Regression Modeling System Using Activation Scale Values as Inputs to a Regression to Predict Healthcare Utilization and Cost and/or Changes Thereto

1 . A computer-implemented method for modeling, using a computer system, to predict healthcare utilization and cost based upon a person's activation scale value, wherein the activation scale value is a variable representing, as a number, a user's patient activation and/or self-management ability in making health decisions, the method comprising:

obtaining activation scale values over a plurality of survey participants;

generating a regression to identify a predictive model that can have a direct explanatory relationship to dependent variables, including healthcare utilization and cost, wherein the predictive model models changes in the dependent variables as a result of changes in the activation scale values, wherein the dependent variables and the activation scale values are equal-interval scale continuous variables; and

outputting results.

2 . The computer-implemented method of claim 1 , wherein the activation scale is an empirically-derived, linear, equal interval scale.

3 . The computer-implemented method of claim 1 , wherein the activation scale values are based at least in part on independent and dependent variables, wherein the independent and dependent variables are equal-interval scale continuous variables.

4 . The computer-implemented method of claim 1 , wherein the activation scale values are determined based on a survey of a user's level of agreement with declarative statements, the declarative statements including:

(a) I am the person who is responsible for taking care of my health;

(b) Taking an active role in my own health care is the most important thing that affects my health;

(c) I am confident I can help prevent or reduce problems associated with my health;

(d) I know what each of my prescribed medications do;

(e) I am confident that I can tell whether I need to go to a doctor or whether I can take care of a health problem myself;

(f) I am confident that I can tell a doctor concerns I have even when he or she does not ask;

(g) I am confident that I can follow through on medical treatments I may need to do at home;

(h) I understand my health problems and what causes them;

(i) I know what treatments are available for my health problems;

(j) I have been able to maintain (keep up with) lifestyle changes, like eating right or exercising;

(k) I know how to prevent problems with my health;

(l) I am confident I can figure out solutions when new problems arise with my health; and

(m) I am confident that I can maintain lifestyle changes, like eating right and exercising, even during times of stress.

5 . A computer-implemented method for modeling, using a computer system, to predict healthcare utilization and cost based upon a user activation scale, wherein an activation scale value is a variable representing, as a number, a user's patient activation, self-management ability, and/or engagement in one's own health and healthcare, the method comprising:

providing a survey of self-management declarative statements to a set of users, to each user of the set of users;

mapping the results of the survey from ordinal responses to an empirically-derived, linear, equal interval scale to form activation scale values;

performing a regression model, employing Rasch measurement modeling, on the activation scale values;

outputting results of the regression model based at least in part on the results; and

using, at least in part, the results to predict healthcare utilization and cost outcomes for each user, of the set of users.

6 . A non-transitory computer-readable storage medium having stored thereon executable instructions that, when executed by one or more processors of a computer system, cause the computer system to at least:

provide a survey of self-management declarative statements to a population of users, each user of the population of users providing ordinal survey responses to survey declarative statements;

map survey responses from ordinal responses to an empirically-derived, linear, equal interval scale to form activation scale values;

perform a regression analysis using Rasch measurement modeling on the activation scale values;

output results of the regression analysis; and

use, at least in part, the results to predict healthcare utilization and cost outcomes for each user of the population of users.

7 . The non-transitory computer-readable storage medium of claim 6 wherein the survey responses, once rendered, provide activation scale values that are determined based on the survey.