An ACO will fail without precise patient population definitions. ACOs need to define populations for many reasons, including identifying their members and attributing those patients to the correct physician and performing population health analytics. The challenges to a good population definition are: multiple providers per member, multiple data sources, and multiple identifiers for each member. Using a clinical integration hierarchy to refine population and subpopulations will solve a lot of these issues. A data warehouse is the foundation that makes it possible.

1. © 2014 Health Catalyst
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© 2014 Health Catalyst
www.healthcatalyst.com
Proprietary. Feel free to share but we would appreciate a Health Catalyst citation.
ACO Success Requires Precise Patient
Population Definitions
By Luke Skelley

2. © 2014 Health Catalyst
www.healthcatalyst.comProprietary. Feel free to share but we would appreciate a Health Catalyst citation.
ACO Success Depends on Accurate
Patient Population Definitions
2
Accountable Care Organizations
(ACOs) must precisely pinpoint
patient populations to understand
the risk to customize solutions.

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How ACOs Use Population
Definitions
3
ACOs define populations for four main reasons
To identify their members and attribute those patients
to the correct physician(s)
To attribute the right patient to the right physician for
pay-for-performance incentives
To accurately report CMS and other quality measures
To perform population health analytics that enable
providers to effectively manage each patient’s health

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Challenges to Defining an ACO
Populations
4
ACOs identify high-risk members and manage their
health more carefully by:
• Performing analytics to predict likelihood of specific events
• Tracking utilization trends across the full care continuum
• Monitoring quality of care by facility and by provider.

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Defining High Risk Populations
5
Key challenges in defining ACO
populations.
• Multiple providers per patient
• Multiple data sources
• Reconciling multiple identifiers for
each member
HOSPITALS REHABS
PHARMACIES LABORATORIES
SURGERY CENTERS DIALYSIS FACILITIES
PRIVATE PRACTICE CLAIMS & BILLING
NURSING HOMES HOME HEALTH

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Clinical Integration Hierarchy
6
Health Catalyst recommends using a clinical hierarchy system for
grouping these common clinical characteristics and identifying
individuals who share these characteristics.
Starting at the most-general and moving to the most-granular level,
this hierarchy is as follows:
1: Clinical program:
Twelve clinical programs make up a comprehensive healthcare
delivery system.
Primary
Care
Care
Process
Families
e.g.,
Diabetes
CV
Care
Process
Families
e.g.,
Heart
Failure
W&C
Care
Process
Families
e.g.,
Pregnancy
G.I.
Care
Process
Families
e.g.,
LowerGI
Disorders
Resp-
iratory
Care
Process
Families
e.g.,
Obstructive
Lung
Disorders
Neuro
Sciences
Care
Process
Families
e.g.,
Spine
Disorders
Musculo-
skeletal
Care
Process
Families
e.g.,
Joint
Replace-
ment
Surgery
Care
Process
Families
e.g.,
Urologic
Disorders
General
Med
Care
Process
Families
e.g.,
Infectious
Diseases
Oncology
Care
Process
Families
e.g.,
Breast
Cancer
Peds
Spec
Care
Process
Families
e.g.,
Peds
CV Surg
Mental
Health
Care
Process
Families
e.g.,
Depression

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Clinical Integration Hierarchy
7
2. Care process family:
Each clinical program consists of multiple care process families.
For Example:
3. Care process:
Represents the most granular level of the hierarchy and may
exist anywhere along the continuum of care.
Cardiovascular clinical program
Ischemic Heart Disease Vascular Disorders
Heart Failure Heart Rhythm Disorders
Ischemic Heart Disease care process family
Hyperlipidemia Coronary Atherosclerosis
Acute Myocardial Infarction Percutaneous Intervention (PCI)
Coronary Artery Bypass Graft (CABG) Cardiac Rehab

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Using Technology to Build and
Refine Registries
Health Catalyst has developed two main tools to easily, efficiently, and
accurately define patient populations. These analytics applications run
on top of our enterprise data warehouse platform.
8
Population Explorer
Delivers a “starter set” of more
than 1,000 different registries.
It begins with standardized
rules for creating the registry
Then adds care mappings to
bring additional data elements
(like laboratory results) into
the registry to create a more
comprehensive rule for
defining the population.
Cohort Builder
This analytics application
enables more sophisticated
definitions of a population.
Teams of clinicians, analysts,
and others work together using
this tool to adjust and refine
the population definition to suit
the ACO’s specific needs.
The level of refinement brought by these tools defines the ACO’s
effectiveness and goes beyond the diagnosis codes to pick up those
patients who might otherwise be missed.

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Summary
9
Using EDW analysis tools mapped to a deep clinical integration
hierarchy allows ACOs to develop the precise, detailed population
definitions, and vastly improve quality and accuracy.

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Other Clinical Quality Improvement Resources
Click to read additional information at www.healthcatalyst.com
Luke Skelley joined Health Catalyst in May 2013. Luke’s clinical
nursing background was in critical care and he managed organ and
tissue donation programs for 13 years. His background includes
orthopedic products, severity adjusted outcomes software for
Medstat Group, clinical pathway development software for
CareScience and prospective payment methodologies for Optum
Insight. Luke was recruited by Navinet for a new line of clinical products for
physician offices before they were acquired by Lumeris. Luke has a BSN and
MSN in critical care nursing from the University of Tennessee and an MBA from
Belmont University.
How Would An Accountable Care Approach Change How A
Patient is Treated? Also by Luke Skelley