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Bigger Data, Better Outcomes
Healthcare Providers Can Improve
Operational Decision Making
By the KPMG Healthcare Data & Analytics Team:
Bharat Rao, PhD, Principal
Mohit Chandra, Managing Director
John Weis, Director
As pay-for-performance replaces fee-for-service, providers and hospitals
need to do more to attract and retain patients. Providers need to focus on:
transparency into the relationship between medical services and costs, reduced
hospitalizations and hospital-acquired complications, fewer readmissions, and
improved health outcomes. However, making all of these operational, financial,
and clinical improvements may seem like a daunting task.
The healthcare industry is currently undergoing a
revolution fueled by the increased availability of
data, similar to what the retail and financial services
industries experienced in the last decade. Today, there
are tools to help healthcare providers not only survive
but flourish, even as the healthcare industry converges,
demands for transparency increase, regulations evolve,
and budgets and resources shrink.
The big data tools and technologies available today
can harness the power of increasingly available data.
Applying advanced analytics to this data can
yield actionable insights into such critical areas as
provider-payer collaboration, population management,
cost reduction, improved health outcomes,
patient safety, physician satisfaction, and more.
Within the data analytics realm, the provider
community is increasingly exploring the use of large
external patient-claims data sets to meet these goals.
From sources like Blue Health Intelligence (BHI),
State-Level All Payers Claims Database (APCD), and
the Centers for Medicare and Medicaid Services
(CMS), these very large data sets allow providers to
understand what is happening to patients outside
the four walls of their institutions. The data sets
can amplify the power of data from providers’
own internal healthcare IT systems and electronic
health records (EHRs). The resulting insights can
help providers elevate their outcomes and maintain
control of quality. And big data predictive models
can be developed with these data elements to
further transform the delivery of care.
Although the complete transformation of the
healthcare industry into a data-driven business
will take many years, well-planned actions can
be beneficial even today. On the journey from
volume to value, big data solutions and insights
can keep you on the right path. Our hope is that
this issue brief will help you take the first steps in
realizing institutional and patient value from the
use of external data sets.
© 2015 KPMG LLP, a Delaware limited liability partnership and the U.S. member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative
(“KPMG International”), a Swiss entity. All rights reserved. The KPMG name, logo and “cutting through complexity” are registered trademarks or trademarks of KPMG International. NDPPS 336084
Big data is a key part of outcome-driven
analytics solutions
Big data has already been in play in the provider world over
the past few years. Clinical data from EHRs is being used to
share information with other internal healthcare providers who
might be involved in a patient’s care. Individual data sets are
being mined by predictive algorithms to derive evidence-based
practices and new treatment protocols. Hospitals participating
in local and regional health information exchanges (HIEs) have
had access to a wide range of clinical, financial, and operational
data. When it comes to sharing of information with external
physicians and hospitals, however, providers have been a
little more reticent. There will need to be a cultural change
amongst providers, since, in the fee-for-service world, there
were no incentives for coordinating care or collaborating to
improve outcomes.
Several factors are pushing the industry toward wider
use of big data. Regulatory demands for quality have
awakened the provider community to the need for
collaboration. Emerging technology for improved security,
de-identification, and encryption are making it easier to
collaborate. Costs matter more now, with the move from
pay-for-service to fee-for-performance and -outcomes,
including value-based payments. Providers who want to get
more value out of technology upgrades and EHR purchases
required for Meaningful Use and HIPAA compliance are
looking for ways to build upon these investments.
Practical use cases
Providers may be asking themselves: What can I do with a
large patient-claims data set? Below are four hypothetical
scenarios that illustrate how providers can realize value from
broad data sets by performing advanced longitudinal analyses
across the continuum of care.
A look at total reimbursement of care
Situation: Providers are reinventing their practices
to take on more and more financial risk for their
patients. Whether it be entering into at-risk contracts, or
providing health plans with justification for higher charges
connected to higher-quality services, providers need to
understand reimbursement patterns and clinical outcomes
across the total continuum of care. A care trajectory can include
several clinical episodes beyond a provider’s own treatment
of a patient, such as specialist referrals, hospital stays, rehab
treatments, skilled nursing care, preventive programs, home
health, and more.
Problem: It has been a challenge for providers to gain insight
into care delivered by other medical professionals. Providers
need additional data to analyze the ramifications of the care
continuum to manage both financial and clinical outcomes,
including potentially avoidable complications.
Solution: A big data-based solution, combined with an
advanced grouper that permits analysis across episodes,
can allow providers to visualize and understand the total
reimbursement for a given disease condition, look at care
paths for their own patients and those being cared for by
other providers, understand the impact of specific treatment
decisions both within and outside their institutions, and
conduct longitudinal data analyses of the efficacy of specific
treatment pathways.
Benefits: Providers will be able to evaluate potential partners
in an ACO network, quantify the true cost of an episode of care,
negotiate better reimbursement contracts, and understand the
factors across the continuum of care that impact the clinical
outcomes of their patients.
010101
101010
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Claims Data
Medications
Patient Cohorts
Procedures
•Analysis of total reimbursement
of care (TROC)
•Impact of treatment location on
patient outcomes & costs
• Referral patterns
• Severity adjustments
Phase 1
Phase 2
Phase 3
• Definition of cohorts, patient
attribution to different centers
• Compute TROC, outcomes for care
across centers
• Visualization/analytics to determine
impact of care site on TROC
© 2015 KPMG LLP, a Delaware limited liability partnership and the U.S. member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative
(“KPMG International”), a Swiss entity. All rights reserved. The KPMG name, logo and “cutting through complexity” are registered trademarks or trademarks of KPMG International. NDPPS 336084
Improved population health management
Situation: New reimbursement models under
the Affordable Care Act (ACA) require providers
to reduce readmission rates and raise quality scores for
patient care.
categorize patients by diagnosis and symptoms to create
cohorts of homologous risk; conduct predictive modeling to
understand future risk; and use visualization tools to summarize
and navigate these findings.
Problem: Meeting these ACA mandates requires a clear
understanding of which patients are most “at risk” due to
such factors as treatment nonadherence, comorbidities,
or difficult-to-control chronic conditions (see next use case
for more information).
Benefits: Providers can identify patients who are likely to
fall through the cracks, focus resources on subpopulations
most likely to benefit from intensive management, address
gaps in treatment, and channel appropriate educational and
self-care information into patient engagement programs.
These efforts should increase patients’ overall health in the
long run, making providers eligible for incentive payments and
eliminating the risk of financial penalties under the evolving
value-based healthcare system.
Solution: Analytics based on external data sets, such as BHI,
APCDs, and/or CMS data, when combined with the institution's
own data can provide significant insights. Providers are able
to compare high-risk populations based on historical data;
Readmissions/chronic disease management
Situation: The Centers for Medicare and Medicaid
Services have enacted new penalties for hospital
readmissions, making it critical for providers to track and
manage patients with chronic diseases.
Problem: Since penalties can be levied up to 30 days
postdischarge, providers cannot rely on typical follow-up
protocols. Instead, they must have a detailed, ongoing
understanding of the chronic disease patient populations they
serve and be able to precisely identify the patient cohorts that
run the highest risk of mismanagement or acute flare-ups.
Solution: Big data algorithms can mine large data sets
across many providers, combined with data sets that provide
insights into the continuum of care. Providers can identify the
combinations of comorbidities and conditions that are likely
to result in hospital admissions and readmissions for chronic
illnesses, predict outcomes for at-risk subpopulations, and
identify potential complications and cost outliers for different
population groups.
Benefits: Providers can use big data methods to create
chronic disease management programs to intervene early with
appropriate patients, reduce operational costs, make efficient
use of existing resources, and, eventually, qualify for higher
payments from payers as the industry transitions to a valuebased reimbursement model.
Consistent patient safety and quality
Situation: “Quality” has become more
than a buzzword in healthcare. The ACA has
transformed the role of quality by linking performance on
select quality measures to reimbursements, potential financial
penalties, and even customer retention under formal and
informal star-rating systems.
Problem: The task of housing and analyzing myriad quality
measurements, viewing them all in an integrated manner
woven around an actionable story, and analyzing their
interrelationships can be overwhelming.
Solution: Combining quality measures from various sources—
and supplementing with external data sets to benchmark
quality performance in comparable institutions and cohorts—
can be a critical component of a quality dashboard solution
with drill-down capabilities. Such a solution allows trending and
analysis of quality metrics in a single data warehouse model.
Benefits: Providers can get both a bird‘s-eye view and a
targeted view of their quality measures, for internal operational
decision making and ease of reporting to both internal
stakeholders and external agencies.
The preceding use cases are just a
sampling of how providers can use large
data sets to create value. Following is a
broader list of care processes for which
data and analytics can be useful.
© 2015 KPMG LLP, a Delaware limited liability partnership and the U.S. member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative
(“KPMG International”), a Swiss entity. All rights reserved. The KPMG name, logo and “cutting through complexity” are registered trademarks or trademarks of KPMG International. NDPPS 336084
KPMG capabilities can provide actionable insights to Healthcare Providers, and help them better
understand the financial and clinical impact of care processes across the continuum of care.
Volume Leakage
Analytics
Revenue Leakage
Support
Provider
Benchmarking
Business Planning
and Forecasting
Market Share
Analytics
M&A Due Diligence
Support
Patient Risk
Stratification
Potentially Avoidable
Complications
Clinical Guideline
Analytics
Referral Patterns
Analytics
At-risk and ValueBased Contracting
Community Health
Needs Assessment
KPMG and big data
One of the elements that sets KPMG LLP (KPMG) apart is our
large strategic investment into a Data and Analytics Solution
Center. This dedicated center houses a team of leading data
scientists; engagement professionals with advanced capabilities
in big data, predictive analytics, optimization modeling, and
analytics technologies; preconfigured analytics technology
platforms; a variety of proprietary and third-party data sets,
including large external reference data sets from CMS and BHI;
and advanced groupers.
Additionally, in 2014, KPMG made several healthcare acquisitions,
including Link Analytics, one of CIO Review's “20 Most Promising
Big Data Companies”; a digital and mobile transformation company
(Cynergy); and an Oracle ERP implementation company serving
larger providers (Zanett). All these are now integrated into KPMG
Healthcare. This team provides a platform to accelerate the design
and delivery of analytical solutions created in conjunction with
our client engagement teams and our robust suite of data and
analytics offerings.
KPMG can help providers use data to thrive in the converging
healthcare landscape. Unlike pure technology companies,
we recognize that data and analytics are not simply
about technology, but a means to an end. With additional
transformational services for Revenue Cycle, Cost Analysis,
Process Redesign, and more, KPMG delivers a complete
service approach to our clients. Our aim is to help providers
flourish in an environment of increased economic pressure and
constant regulatory change, all while serving an increasingly
informed consumer. KPMG’s business-problem orientation
helps us zero in on the right data and apply the appropriate
analytics to generate value for our clients. And, in the longer
term, our business transformation approach allows us to
holistically address a practice’s or hospital’s transition to a
quality-driven and outcomes-based culture.
KPMG can help healthcare providers use data and
analytics to foster both practical solutions and business
transformation focused on improved clinical and
financial outcomes.
About KPMG
KPMG is a leader in convergence, assisting organizations across the
healthcare and life science ecosystem to work together in new ways to
transform the business of healthcare.
With more than 20,000 U.S.-based employees, and 8,600 U.S. partners
and professionals supported by a global network of firms in 155 countries,
we offer a market-leading portfolio of tools and services focused on
helping our clients adapt to regulatory change; design and implement new
business models; and leverage technology, data, and analytics to guide
them on the paths to convergence.
Our professionals can assist throughout the transaction life cycle,
depending on the organization's resource constraints. This can include
marketplace research and thought leadership in establishing a strategic
road map, as well as support with target identification, deal structuring,
valuation, due diligence, and integration assistance, all helping to translate
strategy to successful execution and outcomes.
Contact us
Bharat Rao, PhD
Principal
bharatrao@kpmg.com
Mohit Chandra
Managing Director
mchandra@kpmg.com
John Weis
Director
jweis@kpmg.com
kpmg.com
The information contained herein is of a general nature and is not intended to address the circumstances of any particular individual or entity. Although we endeavor to
provide accurate and timely information, there can be no guarantee that such information is accurate as of the date it is received or that it will continue to be accurate in the
future. No one should act on such information without appropriate professional advice after a thorough examination of the particular situation.
© 2015 KPMG LLP, a Delaware limited liability partnership and the U.S. member firm of the KPMG network of independent member firms affiliated with
KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved. Printed in the U.S.A. The KPMG name, logo and “cutting through complexity”
are registered trademarks or trademarks of KPMG International. NDPPS 336084