Abstract: Systems and techniques are disclosed for determining an intervention for a patient based at least in part on a likelihood of the patient to adhere to a prescription. In some implementations, a patient profile for a patient is obtained from one or more computer-readable storage devices in a patient population, the patient profile including multiple patient attributes; an adherence score is obtained for the patient profile, the adherence score for predicting patient adherence based on one or more of the multiple patient attributes wherein the adherence score indicates a likelihood of adherence of the patient to a prescribed treatment; and the adherence score obtained for the patient profile is modified into a modified score for intervention based on a set of weights for weighting the patient attributes.

Abstract: Systems and techniques are disclosed for determining a health risk assessment score for a patient who did not complete a health risk assessment. In some implementations, the health risk assessment score can be determined for the patient who did not respond based on a behavior prediction score obtained for the patient who did not respond, behavior prediction scores for patients who did respond to the health risk assessment, and health risk assessment scores for the patients who did respond.

Abstract: Systems, methods and devices for modifying a patient adherence score which include, in one implementation, obtaining a patient profile in a patient population, the patient profile including multiple patient attributes and each patient attribute including a value; obtaining an adherence score for the patient profile for predicting patient adherence based on one or more of the multiple patient attributes wherein the adherence score indicates a likelihood of adherence of the patient to the prescribed treatment; and applying a modifier associated with an application to modify the adherence score obtained for the patient profile into a modified score for the application.

Abstract: Behavior predication scores of patients can be aggregated for a physician, a group of physicians, or a health care plan. In some embodiments, social health network data can be obtained for a social health network of health care professionals, the social network data including relationships between the health care professionals; behavior prediction scores can be obtained for patients of a health care professional in the network; the behavior predication scores of the patients of the health care professional can be aggregated to determine an aggregate score for the health care professional; and an influence score for the health care professional can be generated based on the aggregate score.

Abstract: System and techniques are disclosed for determining a recommended prescription. In some examples, a recommended prescription can be determined by obtaining a behavior prediction score for a patient, wherein the behavior prediction score is based at least in part on a likelihood of adherence of the patient to a prescribed treatment; and determining a recommended prescription, from various previously provided prescriptions, based on the behavior prediction score and prescription scores of the various previously provided prescriptions; and providing the recommended prescription for display. The prescription scores can indicate a likely effect of the various previously provided prescriptions on adherence.

Abstract: Systems and techniques are disclosed for determining a health risk assessment score for a patient who did not complete a health risk assessment. In some implementations, the health risk assessment score can be determined for the patient who did not respond based on a behavior prediction score obtained for the patient who did not respond, behavior prediction scores for patients who did respond to the health risk assessment, and health risk assessment scores for the patients who did respond.

Abstract: Systems and techniques are disclosed for determining an intervention for a patient based at least in part on a likelihood of the patient to adhere to a prescription. In some implementations, a patient profile for a patient is obtained from one or more computer-readable storage devices in a patient population, the patient profile including multiple patient attributes; an adherence score is obtained for the patient profile, the adherence score for predicting patient adherence based on one or more of the multiple patient attributes wherein the adherence score indicates a likelihood of adherence of the patient to a prescribed treatment; and the adherence score obtained for the patient profile is modified into a modified score for intervention based on a set of weights for weighting the patient attributes.

Abstract: Systems, methods and devices for modifying a patient adherence score which include, in one implementation, obtaining a patient profile in a patient population, the patient profile including multiple patient attributes and each patient attribute including a value; obtaining an adherence score for the patient profile for predicting patient adherence based on one or more of the multiple patient attributes wherein the adherence score indicates a likelihood of adherence of the patient to the prescribed treatment; and applying a modifier associated with an application to modify the adherence score obtained for the patient profile into a modified score for the application.