According to an International Data Corporation report last year, healthcare data is projected to grow by 36 percent through 2025 — faster than manufacturing, financial services or media data. Once known primarily as “Big Data,” today it has migrated to become more commonly known as data or text analytics, and is the engine that drives what’s more broadly called “business intelligence”.
This is Not Your Parents’ Data Analytics
Like those find-a-word puzzles you might have played as a kid, data scientists develop ways for the rest of us to find patterns that emerge from the huge data sets healthcare generates. Unlocking the promise of big data in healthcare keeps tech titans like Facebook, Apple, Amazon, and Google — not to mention many others — busy these days. Jump to Wired, or Modern Healthcare, and somebody’s developed a new big data analytics application that promises to do everything from predict patients most likely to develop sepsis, to reducing variation and generating cost savings for knee replacement surgeries.
Yet beyond the academic level, data analytics has yet to make significant inroads in the wider world of healthcare. The analytics project that reduced knee replacement costs? Project lead Dr. Caleb Stowell, enterprise director of value-based care at Providence St. Joseph Health in Renton, WA, acknowledged the difficulty of the task: “There’s a reason why other systems haven’t done this — it’s really hard, particularly to do this in a way that is translatable.” Yet to deliver on the promise of better care at a reasonable cost, healthcare can’t afford to shrink from the responsibility of getting their data house in order.
For ASCs, the data analytics now available have significant clinical, financial and business implications. Previously, most healthcare data analysis centered on historical data — i.e., what’s already happened. But today’s analytics technologies, powered by machine-learning algorithms, can go much further to deliver current and predictive views of business and clinical operations. Not only is the data more in-depth, it’s easier to access. Think dashboards instead of spreadsheets.
With the right tools, bringing data analytics into ASC center management may not be as daunting as it seems. Here are four ways ASCs can use data analytics to improve their business and clinical operations.
Scheduling and Staffing
Dr. Stowell was looking for ways to standardize knee replacement surgery, thereby improving productivity, as well as getting a handle on supply chain management. Sound familiar? ASCs should be looking at physician performance to make sure scheduling allowances are made for those who take a bit of extra time.
And speaking of extra time, data analytics is critical for pinpointing the cause of chronic overtime issues. Is the compliance process being inserted into the workflow at the wrong time? It it a staff-driven issue? A combination of both? Accessing the data to pinpoint the cause, and working through the right solutions (maybe it’s time to automate time keeping), gives ASC administrators critical, predictive insight to help manage labor costs.
Bundled Payments
Bundled payments and other value-based care initiatives play a big role in bending the healthcare cost curve. While they’ve yet to significantly impact ASCs, bundled payments are definitely on the horizon. To successfully navigate this prospective model of payment, which puts the provider on the hook for any overages, center administrators can harness data analytics to plot how their clinical and business practices need to respond.
Inventory Management
After payroll, inventory is the biggest expense for most ASCs. Data analytics are critical for the kind of sophisticated forecasting surgery centers will increasingly rely on for managing medications and supplies. With the right data analytics tools, mass quantities of data can be easily processed to keep track of how much of everything is on hand, who’s using it and how quickly they go through it.
Tip: Don’t be like hospitals. According to Cardinal Health, only 17 percent of hospitals are using data-driven solutions to manage supply chain. Their inventory will continue to be the black hole that swallows profitability.
Revenue Cycle Management
With Accounts Receivable over 90 days averaging at 12 percent, ASCs could see that portion grow with the rise of high deductible health plans. Some ASCs are already investing in solutions that can collect a range of metrics, such as average A/R days or average wait times by provider, and compare them to specialty or location-specific benchmarks.
Getting Past the Workforce Skills Gap
There is one significant obstacle that stands in the way of data preparedness and competency for ASCs: hiring employees with the necessary skills to aid in this transformation. According to the IDC study, “40 percent of healthcare organizations still struggle to hire employees with the necessary skill sets.” ASCs may need to contract out services or work closely with their existing technology providers until the workforce skills gap catches up with ASC data analytics demand.
When it comes to bringing data analytics into your ASC operations, the one thing you can’t afford to do is wait. Stepping up your ASC’s data analytics program can yield big results. Imagine tying your incident reports into peer review and checking infection data against your costs. The Simplify ASC platform gives you that kind of visibility into your day to day operations. Our powerful reporting capabilities make it easy for you to find the opportunities to make more money, save more time and get home for dinner.
Take a closer look at how the Simplify ASC platform can help.
