Midas+ Executive Insights: Population Health Management

Population Health: Securing Data Assets and Assessing Organizational Readiness
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Midas+ Executive Insights Forum | May 2015
With Insights from Ashish Jha, MD, MPH
K. T. Li Professor of International Health and Health Policy
Harvard School of Public Health
Professor of Medicine, Harvard Medical School
Director, Harvard Global Health Institute
Population Health: Securing Data Assets and
Assessing Organizational Readiness

Population Health: Securing Data Assets
and Assessing Organizational Readiness
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Contents
Acknowledgments.........................................................................................................................2
Executive Summary......................................................................................................................4
Population Health: Securing Data Assets and Assessing Organizational Readiness...................5
Introduction................................................................................................................................................5
Emerging Trends.......................................................................................................................................6
The Challenge...........................................................................................................................................6
The Method of Discovery ..........................................................................................................................7
Results I: Securing Data Assets ...............................................................................................................8
Medicare Advantage Group ..................................................................................................................8
Medicaid Managed Care Group............................................................................................................9
Commercial Managed Care Group .....................................................................................................10
Results II: Assessing the State of Readiness to Execute a PHM Strategy ............................................11
Conclusions and Areas for Future Inquiry...............................................................................................13
References..............................................................................................................................................14
Appendix: Tables ........................................................................................................................15
Table 1: Priority ranking of pre-defined list of PHM Interventions across all work groups: Medicare
Advantage, Managed Medicaid, and Commercial Managed Care .........................................................16
Table 2: Priority ranking of pre-defined list of PHM Interventions summarized by three payer-defined
segments of Medicare Advantage, Managed Medicaid, and Commercial Managed work groups.........17
Table 3: Expanded List of PHM Technologies and Solution Capabilities .............................................18

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Acknowledgments
The Midas+ Team would like to recognize and thank the following individuals for their generous gift of time and
thought leadership in the development of this point of view.
Larry Allen, MD
Chief Medical Officer
Indiana University Goshen
Hospital
Goshen, IN
Bryan J. Alsip, MD, MPH, FACPM
EVP/CMO, University Health
System
San Antonio, TX
Marcos Athanasoulis
Chief Technology Officer
Healthy Communities Institute
Berkeley, CA
Eliot Asyre
Xerox Managing Director
Health & Productivity
Buck Consultants
St. Louis, MO
Nicolas Beard, MD
International Healthcare
Executive Seattle, WA
Kathy Connolly
Dir. Patient Safety Risk & Quality
Strategy and Business Dev.
ECRI Institute
Charlotte, NC
Joe Coughlin
Dir. MIT AgeLab
Boston, MA
Frederocl (Rick) Curro, PhD
PEARL Clinical Translational
Network, NY
Karen Dunning
Director Care Coordination
Operations
Sutter Health, CA
Carladenise Edwards, Ph.D.
CSO, Alameda Health System, CA
Todd Evenson
VP Consulting & Data Solutions
MGMA
Englewood, CO
Gail Grant, MD
Medical Director
Cedars-Sinai Medical Center
Los Angeles, CA
Dave Graser
CIO, VP, Ardent Health Services
Nashville, TN
Bill Hammock
SVP Oliver Wyman Health &
Life Sciences Practice
Spring Hill, TN
Deena Hannen, RN
Corp Admin Director, Care
Management
Swedish Health Services
Seattle, WA
Gina Huhnke, MD
Deaconess Health System,
Chief Quality Officer
Evansville, IN
Ashish Jha, MD
Professor of Health Policy
Harvard School of Public Health
Veterans Health Administration
Boston, MA
Kim Johns
Chief Quality Officer
Deaconess Health System
Evansville, IN
Shanna Johnson
VP Clinical Quality Analytics and
Improvement, Trinity Health
Livonia, MI
Takaji (Harry) Kittaka, MD
Chief Transformation Officer
Adena Health System, OH
Cindy Klein
VP & Chief Medical Information
Officer
United Surgical Partners
International
Addison, TX
Howard Landa, MD
Chief Medical Information Officer
Alameda Health System
Oakland, CA
Dan McCabe, MD
Chief Executive Officer
AZ Connected Care
Tucson, AZ
Kevin Moley
U.S. Ambassador (Retired)
Scottsdale, AZ
Matt Nee
VP InterSystems
North American Sales
Cambridge, MA
William Peruzzi, MD
Chief Medical Officer
Alameda Health System
Oakland, CA
Scott Rabin
Gen Mgr Xerox - Buck-Prin H&P
Priv. Health Exchange Solutions
Los Angeles, CA
Florence Reinisch
VP Strategy
Berkeley, CA
Steve Reynolds
VP Market Management
Xerox – GHS, NJ
Gayle Sandhu
Corporate Senior Director,
Quality Insurance
Scripps Health, San Diego, CA
Jeff Selwyn, MD
Medical Director
AZ Connected Care
Tucson, AZ
Ann Shimek
SVP Clinical Operations
United Surgical Partners Intl.
Addison, TX

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Gary Starnes
AVP Systems Development,
Integration & Architecture
Ardent Health Services
Nashville, TN
Tamara StClaire, MBA, PhD
Chief Innovation Officer
Xerox Commercial Healthcare
Sacramento, CA
Lionel Tehini, President
Cloud Applications &
Strategic Services, Medhost
Franklin, TN
Juan Tovar, MD
Physician Advisor for Utilization
Scripps Health Management
San Diego, CA
Deryk Van Brunt, President
Berkeley, CA
Neil West, MD
Chair, Catalina Foundation
Tucson, AZ
Scott Williamson
Sr. National Accounts Manager
InterSystems
Cambridge, MA
Terri Yancey, RN
VP Case Management &
Central Appeals
Community Health Systems
Franklin, TN
David Yarger
Chief Operating Officer
AZ Connected Care
Tucson, AZ
Huiling Zhang, MD
VP Strategic Analytics &
Solutions Clinical Operations,
Tenet
Dallas, TX
Xerox Attendees
Lesa Bailey
Account Executive
Midas+ Solutions
Loveland, OH
Brian Baker
Account Executive
Midas+ Solutions
Denver, CO
Jay Bar
Sr VP Healthcare Provider
Services
Xerox
New York, NY
Denise DeMaio
Account Executive
Midas+ Solutions
Raleigh, NC
Lois Gillette, RN
VP Product Design
Midas+ Solutions
Tucson, AZ
Alycia James
VP Care Performance
Transformation Group
Midas+ Solutions
Wilmington, NC
Linda Justice, RN
Solutions Executive
Midas+ Solutions
Greenville, SC
Jim Kirkendall
VP Analytics
Midas+ Solutions
Tucson, AZ
Chris Kuzniak, MD
Medical Director
Midas+ Solutions
Atlanta, GA
Justin Lanning
SVP, Managing Director
Midas+, Healthcare Provider
Solutions
Tucson, AZ
Karen LaRue
VP Operations
Midas+ Solutions
Tucson, AZ
Vicky Mahn-DiNicola, RN
VP Market Research & Insights
Midas+ Solutions
Tucson, AZ
Jeanine Martin
VP Business Development
Midas+ Solutions
Nashville, TN
Cori McDonald
Account Executive
Midas+ Solutions
Sierra Vista, AZ
Clayton Nicholas
VP Products and Marketing
Midas+ Solutions
Nashville, TN
Chris Peebles
VP Information Technology
Midas+ Solutions
Tucson, AZ
Kelly Rakowski
Sr VP Healthcare Payer
Services
Xerox
Milwaukee, WI
Lynn Smith, RN
Clinical Excellence Executive
Midas+ Solutions
Kansas City, MO
David Williams
VP Sales Xerox Provider
Healthcare
Atlanta, GA

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MIDAS+ EXECUTIVE INSIGHTS
Executive Summary
Population Health Management (PHM) is quickly becoming one of the most talked about
organizational strategies to achieve long-term financial viability for hospitals and healthcare
systems reorganizing as ACOs. Health plans and employers are equally vested in PHM
interventions as a means to improve health and control costs.
At the Midas+ Executive Insights forum, held on May 18, 2015 in Tucson, Arizona, over sixty
executive healthcare leaders came together to discuss the ways in which PHM strategies are
established. The first step in the process is to secure the data needed to stratify the population
into meaningful segments. This is critical when identifying and prioritizing which interventions
are best matched to the needs of the population. The next step is to ensure that the
interventions are effective.
When polled at the beginning of the session, 15% of executives reported that their
organizations were “already there” in terms of delivering a fully scaled PHM program, with an
additional 30% reporting that they would achieve this target within the next two years. An
additional 48% reported the journey towards PHM will likely take five to ten years to achieve.
The interventions required to execute a PHM strategy are varied, and require both community
and provider assets. Executive participants were asked to review a list of 18 potential PHM
interventions and identify which were already in place at most organizations, and which were
“must have” vs. “nice to have” in the first 24 months of implementing a PHM strategy. Thirty-
two percent of interventions were deemed as “already in place”, with 38% assigned into the
“must have” category. Twenty percent of the interventions were considered “nice to have”,
with the remaining 10% considered to be longer range or potentially unnecessary strategies.
See Table 1 for a list of these interventions and their ranking.
The discussion groups also identified that there may be different levels of readiness to
execute a PHM strategy, depending on the populations being targeted for PHM. Populations
consisting largely of Medicare patients may require different interventions to address chronic
and complex diseases, compared to a relatively healthier population that is covered under a
commercial plan. Table 2 illustrates the differences in readiness between Medicare
Advantage, Managed Medicaid and Commercial Managed populations.
The visionary leaders in this forum also identified 18 additional PHM interventions that may be
useful to change disease trajectory and promote health. While several of these interventions
require significant financial commitment and long-term planning to implement, such as
predictive analytics, and the use of an integrated data warehouse spanning a community,
many interventions identified were rooted in community and social settings outside of the
traditional “bricks and mortar” of provider organizations. See Table 3 for a complete list of
PHM interventions.
The emphasis on community-based intervention sets the stage for our next series of executive
forums, to be held in Nashville on September 16-17, 2015; where we will be discussing the
ways in which provider-based organizations can secure the right leadership to establish
successful PHM strategies and create new community alliances needed to care for the
populations they serve.

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MIDAS+ EXECUTIVE INSIGHTS
Population Health: Securing Data Assets and
Assessing Organizational Readiness
Today’s healthcare world is relentlessly focused on improving the health of
populations. After all, it’s easierto decrease healthcare costs by creating a
focus on wellness and prevention than it is to treat complex chronic
disease. But to implement the right strategies that will align with the
needs of a community,you must first understand the immediate and longer
term risk of those you are serving.
Introduction
This paper is about the fundamentals of beginning the
journey towards Population Health Management (PHM).
Like any journey, knowing who is going along for the ride
influences where you are going and how you are going to
get there.
PHM is often an ambiguous term that can mean different
things to the stakeholders that provide and manage care
resources across the health continuum. While
fundamentally rooted in public health and community
services, health plans are adopting PHM strategies that not
only involve contractual agreements with medical providers
in order to shift the financial risk of covered populations; but
are engaging directly with patients to coordinate services.
Not surprising then, hospitals, physicians, and ACOs create
additional PHM strategies from a provider-centric view in
order to manage clinical and financial risks of patients for
whom they are accountable.
Provider-based PHM strategies typically consist of
aggressive care coordination interventions, including
follow-up calls to patients following discharge, hospital,
and community case management services, disease
management programs, medication reconciliation
processes, and utilization of provider-owned or managed
post-acute care services. In addition, attempts to engage
and incentivize medical providers to adopt standardized
practice management protocols and care pathways that
show promise in reducing cost of services are typical in
provider-centric models of PHM.
The May 2015 Midas+ Executive
Insights Forum was facilitated by
Ashish Jha, MD, physician,
healthcare policy researcher and
advocate for the notion that an
ounce of data is worth a thousand
pounds of opinion.

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Emerging Trends
An emerging trend in provider-based PHM strategies is to
leverage community-based resources, not only for promotion
of wellness and prevention, but for care of the frail elderly
and those with complex chronic diseases. Programs such as
the American Heart, Lung, and Diabetes Associations may
be used to educate and support patients with chronic
disease. Community and neighborhood health coalitions and
faith-based organizations are leveraged to conduct wellness
clinics and health promotion activities, as well as to provide
care to home-bound citizens in need of social support and
transportation services.
In addition, new partnerships between hospital providers and
other community assets are arising, including partnerships
with retail pharmacies, emergency medical services, and
public and private transportation services, to name a few.
While traditional provider-centric business leaders might
view these partnerships as “eating into our own bottom line”,
many are quickly understanding that the financial benefits of
delivering such services through existing and well-
established infrastructures far outweigh the cost and time to
recreate and sustain similar services. Plus, the added
advantage of leveraging resources that are both convenient
and simple for citizens to access promises increased
consumer engagement in health-related behaviors that
ultimately impact health outcomes.
The Challenge
One challenge with all of these PHM interventions, however,
is to determine which ones are the most urgent for a given
population, and how to prioritize efforts against limited
financial resources. Even for provider-based PHM models,
the answer will differ depending on one’s business position
within the community. Multi-specialty provider groups may
view this challenge from a narrower point of view than an
ACO, which might wish to deliver a broader set of services.
In contrast, health plans and employers may focus services
around contracted providers and services and create
incentives for both providers and consumers to leverage
“in-network” resources in order to limit utilization and reduce
cost.
What all seem to agree on, however, is that in order to
implement the right strategies to care for a population within
a total or partial capitated “at-risk” model, it is first necessary
to understand the baseline disease burden of the targeted
population, including the potential outcome determinants of
risk behaviors, demographics, and socioeconomic variables.
“Population Health Management
is about the outcomes of a group
of individuals and the distribution
of the outcomes across the
population; including the
determinants of those outcomes
– and then segmenting the
population into more
homogenous subgroups so that
you can target your interventions
on the things that you can
potentially impact. There is no
monolithic solution to this
challenge”.
– Dr. Ashish Jha

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The Method of Discovery
By invitation, a group of approximately 55 healthcare leaders
and executives from across the U.S, consisting of Chief
Executive Officers, Chief Information Officers, Chief Medical
Officers, as well as other senior leaders of analytics strategy,
case management, quality improvement, payer, employer,
community and vendor organizations, rallied around the
conversation of PHM during a structured three-hour forum
designed to explore the infrastructure issues needed to
deploy a PHM strategy.
Participants were asked to convene around one of three
business scenarios representing healthcare systems in the
early stages of moving from a traditional fee-for-service
model to the new frontier of full “at-risk” acute care delivery
models.
In the attempt to segment the “at-risk” populations at the
broadest level, three fictitious scenarios were created that
might be typical in an ACO contract with a given health plan:
Medicare Advantage (representing senior citizens 65 and
older, either in relatively good health or with one or more
chronic conditions, including the frail elderly population)
Medicaid Managed Care (representing under-advantaged
citizens less than 65 years with disabilities and including
those with one or more chronic disease)
Commercial Managed Care (representing employed or
economically advantaged citizens with relatively good health
or with existing and new onset chronic disease)
All populations were assumed to have episodic acute care
needs related and unrelated to any underlying chronic
disease, as well as the need for palliative care and end-of-
life services.
Participants were then asked to discuss methods for
identifying the high-risk segments within each of their
populations, including the identification of specific data
assets needed to risk-stratify their at-risk populations.
Finally, participants were asked to classify a list of pre-
identified PHM interventions to identify those most likely to
already be in place at most health care organizations, and
which interventions were “must haves” within 24 months of
establishing the capitated agreement. Participants were also
asked to identify which interventions would be “nice to have”
within the next 24 months; as well as in the next three to five
years. Additional interventions not included in the pre-
defined list were invited, as well as comments about
interventions that might be of little to no benefit in realizing
their objectives.
Hear what executive participants
said when asked:
When do you think your
organization will be ready to
deliver a fully scaled population
health management program?
Already there 5/33 (15.2%)
Within 2 years 10/33 (30.3%)
Within 5 years 12/33 (36.4%)
Within 10 years 4/33 (12.1%)
Won’t get there 2/33 (6.0%)
See Acknowledgments on page 2-3 for a
list of participants and their affiliations

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Results I: Securing Data Assets
Below is a summary of the challenges of identifying the
high-risk patients in each of the three population
segments, and what data assets are generally needed to
identify them. Comments that distinguished the three
payer-based segments are highlighted below.
Medicare Advantage Group
According to DAN MCCABE MD, who was instrumental in
forming a moderate-sized ACO in the Southwest, during the
initial phase of an ACO start up providers are heavily reliant
on historical claims data to understand the utilization history
of the patients for whom they are accountable. However,
often this information isn’t available on day one. The health
plan typically provides the ACO with a list of participants and
the assigned provider or provider group attribution, but a
comprehensive claims history to identify frequent utilizers of
service may not be immediately available for all patients.
Additional data assets identified by the team include
socioeconomic and demographic data, clinical data from the
EMR (both ambulatory and hospital), and community health
data that might be available, including assessments done in
the home by community health workers to assess patient risk.
Collecting basic information such as activities of daily living
(ADLs), in-home medication adherence evaluations, and even
depression and anxiety mood scale information would provide
richer data that can later be used for segmenting the
population. “Ideally we could have a health or risk profile for
each patient, including their risk of falling at home”, said
CARLADENISE EDWARDS, who went on to say that “of course
all of this implies we will need a big data platform to create
predictive analytics, but we also need basic feedback loops in
place to track the effectiveness of provider interventions.”
“There may be gaps in the data initially, but the next thing we
did was to contract with a vendor to help us risk stratify the
population”, said SHANNA JOHNSON. For those organizations
who are analyzing their own data, “it might also be important
to bring in an epidemiology skill set to interpret the data
findings”, said GAYLE SANDHU.
The group agreed that the next step in the risk stratification
process is to get the information into meaningful and useful
formats so that providers can begin implementing the right
strategies. According to LARRY ALLEN, "we need to find the
right balance between hi-tech and hi-touch”. In addition, it is
important not to forget the intuitive clinical insights from
providers, which may be helpful in identifying high-risk patients
within a provider’s practice. “Just ask a provider who their high
risk patients are and they can likely identify those individuals
without sophisticated reports and analytics, said Allen.
“It is projected that as few as 10%
of Medicare patients spend 50%
of the resources. The problem is
that this 10% is made up of many
different segments of people,
including those with disabilities,
chronic disease and the frail
elderly. We can further refine
these three subgroups into those
with acute conditions concurrent
with chronic disease. The
challenge then is to match the
right interventions to the needs of
each group. For example, a
disease management program
will do nothing for the frail elderly
without chronic disease.
Plus we have to understand that
for the 10% of patients that we
deem high-risk based on
historical utilization patterns,
perhaps only 10% of those
represent actual preventable
spending [meaning patients
admitted to acute care vs.
ambulatory care settings].
There is also a portion of this
group who will, in one to two
years, exit our programs due to
natural causes even if we would
do nothing [referring to patients
who die]. We suspect we will see
different patterns in the Medicaid
populations once additional
research in this area has been
conducted and published”.
– Dr. Ashish Jha

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Medicaid Managed Care Group
The challenges in identifying patients within the population of
Medicaid are compounded by the fact that this population
tends to be extremely culturally diverse. According to WILLIAM
PERUZZI MD, the issue is compounded by language barriers
as well as diverse social determinants including gang-related
behaviors [referring to injuries and trauma afflicted by both self
and others], homelessness, and substance abuse. “In our
community we have a large Asian population, where there are
as many as 20 to 30 different languages spoken”, said
Peruzzi. In addition, “social determinants such as coming from
a single parent household, mental health issues, and
educational factors [implying lower levels of health literacy]
play a significant role in determining risk”, said Peruzzi.
Similar to the Medicare group, this group concluded that
historical administrative claims data are useful to identify
frequent utilizers of hospital and emergency department
services, with one participant citing the work of Jeffrey
Brenner on Hot Spotting to gain insights into root causes for
frequent hospital visits (Benner, 2014).
“We are really making judgments on a different plane and
according to different values”, said RICK CURRO, who went on
to propose a change in traditional clinical encounters. “The
objective would be to elevate and standardize the traditional
provider-patient encounter to the level of a clinical study, by
adding an audit trail to ensure best practice,” said Curro.
Another challenge cited by the group is the ability to track patients
across the community. Patients in this group tend to be fairly
mobile, so traditional hospital ADT and patient registration systems
may not be sufficient to track patients over time. According to
FLORENCE REINISCH, “It’s important that we understand the
patterns of movement of these high risk populations over time and
how they move from one risk segment to another”.
The group also cited the use of cell phone technologies as
another potential data source. “In southern Ohio we care for
an Appalachian community that tends to be economically
depressed. However, it’s amazing that probably 99% of
those we care for in the hospital have cell phones”, said
TAKAJI KITTAKA MD.
While all agreed that having an integrated data warehouse and
a standard set of predictive analytics to identify high-risk
segments would be ideal, matching the needs of the population
to the right interventions at the right time is what matters most.
According to GARY STARNES, “Only a handful of places have all
the needed technology solutions in place today. It may be that
we don’t need a different set of analytics for this population, but
rather a different set of interventions…it’s how we act on the
information and how we deliver it that moves the dot”.
“No one is asking hospitals to fix
society, but you can be a
convening force to help move
the needle within each of your
communities”.
– Dr. Ashish Jha

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Commercial Managed Care Group
The commercial managed care population typically consists of
individuals 18 to 64 years of age who are actively working. This
population is generally assumed to have some resources available
to them for accessing and engaging with healthcare services, and
includes newborn and pediatric populations as well as adults.
According to KAREN DUNNING, “It tends to be a fairly
straightforward process to identify the obvious high-cost
utilizers of services such as high-risk babies in NICUs, organ
transplant patients, and trauma cases”. These populations
may not require sophisticated PHM interventions, but rather
more traditional case and utilization management approaches
that are ubiquitous within the managed care space.
However, the need to “engage” this population is of particular
importance, because their behaviors might be different from
those of other populations. According to DAVID GRASER,
“patients in the commercial group often feel invincible” and
their motivation to change lifestyle and behaviors that impact
long-term outcomes could actually be less than other groups,
despite the fact that this group tends to be more sophisticated
with technology access and utilization of technologies like
patient portals and on-line health screening tools.
Because the outcomes resulting from lifestyle changes in
this group are so long-term, it is important to determine
which behavior changes have the greatest potential to
impact long term outcomes and cost. Once those
determinants are identified, the PHM interventions can be
deployed with the long-range objective of changing the
trajectory of actual and potential disease processes. To this
end, “there is a tendency to focus on the more immediate
cost reduction strategies tied to utilization of lower-cost
services, such as generic prescriptions and “in-network”
providers”, said HUILING ZHANG, MD.
There are also patients within the “relatively healthy” segment
who have new or existing chronic diseases that require
focused PHM strategies. These populations can be identified
by historical claims and ambulatory clinical data, such as
laboratory findings, BMI ratios, and medications. “The key is
to project an “actuarial-like” analysis to predict which patients
progress to more complex disease states”, said Graser.
Patient-reported outcomes may also be a valuable source of
information to screen longitudinal risk factors, including
employer-based screening to ensure employees have “skin in
the game”. Incentivizing lifestyle change is personal and
complex. According to DEENA HANNEN, “It’s hard to remember
when I’m 40 that ‘I could lose my eyesight when I’m a 75 year
old diabetic when the desert is sitting in front of me…but it’s
easier to remember $200 less in premiums this year”.
“Much more research needs to be
done across diverse populations
in order to properly segment risk
and understand what causes
people to progress in and out of
the risk segments. We should
expect to see variation across
various population segments and
prepare for the fact that there is
no single solution that will meet
the needs of all populations and
that organizations will have the
difficult task of deciding which
strategies to build into their PHM
strategies, which will impact the
most people. These decisions are
ideally based on data rather than
stakeholder opinion”.
– Dr. Ashish Jha

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Results II: Assessing the State of
Readiness to Execute a PHM Strategy
The challenge identified by all three groups was the need to
match the “right PHM resources at the right time and in the
right place” to meet individual patient needs and impact disease
trajectory. In this part of the work group exercise, participants
were provided with a prepared list of 17 potential PHM inter-
ventions and asked to classify them into one of five categories:
• Likely already in place in most integrated care settings
• Need to have in place in first 24 months of PHM strategy
• Nice to have in first 24 months of PHM strategy
• Defer for years 3-5 (important but not as urgent)
• Not sure strategy is needed or has significant benefit
The purpose of this exercise was to quantify how far along
most provider-based organizations are today with creating the
necessary infrastructure needed to support PHM strategies,
and to identify potential gaps and needs for future success.
Overall, across all three payer-defined population segments
for this exercise, 32% of the capabilities listed in the pre-
defined list of PHM interventions were deemed by
participants as “Likely already in place”, with an additional
38% classified as “Need to have in place in first 24 months”.
Twenty percent of the PHM interventions were identified as
“Nice to have in first 24 months”, with 8% deferred for future
implementation in years three to five. Only 2% of the pre-
defined PHM interventions were listed as “Not sure strategy
is needed or has significant benefit”.
Table 1 describes the distribution of the responses for all
three groups combined. Not surprisingly, the capability to
track immunizations was predominate in the “Likely already
in place” category, as this function was part of the initial
minimum requirements of the Stage I electronic medical
record (EMR) “Meaningful Use” incentive program.
The next largest intervention reported to be in place already
was disease management. While this item was not explicitly
defined for purposes of this exercise, it could be assumed
that most integrated delivery systems and ACOs believe
they already have this capability in place for chronic
populations such as diabetes, cardiovascular, and lung
disease. Further confirmation of this fact may be warranted
in future research.
Patient-reported outcomes were predominately identified as
a future capability in 3-5 years. However, given the
emphasis on patient-reported outcomes by the National
Quality Forum (NQF) and PCORI, this capability could shift
to a more urgent requirement in the next 1-2 years.

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The least urgent capability on the pre-defined list of potential
PHM interventions was genomic testing and Drug-DNA
testing. Although viewed as a largely futuristic PHM strategy,
current technology trends and market forces could also
escalate the need for this capability in the future, especially
in organizations whose PHM strategies are guided by retail
influences that support low-cost genomic testing for the
masses, such as 23andMe, Walgreens, Theranos and other
emerging laboratory testing vendors in this space.
When examining the stages of readiness across the three
payer segments, there were moderate differences among
the three groups. Table 2 illustrates that the Medicare
Advantage group collectively reported the fewest
interventions “likely already in place” (26%) compared to the
commercial group (44%). However, it should be noted that
there were only 5 respondents in the commercial group,
which elected to perform this exercise by group consensus
in contrast to the other two work groups who performed the
exercise as individuals. Further research to understand
differences among the three payer segments is needed.
Nineteen additional interventions that were not part of the
original prepared list were identified across the three work
groups and are incorporated into a post-exercise PHM
intervention list, which is displayed in Table 3. Of interest, 15
of the 19 additional interventions offered by work group
participants were community-based vs. hospital- or provider-
based interventions, bringing the total number of community-
based capabilities to 18 of the 36 (50%) potential technology
and service capabilities listed for PHM.1
Several of the low-cost community interventions offered by
various work group participants included organized trips to the
local Farmer’s Market to purchase organic foods or to parish
nursing programs. When questioned by other participants with
an IT or Medical background about how healthcare
organizations could potentially partner with churches in the
provision of care to frail elderly, KAREN DUNNING, a Director of
Operations at Sutter Health, replied, “You probably already
have these programs in place today – you just don’t know you do”.
This observation sheds light on the potentially untapped
opportunities that may exist through more creative
partnerships with community assets, including churches,
local transportation services, hardware stores, restaurants,
schools, and other organizations and businesses that are
traditionally not viewed as being part of the medical
treatment domain.
1
Within the context of this paper, community-based capabilities are defined as those interventions that are primarily
conducted within a community setting and outside of the direct hospital-based or ambulatory medical care setting, regardless
of the primary funding source. Table 3 designates the focus of the intervention as either provider- or community-based.

13 | P a g e
Conclusions and Areas for Future Inquiry
The findings from this executive work group are two-fold.
First, the data assets required to fully execute a PHM
strategy are continuously evolving. The promise that
advanced analytics brings is enormous; not only to segment
populations into meaningful cohorts so that we can target
our interventions, but to understand what causes people to
shift across the various segments. The need to wait until all
source data is available to answer these questions is not
realistic, nor is it necessary. However, there is little doubt
that more research needs to be conducted in order to
understand the problems we are facing.
In addition, it is imperative that we begin to understand how to
demonstrate a return on investment for the PHM interventions
that are deployed. This is especially critical in order to justify
long-term expenditures for costly interventions that are likely
to require both technical and human resources to deploy.
The second finding is that greater emphasis needs to be
placed on the inclusion of community assets when
developing a PHM Strategy. The Medicare Advantage work
group, which revealed this segment as having the least state
of readiness, may indicate that mature PHM strategies for
effective intervention with frail elderly and those with
complex chronic disease are not yet fully realized by most
healthcare organizations. This may be in part because many
of the necessary PHM management interventions for these
segments likely require a robust set of community-based
services, many of which may not yet be in place in most
provider-centric PHM models today.
A question that might be asked of leaders who are beginning
their journey in PHM is how they will create the necessary
infrastructure to scale an effective PHM strategy. This will
require a major paradigm shift for most healthcare systems,
where the hospital is viewed as the center of the strategy.
Not only will hospital-based leaders need to establish
community-based strategies, they will also need to ensure
they have the right executive leaders in the C-Suite to inspire
and create a new community alliance.
What attributes and skill sets are needed for these emerging
leaders? Will they arise out of public health, nursing, or
marketing domains? A recent was study conducted by the
American Hospital Association and the Association for
Community Health Improvement (December, 2013) that
offers some insights into these questions. More than 1,198
hospitals were surveyed to examine trends in hospital-based
population health infrastructure.

14 | P a g e
What is clear from these findings is that no current standards
exist for implementing PHM strategies. Furthermore, many
health care organizations were found to be implementing
their PHM interventions through part-time director or mid-
level managers without direct engagement at the C-suite
level. Healthcare organizations will have to secure new
executive leaders with full-time accountability for the PHM
strategy and with professional education and experience in
the PHM field.
Though current population health leaders with dedicated
accountabilities for PHM have extensive experience in
healthcare, they tend to be fairly new to their positions and
the field. Community health, health education, and
community benefit are desirable backgrounds for new PHM
executive leaders, while existing leaders should pursue
education in community health needs assessments, healthy
communities, and collaborative facilitation.
So how will hospital-based population health programs
recalibrate their existing infrastructure to realize successful
clinical outcomes and cost reduction strategies and evaluate
their return on investment? These and other questions will
be explored in our next Midas+ Executive Insights Forum to
be held in Nashville, TN, on September 16-17, 2015.
For information on how to become part of the Midas+
Executive Insights Forum, to obtain permission to reprint, or
for questions or comments about this manuscript, please
direct your inquiries to the author, Vicky A. Mahn-DiNicola,
RN, MS, CPHQ, VP Research and Market Insights, at
Vicky.Mahn@xerox.com.
References
Association for Community Health Improvement. (2013,
December). Trends in hospital-based population health
infrastructure: Results from an Association for Community
Health Improvement and American Hospital Association
survey. Chicago: Health Research & Educational Trust.
Accessed June 16, 2015 at www.healthycommunities.org.
Benner, J. (2014, February). Robert Wood Johnson Foundation.
A Revolutionary Approach to Improving Health Care Delivery.
Accessed June 16, 2015 at
http://www.rwjf.org/en/library/articles-and-
news/2014/02/improving-management-of-health-care-
superutilizers.html

15 | P a g e
Appendix: Tables

16 | P a g e
Table 1: Priority ranking of pre-defined list of PHM Interventions across all work groups: Medicare
Advantage, Managed Medicaid, and Commercial Managed Care
Population Health Management
Technologies and Solution Capabilities
Likely to
Already
Be in
Place
Need to
Have
Next 24
Months
Nice to
Have Next
24 Months
Defer
for
Years
3-5
Not Sure
Needed or
Minimal
Value
Vaccination tracking with alerts and reminders 18 1 4 1 1
Disease management solutions for high risk
complex and chronic disease
16 8 1 0 0
Hospital readmission reduction solutions 13 10 2 0 0
Patient portal for scheduling appointments and
access to personal health information
12 5 6 1 0
Solutions to coordinate wellness checks and
primary care visits
11 12 2 0 0
Solutions to coordinate care transitions planning
and services post hospital discharge
11 11 2 1 0
Post-acute care services including home care and
end-of-life care
11 11 2 1 0
Clinical risk assessment and segmentation of at risk
population
11 13 1 0 0
Specialty care referral mechanisms 7 10 4 2 0
Integrated data warehouse for care continuum data 7 11 7 0 0
Community services to provide support groups,
education and parish nursing
6 12 7 1 0
Medication reconciliation and evaluation of
medication efficacy
6 17 2 0 0
Telehealth to treat patients virtually 2 7 11 5 0
Predictive analytics to support proactive and
personalized care management
2 15 5 2 0
Email and e-visits with primary care providers 1 12 11 1 0
Solutions for capturing patient reported outcomes
on mobile devices
0 5 14 5 0
Genomics and DNA-Drug Testing 0 2 2 14 7
TOTAL 134 162 83 34 8
PERCENTAGE 32% 38% 20% 8% 2%
Back to page 10

17 | P a g e
Table 2: Priority ranking of pre-defined list of PHM Interventions summarized by three payer-defined
segments of Medicare Advantage, Managed Medicaid, and Commercial Managed work groups.
Population Health Management
Technologies and Solution Capabilities
Likely to
Already Be in
Place
Need to
Have Next
24 Months
Nice to
Have Next
24 Months
Defer for
Years 3-5
Not Sure
Needed or
Minimal
Value
Medicare Advantage 26% (35) 38% (51) 22% (30) 11% (15) 4% (5)
Managed Medicaid 31% (62) 41% (81) 21% (41) 7% (13) 2% (3)
Commercial Managed 44% (37) 35% (30) 14% (12) 7% (6) 0% (0)
TOTAL ACROSS ALL GROUPS 134 162 83 34 8
TOTAL PERCENTAGE ACROSS ALL
GROUPS
32% 38% 20% 8% 2%
Back to page 11

18 | P a g e
Table 3: Expanded List of PHM Technologies and Solution Capabilities
Additional capabilities added by executive participants displayed in bold italics
Focus: Capability:
Provider 1. Vaccination tracking with alerts and reminders
Provider 2. Disease management solutions for high risk complex and chronic disease
Provider 3. Hospital readmission reduction solutions
Provider 4. Patient portal for scheduling appointments and access to personal health information
Provider 5. Solutions to coordinate wellness checks and primary care visits
Provider 6. Solutions to coordinate care transitions planning and services post hospital discharge
Provider 7. Post-acute care services including home care and end-of-life care
Provider 8. Clinical risk assessment and segmentation of at risk population
Provider 9. Specialty care referral mechanisms
Provider 10. Integrated data warehouse for care continuum data
Community 11. Community services to provide support groups, education and parish nursing
Provider 12. Medication reconciliation and evaluation of medication efficacy
Community 13. Telehealth to treat patients virtually
Provider 14. Predictive analytics to support proactive and personalized care management
Provider 15. Email and e-visits with primary care providers
Community 16. Solutions for capturing patient reported outcomes on mobile devices
Provider 17. Genomics and DNA-Drug Testing
Provider 18. Multi-disciplinary care teams that cross boundaries of health care settings
Provider 19. Standardized care pathways or roadmaps to manage common conditions
Provider 20. Hot Spotting high utilizers of hospital and emergency department services
Provider 21. Predictive analytics to monitor disease trajectory of at risk populations
Community 22. Smartphone applications to monitor care following discharge
Community 23. Solutions to track address and contact information for enrollees across community
Community 24. Partnerships with minute clinics/retail pharmacies for episodic care management
Community 25. Longitudinal tracking of functional Activities of Daily Living (ADLs)
Community 26. Longitudinal tracking of depression and anxiety
Community 27. Expansion of data analytics at a county and state level with merger of census data
Community 28. Home monitoring systems with centralized monitoring of vital signs, weight, O2 status
Community 29. Employer-based wellness screening and health coaching
Community 30. Partnership with schools and universities to promote health, nutrition, exercise etc.
Community 31. Community nursing case management for chronic disease
Community 32. Community social services case management and monitoring tools for frail elderly
Community 33. Farmers market shopping program to support nutrition and whole foods consumption
Community 34. Partnership with local cab and transportations services
Community 35. Partnership with local emergency medical services (EMS)
Community 36. Partnerships with local hardware stores for installing bathtub skid protectors, hardware
Back to page 11

19 | P a g e
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