Dataset Information

A prospective randomized trial examining health care utilization in individuals using multiple smartphone-enabled biosensors.

ABSTRACT: Background. Mobile health and digital medicine technologies are becoming increasingly used by individuals with common, chronic diseases to monitor their health. Numerous devices, sensors, and apps are available to patients and consumers-some of which have been shown to lead to improved health management and health outcomes. However, no randomized controlled trials have been conducted which examine health care costs, and most have failed to provide study participants with a truly comprehensive monitoring system. Methods. We conducted a prospective randomized controlled trial of adults who had submitted a 2012 health insurance claim associated with hypertension, diabetes, and/or cardiac arrhythmia. The intervention involved receipt of one or more mobile devices that corresponded to their condition(s) (hypertension: Withings Blood Pressure Monitor; diabetes: Sanofi iBGStar Blood Glucose Meter; arrhythmia: AliveCor Mobile ECG) and an iPhone with linked tracking applications for a period of 6 months; the control group received a standard disease management program. Moreover, intervention study participants received access to an online health management system which provided participants detailed device tracking information over the course of the study. This was a monitoring system designed by leveraging collaborations with device manufacturers, a connected health leader, health care provider, and employee wellness program-making it both unique and inclusive. We hypothesized that health resource utilization with respect to health insurance claims may be influenced by the monitoring intervention. We also examined health-self management. Results & Conclusions. There was little evidence of differences in health care costs or utilization as a result of the intervention. Furthermore, we found evidence that the control and intervention groups were equivalent with respect to most health care utilization outcomes. This result suggests there are not large short-term increases or decreases in health care costs or utilization associated with monitoring chronic health conditions using mobile health or digital medicine technologies. Among secondary outcomes there was some evidence of improvement in health self-management which was characterized by a decrease in the propensity to view health status as due to chance factors in the intervention group.

SUBMITTER: Bloss CS

PROVIDER: S-EPMC4715435 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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A prospective randomized trial examining health care utilization in individuals using multiple smartphone-enabled biosensors.

Bloss Cinnamon S CS Wineinger Nathan E NE Peters Melissa M Boeldt Debra L DL Ariniello Lauren L Kim Ju Young JY Sheard Judith J Komatireddy Ravi R Barrett Paddy P Topol Eric J EJ

PeerJ 20160114

Background. Mobile health and digital medicine technologies are becoming increasingly used by individuals with common, chronic diseases to monitor their health. Numerous devices, sensors, and apps are available to patients and consumers-some of which have been shown to lead to improved health management and health outcomes. However, no randomized controlled trials have been conducted which examine health care costs, and most have failed to provide study participants with a truly comprehensive mo ...[more]

PMID: 26788432

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Project description:BackgroundEven before COVID-19, there has been an urgent need to expand access to and quality of mental health care. This paper introduces an 8-week treatment protocol to realize that vision-Technology Enabled Clinical Care (TECC). TECC offers innovation in clinical assessment, monitoring, and interventions for mental health. TECC uses the mindLAMP app to enable digital phenotyping, clinical communication, and smartphone-based exercises that will augment in-person or telehealth virtual visits. TECC exposes participants to an array of evidence-based treatments (cognitive behavioral therapy, dialectical behavior therapy, acceptance and commitment therapy) introduced through clinical sessions and then practiced through interactive activities provided through a smartphone app called mindLAMP.ObjectiveTECC will test the feasibility of providing technology-enabled mental health care within an outpatient clinic; explore the practicality for providing this care to individuals with limited English proficiency; and track anxiety, depression, and mood symptoms for participants to measure the effectiveness of the TECC design.MethodsThe TECC study will assess the acceptability and efficacy of this care model in 50 participants as compared to an age- and gender-matched cohort of patients presenting with similar clinical severity of depression, anxiety, or psychotic symptoms. Participants will be recruited from clinics in the Metro Boston area. Aspects of TECC will be conducted in both Spanish and English to ensure wide access to care for multiple populations.ResultsThe results of the TECC study will be used to support or adapt this model of care and create training resources to ensure its dissemination. The study results will be posted on ClinicalTrials.gov, with primary outcomes related to changes in mood, anxiety, and stress, and secondary outcomes related to engagement, alliance, and satisfaction.ConclusionsTECC combines new digital mental health technology with updated clinical protocols and workflows designed to ensure patients can benefit from innovation in digital mental health. Supporting multiple languages, TECC is designed to ensure digital health equity and highlights how mobile health can bridge, not expand, gaps in care for underserved populations.International registered report identifier (irrid)PRR1-10.2196/23771.

Project description:BackgroundA decline in the ability to perform daily intentions-known as prospective memory-is a key driver of everyday functional impairment in dementia. In the absence of effective pharmacological treatments, there is a need for developing, testing, and optimizing behavioral interventions that can bolster daily prospective memory functioning. We investigated the feasibility and efficacy of smartphone-based strategies for prospective memory in persons with cognitive impairment.MethodsFifty-two older adults (74.79 ± 7.20 years) meeting diagnostic criteria for mild cognitive impairment or mild dementia were enrolled in a 4-week randomized controlled trial. Participants were trained to use a digital voice recorder app or a reminder app to off-load prospective memory intentions. Prospective memory was assessed using experimenter-assigned tasks (e.g., call the laboratory on assigned days), standardized questionnaires, and structured interviews. Secondary dependent measures included days of phone and app usage, acceptability ratings, quality of life, and independent activities of daily living.ResultsParticipant ratings indicated that the intervention was acceptable and feasible. Furthermore, after the four-week intervention, participants reported improvements in daily prospective memory functioning on standardized questionnaires (p < 0.001, ηp2 = 0.285) and the structured interview (p < 0.001, d = 1.75). Participants performed relatively well on experimenter-assigned prospective memory tasks (51.7% ± 27.8%), with performance levels favoring the reminder app in Week 1, but reversing to favor the digital recorder app in Week 4 (p = 0.010, ηp2 = 0.079). Correlational analyses indicated that greater usage of the digital recorder or reminder app was associated with better prospective memory performance and greater improvements in instrumental activities of daily living (completed by care partners), even when controlling for condition, age, baseline cognitive functioning, and baseline smartphone experience.ConclusionsOlder adults with cognitive disorders can learn smartphone-based memory strategies and doing so benefits prospective memory functioning and independence.

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A prospective randomized trial examining health care utilization in individuals using multiple smartphone-enabled biosensors.

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A prospective randomized trial examining health care utilization in individuals using multiple smartphone-enabled biosensors.

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