data analytics: are u.s. hospitals late to the party?

1Tipping point: Hospital resilience in a perfect stormData analytics: Are U.S. hospitals late to the party?

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Using analytics to mine large datasets for insights, commonly known as Big Data, is already transforming industries ranging from consumer goods to transportation. Certainly, the healthcare sector has the raw information to join this group. For example, Kaiser Permanente, a California-based health network, has an estimated 27 to 44 million gigabytes of potentially useful patient information. Expectations are that the U.S. healthcare sector will soon have a zettabyte (1021 gigabytes) of these data.1

1 Wullianallur Raghupathi and Viju Raghupathi, “Big data analytics in healthcare: promise and potential,” Health Information Science and Systems, 2014.

TIPPING POINT: HOSPITAL RESILIENCE IN A PERFECT STORMData analytics: Are U.S. hospitals late to the party?


U.S. hospital leaders see exciting potential in this treasure trove. According to an Economist Intelligence Unit (EIU) survey of more than 300 healthcare sector executives conducted for this research program, 63% of respondents say the value of the data that hospitals hold remains largely untapped. In addition, 60% say that Big Data is transforming future opportunities around the patient and 57% believe it can be a game changer for operational performance. Several years ago, McKinsey, a consultancy, estimated that the U.S. healthcare sector could reduce total costs by 8% through the creative application of analytics.1 Cognitive computing systems—which involve machines learning for themselves rather than relying on complex algorithms to analyze data—are even seeking to reshape how diagnoses and treatment plans are made by “thinking” for clinicians.

1 McKinsey Global Institute, “Big data: The next frontier for innovation, competition, and productivity,” 2011.

Technology and data perspectives % of respondents

Agree

The value of the data hospitals hold on patients and outcomes remains largely untapped

63%

Hospitals have lagged other sectors in adopting technology and data analytics

61%

Big Data is transforming future opportunities around patient management and outcomes

60%

In order to get the full potential value out of Big Data in the future, pharmaceutical companies, payors and healthcare providers will need to collaborate on data analytics to determine the most effective and economical patient treatments and protocols

60%

Hospital data can be a significant game changer in operational performance

58%


Slow adopters of technology

However, healthcare has long had a reputation for slow adoption of technology. Already in the mid-1990s, the imminent advances of electronic health records (EHRs) were being touted. Yet seven years after the HITECH Act of 2009 signalled a regulatory push for the adoption of these tools—later given further impetus by the Affordable Care Act (ACA)—a substantial minority are still working on the basics. Twenty-two percent of survey respondents report that in the next three years they will be investing to complete implementation of EHRs and 29% will put money in software or hardware to demonstrate their meaningful use.

The picture for analytics may be similar. Dr. Kip Webb, North American Healthcare Provider Portfolio Lead at Accenture, says that, compared with other industries, “hospitals are already late to the party.” Survey respondents admit as much: 61% say that hospitals have lagged other sectors on data analytics against only 7% who disagree.

An uptick in digitization?

Some important groundwork has been laid, however. The last seven years have seen “a huge uptick in digitization,” notes Dr. Webb, with hospitals actively gathering electronic data, largely as part of EHR implementation. According to the U.S. Department of Health, as of April 1995, 98% of all hospitals had demonstrated meaningful use or at least implemented some sort of EHR.2 As Lloyd Dean, CEO of Dignity Health, puts it, “I could overwhelm you with data. That is not the issue.”

Yet these mountains of data bring their own unexpected challenges. Dr. Amy Abernethy, Chief Medical Officer and SVP, Oncology at Flatiron Health and a board member of athenahealth, two EHR and healthcare analytics firms, says, “There used to be magical thinking around EHRs. [The expectation was that] we would have a rise in immediately actionable data. Then we would push a magic button so that the data would be organized perfectly and tell us what to do. What the sector has learned, though, is that data in its raw form is not all that useful. It needs to be cleaned up and organized. Then analyses need to be done.”

Gathering and bringing some kind of order to the data is an ongoing process at many hospitals. Too often, notes Dr. Webb, even collection is overly costly because “we have made clinicians very expensive data clerks” instead of finding more efficient ways to enter information into systems.

Data standardization and silos, even within individual hospital systems, also remain a widespread problem.3 James Rebitzer, Professor of Markets,

2 “Hospitals Participating in the CMS EHR Incentive Programs,” HealthIT.gov Dashboard, April 2015.

3 “Survey: Unstandardized data biggest barrier to analytics, business intelligence for healthcare,” Becker’s Health IT and CIO Review, 1 May 2015.

“I could overwhelm you with data; that is not the issue.” Lloyd Dean,

CEO, Dignity Health


Public Policy and Law at Boston University Business School, says that often EHR systems “are big, cumbersome beasts that are not that helpful yet for the data analytics challenge.” At the sectoral level, aggregation of information—a key to unlocking Big Data for most providers—has barely begun. “With a few exceptions,” says Charles “Chip” Kahn III, President and CEO of the Federation of American Hospitals, “we do not have interoperability. You need to think of each hospital or hospital system as separate outposts, each with its own data.”

Lots of data, little insight

Despite these challenges, an increasing number of large aggregations of potentially exploitable healthcare data now exist. That number will grow. Rather than the ultimately solvable issues of data organization, the most pressing concern is more fundamental—what to do with the information. “My worry,” says Mr. Dean, “is that we are going to be overwhelmed with data, have it all sitting there and not have the construct to make it actionable.” Dr. Webb agrees: “We have a lot of data now, but not a lot of insight.”

Dr. Abernethy believes that solutions to this problem have begun to emerge. After years of focusing on the data gathering and organization, she says, “we are now at the point where there are examples of how it can be made actionable.” The market is certainly putting substantial money into the capacity to provide such insight. In the first half of 2015, $6.4bn went into venture capital funding for healthcare analytics start-ups, not far shy of the $7.4bn invested in all of 2012.4 At the other end of the business spectrum, in 2014 IBM put aside $1bn to create a business unit for Watson, its cognitive computing system. One of IBM’s main target markets is healthcare.

4 CB Insights, “Healthcare Startup Boom: 2015 Could See More Than $12B Invested Into VC-Backed Companies,” September 2015, https://www.cbinsights.com/blog/healthcare-startup-funding-trends/

How hospitals plan to use data to produce actionable insights* (% of respondents)

Long-term individual patient disease prevention and care

Finding and demonstrating value added from processes and procedures

Monitoring performance of individual medical personnel

Improving care pathways and processes

Improving administrative and other non-medical processes

Individual patient diagnosis and associated care plan

0 10 20 30 40 50

*Timeframe is within the next three years Source: The Economist Intelligence Unit survey, 2016

In the first half of 2015, $6.4 billion went into venture capital funding for healthcare analytics start-ups, not far shy of the $7.4 billion invested in all of 2012.


Only a minority of U.S. hospitals, however, are currently coming to the party. According to the EIU survey, just 37% of respondents say their hospital plans to invest in data analytics in the next three years. Moreover, although every hospital expects to try to make use of analyics in some way in that time period, only a minority plan to exploit the technology for any given task.

The difficulty does not appear to be lack of vision. Dr. Abernethy reports that she sees “a rapid growth in interest” in a wide range of analytics-based tools covering fields from general population health to oncology. Just as the existence of EHRs revealed issues around the need to organize and analyze data, though, now the existence of software that can provide actionable insights “has uncovered new problems,” she adds. These are likely slowing investment in analytics by hospitals.

Realigning reimbursement

One is realigning reimbursement. Dr. Abernethy notes that, to date, use of data in healthcare has not been rewarded financially—and determining how to do so is far from straightforward. The Centers for Medicare & Medicaid Services (CMS) is currently launching a pilot program to use such incentives in cancer care, as are other insurers. Dr. Abernethy says, “The oncology community is trying to figure out how to use the data in order to be paid.”

A bigger, more fundamental problem is with hospitals themselves. The existence of an actionable insight, says Dr. Abernethy, “doesn’t mean you have the resources, bandwidth or team members that know what to do with it. We are all going to have to figure out how to change practice in order to continuously integrate learnings from data.”

Looking ahead, she warns that we are asking doctors to act in completely new ways: “By 2020, the hope is that a doctor can take your personal attributes—age, co-morbidity, biomarkers—and combine that with what we know about management at scale to figure out exactly how to take care of you in a completely customized, instantaneous fashion. We don’t have technology solutions, data, health systems and doctors coordinated and ready to do that kind of work. If we bring technology along so quickly that it is our expectation it will be used, without figuring out how to align the pieces, we may overwhelm things.”

A handful are starting to make the transition. Mercy Health in Cincinnati has taken advantage of Explorsys—an analytics based system based on EHRs from multiple American hospitals to aid with diabetes management—to help improve comprehensive management scores for the condition by 11% between 2013 and 2015.5 At a more general level, Geisinger Health Systems is using analytics to determine optimal

5 “Hospitals use big-data platform to improve care,” Modern Healthcare, 22 August 2015, http://www.modernhealthcare.com/article/20150822/MAGAZINE/308229976

“We are now at the point where there are examples of how it [data] can be made actionable.”Dr. Amy Abernethy, Chief Medical Officer,

Flatiron Health.


treatment choices in a wide variety of areas and to find the best places to intervene at a population level.

The vast majority, though, have not yet begun this part of the change toward using analytics well. Their difficulties should not be surprising. Professor Rebitzer notes that “a big general-purpose technology, like analytics, often takes decades of innovation before we figure out what it is good for.” What sets healthcare apart from other fields, he adds, is that it has lagged in investing in analytics. If hospitals are not going to be late for another revolution, they will need to work through the barriers as they use data to reinvent care.

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This article was written by The Economist Intelligence Unit and sponsored by Prudential. For more information call Prudential Retirement at 1-800-353-2847 or visit www.Healthcare.PrudentialRetirement.com.