By Richard Gliklich, CEO, OM1 – Published in FierceHealth Executive Report

The term big data elicits many different responses from the healthcare community and skepticism runs high among many clinicians and hospital executives. While big data alone can’t transform care, it is rapidly becoming the cornerstone of a fundamental change in the way we practice medicine, from anecdotal to evidence-based, and soon, to data-driven precision. Through the “personalization of big data,” healthcare providers can make care more relevant for the individual patient, while improving both clinical and financial outcomes.

The movement to precision: As consumers, we are surrounded by big data being used to predict or to determine everything from what we may want to buy to whether our credit card numbers have been stolen and misused. By combining those same predictive capabilities with very large healthcare data – from tens or hundreds of millions of de-identified patients – we are able to drive more informed and impactful decisions at the population health and now, the individual patient level.

Benchmarking and optimizing care: Think about the data you are already collecting. Now imagine the possibilities if you could measure benchmark and compare your patients’ clinical and financial outcomes against large numbers of similar patients from similar practices or institutions in your region or nationwide. In every industry, accessing benchmarking data is the first step in the road to optimization and improvement. Big data can serve as that yardstick in your organization – whether it’s for understanding your costs, event rates or patient reported outcomes.

Predicting outcomes, avoiding complications or penalties, choosing the best interventions: Just as in online sales or banking, the power of big data and artificial intelligence in healthcare is in the ability to predict what might or likely will happen with an individual patient at a given point in time. The accuracy of these insights improves significantly with big data and informs better decisions by both providers and patients. For example, knowing the reasons that a specific patient has a
high likelihood of a complication or readmission before an intervention enables the provider organization to take actions that may mitigate that risk. Similarly, knowing the probability of a particular outcome for an individual patient prior to initiating a new treatment can better inform the doctor-patient conversation.

Big data technologies in healthcare will never replace a clinician’s knowledge and experience, but it can complement and augment it in ways we would never had imagined even five years ago. Like most new technologies, the first use cases are those focused on the highest potential return on investment. A single avoided readmission following an orthopedic procedure avoids more than $10,000 in potentially non-reimbursable costs. A single avoided bounce back to the ICU following cardiac surgery might avoid more than $60,000 in additional costs.

Technology overload: The adoption of electronic health records has been tremendously important for healthcare. However, it has also created logjams in many organizations for new technologies as those systems are being rolled out. But that should not prevent innovation. Just like the text that comes to your cellphone when a bank system identifies potential credit
card fraud, big data technologies in healthcare can run behind the scenes in the secure cloud and integrate through existing systems only to the extent that they are needed to inform the right people at the right time. Where EMRs laid the groundwork for enabling patient care in a digital world, next generation AI and predictive analytics using big data will drive that care to be increasingly more precise and impactful for the individual patient while improving costs and outcomes.

Source: FierceHealth Executive Report, March 2017