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The Intelligent Back Office in HealthcareNEO HFMA Leadership Institute KPMG Presentation
2© 2019 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.
With you today
Michael Caporusso
Solution Director in KPMG’s
Intelligent Automation
Practice
mcaporusso@kpmg.com
Rachel Silverman
Director in KPMG’s
Care Continuum
Optimization Practice
rrosenblum@kpmg.com
3© 2019 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.
Who we are
The creative
CIOs agenda:
Getting started
with digital labor
KPMG Intelligent Process Automation Thought Leadership
Digital Labor
and the future of
finance
RPA & Cognitive
Automation in
Healthcare
Transforming
business models
with RPA
Bots in the back
office: The
coming Sprint
of digital labor
KPMG
KPMG ranks the highest of the “Big 4” in digital transformation
Forrester
Insights Service Provider Wave
Leading Advisor
Horses for Sources
Intelligent Automation Blueprint
Leading Independent Advisor
With over 200 implemented Use
Cases, KPMG’s global Intelligent
Automation community of
approximately 13,000 people has
broad capabilities to support
projects around the world.
U.S. Healthcare and Life Sciences professionals
2000+
700+
KPMG operates in 155 countries With 700 +offices worldwide
Modernizing records processing in Government
Natural Language Experiences
3© 2019 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.
Intelligent Automation
Optical Character Recognition
Intelligent Automation in Healthcare
5© 2019 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 perception of disruption
“While
technology
disruption has
always been
an issue, the
difference today
is speed of this
transformation
and technology
availability”
98
%72%
See
technological disruption
as more of an opportunity
than a threat *
Say that
rather than waiting to be
disrupted by competitors,
their organization is actively
disrupting the sector in
which they operate**
49
%45
%61
%
Are concerned about the
integrity of the data on which
they base decisions **
Say they are not leveraging
digital as a means to connect
to their customers and
vendors/suppliers effectively **
Are concerned about
integrating cognitive processes
and artificial intelligence **
*Source: US CEO Outlook 2018 survey: Growing Pains offers insights into the greatest concerns of CEO’s and how they plan to pursue growth and technology driven disruption. Findings based on a
study of nearly 400 US CEOs, with annual revenues greater than US $500 million; 39% have greater than US $10 billion in revenues.
**Source: US CEO Outlook 2017 survey: Disrupt and grow offers insights into the greatest concerns of CEO’s and how they plan to mobilize for the fourth industrial revolution. Findings based on a
study of the 3-year outlook of nearly 400 US CEOs, with annual revenues greater than US $500 million; 32% have greater than US $10 billion in revenues.
6© 2019 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 future of Intelligent Automation
*Source: “LSE - The IT function and Robotic Process Automation” – The London School of Economics and Political Science 2015
“**Source: Artificial Intelligence Market by Offering (Hardware, Software, Services), Technology (Machine Learning, Natural Language Processing, Context-Aware Computing, Computer Vision), End-
User Industry, and Geography - Global Forecast to 2025– Market and Market February 2018
$140M
600% ROI800%AND
50%
Cantor Fitzgerald’s
research suggests that
as many as 110-140 million
FTEs could be replaced
by IA technologies, reducing
costs by 25 – 40%.
Recent research from the London School of
Economics suggests a return on investment in
robotic technologies between 600% and 800%
for specific tasks.*
A recent study by KPMG LLP reports that 50 percent of
respondents would be using Intelligent Automation
technologies at scale within 3 years.
Markets and Markets
estimates that the AI,
or cognitive
computing
marketplace, will be
valued at**billion by 2025
190.61$
26
billion
$
39
billion
$
McKinsey’s 2017
report on the State of
Machine Learning
and AI estimated
that, in 2016 alone,
companies invested
between $26 billion
to $39 billion in
Artificial Intelligence.
Morgan Stanley predicts that 50-60% of white collar work is automatable, and this will have a 30% labor cost reduction.
Gartner predicts that by 2020, smart
machines will be a top five investment
priority for more than 30% of CIOs.
Top
5
7© 2019 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.
Intelligent Automation marketplace is maturing rapidly
Source: 2017 & 2018* CEO Outlook Survey, KPMG LLP (June 2017 & June 2018)
Cognitive technologies
81%Of CEOs are emphasizing trust,
values and strong culture to sustain
the organization’s future
These technologies —from robotic process
automation to cognitive automation—are advancing
at a staggering pace, and will disrupt almost every
business and industry.
Investment in cognitive technologies will
be an area of focus for almost 60% of
CEOs through 2020
45% say they are not effectively
leveraging digital to connect with their
customers
Connecting
with customers45%
60%
60% worry their organizations’ sensory capabilities
and innovative processes will not stand up to rapid
disruption
Active disruption
to gain insightStaying competitive
means embracing digital
86%said their organizations are
actively disrupting their
own sectors*
61% are concerned about integrating
cognitive processes and artificial
intelligence in the workplace.
The concern for
integration
Source: 2017 CEO 12017 anOtk Survey, KPMG LLP (June 2017)
© 2019 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.
8© 2019 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.8© 2019 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. NDPPS 849511
Classification of intelligent automation capabilities
ACT RULES LEARN REASON THINKlike a human Basic process
automation
— Macro-based
applets
— Screen level & OCR
data collection
— Workflow
automation
— Process mapping
— Self executing
Enhanced automation
— Built-in knowledge
repository
— Learning capabilities
— Ability to work with
unstructured data
— Pattern recognition
— Reading source data
manuals
— Natural language
processing
Cognitive automation
— Artificial intelligence
— Natural language
recognition &
understanding
— Self-learning
(sometimes self
optimizing)
— Processing of super
data sets
— Predictive analytics/
hypothesis generation
— Evidence-based
like a human
Class I Class II Class III
9© 2019 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.9© 2019 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. NDPPS 849511
Challenges across the care continuum in healthcare
Emergency
Department
Acute Care
Ambulatory CarePatient is readmitted
Patient provided generic
discharge instructions
Improperly staffed
units and poor bed
management. Delays
in care and increased
LOS
Delays in procedures
or treatments
Delay in discharge due
to unaddressed barriers
or post discharge needs
Delay in diagnosis and
DRG determination
Billing delays due to claim
rejections and coding issues
Supplies wasted when
performing procedure
Key
Clinical Challenges
Patient no-show for follow-up
appointments and does not
fill prescriptions.
Readmission risk increases
10© 2019 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.10© 2019 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. NDPPS 849511
Applying IA across the care continuum in healthcare
Emergency
Department
Ambulatory Care
Patient provided tailored
instructions based on
personality assessment
Number and frequency of
reminders provided based on
the patient’s patterns and
preferences. Alert sent to
staff if medication was not
filled. At home devices to
aid patients in compliance
Scheduling optimization
of patients and staff to
reduce delays and
case cancellations
Machine learning used to target
key barriers to discharge and
provide EHR CDS alerts
Provider alerted that
medication has not been
administered –
concurrent monitoring of
care variation
Billing errors caught with AI/
machine learning, preventing
rejections and coding issues
Analytics used to identify
resource utilization and
opportunities to identify
wasteKey
Analytics and
automation Use predictive
analytics to support
acuity-based staffing
and dynamic shifting
of staff for current
census.
Acute Care
Patient is identified as high risk for
readmission. Appropriate action taken at
discharge. IA to assess risks for mortality
and complications
Use analytics for
placement of patient in
appropriate bed
IA used to detect benign
or malignant tumors in
radiology images for faster
diagnosis
11© 2019 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.
Targeting healthcare back office functions
— Employee on-boarding and off-boarding
— Payroll
— Time recording and compliance
— Repeatable tasks in ERP
— Email notifications
— Populating/aggregating employee
information— Month-End reporting
— Invoice
processing/exceptions
— AP/AR actions
— Close & reconcile sub-ledgers
— Asset depreciation and
impairment
— Fixed asset reporting
— Financial forecasting
— Invoice validation &
processing
— Tax filings
— Order flow through
— Inventory Mgmt.
— Exceptions/fallout
— Research/document
review
— Document preparation
— Controls automation
— Virtual agents (chat bots)
— Call center “agent assist”
— Task execution
— NLP enabled analytics
— Social media mining/monitoring
— Predicting high value sales leads
— Manual CRM updates
— Virtual sales agents
Human Resources
Legal/Compliance
Finance & Accounting
Sales & Marketing
Supply Chain
Customer Support
He
alt
hc
are
Ba
ck
off
ice
Fu
nc
tio
ns
12© 2019 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.
Applying Intelligent Automation to healthcare
Best
Practice:
Start with a
Strategy
AI for Detection
AI research for detection: Radiology,
Pathology, Dermatology, Ophthalmology,
Gastroenterology, Cardiology.
Incorporated into workflows to improve
time from detection to treatment.
AI for Prediction
AI research for improved predictive
accuracy, examples include: in-hospital
mortality, readmission, complications in
ICU patients. Speed and accuracy tested
to support clinical decision making.
AI for Patient Interaction
AI research for voice assistance: patients
in acute setting and home care.
AI is currently used to support call centers
for non-clinical patient interactions –
scheduling, bill payment, questions
AI for Operational Efficiency
AI algorithms used for improved
efficiencies, examples: voice-enabled
workflows, contract, invoice, payroll, and
expense management, chart abstraction,
predictive claims denials and submittals, .
Incorporation into EHRs for improved
‘usability’
13© 2019 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.
Case Study: Improving payment accuracy
Modernizing and accelerating a time-consuming and manual
documentation intake validation process at a healthcare agency with:
― Robotic process automation (RPA)
― Optical character recognition (OCR)
― Machine learning (ML)
― Natural language processing (NLP)
14© 2019 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.
Case Study: Improving payment accuracy
15© 2019 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.
To successfully
incorporate Intelligent
Automation within
processes and teams,
organizations must
proactively address the
impacts to their people
& the overall organization
in order to minimize
business disruption and
expedite the timing of
benefits realization.
Organizational & people impacts – our point of view
Changing Behaviors
Adopting and adapting
the new ways of working
Leadership Vision
Agreeing on future state
vision for the
organization
Talent
Hiring, reskilling
and exiting talent
Culture Shift
Overcoming the
fear factor
Workforce Shaping
Adaptive workforce realignment for
evolving digital labor needs
Organizational
& People Impacts
Speed of
ImplementationThe rate of change is faster
than traditional process and
system implementations
Constant ChangeIntelligent Automation
implementations will be iterative
and constantly evolving to
develop optimal workforce
productivity and ROI
Demands a Higher Purpose
ConversationEmployers will need to
understand and engage with the
impact they will have on society
Unique Characteristics of Intelligent Automation Implementations
16© 2019 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.
Getting started
“Size the Prize” – Evaluate processes by suitability for automation and effort to estimate overall
benefit potential
Conduct a Proof-of-Concept – Demonstrate technology effectiveness and validate performance
Define a Deployment Roadmap – Outline steps to stand up an Intelligent Automation capability and
begin to capture the benefits
17© 2019 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.
Additional considerations and lessons learned
Establish an
enterprise-wide
capability
Partner with your
technology function
Strike the balance
of your digital
transformation
Protect your
business case
Select vendors
aligned with your
ambition
Set your priorities
and the rest will
follow
Build solid
foundations
Identify and
incentivize talent
Start small; deliver
swiftly
Consider business
scalability
Evolve your
analytics capability
Automation ‘horses
for courses’
18© 2019 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.
Questions to start thinking about todayIt’s no longer business as usual
— Where can we streamline and enhance our patient or provider experience?
— Where can we reduce the number of mundane and respective tasks our workforce
performs?
— What message will automation bring to our workforce and how would the future look?
— What are the risks and costs we face when we have rework or corrections?
— Is our data telling us all we need to know?
— Can we offer more within our current footprint? Could we expand our scope/market
share of services we offer?
— Where are we with automation now and where can we expand?
— What if our competitors automate and we don’t?
19© 2019 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. 19
Thank you
© 2018 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.
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