This week, as I read an article in the Washington Post about Poplar Bluff Regional Medical Center and their daily task of taking patients to court, it struck me that this scenario didn't surprise me. Poplar Bluff has filed over 1,000 lawsuits for unpaid medical bills in 2019. Their community simply cannot afford to pay their medical bills. The plight of community/regional/rural hospitals and their patients is a problem we hear about every day at Sift. It's where we're finding that analytics and optimizations have a dramatic impact -- enabling hospitals to capture more of their earned revenue while improving patient relationships.
Predictive analytics and data science have the power to equip healthcare providers to implement strategies that stave off rounds and rounds of phone calls and lawsuits. By advanced modeling around a provider’s historical payments data, Sift identifies:
- Which patients will pay their bills, elite payers who need no extra time/resources.
- Which patients won’t pay any of their bill, under any circumstance, and should be treated as write-offs or charity.
- Which patients will pay some of their bill if you offer a discount or payment plan.
- The optimal amount for a discount or payment plan, enabling providers to proactively work with patients to help them better afford their care.
- When (timing) and how (method/medium) to contact each patient to drive the most successful payment outcome.
Sift delivers much more than the industry-standard propensity to pay score (more on why propensity to pay isn't enough, here). Sift provides regional and community hospitals with actionable recommendations that maximize payment. We integrate our recommendations into providers’ current RCM workflows so that these actionable recommendations can be executed.
This type of AI is commonplace in other industries but is yet to be adopted at scale in healthcare, where it’s desperately needed. Unpaid patient medical bills are a growing problem for community hospitals — and they're a downright crippling problem for rural hospitals. These providers can’t afford not to optimize their revenue cycles and improve their understanding of patient payments.
It is a necessity to develop strategies that fit individual patient populations -- working to maximize payments based on data. As unpaid medical bills become a spotlight problem in the US, I’m proud that Sift's platform is an empowering tool for the communities who struggle with these issues the most.