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Patient access has a revenue leakage issue. Can AI solve it?
A new report finds that a typical health system loses $6.2M in avoidable referral leakage, but AI-enabled patient access centers are recapturing lost revenue.
Hospitals and health systems are losing millions of dollars due to referral leakage, making patient access a cost center rather than the moneymaker it could be, according to a new report.
The report from Innovaccer surveyed over 100 hospital executives who manage $84 billion in combined net patient revenue on financial performance and operational metrics. The insights found that a typical 400-bed health system loses $6.2 million annually in avoidable referral leakage.
These front-end leakage points are hitting operating margins hard, the report indicated. For the typical health system, these avoidable losses translate to 270-315 basis points of operating margin, it found.
Health system operating margins have rebounded from historic lows during the COVID-10 pandemic but still face a tenuous outlook this year as drug, supply and labor expenses continue to outpace revenues.
Referral leakage issues could push health systems with lower operating margins over the edge, though. The report found that bottom-quartile performers for revenue per referral lose $110 million in cumulative enterprise value over five years compared to the top performers.
The gap between the best and worst performers is also widening by about 8% every year, the report stated.
However, recapturing revenue leakage in patient access could significantly improve financials, with researchers estimating a 100-150 basis-point margin expansion without new patient volume, payer rate increases or clinical productivity requirements.
The sources of referral leakage
Healthcare executives responding to the survey identified five issues accounting for 94% of referral leakage.
At the top, they said wait and abandonment accounted for 27% of annual referral leakage, or $1.7 million, followed by limited appointment availability with 24%, or $1.5 million. These issues go hand in hand, according to researchers, since improving wait times only truly works if health systems can get patients in once they reach a scheduler.
Otherwise, patients are getting through just to be disappointed, one CFO stated.
Fragmented workflows also cost health systems more than a million dollars a year in referral leakage. The report found that this issue, specifically, represents 18%, or $1.2 million, in annual referral leakage for health systems.
Staff typically use three to seven systems for patient access, leading to an average handle time of 8.7 minutes, the report showed.
Rounding out the top five sources of referral losses were insurance and prior authorization at 16%, or $0.99 million, and referral loop failures at 14%, or $0.87 million. Manual processes contributed to avoidable financial losses, while the additional time required to verify insurance and process referrals compounded revenue leakage.
Another use case for revenue cycle AI
AI is promising to increase inefficiencies and revenue capture across the revenue cycle, but patient access AI could yield significant ROI quickly, the report suggested.
Researchers calculated that AI-enabled access centers deliver $8.1 million in net benefit on a $2.5 million investment. Health systems can achieve this ROI in just over three months, they added.
With patient access AI, the cost per scheduled appointment is nearly halved versus the traditional access center workflow. The report found that the median cost is $77, while the AI-enabled cost is $52. The worst-performing health systems have costs of nearly $100.
AI-enabled patient access centers also see significant improvement in referral-to-appointment conversion -- from a median of 58.2% to 82.7% -- and patient satisfaction -- from 65% to 87%.
The key to ROI for this use case is accelerating speed. Patient access AI tools help patients connect to the health system faster and manage these requests sooner.
Specifically, the average speed to answer dropped from a median of 82 seconds to just 12 for AI-enabled workflows. The average hold time also fell from 3.2 minutes to under one minute, while average handle time decreased from 6.6 minutes to 4.2 minutes.
The report found that health systems that responded to scheduling inquiries within 5 minutes converted 2 out of 3 patients. In contrast, systems that responded after 24 hours converted fewer than 1 in 10 patients.
Each lost interaction equates to $294 in lost revenue over the next year, researchers said.
Enabling an "intelligent, always-on digital front door" will help health systems "capture the margin expansion that comes with it," Abhinav Shashank, CEO and cofounder of Innovaccer, said in a press release.
Opening the digital front door
Consumerism continues to be a key priority for healthcare executives, as patients grow louder in their demand for personalized, proactive care. In fact, healthcare organizations could lose $54.4 billion over the next decade if they don't meet those expectations, Deloitte reported earlier this year.
This increased emphasis on healthcare consumerism could finally open healthcare's digital front door -- and keep it open. But healthcare organizations will need to ensure their systems are ready for more sophisticated technologies, like AI, the report stated.
IT infrastructure limitations, lack of budget and integration challenges continue to hinder revenue cycle AI adoption, according to a survey from the Healthcare Financial Management Association and FinThrive.
Healthcare organizations are still eager to continue AI adoption but are focusing more on applying AI to the mid-revenue cycle, including documentation improvement and coding, the survey found.
Patient access may not be on the top of AI wish lists for healthcare organizations at the moment. But failing to enable tech-powered access centers could put organizations further behind the adoption curve, as well as damage their market power, net promoter scores and revenue capture.
"For too long, the access center has been treated as a cost to minimize rather than a revenue engine to optimize," Shashank stated.
"What this research makes undeniable is that every hold time, every broken referral loop, every abandoned call is a precise, measurable financial event -- and the organizations that have started treating it that way are pulling ahead fast. The performance gap between AI-enabled systems and traditional operations is not closing, it is widening."
Jacqueline LaPointe is an Executive Editor at Xtelligent Healthcare Media, covering revenue cycle management, healthcare payers, health policy and health IT since 2016.
