Feasibility and impact of remote glucose monitoring among patients with newly diagnosed type 1 diabetes: a single-center pilot study (Preprint)

2021 ◽  
Author(s):  
Stephanie Crossen ◽  
Crystal Romero ◽  
Allison Reggiardo ◽  
Jimi Michel ◽  
Nicole Glaser
Keyword(s):  
Usual Care ◽  
Mobile Health ◽  
Remote Monitoring ◽  
Intervention Group ◽  
Glucose Monitoring ◽  
Control Group ◽  
Newly Diagnosed ◽  
Ipod Touch ◽  
Mobile Health Applications ◽  
Health Applications

BACKGROUND Caregivers of children with newly diagnosed type 1 diabetes (T1D) maintain close contact with providers for several weeks to facilitate rapid adjustments in insulin dosing regimens. Traditionally, patient glucose values are relayed by telephone for provider feedback, but digital health technology can now enable remote sharing of glucose data via mobile applications. OBJECTIVE To test the feasibility of remote glucose monitoring in a population of children and adolescents with newly diagnosed T1D, and to explore whether remote monitoring alters habits for self-review of glucose data or perceived ease of provider contact in this population as compared to a control group. METHODS Data were collected from families participating in remote monitoring (intervention group) as well as from patients receiving usual care (control group). The intervention group received Bluetooth-capable glucose meters and Apple iPod Touch devices. Patient-generated glucose data was passively relayed from the meter to the iPod Touch and then to both the electronic health record (EHR) and a third-party diabetes data platform, Tidepool. The principal investigator reviewed glucose data daily in the EHR and Tidepool, and contacted participants as needed for insulin dose adjustments during the time between hospital discharge and first clinic appointment. Families in the control group received usual care, which involved keeping written records of glucose values and contacting the diabetes team daily by telephone to relay data and receive treatment recommendations. A total of 40 families (20 intervention, 20 control) participated in the study. All families were surveyed at one month and six months regarding self-review of glucose data and ease of contacting the diabetes team. RESULTS Patient-generated glucose data were remotely accessible for 100% of participants via Tidepool and for 85% via the EHR. Survey data indicated that families in the intervention group were more likely than those in the control group to review their glucose data using mobile health applications after one month (P <.001), but by six months this difference had disappeared. Perceived ease of contacting the clinical team for assistance was lower for the intervention group after six months (when receiving usual care) in comparison to during the intervention period (P = .48), and in comparison to a control group who did not have exposure to remote monitoring (P = .03). CONCLUSIONS Remote glucose monitoring is feasible among pediatric patients with newly diagnosed T1D, and may be associated with earlier adoption of mobile health applications for self-management. Use of broadscale remote monitoring for T1D in the future will depend on improved access to Bluetooth-enabled mobile devices for all patients, improved interoperability of mobile health applications to enable data-transfer on Android as well as Apple devices, and new provider workflows to handle largescale panel management based on patient-generated health data. CLINICALTRIAL ClinicalTrials.gov (NCT04106440)

Mobile Health Applications for Prenatal Assessment and Monitoring

2019 ◽  
Vol 25 (5) ◽  
pp. 615-623 ◽  
Author(s):  
Wilfried Gyselaers ◽  
Dorien Lanssens ◽  
Helen Perry ◽  
Asma Khalil
Keyword(s):  
Prenatal Care ◽  
Mobile Health ◽  
Low Income ◽  
Remote Monitoring ◽  
Daily Practice ◽  
Economic Benefits ◽  
Glucose Levels ◽  
Mobile Health Applications ◽  
Monitoring Devices ◽  
Health Applications

Background:A mobile health application is an exciting, fast-paced domain that is likely to improve prenatal care.Methods:In this narrative review, we summarise the use of mobile health applications in this setting with a special emphasis on both the benefits of remote monitoring devices and the potential pitfalls of their use, highlighting the need for robust regulations and guidelines before their widespread introduction into prenatal care.Results:Remote monitoring devices for four areas of prenatal care are reported: (1) cardio-tocography; (2) blood glucose levels; (3) blood pressure; and (4) prenatal ultrasound. The majority of publications are pilot projects on remote consultation, education, coaching, screening, monitoring and selective booking, mostly reporting potential medical and/or economic benefits by mobile health applications over conventional care for very specific situations, indications and locations, but not always generalizable.Conclusions:Despite the potential advantages of these devices, some caution must be taken when implementing this technology into routine daily practice. To date, the majority of published research on mobile health in the prenatal setting consists of observational studies and there is a need for high-quality randomized controlled trials to confirm the reported clinical and economic benefits as well as the safety of this technology. There is also a need for guidance and governance on the development and validation of new apps and devices and for the implementation of mobile health technology into healthcare systems in both high and low-income settings. Finally, digital communication technologies offer perspectives towards exploration and development of the very new domain of tele-pharmacology.

Malaria Geo-Localization with Mobile-Health Applications

2015 ◽  
Author(s):  
Roberto Moro Visconti ◽  
Alberto Larocca ◽  
Michele Marconi
Keyword(s):  
Mobile Health ◽  
Mobile Health Applications ◽  
Health Applications

EFFECTIVNESS OF SPECIFIC MOBILE HEALTH APPLICATIONS (mHEALTH-APPS)in GESTATIONAL DIABTETES MELLITUS: A SYSTEMATIC REVIEW (Preprint)

2020 ◽  
Author(s):  
Claudia Eberle ◽  
Maxine Löhnert
Keyword(s):  
Mobile Health ◽  
Cochrane Library ◽  
Clinical Parameters ◽  
Control Groups ◽  
Manual Search ◽  
Mobile Health Applications ◽  
Short And Long Term ◽  
Mhealth Apps ◽  
Health Applications

BACKGROUND Gestational diabetes mellitus (GDM) emerges worldwide and is closely associated with short- and long-term health issues in women and their offspring, such as pregnancy and birth complications respectively comorbidities, Type 2 Diabetes (T2D), Metabolic Syndrome (MetS) as well as cardiovascular disease (CD). Against this background mobile health applications (mHealth-Apps) do open up new possibilities to improve the management of GDM clearly. OBJECTIVE Since there is – to our knowledge – no systematic literature review published, which focusses on the effectiveness of specific mHealth-Apps on clinical health-related short and long-term outcomes of mother and child, we conducted these much-needed analyses. METHODS Data sources: A systematic literature search in Medline (Pubmed), Cochrane Library, Embase, CINAHL and Web of Science was performed including full text publications since 2008 up to date. An additional manual search in references and Google Scholar was conducted subsequently. Study Eligibility Criteria: Women diagnosed with GDM using specific mHealth-Apps during pregnancy compared to control groups, which met main clinical parameters and outcomes in GDM management as well as maternity and offspring care. Study appraisal and synthesis methods: Study quality was assessed and rated “strong”, “moderate” or “weak” by using the Effective Public Health Practice Project (EPHPP) tool. Study results were strongly categorized by outcomes; an additional qualitative summary was assessed. Study selection: Overall, n= 114 studies were analyzed, n= 46 duplicates were removed, n=5 studies met the eligible criteria and n=1 study was assessed by manual search subsequently. In total, n=6 publications, analyzing n=408 GDM patients in the interventional and n=405 women diagnosed with GDM in the control groups, were included. These studies were divided into n=5 two-arm randomized controlled trials (RCT) and n=1 controlled clinical trial (CCT). RESULTS Distinct improvements in clinical parameters and outcomes, such as fasting blood glucoses (FBG), 2-hour postprandial blood glucoses (PBG), off target blood glucose measurements (OTBG), delivery modes and patient compliance were analyzed in GDM patients using specific mHealth-Apps compared to matched control groups. CONCLUSIONS mHealth-Apps clearly improve clinical outcomes in management of GDM effectively. More studies need to be done more in detail.

scholarly journals OP0198-HPR A STRUCTURED MODEL FOR OA CARE IN PRIMARY HEALTHCARE IS A COST-EFFECTIVE ALTERNATIVE COMPARED TO USUAL CARE FOR PEOPLE WITH HIP AND KNEE OA

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 119-120
Author(s):  
N. Østerås ◽  
E. Aas ◽  
T. Moseng ◽  
L. Van Bodegom-Vos ◽  
K. Dziedzic ◽  
...  
Keyword(s):  
Usual Care ◽  
Primary Healthcare ◽  
Intervention Group ◽  
Cost Effective ◽  
Cost Utility ◽  
Control Group ◽  
Structured Model ◽  
Knee Oa ◽  
Cost Effective Alternative ◽  
The Cost

Background:To improve quality of care for patients with hip and knee osteoarthritis (OA), a structured model for integrated OA care was developed based on international treatment recommendations. A previous analysis of a cluster RCT (cRCT) showed that compared to usual care, the intervention group reported higher quality of care and greater satisfaction with care. Also, more patients were treated according to international guidelines and fulfilled recommendations for physical activity at the 6-month follow-up.Objectives:To assess the cost-utility of a structured model for hip or knee OA care.Methods:A cRCT with stepped-wedge cohort design was conducted in 6 Norwegian municipalities (clusters) in 2015-17. The OA care model was implemented in one cluster at the time by switching from “usual care” to the structured model. The implementation of the model was facilitated by interactive workshops for general practitioners (GPs) and physiotherapists (PTs) with an update on OA treatment recommendations. The GPs explained the OA diagnosis and treatment alternatives, provided pharmacological treatment when appropriate, and suggested referral to physiotherapy. The PT-led patient OA education programme was group-based and lasted 3 hours followed by an 8–12-week individually tailored resistance exercise programme with twice weekly 1-hour supervised group sessions (5–10 patients per PT). An optional 10-hours Healthy Eating Program was available. Participants were ≥45 years with symptomatic hip or knee OA.Costs were measured from the healthcare perspective and collected from several sources. Patients self-reported visits in primary healthcare at 3, 6, 9 and 12 months. Secondary healthcare visits and joint surgery data were extracted from the Norwegian Patient Register. The health outcome, quality-adjusted life-year (QALY), was estimated based on the EQ-5D-5L scores at baseline, 3, 6, 9 and 12 months. The result of the cost-utility analysis was reported using the incremental cost-effectiveness ratio (ICER), defined as the incremental costs relative to incremental QALYs (QALYs gained). Based on Norwegian guidelines, the threshold is €27500. Sensitivity analyses were performed using bootstrapping to assess the robustness of reported results and presented in a cost-effectiveness plane (Figure 1).Results:The 393 patients’ mean age was 63 years (SD 9.6) and 74% were women. 109 patients were recruited during control periods (control group), and 284 patients were recruited during interventions periods (intervention group). Only the intervention group had a significant increase in EQ-5D-5L utility scores from baseline to 12 months follow-up (mean change 0.03; 95% CI 0.01, 0.05) with QALYs gained: 0.02 (95% CI -0.08, 0.12). The structured OA model cost approx. €301 p.p. with an additional €50 for the Healthy Eating Program. Total 12 months healthcare cost p.p. was €1281 in the intervention and €3147 in the control group, resulting in an incremental cost of -€1866 (95% CI -3147, -584) p.p. Costs related to surgical procedures had the largest impact on total healthcare costs in both groups. During the 12-months follow-up period, 5% (n=14) in the intervention compared to 12% (n=13) in the control group underwent joint surgery; resulting in a mean surgical procedure cost of €553 p.p. in the intervention as compared to €1624 p.p. in the control group. The ICER was -€93300, indicating that the OA care model resulted in QALYs gained and cost-savings. At a threshold of €27500, it is 99% likely that the OA care model is a cost-effective alternative.Conclusion:The results of the cost-utility analysis show that implementing a structured model for OA care in primary healthcare based on international guidelines is highly likely a cost-effective alternative compared to usual care for people with hip and knee OA. More studies are needed to confirm this finding, but this study results indicate that implementing structured OA care models in primary healthcare may be beneficial for the individual as well as for the society.Disclosure of Interests:None declared

Mobile Health Applications to Support COVID-19 Self-management: Review and Evaluation

2021 ◽  
Author(s):  
Sahar Khenarinezhad ◽  
Ehsan Ghazanfari Savadkoohi ◽  
Leila Shahmoradi
Keyword(s):  
Mobile Health ◽  
Mobile Apps ◽  
Healthcare Providers ◽  
Vital Signs ◽  
Complete Information ◽  
Self Management ◽  
Management Measures ◽  
Management Procedures ◽  
Mobile Health Applications ◽  
Health Applications

Aim: During the epidemic and with an increase in coronavirus (COVID-19) disease prevalence, emergency care is essential to help people stay informed and undertake self-management measures to protect their health. One of these self-management procedures is the use of mobile apps in health. Mobile health (mHealth) applications include mobile devices in collecting clinical health data, sharing healthcare information for practitioners and patients, real-time monitoring of patient vital signs, and the direct provision of care (via mobile telemedicine). Mobile apps are increasing to improve health, but before healthcare providers can recommend these applications to patients, they need to be sure the apps will help change patients' lifestyles. Method: A search was conducted systematically using the keywords "Covid-19," "Coronavirus," "Covid-19, and Self-management" at the "Apple App Store". Then we evaluated the apps according to MARS criteria in May 2020. Results: A total of 145 apps for COVID-19 self-management were identified, but only 32 apps met our inclusion criteria after being assessed. The overall mean MARS score was 2.9 out of 5, and more than half of the apps had a minimum acceptability score (range 2.5-3.9). The "who academy" app received the highest functionality score. Who Academy, Corona-Care and First Responder COVID-19 Guide had the highest scores for behavior change. Conclusion: Our findings showed that few apps meet the quality, content, and functionality criteria for Covid-19 self-management. Therefore, developers should use evidence-based medical guidelines in creating mobile health applications so that, they can provide comprehensive and complete information to both patients and healthcare provider.

How mobile health applications can help treat depression

2017 ◽  
Vol 33 (9) ◽  
pp. 1-6
Author(s):  
Adam Rosenfeld ◽  
Sachin Pendse ◽  
Nicole R. Nugent
Keyword(s):  
Mobile Health ◽  
Mobile Health Applications ◽  
Health Applications

Integrating a mobile health applications for self-management to enhance Telecare system

2018 ◽  
Vol 35 (4) ◽  
pp. 815-825 ◽  
Author(s):  
Hao-Yun Kao ◽  
Chun-Wang Wei ◽  
Min-Chun Yu ◽  
Tyng-Yeu Liang ◽  
Wen-Hsiung Wu ◽  
...  
Keyword(s):  
Mobile Health ◽  
Self Management ◽  
Mobile Health Applications ◽  
Health Applications

scholarly journals Screening for Atrial Fibrillation in Older Adults at Primary Care Visits: the VITAL-AF Randomized Controlled Trial

2021 ◽  
Author(s):  
Steven Lubitz ◽  
Steven J. Atlas ◽  
Jeffrey M. Ashburner ◽  
Ana Lipsanopoulos ◽  
Leila Borowsky ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Primary Care ◽  
Usual Care ◽  
Controlled Trial ◽  
Oral Anticoagulants ◽  
Care Practice ◽  
Control Group ◽  
Newly Diagnosed ◽  
One Year ◽  
And Control

Background: Undiagnosed atrial fibrillation (AF) may cause preventable strokes. Guidelines differ regarding AF screening recommendations. We tested whether point-of-care screening with a handheld single lead electrocardiogram (ECG) at primary care practice visits increases diagnoses of AF. Methods: We randomized 16 primary care clinics 1:1 to AF screening using a handheld single-lead ECG (AliveCor KardiaMobile) during vital sign assessments, or usual care. Patients included were aged ≥ 65 years. Screening results were provided to primary care clinicians at the encounter. All confirmatory diagnostic testing and treatment decisions were made by the primary care clinician. New AF diagnoses over one-year follow-up were ascertained electronically and manually adjudicated. Proportions and incidence rates were calculated. Effect heterogeneity was assessed. Results: Of 30,715 patients without prevalent AF (n=15,393 screening [91% screened], n=15,322 control), 1.72% of individuals in the screening group had new AF diagnosed at one year versus 1.59% in the control group (risk difference [RD] 0.13%, 95% confidence interval [CI] -0.16,0.42, P=0.38). New AF diagnoses in the screening and control groups differed by age with the greatest effect observed for those aged ≥ 85 years (5.56% versus 3.76%, respectively, RD 1.80%, 95% CI 0.18,3.30). The difference in newly diagnosed AF between the screening period and the prior year was marginally greater in the screening versus control group (0.32% versus -0.12%, RD 0.43%, 95% CI -0.01,0.84). The proportion of individuals with newly diagnosed AF who were initiated on oral anticoagulants was similar in the screening (n=194, 73.5%) and control (n=172, 70.8%) arms (RD 2.7%, 95% CI -5.5,10.4). Conclusions: Screening for AF using a single-lead ECG at primary care visits was not associated with a significant increase in new AF diagnoses among individuals aged 65 years or older compared to usual care. However, screening may be associated with an increased likelihood of diagnosing AF among individuals aged 85 years or older and warrants further evaluation.

Sign in / Sign up

Export Citation Format

Share Document