Kyruus Blog

2018 marked a year of disruption across the healthcare landscape. From the entrance of new players, like Amazon, JPMorgan and Berkshire Hathaway, to the mergers of prominent health systems, like Mercy Health and Bon Secours, organizations across the space were driven by a desire to meet consumer expectations for a more connected, patient-centric experience.

Analytics are becoming increasingly important in healthcare: marketers use it to optimize their campaigns, population health researchers use it to identify at-risk populations, and physicians use it to decide which drugs to prescribe. However, with healthcare organizations and patients generating so much data, it’s sometimes impossible to make sense of it–or make the data actionable. In fact, the amount of health information produced is doubling every three years, and by 2020 it is estimated to double every 73 days.¹ And while the quantity of data is intimidating for most, it also offers health systems an opportunity to drive change, especially to improve patient access.

As the healthcare landscape continues to evolve and patients seek out convenient and affordable care, being able to leverage existing data will be critical to expanding access to care and maintaining patient loyalty. Here’s how to use your data to lay the foundation for enhanced access:

There are so many digital marketing metrics to track, it can leave marketers with a serious case of TMI. Having too much data is overwhelming and looking at the wrong data is a waste of time. The key is to find the data that illustrates the new website visitors you’ve acquired, but also shows opportunity for meaningful optimizations. That raises the question: what metrics matter most for your hospital or health system?

Our nation's healthcare system suffers from a mismatch between patient demand and provider supply, something that we refer to as the "Patient Access Paradox". Almost everyone has had a personal experience with the problem of long appointment wait times, which range between 3 and 30 weeks across the country for both primary and specialist care. Yet at the same time, our hospital clients experience as low as 50-60% physician productivity, struggling to "unlock" the capacity that is buried somewhere in their provider networks.

Thanks to their star player, Johns Hopkins’ pancreatic surgical team has a batting average of .980. This is no small feat.

A health system CEO once told me that anyone who tells you she knows what “population health management” means is lying. While I wouldn’t use similarly strong language to make that point, I have had many conversations with health system and health plan leaders about “population health management”, and through those conversations have come to understand that we do not nearly have a uniform definition of what the term even means. The absence of a uniform definition for population health management can be attributed to market variability, i.e. my population is different from yours, and therefore implies a different approach to managing it.

Rapidly advancing technology is enabling the production and consumption of healthcare data in a way not previously possible. With so much at stake in medicine, can Big Data help us decide on the “right” doctor to meet our medical needs?

In the event of a medical illness, we all want to feel that we will get to the “right” doctor – someone expert in diagnosing and treating our specific condition using the best and latest in medical knowledge. Not surprisingly, there is a large and growing body of evidence suggesting that the “right” doctor for a given patient is the one with the appropriate training and clinical experience in that patient’s condition. This is particularly true in specialist care where procedures are more common and conditions more narrowly defined.

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[Originally posted on O'Reilly Strata Blog]