Abstract: The present technology calculates a value of future adherence (VFA) score which is a patient-level, predicted, expected cost of conversion from non-adherence to adherence over a specified time-frame. The score consists of three general components: (1) probability of being non-adherent, (2) cost reduction associated with being adherent, and (3) probability of converting from non-adherent to adherent. These values can be combined to create an overall VFA score. A user interface is then provided which shows at least a list of patients and information related to the VFA score.

Abstract: The technology described herein relates to using predictions about patients' future health care utilization and/or outcomes (e.g., patients' expected future adherence to medication regimens) and the expected economic benefits of targeted improvements in the same utilization and/or outcomes (e.g., reduced likelihood of hospitalization attributable to more consistent medication use) to implement more effective and efficient health care improvement programs. The technology described here computes which subset of patients should be included in a value-based health care provider payment scheme and what the specific bonus payment amounts should be such that expected benefits from better patient outcomes, once realized, are greater than the expected costs of the payment scheme itself.

Abstract: The present technology calculates a value of future adherence (VFA) score which is a patient-level, predicted, expected cost of conversion from non-adherence to adherence over a specified time-frame. The score consists of three general components: (1) probability of being non-adherent, (2) cost reduction associated with being adherent, and (3) probability of converting from non-adherent to adherent. These values can be combined to create an overall VFA score. A user interface is then provided which shows at least a list of patients and information related to the VFA score.

Abstract: The technology described herein relates to using predictions about patients' future health care utilization and/or outcomes (e.g., patients' expected future adherence to medication regimens) and the expected economic benefits of targeted improvements in the same utilization and/or outcomes (e.g., reduced likelihood of hospitalization attributable to more consistent medication use) to implement more effective and efficient health care improvement programs. The technology described here computes which subset of patients should be included in a value-based health care provider payment scheme and what the specific bonus payment amounts should be such that expected benefits from better patient outcomes, once realized, are greater than the expected costs of the payment scheme itself.

Abstract: The present technology calculates a value of future adherence (VFA) score which is a patient-level, predicted, expected cost of conversion from non-adherence to adherence over a specified time-frame. The score consists of three general components: (1) probability of being non-adherent, (2) cost reduction associated with being adherent, and (3) probability of converting from non-adherent to adherent. These values can be combined to create an overall VFA score. A user interface is then provided which shows at least a list of patients and information related to the VFA score.

Abstract: The present technology calculates a value of future adherence (VFA) score which is a patient-level, predicted, expected cost of conversion from non-adherence to adherence over a specified time-frame. The score consists of three general components: (1) probability of being non-adherent, (2) cost reduction associated with being adherent, and (3) probability of converting from non-adherent to adherent. These values can be combined to create an overall VFA score. A user interface is then provided which shows at least a list of patients and information related to the VFA score.

Abstract: The technology described herein relates to using predictions about patients' future health care utilization and/or outcomes (e.g., patients' expected future adherence to medication regimens) and the expected economic benefits of targeted improvements in the same utilization and/or outcomes (e.g., reduced likelihood of hospitalization attributable to more consistent medication use) to implement more effective and efficient health care improvement programs. The technology described here computes which subset of patients should be included in a value-based health care provider payment scheme and what the specific bonus payment amounts should be such that expected benefits from better patient outcomes, once realized, are greater than the expected costs of the payment scheme itself.