The McPherson Principle by Duke Michael L.;

Author:Duke, Michael L.; [Duke, Michael L.]
Language: eng
Format: epub
Tags: General Fiction
Publisher: White River Press
Published: 2021-07-08T00:00:00+00:00

RPA AND DATA

That evening

WAITING FOR THE TRAFFIC LIGHT to turn green, I sat in the car and pondered the discoveries I’d made in the past hour. Leveraging data not only to enhance operational visibility, but also from a workflow perspective, was the first and foremost priority for us to find a solution to developing an advanced revenue cycle ecosystem.

How to do it was the question.

We’re going to need good data, and to start we need to define “good data.” Mostly, good data should provide the ability to sift through all the noise, and then quickly identify current and future opportunities that are relevant to our performance; we also need to be able to apply that data against business rules to prioritize work activities. What “good data” looks like requires an understanding of how the data should be used, what decisions need to be made, what work that information will help improve, and which actions or process will be supported.

The green light changed, yet I was so involved in these ruminations that I didn’t notice. A few honks from cars behind me conveyed the message quickly, and I sped across the intersection. My mind was racing just as fast.

Assuming we get the right data, the next question is how we can make that data work for us in an actionable way. How can we make it work to support revenue goals? And I don’t mean having something with red, green, and yellow indicators. I mean really actionable!

Thinking about the revenue goals of JHS, my mind went to one of the speakers at the conference who’d explained that, in most cases, key business functions such as clinical departments, accounts payable, finance, and information technology are already collecting data sets from their tactical and day-to-day operations. Although organizations are increasingly fluent about how to combine internally collected data sets such as these that support strategic initiatives, departmental solutions, and general analytic deployments, they have a long way to go when it comes to leveraging data about the functions in which they perform daily operations and how it directly affects workflow. High functioning and successful organizations usually rely on “solid, granular data” to help them with strategic planning as well as with tactical execution.

Which brings me to the big question, I thought. How do I utilize data and implement a solution that improves my situation? It feels as if I’ve been repeating this question again and again without coming up with any concrete answers. There are many approaches to doing this; the first I can remember from early in my career was service line analysis. This approach helps identify which offerings or services could be discontinued with minimal impact to the hospital and the community, and which have considerable growth potential. This type of analysis weighs variables that are most critical to an organization—revenue, profit margins, customer impact—when it comes to driving decisions that both streamline services and enhance profitability . . .

Hold on a second.

I knew there was more swimming in my brain. I waited for it to coalesce into something tangible.

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