Your healthcare data is a valuable asset. It allows clinicians to be proactive in providing care while improving outcomes and patient satisfaction. The recent shift from fee-for-service to value-based pricing has forced the industry to take a deeper look into healthcare data to derive meaningful insights from it.
Healthcare data is crucial to enhancing patient care. Complete and accurate records can mean better diagnoses and treatment as well as improved services. However, most healthcare data remains largely untapped, living at the point-of-care where it was first created in the form of free-text or semi-structured documentation. Approximately 80% of healthcare data remains locked in this unstructured format, lingering and simply taking up space while providing little to no value.
How can we improve healthcare without a complete view of the patient record? How can we predict hospital readmissions, ICU stays, medication compliance and adherence without intelligent healthcare data?
To gain more insights into these challenges, we spoke with Kyle Silvestro, CEO at SyTrue, and recognized thought leader in data-driven healthcare and clinical intelligence. Silvestro outlined five different aspects about your healthcare data that you probably never suspected.
1. Healthcare Data Will Only Get More Complex
Healthcare data will not get simpler in the future. Its complex nature calls for untraditional approaches. It needs to handle multiple sources: hospitals, offices, clinics, and even pharmacies, just to name a few. Data can be structured and unstructured, inconsistent, high volume, and variable in an ever-changing regulatory environment.
Without interoperable technology in place to manage and analyze this data, much of its value will be lost. With the complex nature of medicine today and much of the information trapped in separate “silos”, medical records are left incomplete and inaccurate. With error rates rising, it is even more important for patients to become their own health advocates, demand access to their health data and empower themselves to improve their health.
2. Data Errors Continue to Get Into the Medical Record & Analytics Trail
At the point of care, as ICD (International Classification of Diseases) codes get assigned to cases, their error rates can range anywhere from 20% to 50%. The inaccuracies may come from patient behavior, the record trail itself or from the provider or physician. But errors do seep into the record; a stroke can be labeled a “cerebrovascular accident,” “cerebral occlusion,” “cerebral infarction” or “apoplexy.” Which is right? Does it make a difference?
Nonetheless, data errors continue to be included into the medical record and analytics trail. Additionally, inaccurate diagnosis and recording errors could well be compounded by the medications and treatment used. So when it’s time for using data to generate insights, the problem of “garbage in, garbage out” makes it almost impossible to get useful information.
3. Healthcare Data Fails to Reach Full Potential due to the “Human Problem”
Each year, physicians create approximately two billion clinical notes and reports each year (some of them even legible). That’s 95 new notes every second, or eight million new notes a day. Organizations don’t have a labor force to deal with this kind of volume. It’s not enough just to go through the data; it also has to be extracted, normalized and validated to make it usable.
Typically, outdated technology has been used to capture and normalize data. But in doing so, it eroded the clinical value of the information itself, making it unusable outside of coding for billing workflows. Until hospitals and healthcare organizations adapt new technology that can transform vast amounts of data into real-time analytics at the point-of-care, mistakes will be made, reports will go overlooked, and patients won’t get the timely care they deserve.
4. Critical Findings Are Still Not Reported in a Timely Fashion
Back in 2002, the Joint Commission, an independent body that accredits and certifies tens of thousands of healthcare organizations and programs in the US, established its National Patient Safety Goals program. Among other things, the program requires the timely reporting of critical results, including those rendered by diagnostic imaging services. Thirteen years later many organizations still do not have automated notification systems for relaying critical findings. That means manually reviewing a large number of radiology reports to demonstrate compliance. This process is time-consuming, inexact, and prone to error.
Failure to communicate in a timely and clinically appropriate manner is one of the main reasons why radiologists are being sued. Patients find themselves anxiously waiting for a phone call hours and sometimes days after reports have been read. This is especially frustrating when they identify a critical finding and didn’t respond in a responsible timeframe. Time is of the essence when treating cancers and other maladies diagnosed from imaging services. Any delay can cause long-term effects that could have been easily avoided had there been a system in place to automatically notify patients as soon as a radiology report has been read.
5. Healthcare Data Can Actually Be Used to Improve Workflow
The American Recovery and Reinvestment Act of 2009 requires the use of Electronic Medical Records starting in 2014 and dissatisfaction is growing as workflows are destroyed. Many physicians are frustrated by the time consuming task of data entry while still trying to give patients their full attention. These physicians face a difficult trade-off: divide attention between the patient and the computer, or enter data after leaving the patient, lengthening overall work hours. New technology is being developed to alleviate these issues and improve workflow while optimizing patient outcomes. With the correct tools in place, physicians can stop being data entry clerks and go back to caring for their patients, improve services, and optimize outcomes while still complying with Meaningful Use requirements.
Healthcare organizations are starting to make slow changes to improve upon the use of patient data, but integration is slow. Finding technology that is interoperable with other existing systems is also a major hurdle. Health IT has come a long way and solutions currently exist that can help mitigate or eliminate the challenges listed above. The key is the ability to translate unstructured medical data into smart clinical information at the point-of-care, produce accurate diagnoses and codes to prevent errors, transform the vast volume of data into analytics that drive insight, and improve workflow efficiencies.
The bottom line: If healthcare organizations find their way to the correct solution of accurately and efficiently managing patient data, it’s a win for everyone.
This article was written by Robert J. Szczerba from Forbes and was legally licensed through the NewsCred publisher network.