Using Predictive Modeling Tool to Identify at Risk Patients who has a chance of becoming users of High-Cost Healthcare service and subsequently Reducing PMPM (Per Member Per Month) Costs While Increasing Member Satisfaction

1. Uncover Hidden Opportunity to
Prevent Unnecessary Admissions

2. Predictive Modeling Tool for Sustainable Care Management
Using Predictive Modeling Tool to Identify at Risk Patients who has a chance
of becoming users of High-Cost Healthcare service and subsequently Reducing
PMPM (Per Member Per Month) Costs While Increasing Member Satisfaction.

3. Challenge
• Over the years, Health Maintenance Organizations (HMOs) have been
using traditional care management programs to reduce healthcare cost
and improve quality of care for their plan members.
• GlobalHealth, an Oklahoma based HMO has been doing well at managing
care after a disease or condition is identified.
• But they didn’t have necessary data to identify clinically high risk
members who may not be high utilizers of Care Management programs.
• This resulted increase in ED encounters and readmissions of members
thus increase PMPM.

4. Scenario at a Glance
• GlobalHealth identified group of members who are low utilizer of
services.
• Some of these members experience a sudden acute event that requires a
hospitalization and, consequently, become high users.
• GlobalHealth’s clinical and administrative leaders found clear indicators of
these acute events after reviewing statistics on daily inpatient admissions
(e.g. reasons for admissions, diagnosis, health and claims history)

5. • GlobalHealth realized the need of Predictive Modeling Tool.
• Predictive modeling tool could prevent large percentage hospitalizations
by evaluating the member data and identifying at-risk patients.
• Overall the challenge was to prevent acute incidents by identifying at-risk
patients.
• Indentifying at-risk patients was important from a cost as well as quality
of care and service standpoint.

6. Solution
• GlobalHealth used VitreosHealths predictive modeling tool to
retrospective review of health plan member data.
• Care Managers found approximately 4,000 health plan members who
were low-cost healthcare user at the end of 2011, had a high risk of
facing an acute event.
• These members became ‘high utilizers’ of services between 2012 and
2013 compared to 2011.
• Healthcare costs associated with them tripled in 2012 and again in 2013.

7. • Surprisingly every year about 12 to 15 percent members from ‘hidden’
category moved to the ‘high-utilizer’ of the service category.
• Predictive risk modeling tool can help the HMOs to identify hidden
population—who are not high users of healthcare services but have high
risk for an acute event in future.
• At present this ‘hidden’ cohort members do not take routine care (in the
form of primary care visits, health screenings, and diagnostic tests).
• Routine care could prevent more acute and expensive emergency
admissions.

8. • VitreosHealth’s predictive modeling tool creates a profile for each plan
members after analyzing clinical and nonclinical data.
• Predictive modeling tool use various data like HMO’s Electronic Health
Record (EHR), Utilization data from claims, Medication data from
pharmacy systems, Scheduling data from practice management systems
and Demographic data to create member’s profile
• Then the tool calculates a member’s risk (State of Health score) for
clinical chronic conditions, including congestive heart disease, diabetes,
asthma, and hypertension.

9. Importantly, it also assesses five nonclinical factors that can affect a
member’s risk of experiencing an acute event:
• Utilization: Utilization score is derived from the claims data and calculated
based on member’s resource utilization patterns. E.g. Number of
hospitalizations, ER visits and medication.
• Compliance: Compliance score is calculated by measuring member’s
adherence to evidence-based care protocols such as appointments, lab
test and medications.
• Access to care: Ease of access to appropriate care services have an effect
on availing care management services.

10. • Socioeconomic: Demographic data (e.g. education levels, household
incomes, family size, and native languages) may also affect health status.
• Perceived well-being: This measures how patient feels about his/ her
health condition. Studies have shown that patients’ perceptions about
their health may affect their actual health condition.

11. Vitreos uses a patent pending transformational approach for predicting risk of
hospitalization / ER visits / High Cost Intervention that takes into account 6
dimensions.

12. Based on clinical and non-clinical factors, plan-members are categorized into
four cohorts:
• High risk, high cost
• Low risk, high cost
• Low risk, low cost
• High risk, low cost
Opportunity for cost savings lies in the last cohort – “Hidden”. Healthcare
leaders need to identify hidden members and put them into effective care
management to maximize PMPM savings.

13. Outcomes
• GlobalHealth care managers receive a daily, weekly and monthly report
from the Vitreos predictive modeling tool.
• The report indicates of high-risk members, including the hidden cohort.
• It also identifies problem areas based on the member’s clinical and
nonclinical scores, prioritizes the members who should receive outreach
first, and recommends care management actions.

14. Sample report are sent to the care managers daily, weekly or monthly

15. Key observations
The preliminary result shows GlobalHealth has been successful in reducing
ED encounters and readmissions by 20% in among all members between
January 2014 and May 2014.
• Hospital admissions have declined by 5 %
– 20% reduction of ED visits resulted cost savings of $2 to $3 in PMPM (
one ED visit = 10 % of PMPM costs )
– Saving of $3 to $4 PMPM due to 5 % reduction in inpatient admission (
one inpatient admission represent about one-third of PMPM costs )
• Member satisfaction has increased by 3.5% among all health plan
members

16. Based on the preliminary results of this program the improvement in both
member satisfaction and cost savings exceeded the cost of adding staff.
As a result, GlobalHealth is planning to double its care management staff to
accommodate the additional member outreach in one year.
The results of the program will become more apparent in August or
September 2014, but the overall trend is promising. “Right now it is indicating
very positively that we’re putting our resources in the right spot,” says J. David
Thompson, GlobalHealth’s vice president of health plan operations.