scholarly journals Correction: Building Health Services in a Rapidly Changing Landscape: Lessons in Adaptive Leadership and Pivots in a COVID-19 Remote Monitoring Program (Preprint)

2021 ◽  
Author(s):  
Celia Violet Laur ◽  
Payal Agarwal ◽  
Geetha Mukerji ◽  
Elaine Goulbourne ◽  
Hayley Baranek ◽  
...  
Keyword(s):  
Health Services ◽  
Remote Monitoring ◽  
Monitoring Program ◽  
Adaptive Leadership

UNSTRUCTURED REMOVE

scholarly journals Correction: Building Health Services in a Rapidly Changing Landscape: Lessons in Adaptive Leadership and Pivots in a COVID-19 Remote Monitoring Program

10.2196/31044 ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. e31044
Author(s):  
Celia Violet Laur ◽  
Payal Agarwal ◽  
Geetha Mukerji ◽  
Elaine Goulbourne ◽  
Hayley Baranek ◽  
...  
Keyword(s):  
Health Services ◽  
Remote Monitoring ◽  
Monitoring Program ◽  
Adaptive Leadership

scholarly journals Building health services in a rapidly changing landscape: Lessons in adaptive leadership and Pivots in a COVID-19 remote monitoring program (Preprint)

2020 ◽  
Author(s):  
Celia Violet Laur ◽  
Payal Agarwal ◽  
Geetha Mukerji ◽  
Elaine Goulbourne ◽  
Hayley Baranek ◽  
...  
Keyword(s):  
Health Services ◽  
Remote Monitoring ◽  
Monitoring Program ◽  
Adaptive Leadership ◽  
Strategic Decisions ◽  
Consumer Market ◽  
Considerable Uncertainty ◽  
External Stakeholders ◽  
Start Ups

UNSTRUCTURED Adaptive Leadership has become an essential skill for leaders in the health system to respond to the COVID-19 pandemic as new knowledge emerges and case counts rise, fall and rise again. This leadership approach has been described as an iterative process of taking a wide view of the situation, interpreting the meaning of incoming data from multiple directions, and taking real-time action. This process is also common in start-ups that try to create a new product or service of uncertain value for a consumer market that may not yet exist. Startups manage uncertainty through “Pivots”, which can include changes in the target group, need, features, or intended benefit of a product or service. Pivots are large changes to account for the high likelihood of getting something wrong, and distinct from the “tweaks” or small tests of change that define quality improvement methodology. This case study describes three Pivots in the launch of a remote monitoring program for COVID-19. Adaptive Leadership helped inform strategic decisions, with Pivots providing a framework for internal and external stakeholders to articulate options for changes to address shifting needs. There is considerable uncertainty in the appropriate design and implementation of health services, and although this case example focuses on the use of Adaptive Leadership and Pivots during a pandemic, these strategies are relevant for healthcare leaders at any time.

scholarly journals Building Health Services in a Rapidly Changing Landscape: Lessons in Adaptive Leadership and Pivots in a COVID-19 Remote Monitoring Program (Preprint)

10.2196/25507 ◽  
2020 ◽  
Author(s):  
Celia Violet Laur ◽  
Payal Agarwal ◽  
Geetha Mukerji ◽  
Elaine Goulbourne ◽  
Hayley Baranek ◽  
...  
Keyword(s):  
Health Services ◽  
Remote Monitoring ◽  
Monitoring Program ◽  
Adaptive Leadership

scholarly journals The impact of a remote monitoring program on the prenatal follow-up of women with gestational hypertensive disorders

2018 ◽  
Vol 223 ◽  
pp. 72-78 ◽  
Author(s):  
Dorien Lanssens ◽  
Sharona Vonck ◽  
Valerie Storms ◽  
Inge M. Thijs ◽  
Lars Grieten ◽  
...  
Keyword(s):  
Remote Monitoring ◽  
Monitoring Program ◽  
Hypertensive Disorders ◽  
The Impact

scholarly journals Study on the Types of Elderly Intelligent Health Management Technology and the Influencing Factors of Its Adoption

Healthcare ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1494
Author(s):  
Zhu Chen ◽  
Huiying Qi ◽  
Luman Wang
Keyword(s):  
Health Services ◽  
Influencing Factors ◽  
Health Risks ◽  
Remote Monitoring ◽  
Social Problem ◽  
Health Management ◽  
The Elderly ◽  
Self Monitoring ◽  
Management Technology ◽  
Use Behavior

[Background]: In recent years, aging has become a global social problem. Intelligent health management technology (IHMT) provides solutions for the elderly to deal with various health risks. However, the elderly are facing many difficulties in using IHMT. Studying the application types of IHMT and the influencing factors of the elderly’s acceptance of it will help to improve the use behavior of the elderly. [Methods]: This paper summarizes the application types of IHMT, identifies the influencing factors of the elderly’s adaption of IHMT, and makes a systematic comment on the influencing factors. [Results]: We divide the different functions of IHMT for the elderly into four types: self-monitoring, medical care, remote monitoring, and health education. The influencing factors are divided into three types: individual, social, and technology. [Conclusions]: This study finds that IHMT’s application covers all aspects of the health services of the elderly. Among these applications, self-monitoring is the most used. We divided the influencing factors of the elderly’s acceptance of IHMT into three categories and nine subcategories, having 25 variables.

scholarly journals A Prenatal Remote Monitoring Program in Pregnancies Complicated with Gestational Hypertensive Disorders: What Are the Contributors to the Cost Savings?

2019 ◽  
Vol 25 (8) ◽  
pp. 686-692 ◽  
Author(s):  
Dorien Lanssens ◽  
Sharona Vonck ◽  
Thijs Vandenberk ◽  
Cédric Schraepen ◽  
Valerie Storms ◽  
...  
Keyword(s):  
Remote Monitoring ◽  
Monitoring Program ◽  
Cost Savings ◽  
Hypertensive Disorders ◽  
The Cost

scholarly journals Evaluation of a Diabetes Remote Monitoring Program Facilitated by Connected Glucose Meters for Patients with Poorly Controlled Type 2 Diabetes: A Randomized Crossover Trial. (Preprint)

2020 ◽  
Author(s):  
Daniel J. Amante ◽  
David M. Harlan ◽  
Stephenie C. Lemon ◽  
David D. McManus ◽  
Oladapo O. Olaitan ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Blood Glucose ◽  
Usual Care ◽  
Remote Monitoring ◽  
Treatment Satisfaction ◽  
Monitoring Program ◽  
Cost Of Care ◽  
Glucose Meter ◽  
Diabetes Center

BACKGROUND Patients with poorly-controlled type 2 diabetes (T2D) experience increased morbidity, mortality and higher cost of care. Self-monitoring of blood glucose (SMBG) is a critical component of diabetes self-management with established diabetes outcome benefits. Technological advancements in blood glucose meters, including cellular-connected devices that automatically upload SMBG data to secure cloud-based databases, allow for improved sharing and monitoring of SMBG data. Real-time monitoring of SMBG data presents opportunities to provide timely support to patients responsive to abnormal SMBG recordings. Such diabetes remote monitoring programs can provide patients with poorly-controlled T2D additional support needed to improve critical outcomes. OBJECTIVE To evaluate six months of a diabetes remote monitoring program facilitated by cellular-connected glucose meter, access to a diabetes coach and support responsive to abnormal blood glucose recordings greater than 400 mg/dL or below 50 mg/dL in adults with poorly controlled T2D. METHODS Patients (n=120) receiving care at a diabetes center of excellence participated in a two-arm, 12-month randomized crossover study. The intervention included a cellular-connected glucose meter and phone-based diabetes coaching provided by Livongo Health. The coach answered questions, assisted in goal setting, and provided support in response to abnormal glucose levels. One group received the intervention for six months before returning to usual care (IV/UC). The other group received usual care before enrolling in the intervention (UC/IV) for six months. Change in hemoglobin A1c (HbA1c) was the primary outcome and change in treatment satisfaction was the secondary outcome. RESULTS Improvements in mean HbA1c were seen in both groups during the first six months (IV/UC -1.1% (SD 1.5) vs. UC/IV -0.8% (1.5), p < 0.001). After crossover, there was no significant change in HbA1c in IV/UC (mean HbA1c change +0.2 (1.7), p=0.41); however, those in UC/IV showed further improvement (mean (SD) HbA1c change -0.4% (1.0), p < 0.01). A mixed-effects model showed no significant treatment effect (IV vs. UC) over 12 months (p=0.06). However, participants with higher baseline HbA1c and those in first time period experienced greater improvements in HbA1c. Both groups reported similar improvements in treatment satisfaction throughout the study. CONCLUSIONS Patients enrolled in the diabetes remote monitoring program intervention experienced improvements in HbA1c and treatment satisfaction similar to usual care at a specialty diabetes center. Future studies on diabetes remote monitoring program should incorporate scheduled coaching components and involve family members and caregivers. CLINICALTRIAL Study details can be found at clinicaltrials.gov with the study identifier number: NCT03124043.

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