This site uses cookies that are essential for our site to work. We would also like to use non-essential cookies to help us improve your browsing experience and help make this website better, by collecting and reporting information on how you use our site.

How to better leverage data in healthcare business decision-making

By Lisa Carter, Writer at Arcadia
Updated: July 27, 2023 Posted:
Healthcare Analytics Data Interoperability and Integration Data Management and Quality Unlocking Big Data

Organizations across all industries are recognizing the importance of data in making informed business decisions. The healthcare industry is no exception, where data-driven decision-making has the potential to save lives, improve patient outcomes, and drive operational efficiencies. However, recent research indicates that healthcare organizations are still not fully capitalizing on the power of data when it comes to intelligent business decision-making.

This article explores key insights from Unlocking Big Data, Episode 4 by industry experts Isaiah Nathaniel, Vice President and CIO of Delaware Valley Community Health, Inc., and Jake Hochberg, Vice President of Analytics and Chief Analytics Officer at Arcadia. They share their perspectives on the challenges and opportunities in leveraging data for better decision making based on a recent research study conducted by HIMSS Market Insights.

Insufficient data collection and data trust issues

The research study revealed that only 57% of an organization's data is currently being used to make intelligent business decisions. This seemingly low percentage raises questions about the reasons behind this underutilization.

Jake Hochberg points out one of the major challenges. "People are using so many different systems that are built with different nuances. You’re asking two systems the same question and getting different answers."

Isaiah Nathaniel shares the same sentiment. The first major issue contributing to the low data utilization is trust. "We don't trust the data that's coming out of systems. We have so many disparate systems in all of our organizations. System A may be telling you one set of information. System B is telling you a totally different set, and the criteria are the same."

The lack of trust in data is further compounded by insufficient data collection and asking only the minimum set of required data fields. This often results in organizations only getting a partial view of the complete picture, which limits the potential for data-driven decision making.

The path to increased data utilization

While achieving 100% data utilization may not be a realistic goal, both experts agree that there are actionable steps healthcare organizations can take to significantly increase the percentage of data used for intelligent decision-making.

Nathaniel suggests that organizations can set a standard between 72% and 77% data utilization. To achieve this, he emphasizes the need for collecting more required fields from customers and patients, as well as from employees. By capturing more actionable data, healthcare providers can better serve their patients and make more informed decisions at the point of care.

Hochberg emphasizes that better investment in understanding the nuances of data aggregation across different systems is key to achieving higher data utilization. Additionally, he advocates for a culture shift toward being data-driven from top leadership down to every level of the organization. "The goal is to make sure that when you're making macro-level business decisions, you have data to inform that," he affirms.

Creating a data-driven culture

Leadership plays a critical role in driving the transformation toward a data-driven culture within healthcare organizations. As Hochberg highlights, "The big thing is top-down culture of being data-driven." This means fostering a culture where data is at the core of decision-making processes, and where investment in data platforms and analytics resources is seen as essential for success.

Nathaniel adds that leadership should refrain from making decisions based solely on gut feelings and embrace transparency in data interpretation. Being transparent with data and acting on the insights it provides without judgment is crucial for building trust in data-driven decision-making.

The road ahead: Embracing data interoperability

Both Nathaniel and Hochberg agree that data interoperability is a fundamental component of unlocking the true potential of data in healthcare decision making. Implementing a system framework platform that enables seamless data exchange and integration across the network can significantly enhance data utilization and accuracy.

Data is a powerful tool that can drive transformative change in the healthcare industry. However, the underutilization of data in making intelligent business decisions remains a challenge. Trust issues, insufficient data collection, and the lack of a data-driven culture are among the primary factors contributing to this underutilization.

Healthcare organizations must take steps to increase data utilization, recognizing that achieving 100% data utilization may not be feasible, but significant progress is attainable. A top-down culture shift toward data-driven decision making, investment in data platforms and analytics resources, and a focus on data interoperability are essential elements for success.

By leveraging data more effectively, healthcare organizations can improve patient care, optimize operational efficiencies, and stay ahead in an increasingly competitive industry. Embracing data-driven decision-making will not only benefit individual organizations but also contribute to the overall improvement of the healthcare ecosystem.

View more of the Unlocking Big Data series presented by HIMSS.

Want to continue the conversation?

Check out the Unlocking Big Data companion podcast below or on Apple, Spotify, and Google.