MedCity Influencers, Health IT

Automation Can Drive Post-Covid Healthcare Revenue Recovery

Hospital and health system revenue cycles will face a labor shortage and external economic pressures for the indefinite future. Automation can help streamline and optimize healthcare revenue cycles, but organizations must use this enabling technology with strategic intent.

The worst of Covid-19 may be behind us, but the pandemic continues to have a negative impact on margins and healthcare revenue with 2022 poised to be the worst financial year since the beginning of the pandemic. Costs for everything are up, inflation is at around 7.7% and all health systems are facing staffing shortages in both clinical and administrative positions. A recent study indicates that 92% of revenue cycle teams are understaffed with 1/3 understaffed by more than 20 positions.

The healthcare worker shortage has deeply impacted revenue cycle operations. Kaufman Hall survey respondents cited increased rates of claims denials (67%), a lower percentage of commercially insured patients (51%), and an increase in bad debt/uncompensated care (41%).

Given these alarming numbers, it’s no surprise that nearly half (46%) of U.S. hospital and health system finance leaders responding to another survey said their organizations currently are behind their 2022 revenue goals.

The labor shortage is here to stay. Staffing experts indicate that the shortage will remain for at least five years, leaving chief financial officers and rev cycle vice presidents struggling to fill positions left vacant by overworked, burned-out employees who quit over the past two strenuous years. When 30% to 40% of receivables aren’t being worked because of staffing shortages in the revenue cycle, it leads to lower collections, payment delays or less cash on hand that can devastate a hospital or health system’s finances.

Increased competition for patients from Walgreens, CVS and other disruptors are further squeezing margins for hospitals and health systems. Healthcare labor costs have skyrocketed because of overtime pay and travel nurses, both of which can add roughly 50% to a typical employee’s hourly rate.

Consultants will tell you that any problem can be solved through people, process and technology. Well, hospitals don’t have enough people, while processes in healthcare are largely antiquated and sometimes broken. That leaves technology as the best strategy for success.

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An automation strategy

The good news is that hospitals and health systems are embracing automation as a solution to their operational challenges, particularly in the revenue cycle. Much of the work in the revenue cycle involves critical but redundant tasks.

Automation enables digital workers or ‘bots’ to do many of those repetitive tasks. A revenue cycle worker can handle about 400 accounts a week, whereas a bot can process about 4,750 accounts weekly at an average cost of $2.40 per account. That’s an 1,100% increase in efficiency combined with a 75% reduction in cost. By leaning into automation, revenue cycle leaders can attain the operational efficiencies they need to optimize revenue while saving money.

Here are three quick tips for hospitals and health systems to successfully implement automation technology in their revenue departments:

Automate with intent
Sure, when you have an automation hammer, everything looks like a nail. But your strategy shouldn’t be to automate everything. (In fact, that’s not even a strategy!)

Rather, you should pursue a data-driven approach that starts by identifying your biggest pain points. Look at the data to determine which processes bots can perform to ease those pain points. Let’s say the data shows that human errors are contributing to an unacceptably low “clean claim rate” (the metric for quality of claims data). If bots can be used to autofill information without mistakes, errors will be reduced and the claims process accelerated, meaning faster time to payment.

Experiment and learn incrementally
Once you’ve developed an automation strategy that identifies areas of priority, begin implementation on a small scale to ensure there are no unanticipated problems.

Start by automating the most mechanical tasks in the revenue cycle. Measure results and make necessary changes. Build upon your successes and gradually progress to jobs that require artificial intelligence (AI)-driven insights and analytical work to uncover patterns and detect anomalies such as coding errors.

Continue to build your automation platform incrementally, drawing on your data feedback loop to fine-tune performance.

Have a plan for rev cycle staff
Automating billing and claims tasks can ease the pressure on chronically understaffed rev cycle departments. It also presents an opportunity to free up rev cycle employees from mundane and time-consuming administrative tasks, allowing them to focus on higher-value activities that directly drive revenue.  Prior authorization is a great example for automation.  A recent American Medical Association report indicates that practices are spending an average of 16 hours per week on prior authorization submission.  Automating that process for your major payers is a critical timesaver.

Outsourcing low value but essential tasks to bots can improve operational efficiency and save money by reducing the need to pay overtime or hire expensive contract workers. Automation also can reduce employee satisfaction because rev cycle workers feel that their jobs are meaningful to the organization.

Hospitals and health systems must take advantage of the opportunity automation provides them by developing a human redeployment strategy for upskilling rev cycle staff to perform tasks that involve critical thinking and judgment.

Conclusion

Hospital and health system revenue cycles will face a labor shortage and external economic pressures for the indefinite future. Automation can help streamline and optimize healthcare revenue cycles, but organizations must use this enabling technology with strategic intent.

Photo: Andranik Hakobyan, Getty Images

Ms. Hartsfield is a seasoned healthcare executive with almost 30 years of experience in the payer, provider and consulting arenas. She currently serves as EVP, Growth Enablement at VisiQuate, helping healthcare organizations achieve peak business health by taking command of their data to maximize revenue cycle operations.

Prior to joining VisiQuate, she served as TractManager’s Chief Data Officer, helping to monetize the organization’s strategic data asset. She built a technology-enabled services line of business using artificial intelligence/machine learning and natural language processing to mine and audit hospital contracts to ensure compliance and revenue maximization.

Specializing in hospital operations with a focus on designing and implementing value-based payment arrangements like BPCI and direct to employer contracting, she also served as a Vice President at both ECG Management Consultants and GE Healthcare Camden Group.

Prior to GE Healthcare Camden Group, Ms. Hartsfield was the Director of Enterprise Business Intelligence – Medical Informatics for Arkansas Blue Cross and Blue Shield. In addition to running all of the informatics and analytics across all lines of business for the enterprise, she was responsible for the implementation of Arkansas Health Care Payment Improvement Initiatives (“ACHPII”), a multi-payer statewide bundled payment initiative, including program development, reporting, methodology, and provider engagement.

Prior to Arkansas Blue Cross and Blue Shield, she was the Director, Provider Relations for Arkansas Children’s Hospital. There she created strategic and long-range plans for the management and development of the provider network, including new physician recruitment and all aspects of credentialing in accordance with National Committee for Quality Assurance standards.

She has utilized her experience in the healthcare industry as a frequent presenter, with over 40 national speaking engagements on a variety of topics including data and analytics, compliance, value-based payment models and provider cost and quality transparency.