The U.S. healthcare system is broken, and things are going to get worse before they get better. Despite today’s obsession with artificial intelligence, there is no grand solution in sight.
Putting healthcare back together is going to take an all-hands-on-deck set of strategies, new workflows enabled by the thoughtful application of technologies, new partnerships among providers and a willingness to outsource functions for which organizations lack core competencies.
As a recent report from the Healthcare Financial Management Association and the consultancy Guidehouse concluded: “Fundamental changes in culture, work redesign and workforce development are essential for providers to thrive in the new healthcare economy.”
This “new economy” is fraught with complications on an epic scale:
The Great Resignation from all roles within an organization, from the C-suite to physicians to medical technicians to nursing to the business office
Unpredictable demand for emergency room visits, inpatient care and ambulatory surgery procedures
An ongoing hemorrhage in operating revenue and margins that threatens the closure of services and hospitals, particularly in rural areas and inner cities
A behavioral health crisis unlike anything seen before
The historic scourge of fentanyl
The continued saga of COVID, whether or not people are “over it”
And just as hospital finances have begun to settle into a new, lower normal comes the end of the Public Health Emergency, with the loss of add-on payments from Medicare and subsidies for millions of new Medicaid enrollees that have kept many a safety net hospital open over the past two-plus years.
The best advice I can give about how to begin solving this crisis is to match your core competencies to the relevant problems at hand, focusing on growth where you can find it, and keeping costs as low as possible.
In other words, focus what you do best and outsource the rest.
As an industry, we have to keep improving by utilizing new, cost-effective strategies. In clinical care that might mean a comprehensive plan to augment remaining staff with outside expertise, especially telehealth physicians and nurses. On the business side, that might mean more significant partnerships with vendors, from patient access to coding to collections.
For many organizations, the complexity of revenue cycle management is getting past their ability to do this work in-house. For starters, they lack the staff, having been hit as hard by resignations and layoffs as any other area. Hiring your way out is a long slog. A 2022 survey of HFMA members found that filling an open entry-level revenue cycle position cost hospitals and health systems $2,167 and took an average of 84 days, despite applicants needing no experience. Mid-level positions, which require six to 10 years of experience, cost an average of $3,581 for recruitment and took 153 days to fill. And this is if you can find people willing to work.
Experienced vendors can help avoid front-end errors and missteps, such as registration mistakes, can lead to costly claim denials and rework on the back end of the revenue cycle. Doing relatively simple things such as evaluating closed claims for payer mistakes can return millions of dollars for services rendered.
Managing the self-pay portion of billing in a way that doesn’t alienate the patient is a way to turn a source of dissatisfaction into a means of build relationships that bears fruit when it is time for future care.
Healthcare providers often look to vendors to apply new technologies to automate processes such as checking claims status to transform staff productivity and reduce costs. In the HFMA Guidehouse report, revenue cycle automation was senior leaders’ No. 2 priority for 2023, just behind digital engagement/virtual care (telehealth).
Many organizations also are hearing the siren call of AI, which undoubtably will play a role huge role in the future of revenue cycle management but shouldn’t be oversold today. There are still many things that AI can’t do, such as understanding the nuances of language, which makes claims about its immediate value for clinical documentation spurious. Deep learning, the application behind the ChatGPT frenzy, requires the kind of massive data sets that only a national health system can provide before it can make the connections to be able to predict future activity. Within a few years, if not months, this kind of technology will be available, for a price.
Denial management may be a good starting point for AI in the near future. You needn’t fear built-in mistakes as you would in using it for coding and documentation. It looks for trends or anomalies in the data that can help pinpoint payer mistakes, decrease future denials, accelerate revenue and enable more equitable contractual agreements.
The fact remains that at least for today you need highly trained staff to work account backlogs, tackle difficult accounts receivable and improve the billing process so more claims are paid on a timely basis. As I have noted previously, if you have the right culture of training, teamwork and empowerment, quality staff will stay the course.
The revenue cycle is a critical healthcare process, and its management is central to the business of healthcare and keeping needed services in communities that depend on them. Most providers struggle with it, even as it can be the difference between success and closing the doors. Now is the time to look for a partnership that can solve an important part of the puzzle of reinventing healthcare.
· Overall, the year is off to a difficult start.