From data to decisions: Enhancing healthcare outcomes through strategic data use

Healthcare organizations collect an abundance of data each day. Sifting through this data to unlock its full potential is a major challenge. In the series Unlocking Big Data, industry experts dive into strategies to maximize their data’s potential.

In Episode 3, Mary Kuchenbrod, Vice President of Data Operations at Arcadia, and Julius Bogdan, Vice President and General Manager of Digital Health Advisory North America at HIMSS sat down to discuss ways healthcare organizations can make the most of their data.

A blueprint for success with data accuracy

A recent HIMSS Market Insights Survey gathered responses from more than 100 healthcare leaders. It revealed that 80% of them trust that over half of their organization's data is accurate and reliable. Despite this, just over half report utilizing that data for intelligent business decisions. This gap in leveraging information for strategic purposes highlights a significant opportunity. Healthcare organizations can create a blueprint to ensure they make the most of their data.

1. Create neat piles out of messy data

Healthcare leaders have more patient and operational data than ever before thanks to EHRs and other management systems. Yet, turning this massive amount of data into useful insights is a big problem. Healthcare data is often messy and inconsistent. The challenge is not only collecting data. It's about making sure the data is accurate and organized. That way, healthcare providers can use it to make decisions about patient care and hospital management.

To deal with this, healthcare organizations need to create rules on how to handle and use all this data. This includes:

• Setting up common definitions for medical terms
• Making sure everyone enters data in the same way
• Have everyone in the organization understand these rules and why they’re necessary

By treating data as a key resource, healthcare providers can start to manage it carefully. This will help them make better use of the information they collect and improve everything from patient care to how their organization operates.

2. Leverage data trust tactics to improve reliability

Mary Kuchenbrod outlines a two-pronged approach often used in the military and cybersecurity to describe proactive and reactive data management strategies: left of boom versus right of boom. How can you prepare before something goes wrong? How do you address something after it has already happened? Kuchenbrod stresses the importance of preparing for inevitable data issues with robust response plans.

• Left of boom: Proactive strategies
  These are preventive measures taken to avoid problems with data before they occur. This involves automating tasks that are prone to human error, such as data entry, and putting in place stringent checks for new data as it comes in. The goal here is to be as prepared as possible by establishing processes and systems that minimize the risk of data issues arising from manual operations.

• Right of boom: Reactive strategies
  These strategies are about response and recovery — what to do when a problem with data quality or integrity inevitably occurs, given the complex and often messy nature of healthcare data. We need systems that quickly spot data anomalies and contain these issues. This is to stop them from affecting decision-makers. The focus here is on rapid detection and correction to reduce the negative impact on end users. Right of boom strategy also maintains the safety and reliability of the data ecosystem.

3. Collaborate with a trusted data analytics partner

Uniformity in data interpretation is critical to avoiding inconsistencies. Getting a handle on definitions and metrics that you're going to use is a good first step. This alignment not only facilitates clearer communication and more consistent decision-making but also enhances the reliability of data analytics. By converging on a common understanding and interpretation of data, healthcare organizations can better leverage their datasets for strategic planning and operational improvements.

The discussion shifts to the role of vendors in the era of AI and advanced analytics. Vendors are not only providers of technology, but partners in the data journey. This partnership is particularly important in healthcare, where the complexity of data and decision-making stakes are high. Vendors bring a deep understanding of the intricacies of data systems, from inception to analytics to application, which is crucial for maximizing data insights.

The collaborative efforts between healthcare organizations and vendors focus on several key areas:

• Data lineage and lifecycle: Vendors help organizations trace the origin and evolution of data elements, which is vital for ensuring data integrity and understanding its context.
• Contextualization of data: By working closely with healthcare providers, vendors can tailor their systems to align with the specific workflows and needs of the organization. This approach ensures that the data analytics are not only accurate but also relevant.
• Scalable solutions for complex environments: Vendors are instrumental in developing solutions that can scale across the diverse and voluminous data environments typical in healthcare. These solutions often incorporate machine learning and AI to handle vast amounts of data efficiently and with more insight.

Starting with small, impactful projects can build trust in new technologies. These practical demonstrations show how data can be utilized, setting the stage for broader initiatives. Additionally, transparency in how analytic solutions operate is crucial for building trust. Addressing specific, key problems can further demonstrate the value of data analytics.

Extract the most from your organization’s data

As the healthcare industry evolves, admitting what is unknown and being open to adaptation is pivotal. Embracing uncertainty will aid in the ongoing journey to improve healthcare data utilization.

Learn more about how organizations implement these strategies to transform their data into meaningful solutions. Check out other episodes in the Unlocking Big Data series to see how you can get trusted data to healthcare decision-makers.