Cross the Finish Line First

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 dataprimarily 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 individuals 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 todays calculations unsuitable for
  determining a patients true risk, they provide
  no insight into how an individuals score
  improves or deteriorates after each clinical
  visit.
• Information lags far behind Claims-based risk
  scores are not actionablethey 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
(yellow), and low (green) risk groups by chronic
condition (see Figure 2)
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
  patients 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.

13
(No Transcript)
14
Incentive Management

• Effective incentive programs clearly drive high
  quality and reduce costs for greater value in
  health care by
• Aligning team incentives with population quality
  and cost performance targets (physicians and care
  coordinators)
• Establishing and sharing best evidence practices
  by chronic condition
• Encouraging teamwork to lower healthcare costs
• 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) are useful in designing incentive
programs and illustrate risk-cost quality details
for each patient (Figure 4).
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 teams bonus or penalty.

17
(No Transcript)
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
  0100 for four chronic conditionstype 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 increases, the admission within that band
also increases. Thus, Figure 6 validates the
accuracy and predictive power of the SOH 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 619 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.thehastingsce
  nter. 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.