Managing and Leveraging Data for the Next Wave of Healthcare Capabilities

Introduction

Philips convened a thought leadership roundtable with members of the College of Healthcare Information Management Executives (CHIME) to discuss how the current explosion of accessible data is affecting their respective organizations. Chief information officers (CIOs) and other digital health leaders explored the topic through the lens of a rapidly changing landscape brought on by industry consolidation and unprecedented breakthroughs in contextualizing information.

CHIME President and CEO Russell Branzell moderated the roundtable. Aaron Hillman, senior director of marketing for Philips, and Shannon O’Toole, director of marketing, contributed to the discussion.

CHIME members participating were:

Jitendra Barmecha, MD, Chief Information and Digital Strategy Officer, SBH Health System

Steve Eckert, Chief Technology Officer, Cook Children’s Health Care System

Chris Paravate, Chief Information Officer, Northeast Georgia Health System

Beth Patino, former Chief Information Officer, Dekalb Regional Health System

Tressa Springmann, Senior Vice President/Chief Information and Digital Officer, Lifebridge Health

Tanya Townsend, Senior Vice President and Chief Information Officer, LCMC Health

 

Summary

Across healthcare, more data from more sources has become available to the clinical and operational workflows that support patient care. Optimizing the management and use of clean and accurate data is crucial to improving efficiencies and outcomes in new care models.

Roundtable participants, who represented organizations of varying sizes and resources, agreed on the importance of effectively managing growing streams of data. However, in the absence of a data standard, IT and health system leaders are faced with figuring out how to aggregate and analyze all of this data to make it actionable. They emphasized that IT should not be the ultimate “owner” of data. Instead, the focus of IT should be on standardization and ease of implementation for users, typically through a dashboard interface.

 

The state of data management

Every healthcare organization has its own mix of data sources and care models. With no standard for how to pull in data from so many different sources, hospitals and health systems vary in their approach to data management. Additionally, organizational dynamics such as rapid growth bring new parameters to strategic initiatives.

“The adage in healthcare is just get it done, whatever it takes,” explained Steve Eckert, CTO at Cook Children’s Health Care System in Texas. “We’ve done a good job of getting tools in place and making investments. But at the same time, we need data stewardship, governance, and operational ownership of data. IT shouldn’t own the data. We should be there to facilitate its use throughout the organization.”

Indeed, in an era of healthcare consolidation, being prepared for what comes next can help clear a pathway to eventual success. Dekalb Regional Health System, a comparatively small component of a comprehensive academic health system in Georgia, established efficiency in data management prior to its acquisition, according to its former CIO Beth Patino. “Size doesn’t matter,” she emphasized. “We had good data governance, and that gave us the capability to move forward with it.”

At LCMC Health in Louisiana, mergers and acquisitions have accelerated growth, increasing the complexity of data management. “In terms of software, you name it, we have had it,” stated CIO Tanya Townsend. LCMC operates on unified EHR and ERP systems but has replaced hundreds of other applications in the process. As a result, “we’re doing a lot of data archiving just to make sure we have the legacy information,” she noted.

Moving forward, LCMC will concentrate on defining data and mapping the definitions within its enterprise architecture. At the same time, the organization is conducting an inventory of reporting applications to deliver “the right tool for the right user in the right setting,” according to Townsend.

Along those lines, LifeBridge Health in Maryland has established a center of excellence around the data governance process. LifeBridge appointed subject-matter experts in each of its core business units while providing pathways for data self-service. “Data is the new healthcare currency,” said CIDO Tressa Springmann. “Our ability to capitalize on it to help our patients, and to more effectively run our business, is key.”

SBH Health System in New York is also going through a digital transformation, although Chief Information and Digital Strategy Officer Jitendra Barmecha, MD, characterized it as a “digital exploration.” SBH has consolidated applications and systems in advance of a major EHR migration, but still contends with data silos. “We cater to all. Some people love Excel spreadsheets, which they print out and highlight. Others, on the business side, use our analytics tools because they know what they’re looking for,” stated Barmecha. “We would like to push people away from printing and highlighting, and toward using more dashboard tools.”

 

Data governance nuances

Roundtable moderator Russell Branzell, CHIME president and CEO, pressed further on the process of data prioritization and stewardship. “What is your organization’s approach to data prioritization, and who are the data owners and stewards?”

Chris Paravate, CIO at Northeast Georgia Health System, said his organization sets goals that line up with aspirational pillars such as stewardship, quality, and patient experience. “We have metrics for each goal that we want to hit each year and over multiple years,” he commented. “The metrics are based on our data, which the IT team feeds into dashboards. So, from an IT and analytics perspective, it’s all important.”

Springmann described a slightly different approach to prioritization at LifeBridge. “We use the enterprise organizational chart to inform stewardship of categories or cohorts of data,” she noted. “For example, our chief human resource officer is the operational data steward of our employee data — that whole phenotype or domain of data.”

Nonetheless, assignment of data stewardship becomes more complicated in certain situations such as a registration event. “Is that marketing or financial services? When you are capturing contact information, such as collecting email or cell phone information during a registration event, there could be different groups consuming it,” Springmann shared. Further, when it comes to metadata management, data may be known to different groups by the same name, but “depending on where it’s being reported, it might be calculated, stored, and overseen in a different fashion,” she said.

Barmecha, who is a practicing internist in addition to his IT role, pointed out the divergent needs of clinical and financial personnel. “I’ve been in the health system for almost 27 years, and I don’t think one size fits everyone. From the IT standpoint, it’s more about education — moving toward dashboards and predictions,” he said. “The architectural collection or distribution of data fall under IT, but the use cases come from the business side. They guide us on what needs to be done.”

 

Considerations in emerging technologies

On the cutting edge of technology, software vendors are busy integrating artificial intelligence (AI) and machine learning into traditional applications such as EHRs. The aim is to help healthcare organizations with natural language searches and capabilities for summarizing information. Simultaneously, IT departments must prepare for expanded data demands, whether it’s intended for analyzing encounters, procedures, discharges, insurance coverage, or health and wellness tracking.

Barmecha suggested that healthcare’s current best use for technology such as generative AI is in research and drug development. Nonetheless, mainstream use in running day-to-day operations is approaching at high velocity.

“At the end of the day, domain owners will be called upon to surface that data for decision-making,” predicted Springmann. The right incentive structure would make an impact on the leaders who have the most to gain or lose based on the usability of their data, she added.

Those who understand the data from a clinical perspective could also make emerging systems more usable to other clinicians, according to Patino. “Across healthcare, we lack true data scientists who would work hand-in-hand with informatics staff,” she said.

“Sometimes these magical widgets come flying by and they may not really add any value,” Townsend commented. “We need to look at how the data will be regulated to keep our organization safe from breaches and potential lawsuits. There are a lot of gray areas around who owns the data and who’s responsible for protecting it,” she pointed out.

 

Using data to transform the organization

Hospitals and health systems recognize where the future lies. They share the common imperatives of shifting the value model, building a lean enterprise, and funding innovation. At the same time, however, they know that each of these initiatives depends on making wise decisions with clean, accurate data.

Roundtable participants offered the following recommendations based on their respective experiences:

Don’t go it alone. “Make sure you’ve got an operational business partner at your side,” advised Eckert.

Factor in a budget. “With new organizational strategies, IT is often an afterthought or assumed that we have what we need ready to go,” cautioned Townsend. “It’s an investment in terms of people and resources, so financial support is important to consider.”

Use best practices. Problems arise when workflow gets too convoluted, noted Barmecha. “You are not the first organization to create these types of data. Many health systems across the globe have already done it,” he said. Learn from those established best practices.

Bring data ownership to the forefront. “We can get you whatever you need,” remarked Patino, “but we’ll have to make somebody the owner of it.” Springmann agreed, adding, “If you don’t approach it with a federated governance model, you’re going to end up owning it all yourself.”

Rejuvenate informatics. Refocus informaticists from workflow optimization and back onto making data and information standardized and usable. Recommendations included pairing true data scientists with informaticists and establishing the right architecture to facilitate the use of the data.

Take control of challenges. Organizational culture sets the stage for working on the right things, according to Townsend. “We tend to be the gatekeeper of duplicate requests for essentially the same data. We’ll get more alignment by fostering a culture of accountability to standardize and use the data we already know.” Paravate concurred, advocating for support of problem-solvers — “people who are asking a lot of questions and listening to the answers.” Additionally, Eckert proposed adopting the perspective of ambitious thinking supported by deliberate action. “Instead of trying to solve a big problem, break that big problem down into pieces,” he offered.

Target outcomes. The goal for healthcare organizations is to aggregate, normalize, and optimize data — and then use it across all systems. “Pull together the data needed to get to your main objective,” advised Aaron Hillman, senior director of marketing for Philips. “Think about your outcome space versus the solutions needed to get there. That’s the best place to start.”

Support data standardization. Mirroring other industries, the ideal exchange of data requires identifying the data, standardizing the data by type, and standardizing the transport of the data. Industry business and tech leaders working together to establish clear standards everyone agrees to follow would go a long way to improving data exchange across healthcare.

 

Conclusion

Healthcare entities recognize the potential of advanced analytics in support of business and clinical decision-making. However, the industry has long struggled with lack of universal data standardization —the backbone of data exchange — and IT and health system leaders are now challenged to drive better data usage to improve patient care and health system operation efficiencies.

They’ve adopted or are developing data governance models based on organizational structure and strategic goals. Also, they’re taking steps to ensure that data is properly identified and standardized, and that tools are available to users seeking answers to their most pressing questions. Ultimately, as noted by Paravate, organizations can drive toward effective data management by building a culture of problem-solvers.

 

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