Insight
Building a Data Culture Helps Hospitals Stay One Step Ahead
Managing ever-growing volumes of sensitive data is one of healthcare’s most pressing challenges. To do so, organizations need to change not just their tech stack but also their culture. Before implementing sophisticated digital solutions for healthcare data, consider whether your organization is prepared to evolve how data is collected, analyzed, and used throughout the enterprise.
Organizations equipped for meaningful analytics gain many benefits, including increased operational efficiency, reduced costs, and improved patient outcomes and experiences. The key to success is building a data culture that touches everyone across the enterprise—creating value for patients, providers, and staff.
What Is a Data Culture, and Why Is It Important?
A data culture refers to how an organization uses, values, and integrates data. “Culture is the key word because a data culture impacts everyone and requires a shared understanding of its importance and potential,” said Robyn Whelchel, senior managing consultant at Tegria. Data visualization tools, like MEDITECH BCA, Tableau, and Power BI, are popular because they make analytics more user-friendly and easier to navigate.
However, these tools alone aren’t enough in an increasingly competitive industry. Organizations with a strong data culture are poised to leverage data visualization tools more effectively, supporting departmental collaboration and a holistic view of operations. This approach empowers staff to make data-driven decisions for a more meaningful impact on operations, clinical outcomes, and patient experiences.
Critical Components of a Data Culture
A sound data culture creates a foundation for modern healthcare operations. If your organization lacks any of these critical components, it’s a sign that you have not fully embraced a data culture:
- Data Accessibility: A sound data culture breaks down data silos, ensuring that relevant data is accessible and understandable to encourage efficiency and cross-departmental collaboration.
- Data Governance: Policies should be in place to ensure that data is standardized, validated, consistently updated, and in compliance with regulations like HIPAA.
- Data-Driven Decisions: Staff should be encouraged to make decisions based on data insights versus assumptions or best practices.
- Key Performance Indicators (KPIs): Benchmarks that consistently measure quality, efficiency, and outcomes are essential for ensuring meaningful and continuous progress.
Consider the Big Picture
Hospitals run on data, so many groups within an organization may work with data or reports. However, viewing a singular report or metric without considering the bigger picture can mislead end users. A report might indicate strong performance for a particular metric, but this might not be accurate without combining data to reveal potential weaknesses. For instance, the data might suggest scheduling doctors for 32 daily visits is OK, but how does this affect patient satisfaction if they get only 15 minutes with the doctor?
A recent client of Tegria’s provides a great example. They use an ED fast track to reduce wait times for patients with minor injuries and illnesses. The fast track appeared to perform as well as the regular ED on paper, but a deeper look revealed that the person staffed at the front desk heavily influenced a patient’s experience. This insight prompted additional training and education to create more balance. “Looking at the whole picture is essential to avoid false reports and implement meaningful changes,” advised Whelchel.
Take Key Steps Toward Building a Data Culture
Data visualization tools like MEDITECH’s BCA or Microsoft’s Power BI provide a common ground for discussing metrics, goals, and outcomes. However, these tools will have limited impact unless an organization achieves and embraces a shared understanding of how people will use, share, and interpret the data. To build your organization’s data culture, take the following steps:
1. Ask questions to build the foundation:
- What data do we need?
- What do we plan to do with the data?
- How will we share the data and keep it secure?
- How will we set this up to be successful in the future when we have more people?
- What kind of training and support will we need?
2. Start small, but think big.
Pick a department that already uses and likes data to serve as data champions. For example, Infection Control and Process Improvement touch almost any other area of the healthcare system, so they will help encourage other areas to become more data-focused.
3. Identify your key players.
Every organization should have an executive sponsor who is excited about data. A project champion helps get others on board and minimizes resistance. Informaticists also love data, so make sure they are involved early on. It’s also important to remember that new data practices create a learning curve, and it’s natural for people to get frustrated. A good trainer is essential—someone you can call if you’re stuck building a data set or dashboard.
4. Create your data norms.
When datasets, dashboards, and dossiers are released, some will be in a development or test format. How do end users know if the data is ready? Establishing your data norms, including branding data to signal when it’s ready, fosters shared understanding and collaboration. Some organizations take this further by color coding the data according to year or facility to visualize it more easily.
5. Know what to expect.
Having the right resources in place is essential for a thriving data culture. Resources include data governance, training, and data champions to foster a culture mentality. Commitment from busy leadership can be challenging but is vital for getting others on board. Also, be aware that looking more closely at data can make people nervous, so help them understand that identified issues provide opportunities for improvement. “Building a data culture is a team effort with a willingness to view the data in terms of what is supposed to happen versus what is happening now,” concluded Whelchel.