Leveraging Benchmarking Data to Drive Improvements in Revenue Cycle Performance Across Healthcare Facilities

Healthcare facilities across the United States have ongoing challenges in managing their revenue cycle well. Patients are paying more, claim denials are rising, and billing is complicated. Because of this, administrators, owners, and IT managers look for clear ways to improve how their operations and finances work. Benchmarking data helps healthcare organizations compare themselves to others, find weaknesses, and make focused improvements. This article looks at how benchmarking helps healthcare providers improve revenue cycle performance and talks about the growing use of artificial intelligence (AI) and workflow automation to make these processes better.

The Importance of Benchmarking in Healthcare Revenue Cycle Management

Benchmarking means comparing an organization’s operational and financial numbers with similar institutions or industry standards. In healthcare revenue cycle management (RCM), this helps show how an organization performs on important measures like accounts receivable days, denial rates, money collected at service time, and bad debt levels. These numbers help find areas that need improvement to get more cash, reduce losses, and keep patients happier.

Recent data from over 2,100 hospitals and 300,000 doctors using the Kodiak Revenue Cycle Analytics platform showed big differences in how organizations perform. The top performers had almost 35% fewer true accounts receivable (A/R) days than the average. They also had 22.5% of true A/R days over 90 days, compared to 35.9% average for all users. These differences show that organizations using benchmarking can focus better on collecting payments and reducing denials to make their revenue cycle faster.

Benchmarks also showed that the best performers had almost 74% fewer credit days and bad debt rates over 64% lower than average. Their point-of-service cash collections were 2.5 times higher than average. These facts show that comparing operational numbers with others helps find specific problems like billing delays or poor patient payment capture that affect finances.

Areas Where Benchmarking Drives Revenue Cycle Improvements

• Accounts Receivable and Denial Management

Accounts receivable days measure how long it takes a healthcare organization to collect payment. Shorter A/R days mean billing, coding, and payment follow-up work better. By comparing A/R days with other places, managers can find delays like slow physician notes or claim submissions that do not work well.

Denials, including initial and final ones, are a big problem. Data shows denial rates are going up for many payors, like commercial insurers and Medicare Advantage. By comparing denial rates, administrators can spot unusual rises or trends and fix root problems. Organizations with teams focused on denials and using data to guide actions do better. For example, Kodiak’s data showed top organizations combine clinical work with revenue cycle tasks, improving documentation and payor talks.

• Credit Days and Bad Debt Reduction

Credit days are how long payments are delayed because of credit issues like contract disagreements or patient eligibility. Cutting down credit days helps cash flow and financial health. Benchmarking shows how an organization’s credit handling compares to others and offers ideas for better strategies. Automated credit systems use past data to help teams focus on which accounts to review and follow up.

Bad debt is still a big problem. Insured patients now make up more than half of bad debt cases. Tracking bad debt compared to others helps hospitals check how well collection rules and patient financial help programs work. Improving money collected at service time usually lowers bad debt write-offs a lot.

• Point-of-Service Collections

Payments made at the time of service affect revenue directly. Top organizations collect patient payments almost two and a half times more than average. They do this by offering clear payment options, explaining patient financial responsibility well, and making payment easy. Comparing payment compliance helps improve front-desk work, train staff better, and use technology that supports simple payments.

• Final Billing Timeliness

The number of days not final billed measures how much time passes from service to bill submission. Lowering these days helps revenue come in faster and reduces extra work. Organizations that compare this number to others can find slow steps like delayed physician replies that hold up billing. Teamwork between clinical staff and revenue cycle teams is important here.

• Payer Contract and Payor Relationship Management

Strong payor relationships help reduce the money lost from claim denials and late payments. Benchmarking data gives fact-based information to help with payor talks. This points out where contracts may need changes to get better payment rates and terms. Top organizations keep a balance between good operations and working well with payors to avoid disputes that hurt revenue.

Using Real-Time Analytics and Data Integration for Continuous Improvement

Many healthcare groups start with manual or spreadsheet methods for revenue cycle data. These ways can be broken up, slow, and have errors. This makes it hard to get quick and useful reports. New tools combine data from many parts of the business to give real-time views on patient access, billing, accounts receivable, and collections.

Systems like Millennia’s Patient Payment Solution use real-time dashboards made with PowerBI. These show engagement stats, payment info, account details, and patient satisfaction. Dashboards let managers see how things are going right away and alert them when something unusual happens, like more denials or late payments. Custom reports allow detailed reviews based on what the organization needs.

With regular performance checks by support managers, healthcare places get expert advice based on current data. This helps them change plans before problems get worse instead of waiting. This approach helps get more money and makes paying easier for patients.

Impact of Benchmarking in Healthcare Mergers and Acquisitions

Benchmarking data also helps in bigger healthcare deals, like mergers and acquisitions (M&A). These deals often have messy or incomplete data. Companies like Aesto Health and Veradigm work together to pull out, organize, and study important clinical, financial, and operational data.

Better data access cuts due diligence time by 30%. This lets buyers and sellers focus on decisions instead of collecting data. After a deal, benchmarking guides how to improve operations, fix revenue gaps, and raise profit margins. Leaders use this detailed benchmarking to check on acquired practices and track progress toward money goals.

Strategies for Ambulatory Surgery Centers (ASCs) Using Benchmarking

Ambulatory Surgery Centers (ASCs) use benchmarking to find ways to cut costs and increase revenue. Recent surveys show 54% of ASCs cut costs by managing their supply chains better. They do things like buying in bulk and negotiating with vendors. Saving on energy can lower bills by about 20%, and better staffing plans cut labor costs by up to 15%.

ASCs that added services like pain management and orthopedics saw patient numbers and revenue go up by 20%. Comparing supply chain costs, staffing, and patient counts to others helped centers use resources smartly and add new services. Keeping accurate coding and documentation—tracked with KPIs—also protects their revenue from costly mistakes.

AI and Workflow Automation: Enhancing Revenue Cycle Operations in Healthcare

One fast-growing change in revenue cycle management is using artificial intelligence (AI) and automation. These help healthcare groups make workflows simple, cut manual mistakes, and predict money risks before they become big problems.

For instance, FinThrive’s system uses AI to find problems that cause revenue loss through predictive analytics. Its Real-Time Insurance Discover checks patient coverage when scheduling, reducing denials from eligibility issues. After using this, one health system reported a 53% improvement in revenue capture by using AI to prioritize worklists.

The FinThrive Authorization Manager automates predicting and processing prior authorizations. This cuts delays that often cause denials and revenue loss. The AI system sends alerts to front-office staff, helping revenue cycles work better and making the patient payment experience smoother.

Automation also helps manage claims by tracking denial patterns and automatically creating appeal letters using AI. This lowers the amount of work and speeds up cash collections. Automated tools also help with credit issues by sorting accounts based on payment history and choosing the best follow-up methods.

Using predictive and prescriptive analytics helps revenue teams move from fixing problems after they happen to managing them before they start. By guessing trends, finding blockages, and suggesting fixes, AI helps keep operations and finances steady over time.

Data Literacy and Organizational Culture

Using benchmarking and AI tools is not enough without building a data-focused culture in healthcare organizations. Training all staff to understand analytics, know KPIs, and use data dashboards helps teams make good decisions.

Programs to teach data skills give revenue cycle workers, doctors, and managers the ability to link data results with business actions. This shared understanding supports teamwork between clinical and operational groups. This teamwork is a key part of improving revenue cycle measures, as shown by Kodiak’s Revenue Cycle Performance Awards.

Leaders who make staff responsible for their performance numbers and encourage different departments to work together usually get better financial results. Clear responsibility, supported by benchmarking data and analytics, helps keep attention on steady improvement and a strong revenue cycle.

In summary, benchmarking data helps healthcare facilities in the United States by giving clear comparisons that lead to better revenue. Combined with real-time data, AI, and automation, these methods help administrators, owners, and IT managers solve issues like slow payments, more denials, and higher patient costs. Through smart decisions and improved workflows, healthcare groups can be more efficient, lose less revenue, and improve their financial condition.