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The Power of Analytics 2.0:
Improving Patient Care, Reducing Costs
Featuring the results of the
Business Intelligence/Analytics Survey, February 2012
D
riven by changing reimbursement models, the rapidly changing science of medicine and
increasing competitive pressures on health systems, enterprise-level analytics is critical for
healthcare organizations.
Historically, health systems have approached analytics primarily from an incremental, retrospective and operational-siloed
approach. This approach, “Analytics 1.0,” has historically labored under several constraining factors, such as inadequate
electronic source data (too many manual processes), source data limited to transactional silos (data constrained
departmentally) and a focus on the use of analytics to merely satisfy external reporting requirements, versus higher order
predictive analyses. Solutions designed for the “Analytics 1.0” environment often followed these limitations, either as
manual spreadsheet/database solutions, or niche solutions narrowly focused on operational needs.

Today’s health systems must operate in an entirely different climate. Health systems are now dealing with an abundance of source
data, with the growing digitization of medicine including the proliferation of electronic health records, personal health records, mobile
technologies, health-related social media and molecular-level profiling. The requirements around analytics have also shifted, being
elevated from simple departmental reporting of performance to enterprise-wide, C-suite needs for clinical and business intelligence.
Niche analytic solutions have been unable to fulfill these requirements or have not been able to assimilate data from the multitude of
source systems required, and thus a new breed of analytic solutions, “Analytics 2.0,” is needed. Table 1 illustrates the evolution of the
analytic environment in the healthcare industry.
Healthcare IT News conducted an online survey of 209 respondents from February 1 to March 7, 2012 on behalf of Oracle and Deloitte1
to identify the driving forces for deploying an Analytics
2.0 infrastructure for healthcare providers. The
survey found that while healthcare providers strongly
recognize the need for timely access to high-quality
analytics, the results achieved thus far have been
limited. The demand for a more integrated view
of the enterprise has increased as many begin this
transformational process, and as a result, Analytics 2.0
is emerging in the industry.
High Demand for Analytics 2.0
Deliverables
Related to finance and business operations, survey
respondents cited the following areas within their
organization as having an identified need for timely
access to high-quality analytics: corporate and clinical
risk measurement, resource utilization, predictive
analytics for forecasting and market development,
financial information about past performance, revenue
cycle, and supply chain/spend analytics. On the clinical
side, healthcare providers cited a great need for
analytics for quality reporting, patient safety, utilization
and access to healthcare services (See Graph 1).
The high percentages across all areas underscore the
technical importance of extracting information from
multiple sources. Driving environmental forces and
opportunities – such as the shift from pay-for-volume
reimbursement to value-based accountable care;
delivering cost-effective, translational and comparative
effectiveness research; novel collaborative partnership
opportunities with pharmaceutical or medical device
organizations; cost-effective care management for high-
risk patient populations; health information exchange
(HIE); and personalized healthcare – require access
to and synthesis of information from multiple source
systems. To effectively participate in any of these
1. As used in this document,“Deloitte” means Deloitte Consulting LLP, a subsidiary of Deloitte LLP. Please see www.deloitte.com/us/about for a detailed description of the legal structure of
Deloitte LLP and its subsidiaries. Certain services may not be available to attest clients under the rules and regulations of public accounting.
Predictive analytics (forecasting,
market development, etc.)
Quality reporting
Revenue cycle
Supply chain/Spend analytics
Resource utilization
Corporate and clinical risk
measurement
Financial information about past
performance
The quality and safety of services
delivered
Patient’s ability to access health
care services
1%
0%
0%
1%
0%
0%
0%
0%
2%
46%
49%
4%
2%
67%
31%
48%
44%
7%
31%
58%
10%
45%
50%
5%
46%
51%
3%
43%
52%
5%
70%
28%
1%
43%
51%
4%
“My organization needs timely access to high quality
analytics in the following areas:”
Strongly Disagree
Disagree
Agree
Strongly Agree
Source: Healthcare IT News Business Intelligence/Analytics Survey, February 2012
0 20 40 60 80 100
“Analytics 1.0” “Analytics 2.0”
• Data derived from manual data sources or single-source transactional
systems
• Focused on retrospective analyses of unit or department-level performance
• Simple questions – “Show me all patients with diagnosis X who experienced
outcomeY”
• Industry solutions – manual reports and dashboards,“niche” analytics
applications
• Multiple solutions required – “Build once, use once”
• Data derived from multiple transactional source systems
• Focused on enterprise-level prospective and predictive
analyses
• Hard questions – “Show me the effect of nursing
overtime patterns on ICU quality measures and patient
satisfaction metrics”
• Industry solutions – enterprise health analytic platforms
• Single enterprise solution – “Build once, use many times”
Table 1
Graph
1

initiatives in which survey respondents have indicated high interest (see Graph 2), healthcare providers require a data-holistic view of
their organization.
As many healthcare providers are already realizing, bolting “niche” analytics solutions atop multiple transactional systems across
departments can be cost prohibitive and short-sighted. Health systems should adopt organization-level strategies leveraging enterprise
analytic solutions rather than maintaining a portfolio of niche analytic solutions in order to leverage existing resources and cost-
effectively meet current and future needs. An enterprise-wide business intelligence and analytics strategy can economically and
holistically address these needs.
Closing the Gap between Current Capabilities and Demand
Current Analytics 1.0 capabilities are not fully meeting survey respondents’ requirements in the financial, operational or clinical
domains. Many have indicated they are taking decisive steps to rectify the situation by exploring an enterprise-oriented strategy. Graph
3 highlights some of the critical barriers to address in this evolution.
In the past, organizations had to sacrifice ease of use for flexibility and analytical sophistication. Over the last decade, analytics
technology has been evolving at such a rapid pace that analysts and other end-users can now perform functions that previously required
programmers and statisticians. At the same time, the healthcare industry faces the challenge of analyzing a growing amount of data to
solve increasingly complex problems. Healthcare providers who know how to leverage these powerful capabilities can have a competitive
advantage while those who do not face an uncertain future, according to Dr. Mitch Morris, Principal, Deloitte Consulting LLP and
healthcare technology leader.
Despite the growing awareness that high-quality analytics can define effective health systems in the new healthcare environment, classic
implementations of transactional systems such as electronic medical records (EMRs) often give little attention to analytics. This issue
has become magnified as health systems rush to achieve compliance with well-meaning initiatives such as Meaningful Use Criteria from
the HITECH Act. Dr. Frederick Lee, Director for Clinical and Translational Informatics at Oracle Health Sciences, advises healthcare
providers to step back and realize that decisions made during hasty EMR implementations can impact their ability to cost-effectively
conduct analytics downstream. “This is a vestige of Analytics 1.0 thinking – implementing a solution to support operational workflows,
without consideration of how this data will be used to power an analytics strategy,” he said. Following suit, forward-thinking healthcare
providers have allowed analytic use cases to inform their EMR implementation. The rush to implement EMRs with an Analytics 1.0
mindset can also give rise to false expectations that a health system’s analytics needs will be met by an EMR implementation alone;
organizations are often surprised that additional spend for an enterprise analytics solution is needed downstream. “EMRs can get you
into the red zone, but today a health system needs an enterprise analytics solution to get into the end zone,” Lee said.
Historically, only the largest, most technically sophisticated organizations with significant IT outlays in budget and resources could
build and maintain enterprise data warehouse solutions capable of powering Analytics 2.0 strategies, according to Brett Davis, Senior
Director of Healthcare Strategy and Business Development for Oracle.. However, even these pioneers have realized that these efforts
are not sustainable in the face of an ever-expanding diversity of data types and sources, exponentially complex data quality issues as
0
What are the top three strategic drivers for your organization to evaluate secondary uses
of your transactional data?
52.2%
74.2%
29.7%
56.5%
70.3%
17.2%
Improved care management of high cost
populations
Health information exchange to improve care
and coordination
Accelerating translational or personalized
healthcare strategies
Shifting to value based care and accountable
care organizations
Looking for new revenue streams with pharma
or medical device industries
Currently not evaluating secondary uses of
transactional data
Graph
2
80
70
60
50
40
30
20
10

more sources come online, and a regulatory and compliance environment that is constantly changing analytic requirements. Moreover,
true Analytics 2.0 requires empowerment of clinical and business end-users themselves: Clinicians and managers need agile analysis often
at the point of care. “The model of ‘building your own’ data warehouse is no longer sustainable, not that this was ever an option for the
average health system,” said Lee.
Academic medical centers have historically been the early adopters of analytics, according to Davis; however, hospitals, integrated
delivery networks (IDNs) and ambulatory care facilities are now looking to analytics as a solution. Graph 4 reveals the various stages
of analytics adoption by survey respondents who predominantly work for these three types of healthcare organizations compared to
those who work for academic institutions, 82 percent and 2 percent, respectively. As enterprise analytics continues to move into the
mainstream, an efficient approach is to implement an effective architecture that can deliver defined information to a target audience in a
timely manner through whatever format and channel that works effectively for them.
Analytics 2.0 Success: Combining Data Governance and Technology
Effective strategies to solving complex healthcare issues involve a combination of leadership, teamwork, technology and demonstrated
approaches that can address identified issues on many different levels – strategic, tactical and operational. An effective governance
strategy is a requirement to an effective enterprise analytics program – it is the linchpin that maintains alignment among the
organization’s mission, analytics program initiatives, data management practices and technical resources, according to Michael Brooks,
Specialist Leader in Healthcare Information Management, Deloitte Consulting LLP. “Effective enterprise analytics programs involve close
collaboration among executives, technical teams, the user community and other subject matter specialists. More often than not, these
programs go beyond data and technology and address a variety of cultural, behavioral and other issues that extend well beyond the IT
department” says Brooks.
One of the major challenges for any analytics initiative is resource and budget constraints. Indeed, 48 percent of respondents cited
limited access to skills and resources as a barrier. Attracting skilled resources who understand healthcare and analytics may continue
to be a challenge. Addressing this resource gap warrants new deployment approaches that are based on a combination of enabling
accelerators and pre-configured architectures that can substantially shorten the implementation time, cost and risk of changing
requirements. The value of such agility to the organization and its patients can be significant. The quicker organizations can respond to
opportunities and challenges, the more competitive they can become.
Diverse healthcare organizations are implementing enterprise data governance strategies that fit within their culture and operating
model. These strategies require an assessment of impacted data sources to determine what transformations are needed to obtain
0
What are the three biggest barriers you face in becoming a data-driven enterprise?
39.7%
48.3%
43.5%
52.2%
26.8%27.3%
39.2%
16.3%
6.7%
60
50
40
30
20
10
0
Poor Data Quality - Diverse range of data sources
impacts on ability to create a single source of
truth difficult
Limited access to skills and resources
Information is not available in a timely manner,
so decisions are made without being data driven
Limited analytics champion/sponsorship
Lack of a clear vision on how the organization can
benefit from analytics
Poor Data - Too many manual systems deployed -
we don’t have sufficient electronic data
Poor Data - We have transactional systems, but
we can’t unlock out data easily
We are not culturally ready to become a data-
driven organization
Other (please specify)
Graph
3

high-quality, action-oriented information. An important component of the process involves change management. With 16 percent of
respondents reporting that their healthcare organization is not culturally ready to become a data-driven enterprise, the ability to garner
executive sponsorship and guide change management are critical first steps to embracing analytics. This requires the skillful development
of a clear vision based on common values and goals, and a resulting change management strategy that addresses process and decision-
making integration, as well as technology and data integration.
Oracle has further accelerated the implementation process by designing preconfigured data warehouses based on healthcare industry
leading practices. The warehouses can be customized to meet the individual needs of healthcare organizations and adapt in terms of
volume and complexity, which benefits both small community hospitals and large IDNs, according to Simon Instone, Director of Oracle’s
healthcare solutions for Europe, the Middle East and Africa. Instead of working harder, healthcare organizations of any size can work
smarter.
In another effort to democratize enterprise analytics for healthcare, Oracle has productized the data model – which is upgraded
with new applications developed by third-party software vendors – that represent the whole of the integrated view of healthcare
across clinical, financial, supply chain and other systems. “We’re fundamentally trying to shift the economics and speed with which
an institution can deploy enterprise analytics,” said Davis. Speed is important to 57 percent of respondents who cited cost-effective,
timely implementation and 35 percent who cited faster access to information and reporting as factors for their organizations to deploy
analytics.
Building analytics applications from the ground up or resorting to a tools-based approach can be unsustainable. It can be more
economical – especially in an era of multiple IT initiatives meeting complex mandates and requirements – for healthcare organizations to
take advantage of a platform approach to analytics with productized components, given that many analytics challenges organizations face
are similar. This approach appeals to respondents who cited the ability to leverage their existing technology; user-friendly analytics tools;
and analytics initiative aligned with other health IT initiatives within their organizations as factors for implementing analytics. “Whatever
the use case – preparing to be an ACO, operational efficiency, managing patient populations more efficiently through personalization –
it’s the same data,” Davis explained. “Build the infrastructure so you integrate once and use many times versus taking the silo approach.”
The Real-World Power of Analytics 2.0
Twenty-eight percent of survey respondents cited documented effective uses of analytics as a factor in potentially deploying the
technology. Oracle’s and Deloitte’s collaboration can deliver value for healthcare organizations. For example, an academic medical
center shortened its process of identifying protocols for Phase II clinical trials and recruiting patients from 18 to 24 months to less than
three months. The acceleration bolstered the medical center’s position as an academic research leader in its specialty, benefited its
pharmaceutical collaborators and resulted in collaborations with new pharmaceutical companies.
With analytics, healthcare organizations can leverage information to better manage their resources and supply chains. One healthcare
provider applied analytics to identify the root causes for its denied insurance claims. By gaining insight into physician practice ordering
patterns, another healthcare provider standardized implant purchases, which streamlined ordering processes and reduced costs.
Healthcare providers have also analyzed utilization patterns to better coordinate staffing while managing overtime and contractor costs.
Where is your organization in terms of use of BI / Analytics?
Extensive use of analytics to improve operational efficiencies
Extensive use of analytic capabilities for translational research and
clinical effectiveness
Predominant use of standalone departmental datamarts
Enterprise data warehouse planned and under development
Enterprise data warehouse implemented and operational
Currently don’t use analytics, but planning to soon
No clear analytics strategy/do not intend to pursue
13.4%
8.6%
19.6%
16.7%
12.9%
20.1%
8.6%
Graph
4

Produced by MedTech Media Custom Group, 2012. All rights reserved.
71 Pineland Drive, Suite 203 • New Gloucester, ME 04260 • 207.688.6270 • www.medtechmedia.com
Analytics 2.0 goes beyond helping to solve the economics of healthcare to the future of healthcare, which is already here for visionary
healthcare organizations. Thirty percent of respondents cited looking for new revenue streams with pharmaceutical or medical device
industries as a strategic driver for their organization to evaluate secondary use of transactional data. Revenue-generating partnerships
are being considered by community hospitals and health systems, normally the milieu of research institutions. The timing is good: The
pharmaceutical industry’s business model is undergoing a seismic shift, thanks to healthcare costs, bar-raising comparative-effectiveness
requirements and the move from blockbuster drug to targeted drug, among other pressures. The pharmaceutical value chain – including
discovery, clinical trials and post-marketing – requires real-world healthcare data that is clean, normalized and longitudinal. As a result,
new business opportunities are emerging in which pharmaceutical companies are looking to collaborate with heathcare organizations to
ethically leverage their transactional data.
Building a Sustainable, Data-Driven Healthcare Enterprise
There is an emerging awareness among leading healthcare providers, payers and other organizations that a more complete view of
enterprise performance and market dynamics is needed to excel in today’s environment. Analytics can make it possible to get the
insights decision makers need and is quickly becoming recognized as a new game changer, according to Brooks. A number of healthcare
organizations have already begun the journey, according to the Healthcare IT News February 2012 online survey results.
What should help move the needle from early adoption to critical mass is the awareness of the areas Analytics 2.0 can positively impact
(See Graph 5). As healthcare providers begin to engage in quality and cost initiatives, new partnerships and revenue streams, and
other projects, it is anticipated that awareness will shift to deployment. According to the survey, 17 percent of respondents said their
organization is currently not evaluating secondary uses of transactional data and nearly 9 percent said their organization has no clear
analytics strategy and does not intend to pursue one. Sooner rather than later, nonparticipation will no longer be an option for survival.
Healthcare organizations that understand the benefits of Analytics 2.0, however, will be in a position to rapidly and nimbly participate in
current and future initiatives and not only survive but thrive in the new healthcare environment.
As far as your health care organization is aware, analytics can impact the following areas:
85.72%
100
80
60
40
20
0
37.78%
77.0%
53.6%
46.4%
Cost-effective improvement of care management for high-cost,
high-risk patient populations
Assist in transitioning organization to value-based care models
Enable participation in health information exchange initiatives
Accelerate translational or personalized healthcare strategies
Ability to drive new revenue streams with pharma or medical
device industries
Graph
5
Deloitte Statement
This document contains general information only and Deloitte is not, by means
of this document, rendering accounting, business, financial, investment, legal, tax,
or other professional advice or services.This document is not a substitute for
such professional advice or services, nor should it be used as a basis for any
decision or action that may affect your business. Before making any decision or
taking any action that may affect your business, you should consult a qualified
professional advisor.
In addition, this document contains the results of a survey conducted by a third
party on behalf of Deloitte. The information obtained during the survey was
taken “as is” and was not validated or confirmed by Deloitte.
Deloitte, its affiliates, and related entities shall not be responsible for any loss
sustained by any person who relies on this document.
Copyright © 2012 Deloitte Development LLC.All rights reserved.
Member of Deloitte Touche Tohmatsu Limited
About Oracle
Oracle is the world’s most complete,open,and integrated business software and
hardware systems company.For more information about Oracle,please visit our
Web site at www.oracle.com.

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