The Affordable Care Act of 2010 (ACA) opens the door to a wealth of opportunities for hospitals and physician groups. They are beginning to adapt to the new pay-for-performance and bundled payment systems and develop population-based care management programs. While the goal of ACA is to hold hospitals and physicians jointly responsible for quality and cost of care, the new payment models span the entire care continuum, including primary care physicians (PCPs), specialists, hospitals, post-acute care, and re-admissions. The biggest winners will be those who can improve quality of care while driving down costs. Those that focus first on preventive care for top chronic illnesses will be the first to cross the finish line.

1. Cross the Finish Line First
BY LISTER ROBINSON

2. Why Chronic Conditions First?
According to the Centers for Disease Control and Prevention
(CDC), "Chronic diseases are the leading cause of death and
disability in the U.S.," and Healthcare Cost Monitor underscores
this fact, revealing that "Seventy-six percent of Medicare
spending is on patients with five or more chronic diseases”. The
Agency of Healthcare Research and Quality (AHRQ) also
emphasizes the high cost of chronic conditions.

3. Yesterday: Claims-Based Predictive Models
For years, healthcare insurance companies (payers) have mined
claims data for chronic patients and have built predictive models
to identify high-risk patients.
Data used by payers to flag high risk patients are historical
claims data—primarily costs, admissions, and diagnoses.
Because this view is retrospective and heavily biased toward
cost, patients with past high acute care costs are flagged as
"risky" regardless of their current State-of-Health (SOH).

4. These models lack a correlation to clinical information.
The score becomes even more credible when there is evidence
of ER admissions or acute care inpatient (IP) admissions.
Unfortunately, an individual’s current SOH has no bearing on his
or her claims-based risk score.
Claims based risk scores are created with regression analysis at a
population level to predict scores at the patient level.

5. Claims-based risk scores provide no insight for care at the
provider level.
Not only are today’s calculations unsuitable for determining a
patient’s true risk, they provide no insight into how an
individual’s score improves or deteriorates after each clinical
visit.
Information lags far behind; Claims-based risk scores are not
actionable–they provide no insight for care at the provider level.

6. A New Approach
The best approach is to monitor all patients, healthy and
chronic, for risk of hospitalization.
There is inherent conflict between physicians and payers. To
realize bonuses, they must choose cost of care over effective
care.
Progressive medical groups do not use claims-based patient risk
reports created by payers to develop care management
programs.

7. Vital Progress
The new generation of primary care management solutions
delivers real-time, meaningful use clinical data from EHR
records.
These systems use patient medical records to measure SOH and
evaluate the effectiveness of care programs and evidence-based
medicine.
Real-time clinical data from EHR records is also being used to
create sustainable, repeatable programs to reduce the number
of high-risk patients and design individualized care management
programs.

8. Closed-Loop CMP
Using real-time clinical data
from EHR records, healthcare
providers now have the
capacity to design a closed-
loop population care
management program (Figure
1).
A well-designed program
delivers primary care to drive
higher quality, reduce costs,
and deliver greater value in
health care.

9. Population SOH Stratification
The very foundation of the well-designed program is population SOH
stratification, the ability to categorize patients into high (red), moderate

10. SOH stratification provides actionable and measurable
information about actual health status at the population and
patient levels, with visibility of controllable and non controllable
factors.
An SOH model takes into consideration every patient’s age,
gender, ethnicity, family history, all clinical factors (e.g. BMI,
lipid panel, blood HM, HcA1C).
A low score indicates excellent health.

11. Origins of SOH Models
Nationally accepted clinical models are the basis for SOH
models.
SOH scores are calculated at the patient level and rolled up to a
population level.
This approach allows healthcare providers to design meaningful
preventive care programs for the exact population and create
individualized programs for specific patients.

12. Chronic Disease Management
Patients who comply with prescribed care programs are typically
more successful in managing chronic conditions.
This is where care coordinators play an important role.
Leveraging SOH scores, care coordinators pinpoint high-risk
patients by chronic condition.

14. Incentive Management
Effective incentive programs clearly drive high quality and
reduce costs for greater value in health care by:
I.Aligning team incentives with population quality and cost
performance targets (physicians and care coordinators)
II.Establishing and sharing best evidence practices by chronic
condition
III.Encouraging teamwork to lower healthcare costs
IV.Illustrating accurate physician and clinical coordinator
population performance and the impact on incentives

15. Incentive programs reward care teams for reducing population risk
scores, improving patient satisfaction scores, and reducing overall
patient costs. Continuum of care dashboards (ambulatory and acute)

16. In this case, the quality metric captures population SOH, ACO
quality measures and patient satisfaction scores. The
intersection of the crosshairs is the target for quality and cost for
the specific patient population.
Each bubble corresponds to a specific physician/care
coordinator team, and the size of the bubble illustrates the size
of the population they manage. The distance of each bubble
from the crosshair indicates the positive or negative variance
from the target and is proportional to each team’s bonus or
penalty.

18. Results: Validating the SOH Model Approach
To validate the new SOH model, researchers (authors of this
article) compared it with a leading claims-based risk model
(payer model).
The SOH model calculated a risk score between 0–100 for four
chronic conditions—type 2 adult diabetes, coronary artery
disease (CAD), CHF, and asthma.
Next, researchers calculated an SOH score for each patient using
historical data over two years (2008– 2009) and stratified the
population based on SOH scores.

19. Relationship: IP/ER Admissions and SOH Score
Figure 6 shows the relationship between SOH scores and IP/ER
admissions. The X axis shows SOH ranges. Y Axis shows the percentage
of patients in the SOH range with IP/ER admissions. As the score

20. Proven Track Records
Healthcare providers can enable continuous improvement using
SOH models together with care management programs. This
approach already has proven track records in a number of
leading PCMHs such as the Medical Clinic of North Texas
(MCNT). Within these organizations, a wide variety of individuals
actively use these models in their daily work, including:
Administrators and management
Physicians
Care coordinators

21. MCNT has pioneered the SOH-based population management
approach.
Their managed population of 2.4 percent better-than-market
performance was the culmination of various quality-of-care
drivers.
Overall performance index improved in Facility Outpatient (-5%),
Other Medical Services (-6%), and Professional (-1%) categories,
relative to the market.

22. Chronic Diseases
CDC on Chronic Diseases
Seven out of 10 deaths among Americans each year are from
chronic diseases. Heart disease, cancer, and stroke account for
more than 50% of all deaths each year.
Obesity has become a major health concern. One in every 3
adults is obese, and almost 1 in 5 youth between the ages of 6–
19 is obese.
Source: www.cdc.gov/chronicdisease/overview
/ index.htm

23. AHrQ on Cost of Chronic Conditions
The 15 most expensive health conditions account for 44% of
total healthcare expenses. Patients with multiple chronic
conditions cost up to seven times as much as patients with only
one chronic condition.
Source: www.ahrq.gov/research/ria19/expendria.htm

24. Cost Monitor: Chronic Disease Spending
76% of Medicare spending is on patients with 5 or more chronic
diseases.
Currently, 10% of healthcare dollars are spent on overall direct
costs related to diabetes, amounting to $92 billion a year (1.5X
the amount spent on stroke or heart disease).
CDC predicts spending on diabetes care will reach $192 billion in
2020.
Source: http://healthcarecostmonitor.thehastingscenter. org/
kimberlyswartz/projected-costs-of-chronic-diseases

25. Summary
To lower health costs, physician networks and medical homes
must employ a closed loop population management program
that focuses on patient SOH (risk) stratification, chronic disease
management, care coordination, and incentive management.
To become masters in their population management programs,
they need decision support systems such as population SOH
stratification and predictive models.