Personally, I’m a proponent of giving patients self-titration schedules, particularly in my patients with systolic heart failure in whom I’m trying to maximize medical therapy. It’s a strategy I use somewhat sparingly though in part because of the difficulty to follow the home monitoring these patients are doing between clinic visits.
In the TASMIN-SR study by McManus et al, randomized approximately five hundred patients considered to be at “high risk,” meaning presence of comorbidities like diabetes mellitus, cardiovascular disease, or renal disease. Half were managed with usual care with their primary care physician.
The other half were randomized to a self-management program that began with two to three 1-hour training sessions to learn how to perform home blood pressure monitoring. They then met with their primary care physician to come with up a self-titration schedule, transcribed onto paper, based on those readings of up to three steps at a time; those steps could be serial increases in a single agent or addition of additional agents.
At twelve months, the intervention arm achieved a blood pressure reduction of 9 mm Hg / 3 mm Hg in comparison to the usual care group. This effect was attributed to a significantly greater medication use, both dose and number, in the intervention group.
In this study, the self-titration plan was agreed upon in a clinic visit and then transcribed onto a paper given to the patient. The patient then used an unconnected blood pressure cuff at home with pre-set parameters for the patient to notify their primary care physician if their readings were too high or too low. Notifications of self-titration were accomplished by having the patient send in paper notifications to their primary care physician.
There are clearly a number of opportunities here to streamline the process to help make it less cumbersome for the patient and improve the monitoring of patients undertaking this kind of self-titration strategy. There are a number of wireless blood pressure cuffs on the market as well as wired devices that can transmit data through USB connections to a computer.
With the coming standardization of health data being captured by personal health devices thanks to Google Fit and Apple HealthKit, this data can then be readily transferred into the electronic health record. Practice Fusion already does that with some personal health devices; Apple and Epic are working on developing that integration as well. Trials and pilots underway at institutions like Stanford and Duke are exploring the creation of automated alert systems to help filter the data being collected with pre-specified rules as it flows into their EHR.
There are a number of limitations in this study. When considering the integration of mobile health devices, two stand out. Of the 7,411 patients invited to participate, only 1,201 made it to the initial screening visit. About 2,000 patients gave reasons for not participating and somewhat surprisingly, roughly thirty percent said they did not want to self monitor and/or titrate medications themselves. In fact, the authors estimate that roughly twenty percent of “high risk” patients would be appropriate for this strategy of management.
Second, its worth noting that there was a lot of education that happened at the start of the study for the patients in the intervention group. Aside from the potential confounding effect that education alone could have, systematically teaching patients how to use these connected devices is something that can not happen in a current model of fifteen minute follow up visits.
Finally, cost is an important consideration here when it comes to using connected health devices. The cheapest wireless blood pressure cuffs are $100; the smartphones they require can be expensive as well but certainly don’t have to be particularly in the Android market. A standard, non-connected automated blood pressure cuff is roughly half that price.