Why Daily Clinical Analysis May Be A Game-changer In Patient Outcomes
By Benjamin Yu, MD, PhD
Benjamin Yu, MD, PhD is vice president of medical informatics and genomics at Interpreta of San Diego, CA.
A missing piece in population health is real-time data and its real-time and continuous analysis. It’s a key ingredient that can help streamline health delivery, improve outcomes, and manage a dynamic patient population. Real-time interpretation is a keystone in many service industries, especially finance and e-commerce. However, its value is often overlooked in healthcare.
Instead, the health industry typically relies on monthly or quarterly business reports to spotlight health needs (e.g., gaps in care, medication management, etc.) and to find regional deficiencies. Using this information, groups plan and carry out campaigns to target and improve care through a variety of outreach mechanisms such as care managers, call centers, and provider network contacts.
However, during the laborious process of assessing static reports, millions of conditions change. It’s analogous to using turn-by-turn instructions for driving based on outdated information. Normally, turn-by-turn directions help the driver navigate through unknown roads and emerging traffic conditions in real time. However, if the system is not current, it might alert the driver long after he/she has missed a turn.
Similarly, in healthcare, by the time an outreach takes place, the member’s medications may have changed, a new refill may have been missed, a vaccine or screening may have been completed without the knowledge of the campaign, or a patient could have become ill or hospitalized before discovery of his/her risk. Thus, in addition to being expensive, the discover-and-campaign approach can be disjointed and too slow to adapt to the ever-changing landscape of a patient population.
Despite their potential benefits, real-time clinical solutions have been hampered in population health for several reasons. Many groups fear that real-time clinical data means too many alerts. While this may be true of some clinical information systems, it is not inherently true. In fact, the opposite may be true in that one of the major efficiencies provided by real-time data is reduced noise.
Because data is up to date, resolved issues should quickly disappear from the clinical workflow. For example, when a health plan calls a patient, instead of reviewing a long list of care initiatives — many of which are already complete — the clinician or plan can focus on future needs that are of the highest priority. Using up-to-date information ultimately can reduce alert fatigue and provide a more satisfying and impactful patient experience. In summary, real-time analysis is a noise reducer.
Indeed, the fear of ‘too much information’ often stems from the design of current health information systems, which rely heavily on clinicians and staff to sort through printouts, inboxes, notifications, and data reports to resolve issues in the clinic. Notably, real-time data should not be considered synonymous with an increase in graphs and decisions. Using the driving analogy, data is constantly changing in a turn-by-turn application. However, these applications natively interpret incoming data and only alert the user with upcoming turns or changes to the route. With respect to healthcare, real-time systems also need to be designed to interpret real-time data with actions and prioritizations of the clinician in mind.
The value of real-time data is underestimated. While some inherently accept that real-time clinical information is better than outdated information, real-time data and its immediate interpretation impacts far more than today’s era of business reports. Real-time data and analysis enables feedback interactions and behavioral modifications that cannot be derived from periodic reports.
In the consumer market, real-time responses enable end-to-end services such as ride share, routing, and many financial transactions. In healthcare, real-time clinical information enables better predictive technology and thus an ability to identify trends much earlier. In an increasingly connected world, new clinical services and technologies require instantaneous feedback and timely actions for members and users, enabled by real-time clinical information. If the rapid growth of consumer health devices like wearable monitors is an indicator of upcoming trends, real-time clinical data in population health is just around the corner. Leading healthcare institutions and technology providers need to make sure they don’t miss the turn.