The massive pressure to reduce the costs of healthcare delivery has created foundational shifts in the industry.
In particular, changes in risk and payment structures, first piloted by the federal government and now being mandated by private payers, require providers to assume additional risk as part of a financial rebalancing equation. Instead of a fee-for-service system, healthcare providers are becoming responsible for taking care of all the patient’s needs for a period of time: value-based care.
More than ever, providers need to work smarter to stay ahead of competition and control costs without sacrificing quality healthcare.
Fortunately, due in large part to requirements from The Affordable Care Act, the industry is becoming digitized. Hospitals and health systems now sit on a treasure trove of data that can validate critical decisions related to improving quality of care, evaluating performance, lowering costs, and driving patient satisfaction and safety. By tapping into knowledge hidden in this increasingly complex digital environment, healthcare providers have an opportunity to make smarter decisions.
That said, healthcare is a relative “newbie” to the data-driven age. There remain significant roadblocks to hospitals’ ability to use data effectively. For instance, multiple information systems collect massive amounts of data, which is fed into an ever-increasing number of decision support systems and dashboards. And, there are few controls around the data. A proliferation of reports makes finding the right data difficult.
More important, the data informing those reports is not always understood—or trusted—by the people who rely on those reports to make decisions. There’s significant confusion regarding what the data means, and how it’s collected. Consider the term “length of stay.” Depending on the department, the definition of the term varies. Without a common definition, it’s impossible to evaluate data from a quantitative perspective or even know if it should be compared.
This is a challenge the industry needs to quickly address given the volume at which healthcare data is growing. At 48% annual growth, it is outpacing the 40% growth rate seen across most industries.
Data governance is necessary to ensure that the growing volume of data - clinical, regulatory, operational an administrative -- can effectively be turned into actionable information. It provides a framework to quantify and document what the data is intended to measure or clearly define. By establishing the data’s context and integrity through data governance initiatives, organizations can begin to trust the data to make decision that will support operational, clinical and financial goals.
While the benefits of data governance are clear, getting started can seem like an overwhelming proposition. There isn’t a singular starting point for governance, however, a few areas have proven to offer a lower barrier to entry with high success, and are worth considering:
Deploy an Enterprise Report Catalog. Set up a catalog that creates a single place to find the best reports and information available. Providers are awash in reports, from both applications vendors and their own analytics teams. A greater number of reports, however, hasn’t resulted in better answers or ensured that users can find the reports that currently exist.
An enterprise report catalog enables users to find and request access to a wealth of reporting assets. Self-service data users can easily “shop” for the reports they need in the data catalog (just as they shop online through services like Amazon.com). At the same time, these users can help curate reports, bringing the best to the forefront.
Stop Documenting in Excel. Microsoft Excel is a powerful tool, but it isn’t designed for documentation or multi-user collaboration. For many organizations, Excel is the default tool for documenting metadata – definitions, issues, lists of reference data codes, source-target mappings, etc.
Employ tools and approaches that make documentation easy to use and accessible. Documentation is a great source of business metadata, but is only an asset if it is complete and accessible.
Take a Top Down Approach: With so many systems, reports and columns of data, governing all of these assets can take years. Instead of starting with all of data and trying to define all of the terms, take a top down approach and enrich details as demand and resources permit. For example, starting with the key metrics used by executive leadership, provides high visibility and focuses on what’s important. Think about what is most important to business users, not necessarily what exists in technical metadata repositories and systems.
Regulatory, legal, clinical, and technical shifts in the healthcare industry require us to re-think how we’ve been managing our data. Contrary to popular belief, data governance does not restrict access to data. It opens data doors. It’s an enabling technology that provides critical context to enterprise data, allowing more individuals to work with data and glean insight that will help organizations meet critical cost-cutting goals while providing outstanding patient care.
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