• Blake Eaton Samuel Taylor, Trae Robison, Eric Lo, Kyle McCormick, Eliza M Bruce, Geoffrey Appelboom, and E Sander Connolly.
• Neurosurgery. 2015 Aug 1;62 Suppl 1:215.

IntroductionEarly unplanned readmission is a major source of avoidable morbidity, mortality, and health care expenditure. In neurosurgery, 30-day readmissions are most often due to complications, the majority of which are associated with a decrease in physical activity. Wearable, commercially available motion sensors measure movements over time and transmit these data wirelessly via a smartphone application. These novel devices have the potential to objectively monitor patient recovery and capture complications and resulting readmissions as a single end point of activity. We sought to explore patient mobility patterns after discharge and their relationship to readmission.MethodsPatients with a smartphone (eg, iPhone, Android) were recruited postoperatively before hospital discharge. Each was given a FitBit ZipTM (FitBit Inc., San Francisco, California) (Table 1), a motion sensor whose accuracy we have previously validated. After syncing with patients' smartphones via Bluetooth, subjects were instructed to wear the FitBit clipped to their socks (Figure A). The number of daily steps recorded, a well-recognized surrogate of physical activity, was then monitored remotely for 30 days after discharge.ResultsOf the 23 patients enrolled, 4 were readmitted. Somewhat surprisingly, we observed that the integrity of the data was more associated with readmission than any particular pattern of physical activity pattern (Table 2). There were no readmissions among patients with complete data (Figure B), and an 11% readmission rate (expected in neurosurgery) among those with no data. However, subjects with either intermittent data, or data that were complete for the initial 5 days but subsequently became incomplete, had 2- and 4-fold the incidence of readmission (Figure C).ConclusionMobility sensors may be used to track patient recovery after discharge, and are scalable to a large patient population. Incomplete data may indicate poorer health status or poor compliance with wearing the device. Consistent with emerging data from others, poor compliance itself may indicate a higher risk of readmission. Our future efforts will aim to target patients at high risk of readmission and develop appropriate interventions.

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