Cold Spring Harbor is now hosting bioRxiv.org, a preprint archive
of biology papers, similar to the well known, decades-old physics one at
at Cornell's arXiv.org. This archive, if it becomes generally used, should break the unfair paywalls on publicly funded study results, at least for preprints. It should also allow often unpublishable negative studies to be placed where meta-analysts can use them. Therefore, this new archive deserves praise.
I intend to take advantage of this new source, and plan to review at least one preprint per weekend on this blog, unless the weekend gets too hectic. I intend to focus on neuroscience and clinical medicine related papers, but potentially will include other biological topics if they strike me as unusually interesting. Today, I'll review the only clinical trial paper in the archive so far.
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A prospective randomized trial examining health care utilization in individuals using multiple smartphone-enabled biosensors
Cinnamon S Bloss, Nathan E Wineinger, Melissa Peters, Debra L Boeldt, Lauren Ariniello, Ju Young Kim, Judy Sheard, Ravi Komatireddy, Paddy Barrett, Eric J Topol
bioRxiv doi: http://dx.doi.org/10.1101/029983
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) 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.
Clinical trial registration ID # NCT01975428
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The study was done on persons in the San Diego region who had hypertension, diabetes, or chronic cardiac arrhythmia. The subjects were given an iPhone based monitor for their condition which allowed them to periodically take a relevant measure of their condition and maintain records of these measurements with the Health Circles iPhone app. Both these persons and the controls were also "enrolled in the HealthComp disease management program, which involved outreach by HealthComp nursing staff for purposes of relaying medical education and wellness information with regard to disease prevention and chronic disease management."
The results were negative regarding health care financial costs: there was no endpoint statistical difference on health claims or visits to the hospital in the intervention group versus the control group.
This study suggests that adding a smartphone app database to the monitoring of chronic health conditions does not improve at least some measures of health costs. However, it does not include the newer, continuous monitoring devices, like the smartwatches which monitor pulse. I think that, to make a real difference in behavior, the measurement tech may need to function as a monitor in the background which can provide potentially unexpected feedback in the foreground when needed: it should be continuous and provide feedback otherwise not available to the patient, with little or no extra effort required by the patient. That type of technology is not yet available or ready for general use.