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Find out what’s a barrier to entry for healthcare marketing analytics, as well as what these institutions are hoping to learn and gain from big data.
Operating in a highly regulated environment with complex compliance and security requirements, the healthcare sector historically lags behind other industries when it comes to technology adoption, and marketing analytics is no exception. Instead, the focus in medicine has been squarely on technology that directly relates to healthcare and how it can affect positive outcomes in patients.
This is slowly changing, as hospital networks and other medical practitioners begin to more earnestly compete for market share. Healthcare marketing departments approach market share issues in two ways: by identifying prospective patients who are most likely to need the healthcare services they provide, and by ensuring these customers stay within their institutional networks once they become patients.
“We are seeing a growth of interest in demographics analytics in healthcare,” said Matt Elson, a senior vice president for Evariant, which has developed a healthcare CRM platform that combines digital marketing solutions, big data, and analytics. “More of our healthcare clients want to be able to both manage and monetize big data,” he said.
Elson said that one barrier to entry for healthcare marketing analytics is that developing these analytics must be a task that end business users can do — without having to enlist the help of an IT data analyst, or even a data scientist. “If you are a vendor in this business, you have to be able to ‘abstract’ big data in ways where the end user can work with the data without having to know the technical intricacies,” he explained.
“They want predictive analytics derived from big data that can help them to better understand consumer behaviors and patterns in their service areas so they can determine which of their services is most likely to be in demand for certain demographic segments,” said Elson. This might mean determining if there are certain demographic profiles at high risk for diabetes that might need preventive or treatment care. In other cases, analytics can be employed to assist hospital personnel in keeping add-on revenues within the institution by measuring which doctors regularly make referrals out of network where these add-on revenues are lost — or even preventing costs by identifying patients who should be reached out to for preventive care, which in turn can lessen visits to the ER.
There is also the “payback” side of every marketing campaign. In other words, if you invested one million dollars in a marketing campaign, did you derive more than one million dollars in revenue from the campaign?
This excerpt is from the Tech Republic. To view the whole article click here.
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