Long Live the EHR!
Guest post by Ellen Derrico, director of global market development, life sciences and healthcare at QlikTech.
Electronic health records (EHRs) are getting a lot of attention these days, but amid the hype there are skeptics out there arguing that the EHR is old news. However, I’d like to argue that the EHR is not dead; in fact, it’s growing up.
Today’s EHRs are so much more than a digital version of a paper chart. They are evolving and getting more sophisticated. One of the most promising and exciting developments of this is the integration of data discovery and analytics to analyze and compare EHR data. Where business intelligence (BI) was once used primarily to analyze data from a business perspective – revenue cycle management, finance, supply chain management – it’s increasingly being used to analyze patient data, physician performance, facility and utilization – all to improve clinical outcomes.
In healthcare, data discovery and analytics offer the possibility of improving patient care by synchronizing the resource planning with patient logistics and allowing physicians and nurses to focus on improving performance. With BI technology medical practitioners can look across data from different people and locations to support decision making not only for their individual patients, but also for larger patient populations. As a result, practitioners can improve patient outcomes and population health.
A great example of this comes from one of our QlikTech customers, Nemours Children’s Hospitals. Nemours is sharing physician and nurse performance data from EHRs with the physicians, nurses, their pediatric patients and their adult caregivers. The increased visibility is creating a culture of high-performing healthcare teams, as well as improved patient satisfaction and outcomes. For the first time, physicians and nurses are getting feedback from the data systems that they have been entering data into. And their patients are benefiting from less wait time, more smooth care transitions and a better experience.
In addition to improving care, as data analytics become more integrated into health records and information systems, we’re also understanding their value and necessity in positively affecting patient outcomes and meeting government standards. Take for example, the meaningful use requirements of the Affordable Care Act and especially those required for Stage 3. In Stage 3, providers must show:
- Decision support for national high-priority conditions
- Patient access to self-management tools
- Improvements to population health
With a powerful data discovery solution and the ability to do analytics on “big data,” such as population data sets, health records and claims records healthcare organizations can reach compliance faster, improve quality of care, provide decision support and enhance care provided to populations over time. In fact, we are already seeing leading Accountable Care Organization (ACO) pioneers, like Allina Health, capitalizing on this by investigating the use of analytics to determine the effect of different clinical pathways on patient populations and to show the value for reducing care variances by measuring and analyzing patient outcomes.
Looking ahead to the next era of EHR maturity we are seeing that data analytics can actually help improve outcomes and save lives. Insights gleaned from the meaningful use of patient data can show trends in population health, guide decision support for national high-priority conditions, and empower patients with information about their own health.
In addition to Nemours driving improved patient outcomes with analytics, Colchester Hospital University, part of the NHS in the UK, and University Hospital Tubingen in Germany have improved operating room utilization and reduced patient wait times. At Colchester, they have driven down the mortality rate by 158 less deaths in their first year of using new data discovery solutions. At University Hospital Tubingen, they have reduced inefficiencies and increase operating room availability by two full days on a five-day operating schedule in two years, and gained one full day within six months of using analytics to drive their most critical processes. Since utilizing data discovery and analytics, they were able to give life-saving operations from 200 to 300 additional people per year in just one facility.
It’s easy to see the value of EHRs when you look at their potential to unlock lifesaving insights. When data analytics solutions are integrated into the EHR, it creates an environment where any information can be rapidly accessed, analyzed, and viewed exactly as needed, improving response time and thus patient outcomes. And this can often times be a matter of life or death.
So when asked if the EHR is dying, I for one strongly disagree. From my point of view the EHR is still in its adolescence and I certainly look forward to seeing it grow up over the years to come, saving lives along the way.