Predictive analytics represent the future of medicine for ASCs and other all healthcare organizations, and not just in the clinical sense.
Insights gleaned from day-to-day encounters and transactions can also strengthen revenue-cycle management (RCM) by driving informed decision-making. Data can influence decisions such as whether to renew payer contracts, outsource certain billing functions to a third party or offer flexible patient payment and financing plans.
Yet many of the latest generation of predictive analytics tools, which rely heavily on machine-learning algorithms, are still underutilized among ASCs.
Part of this may be due to the fact that specialty practices are only starting to feel the impact of rising premiums and high-deductible health plans [HDHP], which are steadily growing. According to the Kaiser Family Foundation’s 2018 Employer Health Benefits Survey, annual premiums for employer-sponsored family health coverage rose 5 percent, while the average deductible for workers that held a plan with a general annual deductible reached $1,573.
Numbers like these influence patient spending behaviors, and we’ve seen a rise in patients pushing procedures into the final months of a calendar year so they can meet their deductible first. Ultimately, this kind of behavior trickles down to healthcare organization’s cashflow.
Another reason that ASCs aren’t tapping into predictive analytics is a lack of understanding on how having access to the right data can not only strengthen the revenue cycle, but also help an ASC enhance customer service, boost patient satisfaction, and make staff more efficient.
Employing predictive analytics tools can potentially do all of these things. Moreover, having access to a wealth of RCM data can put surgical centers ahead of the curve, and offer a competitive advantage.
Predictive and Powerful Tools
Many ASCs already use some form of analytics to gain insight into the revenue cycle; for example, patient bill-estimation solutions that tell us what a surgery or clinical encounter will cost the patient out of pocket.
Medical practices that leverage these technologies can’t imagine life without them. The ability to estimate healthcare costs in advance empowers patients to make the best decisions about when they need elective medical care and promotes good will between the practice and the patient.
But cost estimates are only one insight that can help both ASCs and their patients.
The next generation of predictive analytics tools can do so much more, by tapping into sophisticated machine-learning algorithms that can compare multiple metrics — e.g., average days in A/R; denials among patients with a particular insurer; average wait times by provider — to specialty or location-specific benchmarks. This offers administrators a much more comprehensive picture of a practice’s operations.
Even more important, having real, objective insights into performance removes human emotion from the equation. Armed with data, we can let go of our erroneous “hunches” about our practice’s problem areas, and focus our energies on solving the real, day-to-day operational issues.
So how does having such high-level insights help us to improve the performance of our ASC? The answer depends on what the insights tell us, as well as the objectives of the practice. But we can think of several examples of how analytics can play a crucial role in operations.
Let’s say our analytics solution shows us that 8 out of 10 patients with a certain kind of procedure, such as a total knee replacement, postpone surgeries to the second half of the calendar year. Our analytics system tells us that most of these patients use a high-deductible health plan. From that information, we can hypothesize that these patients are hoping to curb what they expect are high out-of-pocket costs, and tailor our response accordingly.
For example: We can boost our education efforts and ensure that we’re transparent about costs. We can emphasize the recovery benefits of scheduling surgery earlier in the year. And we can offer patients more flexible payment opportunities, so they won’t have to worry about an onslaught of huge medical bills coming in the mail. One option growing in demand includes offering a low- to no-interest credit financing plan. Giving patients the option to finance their elective surgeries now, rather than putting them off, will increase patient satisfaction dramatically and keep cash flow steady.
Or, let’s say that our analytics tool informs us that half of our patients don’t pay balances within 30 days of services rendered. We can then ask ourselves if we’re sending out our bills in a timely manner. Or, we can investigate what’s happening at the front desk: Is administrative staff consistently verifying eligibility, using a payment-estimation tool and collecting as much money up front as possible? Are we continuing to schedule patients who have high amounts of current patient debt?
Going forward, ASCs will have to contend with a number of challenges: competition with each other and large hospitals, a dwindling physician workforce, and leaner payer contracts. Nevertheless, patients will still need healthcare — often in the form of surgery.
Gaining as much insight into the revenue cycle as possible will help ASCs stay afloat, so they can focus on providing the best care and service to all patients in the evolving healthcare marketplace.
Matt Seefeld is the executive vice president of MedEvolve.