Transcript Powerpoint

Scientific Approaches to Enrollment,
Engagement and Activation
POPULATION HEALTH & DISEASE MANAGEMENT COLLOQUIUM
March 3, 2009
© 2009 LifeMasters – Proprietary & Confidential
Current State of Disease Management
• Health plans in-sourcing to cut costs – pendulum swinging
back/skeptical about DM impact & causality
• Focus on Medical Home as silver bullet – all eggs now going into MD
basket
• Employer desiring “one-stop shop” with wellness/prevention focus –
nice but unproven
• Government focused on HIT as solution – critical but distant and
insufficient
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How We Got Here
• MHS flaws created skepticism
• Conflicting ROI methodologies – consultants, DMAA, academics
• DM industry consolidation/distraction
• Complex healthcare system – lots of problems to solve – constant
search for the silver bullet (Bob Berenson, Urban Institute, NYT
2/6/09)
• Economy isn’t helping
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Challenges DM Needs to Overcome
• Harness the power of the patient – really change behavior
• Better value demonstration
• Integration with other health improvement programs
• Support for the Medical Home and P4P
• Overcome perceptions of cost/value
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What We Are Still Trying to Achieve – Behavior
Change
Cost savings through better quality and improved health
Greater adherence by the patient to care plan and healthier lifestyles
• Greater understanding by the patient about how their behavior
contributes to their health
• Support and tools to help the patient change their behavior and stay
healthier
• Self-efficacy and motivation equals confidence
Earlier intervention by healthcare system to improve prevention and
prevent exacerbations
• Predictive models
• Monitoring and messaging
• More use of evidence-based care
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High Cost is Driven by Lack of Adherence to
Evidence-Based Care
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Patient Behavior is the Major Determinant of Health
Status
Determinants of Heath Status
*Source: IFTF, Centers for Disease Control and Prevention
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Where Does DM Need to Go?
Current State of Industry
DM 2.0
• Relentless focus on driving ROI through
• Consolidation – fewer, very large players;
lower cost and more targeted
interventions
– More effectively engage most appropriate
unfocused strategy
• Skepticism – MHS has created doubt about ROI,
ROI difficult to demonstrate; DM perceived as too
expensive
–
• Duplication and Fragmentation – efforts to solve
multiple problems has created multiple,
fragmented solutions resulting in greater cost and
complexity
–
• Loss of focus on true drivers of healthcare cost
increases – there has been demand created for
other types of programs that have not yet
demonstrated ROI distracting health
improvement firms from a focus on chronic
conditions and risk factors
–
–
• Slowing of demand – the economic downturn has
exacerbated the need to demonstrate true value
for every dollar spent on disease and care
management
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participants through segmentation
approach and integrated front end
Achieve higher levels of engagement
through alternative channels of
communication – high tech and high
touch
Drive better outcomes through more
targeted proven behavior change
techniques and physician participation
Achieve greater credibility of results
through transparency in pricing and value
demonstration
Reduce program cost through less
duplication and greater efficiency,
interoperability and integration of systems
and processes, and unbundled capabilities
to support existing client programs
DM Critical Success Factors
Establish supportive environment
• Data availability
• Organizational and support system alignment
• Incentives and encouragement
Segment population
• Preferences
• Risk level
• Activation
Intervene appropriately
• Outreach
• Monitoring
• Coaching
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These Apply to Each Step in the Process
Identify, find, and reach out:
• Environmental support
• Segmentation
• Intervention
Enrollment
Achieve appropriate and sustained participation:
• Environmental support
• Segmentation
• Intervention
Engagement
Improve knowledge, skills and confidence:
• Environmental support
• Segmentation
• Intervention
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Activation
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Activation is the Next Frontier in DM
Improve knowledge, skills and
confidence:
• Establish supportive environment
•Removing barriers
•Engaging physicians
• Segment the population
•Patient Activation Measure (PAM)
• Intervene appropriately
•Motivational interviewing
•Biometric monitoring
•Messaging and alerting
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Activation
LifeMasters’ Experience
• In conjunction with Judith Hibbard of the University of Oregon, LifeMasters conducted
a 12-month study, still under review for publication, to determine whether DM
outcomes can be improved by customizing patient care plans to the individual patient’s
level of activation (knowledge, skill, and confidence for self-management)
• Study design
• Quasi intervention-control groups by call centers
• Intervention – train healthcare professionals on use of PAM tool and Motivational
Interviewing (ABQ)
• Control – use PAM, but do not show results of tool, do not train on tool, but train
on Motivational Interviewing (SAC)
• Measure Activation scores at 2 – 3 month intervals
• Outcomes including: Δ PAM scores, clinical indicators, operational, cost outcomes,
nurse effect
• Population characteristics
• No difference in age, gender, level of depression
• Primary Dx Control groups – 43% HF, 12% CAD, 41% DM
• Primary Dx Intervention group – 12% HF, 32% CAD, 42% DM
• % Severity Level High – 92% Control, 75.2% Intervention
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Health Activation
• The term “patient (or health) activation” refers to having the knowledge,
skills, beliefs, and confidence to manage one’s health
• By understanding participants’ “activation levels,” health professionals
can better tailor participant coaching to an individual’s level of
activation, helping him or her identify and overcome barriers to
behavior change
• Higher levels of activation are correlated with improved selfcare
behaviors
• Increasing health activation results in improved adherence to plan of
care
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PAM™ Segmentation Characteristics
12% of the population
37% of the population
29% of the population
22% of the population
PAM segments participants into one of four progressively higher activation
levels. At the low end of the spectrum, an individual makes little to no
connection between his behaviors and health outcomes. At the high end,
participants have adopted new behaviors but need support in the face of
stress.
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Health Style Varies Dramatically When Seen
Through Lens of Self-Management
“I was really confident before I
got sick. I smoked, drank. I felt
fine. Then, I had to have open
heart surgery. I don’t know if I’ll
ever feel confident about my
health again”
“I don’t really understand what
they do (medications), but I try
to understand their side effects”
“I don’t know (treatment options)
… I just try to do what the doctor
tells me”
“My doctor takes care of me”
“I joined a support group. I
determined that I’m not going to
let this take over my life”
“My doctor can only do so much.
I have to manage my health”
“I write down my concerns. I
also have goals for myself – like
losing weight. I write down how
I’m doing with my goals. I’ve
lost 20 pounds!”
“I try to keep a positive attitude.
I exercise frequently, limit
intake of cholesterol, and try to
learn about my disease and
survivability”
15
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Self-Care Behaviors Display Across PAM Stages
Source: US National sample 2004
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Patient Activation Measure™ (PAM)
• The Patient Activation Measure™ (PAM)
was designed to assess an individual’s
knowledge, skills and confidence in playing
a role in one’s own health and healthcare.
• PAM consists of a 10 to 13-question survey
that asks people about their beliefs,
knowledge and confidence for engaging in
a wide range of health behaviors. Based on
responses to the survey, each person is
assigned an “activation score” and “level”
• Highly valid tool, tested in large
populations of all ages; some challenges in
ethnic groups
• Helps identify barriers to self-efficacy.
Coaches and participants work together
toward behavior change.
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PAM 13 - Tool (Low Literacy)
1.
When all is said and done, I am the person who is responsible for taking care of my health
problems.
Strongly Disagree
Disagree
Agree
Strongly Agree
2.
Taking an active role in my own health care is the most important thing that affects my
health.
Strongly Disagree
Disagree
Agree
Strongly Agree
3.
I am confident I can help prevent or reduce the problems associated with my health
condition.
Strongly Disagree
Disagree
Agree
Strongly Agree
4.
I know what each of my prescribed medications does.
Strongly Disagree
Disagree
Agree
Strongly Agree
5.
I am confident I can tell whether I need to go to the doctor or whether I can take care of a
health problem myself.
Strongly Disagree
Disagree
Agree
Strongly Agree
6.
I am confident that I can tell a doctor my concerns even when he or she does not ask.
Strongly Disagree
Disagree
Agree
Strongly Agree
7.
I am confident I can follow through on medical treatments I need to do at home.
Strongly Disagree
Disagree
Agree
Strongly Agree
8.
I understand my health problems and what causes them.
Strongly Disagree
Disagree
Agree
Strongly Agree
9.
I know what treatments are available for my health problems.
Strongly Disagree
Disagree
Agree
Strongly Agree
10.
I have been able to maintain (keep up with) lifestyle changes, like eating right and
exercising.
Strongly Disagree
Disagree
Agree
Strongly Agree
11.
I know how to prevent further problems with my health condition.
Strongly Disagree
Disagree
Agree
Strongly Agree
12.
I am confident I can figure out solutions when new problems arise with my health
condition.
Strongly Disagree
Disagree
Agree
Strongly Agree
13.
I am confident I can maintain lifestyle changes, like eating right and exercising, even
during times of stress.
Strongly Disagree
Disagree
Agree
Strongly Agree
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Empirical Validation of PAM ™
More than 80 studies of the Patient Activation Measure™ selfassessment tool have been completed or are underway worldwide. A
selection of key studies is outlined below.
• Development of the Patient Activation Measure™ : Conceptualizing and
Measuring Activation in Patients and Consumers
• Do Increases in Patient Activation Result in Improved SelfManagement Behaviors?
• Is Patient Activation Associated with Better Outcomes for Persons with
Diabetes
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Most Recent Literature
• 2007 Health Tracking Household Survey is the first large nationally
representative survey—information on 13,500 adults
• People with low incomes, less education, Medicaid enrollees, and people with
poor self-reported health can be activated but have farther to go
• Overall, people with chronic conditions are more likely to have lower levels of
activation—about 26% in level one or two—compared with people without any
chronic conditions—about 18% in level one or two
• People with lower activation levels are much more likely to report unmet medical
needs, to delay care and to have unmet prescription drug needs. Less activated
people are also less likely to have a usual source of care
• 83.6 percent of those at the highest activation level reported that their health
care provider helped them to set goals to improve their diet, compared with 48.3
percent at the lowest activation level
Robert Wood Johnson Foundation, Center for Studying Health System Change (HSC), 10/16/08
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Motivational Interviewing Key Component of
Engagement
• “Think of it like this - if someone drives you to the
location, you have no way of knowing how to get
there yourself. Only when you are in the driver's seat
do you learn the route and remember how to get
there. If we keep spoon-feeding the participants
with all the information, tips, advice, direction we
think they need, they'll never learn the route
themselves. With MI, the participant drives and
learns the way. As a collaborative partner with the
participant, we are in the passenger seat, ready to
help, but the participant drives.”
• B. Gonzales
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Unique Coaching Model: Primary Nurse + MI + PAM
• Model provides each participant with his or her own
dedicated LifeMasters Health Professional, which creates
trust channel and drives continuous engagement
• Patient Activation Measure segments the population
• Motivational Interviewing guides the interaction
Patent Pending
* Motivational Interviewing + Patient Activation Measure Segmentation
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Preliminary Outcomes (Under Review for Publication)
Change in PAM Score over 6 Months
PAM Score
70
68
66
64
62
Control Usual Care
PAM Intervention Group
Baseline
Mediation Drop Out Rate over 6 Months
Post
N=245 in intervention group; N=122 in control group. Only those with 3
PAM scores are included. Repeated measures show that the gains in
activation are significant in the intervention group and not significant for the
control group (P<.001)
45%
40%
35%
30%
25%
20%
15%
10%
5%
0%
PAM Intervention Group
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Control Usual Care
Preliminary Outcomes (Under Review for Publication)
Talk Times in Intervention and Control Group
Average talk time (minutes)
Coaching Call Talk Times
19
18
17 17
16
17
16
Activation Level 1
Activation Level 2
Activation Level 3
Activation Level 4
16 16
16
13
Control usual care
PAM tailored
Coaching
Source: National DM Firm. N=1030 intervention; N=501 in control group.
Difference between the two groups is significant at the .05 level
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Preliminary Outcomes (Under Review for Publication)
•Clinical Indicators trend toward improvement in Intervention
•LDL and DBP improved
•No change A1c, SBP
•Adherence to recommended tests and treatment improved in
Intervention over control including (met SS):
•Aspirin therapy for CAD
•Anti-platelet with Diabetes
•Anti-lipidemic therapy
•Beta Blocker therapy
•Flu Vaccine
•Pneumococcal Vaccine (did not meet SS)
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Preliminary Outcomes (Under Review for Publication)
• Utilization rates fell in intervention group - range from 8% in office
visit costs to 54% in inpatient costs
• Significantly greater cost reductions occurred in intervention group in
all categories of utilization
• Costs in control group stayed flat in two categories, increased in two
categories, and dropped in two categories.
• Self-Monitoring Sessions decreased in both Control and Intervention,
but steeper decrease for Control
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PAM Study Conclusions
“Overall, the findings show a consistent picture
indicating a positive impact of the Intervention.
Activation scores increased, clinical indicators improved,
and costs and utilization declined to a greater extent in
the intervention group than in the control group. That is
to say, the trends appear to be consistent and in the
same direction across indicators.” – Dr. Judith Hibbard
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Limitations of Study
• Shortened time of study due to real-life issues with clients may not have
allowed full effect of outcomes to surface
• Not full data on all the parameters
• Study didn’t randomly assign participants to control and intervention
groups (randomization done on healthcare professionals)
• An additional matched control population was compared to the
intervention population. The outcomes held.
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Further Questions for Study and Consideration
• Is movement through activation level a better measure of DM program
success than ROI or clinical gap closure?
• How does the strong correlation between activation and selfcare
behaviors translate into improved outcomes and lower costs?
• What role can/should physicians play in getting their patients more
activated?
• Can Activation be improved using other types of touches (high tech
versus high touch MI)?
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Questions & Discussion
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