A CHIME Thought Leaders Roundtable: Using Data Analytics to Change Outcomes and Behaviors
The participants were:
- Scott MacLean, Senior Vice President and CIO, MedStar Health
- Kara Marx, Vice President of IT Applications, Sharp HealthCare
- Kent Petty, CIO, HCA HealthTrust
- Kevin Shimamoto, Vice President and CIO, Valley Children’s Hospital
The four participants represent healthcare organizations that share many goals and needs but differ in size, type, patient populations, locations and cultures. All see analytics playing a role in their efforts to affect costs, quality and outcomes. But to drive change within their organizations they need to change the minds of leadership, with industry partners and CHIME being possible catalysts.
It Starts with the Data
All the participants report having an abundance of data, in some cases going back two decades. But issues like ownership, quality and standardization sometimes stand between that data and meaningful insights that can improve performance.
“Over the past decade, we have become very good at gathering data in our EMRs (electronic medical records) and ERP (enterprise resource planning), but when it comes to using the data to produce actionable insights from analytics, the big question is, where does it fit in the organization?” said Kent Petty, CIO at HealthTrust in Nashville. HealthTrust is a group purchasing organization that serves more than 1,600 hospitals and health systems as well as 43,000 other entities such as ambulatory surgery centers and physician practices. “Does analytics belong in data sciences, clinical services group, CFO, or core IT? Is it just more reporting than data analytics? We are struggling with the maturity to know who owns data analytics, so we continue to have individual stacks of analytics.”
Valley Children’s Healthcare, a pediatric network serving more than 1.3 million children in Central California, is in the process of switching from several EHRs to one integrated system. They have 20 years’ worth of data that has been collected using various protocols and standards – or in the earliest days, no standards. They now must try to normalize the data, CIO Kevin Shimamoto said. “We are trying to determine 1) how good is our data and 2) once we do find it is good data, will we be able to write reports and do other things,” he said. “The tough part is trying to make sure that the data we do have is good so we can utilize it.”
“Like everyone else, we have a lot of data. We need to organize it well,” said Scott MacLean, senior vice president and CIO at MedStar Health. MedStar Health is a $5.6 billion, not-for-profit regional healthcare system based in Columbia, MD, and one of the largest employers in the region. The system’s 31,000 associates and 4,700 affiliated physicians support MedStar Health’s patient-first philosophy that combines care, compassion and clinical excellence with an emphasis on customer service. “Actionable information, knowledge, wisdom coming from the data we have is really where we need to be. Having said that, we are working diligently to change the data into useful applications that we can then operationalize to have different outcomes.”
Sharp HealthCare in San Diego, Calif., has a strategic plan that focuses on enterprise analytics, said Kara Marx, vice president of IT Applications. Sharp has four acute-care hospitals, three specialty hospitals, three affiliated medical groups and other facilities and services. They have an 18-year-old data warehouse and for the past few years have continued to add more data. Sharp continues to modernize in pursuit of a logical data warehouse. Their governance committees are multidisciplinary and business focused. “Analytics reports to IT right now but our business guides all the governance,” she said. “I think that we are in a good place, but we can always move faster.”
Making Data-Driven Decisions
Their organizations see data as a strategic asset that can be used to reduce costs and variability and help them meet the demands of pay-for-performance and value-based care models. All have made progress using analytics to drive change although incorporating more sophisticated analytics remains a challenge.
HealthTrust, which is a partner of BD, has had success applying analytics to help identify variability in costs, quality and outcomes related to medication management. “If you control variations, you start standardizing and cutting costs,” Petty observed. “We look at variability: What was wasted? What was utilized? Why did you use this specific device over another device? We are down to that level in variability.” They deliberately separate data science from IT and keep the clinical data warehouse separate from their standard data warehouse. “When we look at diversion or inventory management or waste inside a procedure, there is a team of clinicians leading those efforts to ensure the highest patient care and best outcomes.”
MacLean said MedStar has integrated what MacLean called “small a” analytics and is working with Health Catalyst to get “capital A” analytics focusing on sepsis, joint replacements and heart failure into the clinical workflow this past year. “The chiefs look at the data and they say this is terrific,” he said. “Operationalizing that to change behavior is where we are at, and of course there are so many more use cases.”
At Sharp, clinicians are comfortable with “little a” basic functions such as alerts. Sharp is partnering with boutique companies to test more comprehensive tools that address a single clinical scenario, such as insulin administration, Marx said. Clinicians trust these narrowly designed analytics. Ongoing evaluation is occurring for “capital A” analytics with clinicians at the table.
Using analytics, the Valley Children’s ITS team developed a program to support the Emergency Department’s triage team to quickly identify patients with serious bacterial infections where the patient needs immediate treatment with antibiotics.
The Big Challenge: Changing Behavior
An analysis of Most Wired data found a wide spread in analytics adoption, Branzell noted. “All of you are doing well but maybe not as well as you want to,” he offered. “What is the thing that will get you from where you are today to where you want to be?”
MedStar is actively implementing EHRs into facilities, which for now leaves fewer resources for analytics, MacLean said. Petty emphasized the need for “governance and data stewardship all around. Has the vendor agreed? Has the physician approved? Was operations engaged?” Marx pointed to change management and data literacy. “First, we are trying to get the governance right and get everybody to agree to the strategic plan, bring everybody up to the same level and then maybe we can start to standardize some of our tools to go faster. But that piece is very difficult to go fast with. There are still a lot of people in data silos. ‘That is my data, don’t touch my data.’”
Industry partners like BD can help, the participants said, with their commitment to understanding the health organization’s operations, the systems they work on and their unique cultures. “Piggyback on the culture I already am trying to drive,” Marx advised. “It might be burdensome to our partners, because every health system is different, but I want them to know me, help me move my needle.” Petty suggested using the deep resources or unique skills from their vendors to help address common disruptors, citing drug shortages as an example. “Can our vendors help, with predictive analytics, to derive insights to those items that will impact or disrupt the delivery of healthcare?”
CHIME, with the ability to bring leaders from industry and provider settings to the table, might provide a venue that would help individual healthcare organizations and the healthcare industry as a whole leverage analytics to improve health and care. The thought leaders said CHIME’s Opioid Task Force is a case in point; the task force’s volunteer membership includes industry representatives – some from competing companies – and CHIME members who are working together to tackle the opioid epidemic. “When we get minds together,” Petty noted, “all of a sudden tough problems start to get manageable and understandable.”
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