Consumer Directed Health Plans and Patient Activation Judith Hibbard Jessica Greene Martin Tusler University of Oregon Funding Provided by the Robert Wood Johnson Foundation through the HCFO Initiative
A Key Assumption is that CDHPs will activate consumers to become better managers of their health and health care.
Emerging Evidence Suggests that Consumers do change Behavior in a CDHP Seek out information Increase use of preventive care Reduce utilization Cease chronic disease medications
Specific Research Questions: Do the more activated choose a CDHP? Do those in a CDHP become more activated over time? Are the more activated more likely to engage in health promoting behaviors? More likely to adopt new health promoting behaviors? Are the more activated less likely to engage in unproductive behaviors? Less likely to adopt new unproductive behaviors?
Measuring Activation Patient Activation Measure assesses knowledge, skills, and confidence for managing health and health care Developed using qualitative methods, classical test theory, and Rasch analysis. The resulting metric, is a unidimensional, interval level, Guttman-style measure with strong psychometric properties.
Data Mixed mode survey (2004 and 2005) from employees offered CDHP and PPO plans in 2004 (n=2104) response rate 79%; 2005 (n=1616) response rate 80% Collapsed high deductible and low deductible CDHP in this analysis Analysis compares the PPO enrollees with those who opted into the CDHP
Favorable Selection into CDHP Fewer Chronic Conditions Lower Medical Claims Lower Pharmacy Claims Better Educated
Those who are More Activated More likely to Enroll in a CDHP PAM score by plan type Key: *** p <.001
Activation Did Not Change Significantly for CDHP or PPO enrollees from Key: Differences are not significant, Paired-Samples t-test
Information Seeking by Plan Type Plan type with higher likelihood of behavior Behavior Used any health website CDHP***CDHP** Used a telephone advice nurse NSNS Was persistent in asking doctor to explain questions NSNS Key: * p <.05, *** p <.001
Behaviors by Plan Type Plan type with higher likelihood of behavior Risky Cost Saving Behaviors Didn't go to doctor to save money PPO*PPO* Took lower dose to save money NSNS Did not fill prescription to save money NSNS Healthy Behaviors Limited fat in diet CDHP***NS ExercisedCDHP***NS Ate 5 daily servings of fruits or vegetables NSNS Key: * p <.05, *** p <.001
Multivariate Analysis: Information Seeking by PAM Score in 2004 Key: * p <.05, ** p <.01, *** p <.001, Controlling for Education, Income, Age, Health, job type, gender, and survey mode PPOCDHP Legend:Did not do the behavior Did the behavior
Multivariate Analysis: Risky Cost-Saving Behaviors by PAM score in 2004 PPOCDHP Legend:Did not do the behavior Did the behavior Controlling for Education, Income, Age, Health, job type, gender, and survey mode
Multivariate Analysis: Healthy Behaviors by PAM score in 2004 Key: * p <.05, ** p <.01, *** p <.001 Controlling for Education, Income, Age, Health, job type, gender, and survey mode PPOCDHP Legend:Did not do the behavior Did the behavior
Multivariate Analysis: New Information Seeking by PAM score in 2005 Key: * p <.05, ** p <.01, *** p <.001, Controlling for Education, Income, Age, Health, job type, gender, and survey mode PPOCDHP Legend:Did not adopt the behavior Adopted the behavior
Multivariate Analysis: New Risky Cost-saving Behaviors by PAM score in 2005 PPOCDHP Legend:Did not adopt the behavior Adopted the behavior Controlling for Education, Income, Age, Health, job type, gender, and survey mode
Multivariate Analysis: New Healthy Behaviors by PAM score in 2005 Key: * p <.05, ** p <.01 Controlling for Education, Income, Age, Health, job type, gender, and survey mode PPOCDHP Legend:Did not adopt the behavior Adopted the behavior
Activation As a Predictor of Information Seeking Behaviors Activation As a Predictor of Information Seeking Behaviors Behavior Used any health website *** Used a telephone advice nurse **** Was persistent in asking doctor to explain ****** KEY: Based on Logistic Regressions controlling for Education, Income, Age, Self- reported Health, Gender, Hourly/Salaried, Plan Type, and Survey Mode
Activation as a Predictor of Behavioral Adoption Activation as a Predictor of Behavioral Adoption KEY: Based on Logistic Regressions controlling for Education, Income, Age, Self- reported Health, Gender, Hourly/Salaried, Plan Type, and Survey Mode Risky Cost Saving Behaviors Didn't go to doctor to save money NSNS Took lower dose to save money NSNS Did not fill prescription to save money NSNS Healthy Behaviors Limited fat in diet ****** Exercised***** Ate 5 daily servings of fruits or vegetables *****
Summary Those more activated more likely to enroll in a CDHP Experience in a CDHP does not appear to increase activation Activation is related to many of the behaviors encouraged by health plans, this is true regardless of plan design CDHP’s good choice for those already activated