How Fit Is Your Healthcare Data?
Guest post by Michelle Blackmer, director of marketing, healthcare, Informatica.
Several weeks into the New Year, our fitness resolutions are still top of mind. Whether tracking calories or steps, we are asking ourselves questions like “how many pounds have I lost?”, “how many calories did I eat?” and “how many steps did I take?” To take the guesswork out of it and to hold ourselves accountable, many of us put a Fitbit, Nike Fuel or Jawbone on our wish lists. Our physical fitness has become data-driven; these devices create data that provide insight, enable us to visualize patterns and generate millions of bytes of data, which helps account for the anticipated annual 40 percent growth in big data. However, this is only the tip of the iceberg for data-driven healthcare.
Health information leaders must continue to assess their business resolutions and take stock of their healthcare data fitness. This is especially important since an alarming 40 percent of healthcare executives gave their organizations a grade of “D” or “F” on their preparedness to manage the data deluge. What’s more is that none felt their organization deserved an “A.”
Successful transformation to value-driven care requires an investment in enterprise information management. However, healthcare organizations are tightening their belts and bracing for the hit to their bottom lines in response to the health reform law that took effect on January 1, 2014. Instead of scaling back, healthcare organizations must invest in the fitness of their data. After all, if the wrong data is analyzed (i.e., inaccurate, incomplete, missing or even unnecessary), organizations are going to make the wrong decisions. What is the cost of making the wrong decision?
Assess your data fitness. Ask yourself the following questions:
How are you making legacy or M&A data available from within new applications?
When the largest children’s hospital in the U.S. was implementing a new EHR, it knew it had requirements for historical data access, including providing clinicians a longitudinal view and supporting access in the case of a legal audit. However, maintenance costs for the legacy EHR would negatively impact ROI goals. Data archiving allowed this health system to retire patient records, retain access for care delivery and regulatory compliance and achieve resource agility. Annual support and maintenance cost savings are anticipated at $2.8 million.
How fast are you able to respond to business inquiries for changes to reporting?
A recent report from Frost & Sullivan predicts that while just 10 percent of U.S. hospitals implemented data analytics tools last year, more than half will do so by 2016, with the goal of discovering patterns and insights helpful for improving treatment and reducing costs. Healthcare organizations need to invest in the data behind the analytics; ensuring that data is clean, safe and connected will improve the quality of the decisions made.
What types of device data are you incorporating into analytics?
Ninety percent of hospitals use six or more types of devices that could be integrated with EHRs. Yet, only one-third of hospitals integrate any medical devices with EHRs, and those that do, usually integrate only three types of devices. Improving interoperability between medical devices and EHRs in hospitals could save more than $30 billion a year while improving patient care and safety.
How are you incorporating unstructured data into applications and analytics?
Of the 1.2 billion clinical documents produced in the U.S. each year, approximately 60 percent contain valuable information trapped in unstructured documents that are unavailable for clinical use, quality measurement and data mining. Advancements in natural language processing automate discovery within unstructured data like clinical notes and discharge summaries. By converting unstructured data to structured data, NLP enables this data to be included in analysis; resulting in more informed decision making.
How secure is your data? Is production data being used to test new applications and analytics?
In Q1 last year, 874,667 total records were exposed in data breaches as reported by the Identify Theft Resource Center. Keep your healthcare organization off the wall of shame. The reality of working with data today is that data is on the move – moving from one server to another, to flash drives and to personal laptops. People are human, and mistakes happen. Healthcare organizations can minimize risk via data masking. Data masking reduces exposure by de-identifying data for safe internal and external sharing.
The time is now to treat data as an asset and realize its dividends – the cost of not utilizing data is too great to ignore.