For reasons obvious to all, I want to start by taking a look at information security. This year, security has been a major focus for every part of the healthcare system following a number of high profile ransomware attacks against hospital systems and healthcare providers. CIOs and CISOs already had their hands full with cyberattacks aimed at exfiltrating Protected Health Information (PHI) and patient records, so these highly effective attacks that can take an entire facility off-line are definitely an unwelcome addition.
Some healthcare organizations have moved very quickly to embrace advanced, predictive analysis vectors to identify breaches before damage can be done, moving organizations from a defensive to an offensive security posture. But IT leaders aren’t stopping there – they’re also looking at how to mitigate the impact of an attack at the level of infrastructure design. With the ability to create snapshots or backups every hour, or even every 15 minutes, of a complex data environment, ransomware loses some of its menacing impact. Where healthcare organizations once had to wait for hours and perhaps days for a complete back up and recovery of both clinical and insurance/payer data, it now takes minutes. So rather than losing hours, if not days of patient data (or paying a hefty ransom) disrupting patient care and likely compromise patient outcomes, the data is backed-up and available without disruption.
Beyond information security, one area of healthcare IT innovation that has a direct impact on patient care is the ability to use data and predictive analytics tools to derive meaningful improvements in outcomes. Recently, I was part of NetApp’s annual Advisory Board meeting where C-level executives from healthcare organizations around the country share their challenges and we brainstorm ways emerging technologies can drive solutions.
During this meeting, one of our keynote speakers, Damian Mingle, Chief Data Scientist for WPC Healthcare, discussed how WPC Healthcare, developed a system that provided early identification of a patient’s susceptibility to sepsis. By collecting demographic data at the point of registration, several hours before post-admission clinical observation would begin and that data would typically be collected, caregivers had early alert to at risk patients. The system was able to reduce mortality by a little over 30 percent per sepsis patient, with identification of those patients occurring 4 hours earlier than through clinical methods alone, and reducing these patients’ length-of-stay by 3 – 6 days. These are tremendous improvements in the treatment and outcomes of a costly and prevalent disease process, with many of the improvements made through analysis based upon easily obtainable demographic information.
There are undoubtedly many interesting developments, twists, and turns awaiting those of us in the healthcare field in the coming year. What’s important to remember when thinking about investing in backend solutions is to be able to explain the value, not just in terms of benefit to our teams, but the benefit it brings to all key stakeholders, the most important of whom are the patients.
A version of this article also appeared on Future Healthcare Today in December 2016.