Capturing person-specific self-reported subjective experiences as behavioral predictors
AssigneeAdoh Scientific, LLC
InventorsGregg T. Hanold, Brian Sullivan, Corley Sullivan
Life of this patent
Estimating the term…
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AssigneeAdoh Scientific, LLC
InventorsGregg T. Hanold, Brian Sullivan, Corley Sullivan
Estimating the term…
Disclosed methodologies provide improved predictors of patient treatment adherence by using person-specific subjective experience and social-environmental factors. Methodologies combine emotion and data sciences. Advanced tools capture, measure, store, and analyze self-report of subjective experiences using digital applications and platforms. Patient-specific data is obtained regarding emotional or affective determinants and social determinants for generating a calculated composite score of the patient's probability of adherence or achievement relative to target outcomes, e.g. adherence to treatment plans, wellness activities, etc. for a subject individual. Internal/subjective factors are judged by self-report measures designed to validly judge tested factors based on a patient adjusting continuously-variable graphical interfaces to capture and measure subjective experiences. Emotional characteristics may include perception and intensity in each category of sickness versus wellness, stress, depression, anxiety, pain, and feelings about most recent health provider/staff interaction (with determined intensity for choices of Delighted, Satisfied, Meh, Disappointed, Frustrated). Emotional characteristics may be considered among health, and social characteristics in measuring potential obstacles to adherence.
A methodology for predictively determining a patient's likelihood to adhere to a healthcare treatment plan for such patient, comprising:
A methodology for predictively determining a participant's likelihood to adhere to an activity plan for such participant, comprising:
A system for predictively determining a given patient's likelihood to adhere to a healthcare treatment plan for such patient, comprising:
Dependencies are inferred from the claim text.