Star Ratings are increasingly challenging to maintain and improve upon each year. It is incredibly important to improve upon programs each year. What you were doing last year may not earn you the same Star Rating due to increasing cut points. Focusing on pharmacy measures and the patients with diabetes may be a great way to improve upon those ratings.

1. 3 Steps that Improve Star Ratings:
A Focus on Medication Adherence
Making the most of triple-weighted medication measures for
patients with diabetes

2. 50%
of patients with chronic
conditions do not take their
medications as prescribed THE REAL
IMPACT OF
POOR
ADHERENCE
75%
of patients who are
prescribed statins stop
taking them after 2 years
Of all medication-related
hospitalizations that occur
in the US,
1/3 to 2/3
are the result of poor
medication adherence
Poor medication adherence
takes the lives of
125,000 people
a year and costs the
US healthcare system
$300 Billion
Up to
2© 2020 Health Dialog

3. • Medication adherence is one of the
most challenging yet impactful ways
to improve Star Ratings
• It’s difficult to move the needle and
traditional programs often don’t
address root cause
• Proper medication use has long term
and significant effects on a member
and a population’s overall heath
WHY PHARMACY MEASURES?
© 2020 Health Dialog

4. The Numbers
8 of the 47
measures:
Directly related to medication
management.
18 of the 47
measures
(40%):
Related in some way to
medication-taking behaviors.
Overall:
50%
of the weighting for the
aggregate Star Rating is tied to
the efforts employed to support
proper medication utilization.
WHY PHARMACY MEASURES?
4© 2020 Health Dialog

5. • The need for support may be higher
• These measures are triple-weighted
• SUPD may become an additional
triple-weighted Star measure in the
future
• Focusing on patients taking multiple
measure-qualifying scripts can drive
the higher ROI
WHY PATIENTS WITH DIABETES?
© 2020 Health Dialog

6. MEASURE COUNTS FOR PATIENTS WITH DIABETES
0
20
40
60
80
100
120
Members in 2+ measures Members in 3+ measures
Diabetes RASA Statins
96%
66% 62%
77%
25% 24%
6© 2020 Health Dialog

7. Members With Diabetes:
AVERAGE NUMBER OF MONTHLY MEDICATIONS AND COPAYS
Members Without Diabetes:
All Medications:
Average
6.6 prescriptions
and $49.99 in copays
Big 3 Medications:
Average
2.6 prescriptions
and $27.83 in copays
All Medications:
Average
4.5 prescriptions
and $35.51 in copays
Big 3 Medications:
Average
1.3 prescriptions
and $7.39 in copays
7
“Big 3 medications” include Diabetes, RASA, and Statin medications
© 2020 Health Dialog

8. Through the Affordable Care Act, CMS makes Quality Bonus Payments (QBPs) to
MA plans that meet quality standards measured using a Five-Star quality rating
The QBP percentage for each Star Rating for 2019 payments:
3.5 stars or below
0% bonus
4 stars or more
5% bonus
The MA rebate level for plans is tied to the contract's Star Rating.
8© 2020 Health Dialog

9. STEP 1
Identify the Gaps in Your Current Program and
the Impact on Your Star Ratings

10. • Patients are typically identified when they are already non-adherent—
and that is too late
• The root cause of non-adherence is usually not addressed, which could
lead to non-adherence in the future
• If you have a vendor doing outreach on your behalf, it’s important to
understand what they are doing
• Starting outreach efforts early in the year is a must!
THERE ARE CRITICAL GAPS IN TODAY’S PROGRAMS
10© 2020 Health Dialog

11. Increasing cut points makes it harder to reach your goals year after year.
Even if you are doing well, it’s hard to maintain your Star Rating and not fall behind.
11© 2020 Health Dialog

12. STEP 2
Build the Foundation for a Successful Program

13. Disease
Stage Data
Social
Determinants
of Health
Medical
Claims
Rx
Claims
Engagement
Data
Other
Available
Data
HOW TO FIND THE RIGHT PATIENTS
13© 2020 Health Dialog

14. • Younger (<70), new-to-therapy patients are less likely to be
adherent to their diabetes medications
• Patients who are also taking Statin and/or RASA medications
are more likely to be adherent to their diabetes medications
• Patients whose total copay for the year for all drugs is lower
are more likely to be adherent to their diabetes medications
• Married patients (no kids at home) are most likely to be
adherent to their diabetes medications; patients living alone
are less likely to be adherent to their diabetes medications
Predictive models can identify patients based on
multiple elements, for example:
HOW TO FIND THE RIGHT PATIENTS
14© 2020 Health Dialog

15. POPULATION
STRATIFICATION STRATEGY
Patients identified for a potential intervention
are stratified and prioritized based on:
• Predictive model scores
• Proportion of days covered
• Timing of nearest fill due date (past or
future)
• Number of medication types utilized
• For defined industry measures, likelihood
of meeting measure criteria
© 2020 Health Dialog

16. STEP 3
Uncover Barriers to Adherence and Work to
Change Long-Term Behaviors

17. 17© 2020 Health Dialog
53.8% 57.2%
14.1%
13.8%
3.8%
3.9%
5.5% 5.4%
5.5%
6.1%
4.1% 1.8%
Transportation
Financial
Side Effects
Motivation
Knowledge
Provider
Time
Management
TOP BARRIERS TO MEDICATION ADHERENCE
Barriers Patients
with Diabetes
Barriers Patients
without Diabetes

18. Ready?
1. Assess readiness
2. Explore understanding
3. Build an alliance
4. “Make it personal”
Set.
1. Set goals
2. Explore barriers
3. Collaborate on strategies
4. Address ambivalence, pros, and cons
Go!
1. Assess progress
2. Set long-term goals
3. Begin maintenance and sustainability discussions
BEHAVIOR CHANGE

19. • Different times of day
• Timely manner
• Personalized follow-up schedule
• Verify where scripts are being filled and
which ones patients are filling
• Caller ID – recognizable number
• Right staff with right training and tools
TIPS TO CONDUCTING OUTREACH
© 2020 Health Dialog

20. Meet Patrick, our first-fill patient case study
Overview
• Age: 67
• Conditions: Newly-diagnosed diabetes & hypertension
• Medications: Metformin & Lisinopril
• Overall in good health and leads an active lifestyle
Patrick’s doctor has prescribed him two new medications after
an elevated hbA1c reading and slowly increasing blood
pressure levels. He doesn’t feel so sure he really needs these
new medications. He’s always been pretty healthy and lives an
active life style but he fills the prescription anyway.
“I feel fine and exercise almost every
day. If I was sick, I would take a
medication, but I’m not.”
PATIENT CASE STUDY
Meet Patrick
© 2020 Health Dialog

21. Engagement strategies targeted to Patrick addressed a
variety of topics and issues:
• Disclosed possible side effects
• Evaluated knowledge gaps about his conditions and medications
• Assessed barriers to obtaining medications
• Sent him educational information about his conditions and medications
By the end of the coaching session, Patrick felt more comfortable taking his
new prescriptions and understood the important role that medication plays in
maintaining his good health. The health coach scheduled a follow up call for
the following month.
CASE STUDY RESULTS
© 2020 Health Dialog

22. RESULTS

23. Coached patients across targeted plans had higher adherence levels than non-coached patients across all three measures1
COACHING IMPACT
7.5% 7.3%
7.9%
0.0%
2.0%
4.0%
6.0%
8.0%
Diabetes RASA Statins
Additional Percent Adherence
Coached vs. Not Coached
3.2K
additionally
adherent
patients2 across
measures
1 Patients coached and those not coached were propensity-matched on age and gender to minimize inherent differences between the two groups.
2 Patients may be counted for each measure. The same patient may be counted more than once.
23© 2020 Health Dialog

24. • Traditional programs aren’t working;
behavior change is necessary to see
results
• Finding the right patients to enroll in
outreach programs is key
• Personalized one-on-one coaching
and addressing individuals’ specific
needs drives behavior change in
patients
SUMMARY