METHOD FOR MODELING BEHAVIOR AND HEALTH CHANGES

1 . A method comprising:

selecting a subgroup of patients associated with a health condition from a population of patients, patients in the subgroup exhibiting similar behavioral characteristics;

for patients within the subgroup, characterizing communication behavior of a patient based on use of a native communication application executing on a corresponding mobile computing device by the patient during the period of time;

extracting characteristics of medical symptoms of patients within the subgroup from surveys submitted by patients within the subgroup;

identifying a relationship between communication behaviors of patients within the subgroup, characteristics of medical symptoms of patients within the subgroup, and a treatment regimen administered to patients within the subgroup;

generating a treatment efficacy model for the subgroup based on the relationship, the treatment efficacy model defining a correlation between a change in communication behavior and efficacy of the treatment regimen in alleviating medical symptoms of patients within the subgroup.

2 . The method of claim 1 , further comprising

accessing a log of use of a native communication application executing on a corresponding mobile computing device by a subsequent patient,

selecting the treatment efficacy model based on the log of use of the native communication application and a communication behavior common to the subgroup,

predicting an efficacy of the treatment regimen for the subsequent patient based on the log of use of the native communication application and the treatment efficacy model, and

transmitting a notification to a care provider associated with the patient in response to the efficacy of the treatment for the patient that falls below a threshold efficacy.

3 . The method of claim 1 , wherein generating the treatment efficacy model for the subgroup comprises generating the treatment efficacy model that defines a correlation between a change in communication behavior and response to the treatment regimen within the subgroup based on characteristics of medical symptoms of patients within the subgroup during administration of the treatment regimen.

4 . The method of claim 1 , wherein extracting characteristics of medical symptoms of patients within the subgroup from surveys submitted by patients within the subgroup comprises extracting characteristics of medical symptoms of a subset of patients within the subgroup from surveys submitted by the subset of patients.

5 . The method of claim 1 , wherein characterizing communication behavior of a patient, for the patient within the subgroup, comprises detecting a change in communication behavior by the patient, wherein extracting characteristics of medical symptoms of patients within the subgroup comprises detecting changes in symptom severity within patients within the subgroup, and wherein identifying the relationship between communication behavior of patients within the subgroup and characteristics of medical symptoms of patients within the subgroup comprises identifying a relationship between changes in communication behavior and changes in symptom severity for patients within the subgroup.

6 . The method of claim 11 , wherein characterizing communication behavior of a patient within the subgroup comprises generating a quantitative assessment of a frequency and a duration of outgoing phone calls and textual communications from the corresponding mobile computing device during a preset time period.

7 . A method comprising:

selecting a population of patients prescribed a treatment regimen for a health condition;

for a patient within the population, characterizing communication behavior of the patient based on use of a native communication application executing on a corresponding mobile computing device by the patient prior to initiation of a treatment regimen and during administration of the treatment regimen to the patient;

selecting a subgroup of patients from the population of patients based on similar communication behaviors prior to initiation of the treatment regimen;

extracting treatment responses from surveys completed by patients within the subgroup during administration of the treatment regimen;

generating a treatment regimen model for the subgroup, the treatment regimen model defining a correlation between communication behavior, treatment responses, and treatment regimen outcomes for patients within the subgroup;

characterizing communication behavior of a subsequent patient based on use of a native communication application executing on a corresponding mobile computing device by the subsequent patient; and

generating a predicted treatment regimen outcome for the subsequent patient based on a similarity between communication behavior of the subsequent patient and communication behavior common within the subgroup.

8 . The method of claim 7 , further comprising transmitting the predicted treatment regimen outcome to a care provider specified in a digital health profile associated with the subsequent patient.

9 . The method of claim 8 , further comprising generating a custom treatment regimen for the subsequent patient, the custom treatment prescription defining a medication dosage based on the predicted treatment regimen outcome, wherein transmitting the predicted treatment regimen outcome to the care provider further comprises transmitting the custom treatment regimen to the care provider.

10 . The method of claim 7 , wherein characterizing communication behavior of the subsequent patient comprises accessing a log of use of outgoing voice communications from a phone call application executing on the corresponding mobile computing device.

11 . The method of claim 7 , wherein characterizing communication behavior of patients within the subgroup comprises characterizing frequency, duration, timing, and contact diversity of voice communications and frequency, duration, and timing of accepted incoming voice communications within phone call applications executing on mobile computing devices corresponding to patients within the subgroup, and wherein generating the treatment regimen model for the subgroup comprises identifying patterns in communication behavior during administration of the treatment regimen and correlating patterns in communication behavior with treatment responses of patients within the subgroup.

12 . The method of claim 7 , wherein selecting the population of patients comprises accessing anonymized patient profiles tagged with the health condition.

13 . The method of claim 7 , wherein extracting treatment responses from surveys completed by patients within the subgroup comprises analyzing anonymized survey responses uploaded from mobile computing devices corresponding to patients within the subgroup and stored in association with corresponding patient profiles.

14 . The method of claim 7 , wherein generating the predicted treatment regimen outcome comprises predicting a health condition relapse risk for the subsequent patient based on the treatment regimen model.

15 . A method for supporting a patient through a treatment regimen, the method comprising:

accessing a log of use of a native communication application executing on a mobile computing device by a patient within a period of time;

selecting a subgroup of a patient population based on the log of use of the native communication application and a communication behavior common to the subgroup;

retrieving a regimen adherence model associated with the subgroup, the regimen adherence model defining a correlation between treatment regimen adherence and communication behavior for patients within the subgroup;

predicting adherence to the treatment regimen by the patient based on the log of use of the native communication application and the regimen adherence model;

extracting a treatment response of the patient from a patient survey corresponding to the period of time;

estimating an efficacy of the treatment regimen in treating a health condition of the patient according to a comparison between the treatment response and the adherence to the treatment regimen by the patient;

transmitting a notification to a care provider associated with the patient in response to the efficacy of the treatment regimen that falls below a threshold efficacy.

16 . The method of claim 15 , further comprising generating an updated treatment regimen according to the efficacy of the treatment regimen; and

17 . The method of claim 15 , wherein accessing the first log of use of the native communication application comprises generating a quantitative assessment of a log and a duration of outgoing phone calls and textual communications from the mobile computing device during the first time period.

18 . The method of claim 15 , wherein generating the updated treatment regimen comprises modifying a medication dosage specified by the treatment regimen according to the efficacy of the treatment regimen, and wherein presenting the notification to the patient comprises displaying the medication dosage on a display of the mobile computing device in accordance with the updated treatment regimen.