In healthcare, just as in life, no one likes losing money-particularly when you don't know why it's happening.

Hospital revenue cycle leaders understand how critical it is to reduce fraud, waste, and abuse as much as possible, from both an operational and financial perspective. Yet even the best-designed revenue cycle management (RCM) system will not prevent internal errors in intake, billing, and follow-up processes that can result in significant undetected losses.

Healthcare organizations ultimately perform better when their processes are reviewed for vulnerabilities and random errors are corrected accordingly. Identifying systematic outliers is not only a proactive business strategy for providers, but it's also a major cost-saver.

Instances of fraud, waste, and abuse cumulatively cost healthcare organizations between $760 billion to $935 billion per year, according to a 2019 JAMA analysis of more than 50 studies. Additionally, the analysis found that the estimated annual savings from interventions that address payment errors and associated administrative expenses were between $191 billion to $286 billion. 

There is real money to be saved if hospitals and health systems implement computing solutions that actively search for statistical outliers and smooth out the cost curve to ensure that payment is accurate and timely. Left untouched and unmanaged, these mistakes can metastasize and lead to increased bad debt, chronic payment delays, and reduced revenues.

Anomaly detection services identify root cause areas that affect a provider's ability to collect all that they are due for the services they provide in a timely manner.

Anomaly detection typically focuses on four core RCM functions: self-pay conversion, payer yield, billing/coding, and denials. On the front end, anomaly detection examines point-of-service collections, then patients who are unbilled in the mid-cycle, as well as 'black hole accounts' on the back end.

Anomaly detection technology does the hard work of joining disparate datasets to surface correlations and charge-level detail anomalies, forming a longitudinal patient record that gives hospitals a holistic financial picture for each patient.

By embracing a data-centric strategic plan, providers can improve their overall functionality, repair their relationships with payers, and return the majority of their attention to patient care. For hospitals and health systems already operating on thin margins, eliminating problematic processes is of paramount importance, as it allows them to invest more resources into patient care.

Once uncovered, some of the identified anomalies may seem obvious in retrospect. But if providers are unaware of these broken processes in the first place, simply understanding they exist can be a revelation. Anomaly detection fills in the gaps of incomplete data and delivers a curated plan of action for the provider.

These services show providers the pain points they otherwise wouldn't have seen, and help ensure health plans don't become overwhelmed trying to fix them.

For a long time, many healthcare organizations have assumed that bad debt is simply the built-in inevitable price of doing business. Due largely to the COVID-19 pandemic, nearly 50% of hospitals saw increases in bad debt and uncompensated care in 2020, according to Kaufman Hall's Performance Improvement report.

While bad debt is undoubtedly part of life as a hospital, that doesn't mean it can't be mitigated.

Hospitals shouldn't feel like it's a rite of passage to surrender a sizable portion of their revenue due to statistical outliers that arise during the normal course of business. These anomalies can occur for any reason, such as aged-out processes or mis-payments from payers, but now there are modern computing solutions available to assist providers in these endeavors.

Another promising aspect of anomaly detection is that it's a continual, sustainable process that builds incrementally and shifts towards automation rather than manual work. Once an error is identified and addressed, providers have time to explore other vulnerabilities that may already exist or emerge down the line.

Corrections can only take place when errors are highlighted for decision-makers to act.

Fraud, waste, and abuse present a pressing and expensive risk to the core functionality of the American healthcare system, so it's in the best interest of revenue cycle leaders to pursue available solutions. There's no honor in bleeding money, especially at a time when so many organizations are trying their hardest to keep every earned dollar.

Anomaly detection points out the costly problems facing healthcare organizations and offers a roadmap for rectifying the situation. As the industry and the world at large become more reliant on automation and data-centric solutions, hospitals should aim to fight the invisible enemy of fraud, waste, and abuse with all the tools at their disposal.

Sean Kirby is EVP, Velocity Consulting.