What Should We Be Doing with EHR Data?
By: Karen Knecht | April 14, 2015
U.S. hospitals and physicians have made significant progress in adopting electronic health record (EHR) technology since the inception of the federal EHR incentive program. According to the Robert Wood Johnson Foundation, at least 58.9% of all hospitals and almost 50% of all physicians had a basic EHR in 2013. As the broad range of disciplines in the provider community continue to become more engaged with HER technology, progress has been made not only in collecting data and automating workflows, but we’ve also seen the EHR data
help enable some early decision support functions such as concomitant medication checking and drug-allergy checking as well.
However, as indicated by this report as well as by other industry analysts, there is much more work to be done. To date, there has not been a significant focus on transforming the data to gain insights on clinical performance, clinical quality and patient outcomes. Hospitals and providers need to begin to use this digital foundation to drive demonstrable value for their internal stakeholders as well as externally across the ecosystem.
The wealth of real-world data stored in EHR systems can have a tremendous impact on current and future biopharmaceutical research as well. It can inform processes, policies and training opportunities, offer insights into operational and clinical performance, provide insights into the relative value and outcomes of various treatment approaches, illustrate at an aggregate and detailed level the transitions in the ‘patient journey’ in various diseases, and help us refine and validate our burden of illness and statistical disease models.
Leveraging the EHR digital foundation requires an entirely different analytical process that focuses on gaining visibility into the clinical granularity of the data. But this can only be done if two things occur.
First, data needs to consistently be captured for all real-world outcomes for their patients in a standardized manner. Such data can range from changes (or consistencies) in key health indicators such as weight, blood pressure, or glucose levels, as well as information about the treatment provided, and whether the patient followed the prescribed treatment plan. The more data physicians and clinicians capture on a consistent and standardized basis, the more robust the entire resource of data will be, making it easier for clinician to identify patterns and deviations from the norm.
The second requirement is that we start to examine this wealth of data through the eyes of scientists trained in clinical data analytics -- not through the lens of an actuary trained in balance sheets and financial risk. Applying innovative analytics could simultaneously expand clinicians’ abilities to identify key trends, such as whether physicians are following approved standards for care, how different populations respond to different treatments, and what might cause certain patient populations to respond differently to the same treatments
This combination of data quality and analytical expertise is how we will unlock the value of this patient data, which will further bolster the industry’s ability to follow the best and most productive treatment development and delivery paths. This approach to improved healthcare data management will help industry stakeholders demonstrate value for evidence-based care delivered to their patient populations and care based on performance and economic value of the drug, as well as drug effectiveness in the general population – all of which leads to better market performance, and more effective treatments for the patient population.
There are still many challenges to address in the area of analytics for EHR clinical applications. We need to devise more rigorous structures for how data is securely captured, stored and shared so we can more uniformly translate the data for research purposes. We need to continue to expand the connectivity of these systems through better standards for information exchange, to ensure accessibility for key team members across the industry. And we need to begin to apply the skills of clinical data analysts now to access and analyze this tremendous growing pool of clinical data.
Over the past 10 years, the healthcare industry in conjunction with federal incentive programs have invested billions of dollars to build a network of EHR systems and health information exchanges (HIEs) in an effort to digitally capture healthcare data and begin to share it across broad networks of stakeholders. And while the network is far from complete, a digital foundation is in place that can be used to better understand health outcomes and inform new treatment development – but only if we capture and analyze the data in the right way. The more aggressively we develop the skills to harness these data and the standards to make it uniform, the more powerful an asset it will be for us all.