studies about the factors and strategies to improve participant retention.
They are rapidly becoming an important part of health care | Technology Quarterly
|
Scoop.it!
