Behavioral data is the information collected about individuals' actions and interactions across various digital and physical environments. The data provides insights into how patients engage with services and respond to interventions and can help reveal the “why” behind patient behaviors rather than just the “what”.
According to a study published in Nature Neuroscience, “The promise of big behavioral data: to sample more densely in a systematic fashion and to interconnect different sampled regions by means of standardizing and sharing data.”
For example, behavioral data can provide patterns in medication adherence, identify barriers to care, or detect early signs of health deterioration through changes in activity or engagement with health resources. It allows healthcare providers to personalize care plans and anticipate needs through predictive analytics.
Analyzing patient behaviors allows providers to identify patterns that reveal underlying challenges or opportunities for intervention. If behavioral data shows that a patient frequently misses follow-up appointments, the insight could indicate barriers like transportation issues.
A study published in Behavioral Insights in Healthcare notes, “Behavioural insights has been described as ‘the application of behavioral science to policy and practice with a focus on (but not exclusively) “automatic” processes’. Both behavioral economics and behavioral insights draw on the idea that people have two systems for processing information and decision-making – the automatic and the reflective.”
Wearable device data tracking sleep and activity levels can help detect early signs of health deterioration like fatigue. Predictive analytics further improves insights by forecasting future behaviors and risks based on historical data, allowing organizations to proactively allocate resources and design preventative strategies.
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Predictive analytics uses historical and real-time data to identify high-risk patients and anticipate their needs, enabling healthcare providers to proactively engage these patients with targeted interventions.
Technology allows for patient engagement through platforms like patient portals, mobile apps, and telehealth services that allow for easy access to health information and direct communication with providers.
Providers can measure effectiveness through patient satisfaction surveys, tracking adherence rates to treatment plans, monitoring health outcomes, and analyzing feedback.