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The volume of healthcare data is growing rapidly—indeed, at 48% annual growth, it’s outpacing the 40% growth rate we see across most industries. Data has the potential to help healthcare organizations improve quality of care, evaluate performance, lower costs, and drive patient satisfaction and safety. But for healthcare, this big explosion of data has become a big headache. And that’s bad news in an industry under pressure to improve affordable, value-based care.
Multiple information systems—across the health system and even beyond it—feed massive amounts of data into the many decision support systems and dashboards that healthcare professionals use every day. While healthcare organizations today might have basic data management in place—storage, cleansing, and consolidation—most still struggle with getting good information to the stakeholders who need it. A proliferation of reports makes finding the right data difficult. The data informing those reports is not always understood—or trusted—by the people using those reports to make decisions. And when trust in your data begins to erode, the investments you’ve made in self-service business intelligence tools, data warehouses, big data platforms won’t deliver the expected results.
Data governance is a framework for creating a set of rules, definitions, and processes to help determine who actually owns, manages, stewards, and is allowed to use the organization’s data. It’s essential to providing trustworthy, actionable data to the people who need it to do their jobs. Unfortunately, healthcare has been slow to adopt a systematic, consistent approach to data governance. Most have rudimentary governance structures at best. More often, data processes around are strung together through spreadsheets, meeting notes, extended email threads, and local, onsite experts.
If data is going to deliver on its promises, healthcare organizations need to assure its integrity, lineage and transparency. Good governance establishes context for data and lineage makes visible how data flows across systems, reports, and analytical models. That knowledge increases trust and allows stakeholders to make timely decisions based on accurate information. When we trust the data and outcomes it reflects, we can maximize our analytics to make continuous improvements.
The words “data governance” don’t necessarily bring everyone to the table ready to participate. To get stakeholders energized and engaged, we suggest starting with a project that will demonstrate the value of data governance clearly and immediately: a reporting catalog that makes essential reports easy to find for anyone across your health system who needed them.
Begin by identifying silos of reports that exist across the organization. Inventory those existing reporting assets and have your stakeholders work collaboratively to resolve any duplicate and redundant reports. Get agreement on which reports are needed to answer your most critical questions and then cull your list to reflect that.
Once your catalog of reports is defined, those reports can be enriched with the metadata you need to truly govern them: what data comprises these reports, what is the quality of that data, what has been included or excluded, what calculations and assumptions are being used to answer critical questions?
That is the value of governance. By starting your efforts to deliver tangible value such as building a reporting catalog that reaches across your organization, you are demonstrating the value of data governance and building momentum for your next initiative. And rather than struggling to define the theoretical value of data governance, you are showing it in action: by delivering better, more accurate, and more meaningful reports.
Learn more about how a report catalog can help you wrangle the healthcare data beast.
Chris helps healthcare organizations get more out of their data-driven initiatives by focusing on data governance as a tool for engaging the business and clinical organizations.
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