Value-Based Care and Healthcare Data Management

“As we become more data-driven in our decision-making, people will begin to see the value in putting high-quality data in. Healthcare data management is a tool we can use to innovate and better manage the growth and overall costs of the healthcare system.”

Andy Boyd, MD, Associate Professor, University of Illinois Chicago (UIC) College of Applied Health Sciences

Healthcare’s tectonic plates are shifting. One such plate is value-based care, which has healthcare leaders reconsidering how success is measured. An alternative to the fee-for-service model, value-based care ties provider payment to the quality of care provided rather than the amount of care provided.

It’s not a match for every organization, but it’s gaining adoption: private capital inflows to value-based care companies more than quadrupled between 2019 and 2021, and some experts project the value-based care market could reach a valuation of $1 trillion in enterprise value for payers, providers, and investors (McKinsey 2022).

Value-based care represents a fundamental change in the way that healthcare organizations operate. In theory, the model incentivizes efficiency, cuts down on waste, and improves patient outcomes.

But value-based organizations also have to take on more financial risk and get savvy about how to allocate limited resources. Put simply, value-based care models require healthcare organizations to work smarter rather than harder, and that’s where one tectonic plate meets another: in healthcare data management.

Healthcare data management is a major part of any contemporary healthcare organization. Done well, it can lower costs, improve outcomes, and increase health equity—all key needs in value-based care. But healthcare data management is undergoing its own fundamental shifts, with all the challenges and opportunities that go with it. Read on to learn more about healthcare data management and how it intersects with value-based care.

Meet the Expert: Andrew Dallas Boyd, MD

Andrew Dallas

Dr. Andy Boyd is an associate professor in the Department of Biomedical and Health Information Sciences at the University of Illinois Chicago (UIC) College of Applied Health Sciences. He earned his MD from the University of Texas Southwestern Medical School, and completed his postdoctoral work in biomedical informatics at the University of Michigan.

Dr. Boyd’s research focuses on data simplification to improve clinical outcomes, engaging administrators, researchers, and patients. His recent research succeeded in simplifying the transition for International Classification of Disease version 9 clinical modification (ICD-9-CM) to version 10 (ICD-10-CM). Over 200 news publications have cited his work, including Crain’s Chicago Business, POLITICO, and Inside Health Policy.

The State of Healthcare Data Management Today

“Healthcare data management in the US in the last decade has undergone a fundamental change, as we’ve finally gotten a supermajority of the providers to digitally collect their data,” Dr. Boyd says. “But the true value of that data has not yet permeated through the entire healthcare system. It’s going to take a while for everyone to transform their work processes to take a data-driven approach.”

Dr. Boyd points to the automotive industry, where manufacturers began putting sensors on every component of the car construction process. It took years to be able to leverage that data in actionable ways. But auto manufacturers are now able to perform extremely targeted product recalls—some that might only target a few hundred cars, but which save lives and lower costs. Capturing the data that leads to recalls also helps them avoid recalls in the future.

Roughly speaking, the healthcare system’s version of a recall is the hospital readmission, where a patient who has been discharged from a hospital is readmitted within a particular time frame. In 2018, there were a total of 3.8 million adult hospital readmissions within 30 days, with an average readmission rate of 14 percent and an average readmission cost of $15,200 (AHRQ 2018). Lowering readmission rates is in everyone’s best interests, and it’s particularly crucial in a value-based care organization.

“With good data management, you can better understand what contributes to patients getting readmitted to the hospital,” Dr. Boyd says. “Some patients need more care, and others don’t. No health system has enough money to send the equivalent of a concierge for every patient who leaves a hospital. But how do you target limited resources to the patients most likely to end up back in the hospital?”

Opportunities and Challenges in Healthcare Data Management

Effective data management is about the sharing of data to help make better informed, lower cost decisions. But data collection has been, and remains, too physician-centric. The future of healthcare is team-based and collaborative: nurses, nurse practitioners, pharmacists, physician assistants, physical therapists, and medical laboratory scientists all have valuable roles to play in data collection and analysis. In many ways, that future is already here, but the data collection aspect has yet to catch up.

“We have historically leveraged physician data because it’s easy to get to,” Dr. Boyd says. “One of the top data challenges from a system point of view is how to leverage all the other health professions to make better-informed decisions. This is a team sport. “You need everyone playing and passing the information to one another.”

Another challenge in healthcare data management is data quality. An issue in every field, it comes with its own unique challenges in healthcare: care providers are care providers first, focused on the needs of the patient; record-keeping has always been a distant priority in comparison. But making data collection and analytics simple and intuitive can create a virtuous cycle within a value-based care organization.

“As we become more data-driven in our decision-making, people will begin to see the value in putting high-quality data in,” Dr. Boyd says. “Healthcare data management is a tool we can use to innovate and better manage the growth and overall costs of the healthcare system.”

The Future of Healthcare Data Management

Talk about the future in any sector tends to move quickly toward AI and automation, whose effects can be exponential. Autonomous medical coding is indeed catching on in some areas of healthcare. While still in its early stages, some experts have drawn comparisons between it and the state of electronic health records (EHR) in the early 2000s. But data privacy and reliability questions mean that the healthcare sector will be more cautious than others in adopting experimental AI-powered solutions.

The near future for healthcare data management involves leveraging patient-reported outcomes. Just as allied health professions are important data sources, so are the patients themselves, empowered by a greater healthcare knowledge than past generations and a suite of fitness-related wearable technologies. Patient-reported data allows providers to monitor how a patient is moving after a hip replacement, for example, allowing them to catch any issues before they become costly or harmful. Proliferating patient questionnaires and studying responses can also help providers detect tangential issues early: i.e., asking about smoking cessation or depression, and providing patients with options.

“Keeping patients informed about what their choices are, and the implications of their choices, is a critical aspect,” Dr. Boyd says. “At the end of the day, all of healthcare is about patient choice.”

As the vastness of America’s healthcare data gets put under the metaphorical microscope, health informatics professionals can derive more actionable insights. Healthcare data will tell value-based organizations the story of how to reduce readmissions, increase medication adherence, and help patients make healthy choices. Healthcare itself can become more personal, more effective, and more equitable.

“We’re just in the beginning, worldwide, of this data collection and optimization,” Dr. Boyd says. “We will have some quick wins. We’ll have some successes, but healthcare is conservative, and it’s a very deliberative process that’s going to take some time to realize the true value of all this investment.”

Matt Zbrog
Matt Zbrog Writer

Matt Zbrog is a writer and researcher from Southern California. Since 2018, he’s written extensively about emerging topics in medical technology, particularly the modernization of the medical laboratory and the network effects of both health data management and health IT. In consultation with professors, practitioners, and professional associations, his writing and research are focused on learning from those who know the subject best. For, he’s interviewed leaders and subject matter experts at the American Health Information Management Association (AHIMA), the American Society of Clinical Pathology (ASCP), and the Department of Health and Human Services (HHS).