Medical accountable provider platform
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.
1. A system configured to identify a patient population in a healthcare program based on, in part, a predictive function applied to characteristics of a patient, the system comprising:
a processor; and
a memory configured to store computer readable instructions that, when executed by the processor, cause the system to:
determine a list of health care providers and a list of patients;
obtain one or more data files including historical data for each patient;
apply the historical data to one or more variables and generate a resultant data file;
apply the resultant data file to a model setup procedure to generate a prediction function;
generate an adherence risk score for each patient, in the list of patients, using the prediction function;
apply the score to each patient in the list of patients;
identify a subset of patients, from the listing of patients, based on, at least, factors related to a likelihood of adherence after an intervention is carried out; and
generate a user interface for display having at least a first view, a second view, and a third view, wherein the first view includes:
a home menu display having a plurality of selectable options; and
the second view includes:
an itemized listing of patients from the subset of patients, wherein each line in the itemized listing includes an identification of each patient and at least one therapy associated with each patient, and each patient in the itemized listing is associated with the applied score; and
the third view includes patient details associated with a first patient from the itemized listing of patients, and the third view further includes:
a first portion identifying a therapy associated with the first patient, and an indication associated with a refill value for the therapy associated with the first patient.
2. The system of claim 1 , wherein the home menu display includes a text portion having introductory text.
3. The system of claim 1 , wherein
a first option, from the plurality of selectable options, includes a patient list option, and
selection of the patient list option enables changing of display from the first view to the second view.
4. The system of claim 1 , wherein the third view includes a financial indicator in association with the first patient and the associated therapy.
5. The system of claim 1 , wherein the third view includes a first portion having barrier assessment indicators for identifying one or more barriers associated with adherence to the therapy associated with the first patient.
6. The system of claim 1 , wherein the third view includes indication of bonus opportunity associated with the therapy.
7. The system of claim 1 , wherein the third view includes indication of a prescriber associated with the therapy.
8. The system of claim 1 , wherein generating the adherence risk score for each patient comprises:
defining relevant time periods for analyzing the historical data;
defining a dependent variable indicative of a measure to be predicted;
determining at least one independent predictor variable;
creating the resultant data file including the dependent and independent variable; and
deriving the adherence risk score based on the resultant data file.
9. The system of claim 1 , wherein the model setup procedure includes dividing the resultant data file into a training data file and a validation data file.
10. A method for identifying a patient population in a healthcare program, the method comprising:
at an information processing system including at least one processor:
determining a list of health care providers and a list of patients;
obtaining one or more data files including historical data for each patient;
applying the historical data to one or more variables and generate a resultant data file;
applying the resultant data file to a model setup procedure to generate a prediction function;
generating an adherence risk score for each patient, in the list of patients, using the prediction function;
applying the score to each patient in the list of patients;
identifying a subset of patients, from the listing of patients, based on, at least, factors related to a likelihood of adherence after a given intervention is carried out; and
generating a user interface for display having at least a first view, a second view, and a third view, wherein the first view includes:
a home menu display having a plurality of selectable options; and
the second view includes:
an itemized listing of patients from the subset of patients, wherein each line in the itemized listing includes an identification of each patient and at least one therapy associated with each patient, and each patient in the itemized listing is associated with the applied score; and
the third view includes patient details associated with a first patient from the itemized listing of patients, and the third view further includes:
a first portion identifying a therapy associated with the first patient, and an indication associated with a refill value for the therapy associated with the first patient.
11. The method of claim 10 , wherein the user interface further includes indication of adherence opportunity associated with a practice group.
12. The method of claim 10 , wherein the user interface further includes an identification of a number of patients associated with a practice group.
13. The method of claim 10 , wherein the user interface further includes a bar graph reflecting an adherence opportunity associated with a practice group.
14. The method of claim 10 , wherein the user interface further includes a first portion identifying adherence opportunities achieved by a practice group, and a second portion identifying adherence opportunities currently unachieved by the practice group.
15. A non-transitory computer readable storage medium storing computer readable instructions that, when executed by a processor, cause the processor to provide execution comprising:
determining a list of health care providers and a list of patients;
obtaining one or more data files including historical data for each patient;
applying the historical data to one or more variables and generate a resultant data file;
applying the resultant data file to a model setup procedure to generate a prediction function;
generating an adherence risk score for each patient, in the list of patients, using the prediction function;
applying the score to each patient in the list of patients;
identifying a subset of patients, from the listing of patients, based on, at least, factors related to a likelihood of adherence after an intervention is carried out; and
generating a user interface for display having at least a first view, a second view, and a third view, wherein the first view includes:
a home menu display having a plurality of selectable options; and
the second view includes:
an itemized listing of patients from the subset of patients, wherein each line in the itemized listing includes an identification of each patient and at least one therapy associated with each patient, and each patient in the itemized listing is associated with the applied score; and
the third view includes patient details associated with a first patient from the itemized listing of patients, and the third view further includes:
a first portion identifying a therapy associated with the first patient, and an indication associated with a refill value for the therapy associated with the first patient.
16. The non-transitory computer readable storage medium of claim 15 , wherein the user interface further includes an indication associated with practice group participation.
17. The non-transitory computer readable storage medium of claim 15 , wherein the user interface further includes numerical values associated with adherence opportunities of patients within each practice group from a plurality of practice groups.
18. The non-transitory computer readable storage medium of claim 15 , wherein the user interface further includes information details associated with a first practice group from a plurality of practice groups.
19. The non-transitory computer readable storage medium of claim 18 , wherein selection of an item in the second view enables changing of display from the second view to the third view.
20. The non-transitory computer readable storage medium of claim 18 , wherein the user interface further includes an identification of prescribing opportunity associated with at least the first practice group from the plurality of practice groups.