Calculating Cost to Collect: A Crucial Metric for Assessing Operational Efficiency in Healthcare Revenue Cycles

Cost to Collect is an important measure used in managing healthcare revenue. It shows the percentage of money spent to get payments for patient services. This includes things like staff pay, fees to vendors, billing system costs, office expenses, and costs with handling claims and collections.
For example, if a healthcare provider spends $1 million to collect payments and earns $20 million in patient revenue, then the Cost to Collect is calculated as:
Cost to Collect = Total Collection Cost ÷ Net Patient Service Revenue = 1,000,000 ÷ 20,000,000 = 5%.
A lower percentage means the revenue cycle is running well because less money is spent to collect each dollar. A higher percentage shows inefficiency and possible waste, which can hurt the financial health of the provider.

Why Is Cost to Collect Important for Healthcare Organizations?

Cost to Collect helps healthcare organizations check if their revenue collection efforts are worth the cost. The healthcare field faces tough problems like fewer workers, higher patient costs, and more unpaid bills. These problems make managing revenue harder.
Experts say that a good Cost to Collect rate should be between 2% and 4% of the patient revenue. If it is higher, it may mean problems like many claim denials, long times to collect payments, and high administrative costs.
Lower Cost to Collect rates help providers have better cash flow, more available money, and the ability to spend on patient care. For instance, steady cash flow can help keep enough staff, buy new technology, and offer quick services. These things are important in today’s health market.

How Cost to Collect Relates to Other Key Healthcare Revenue Cycle Metrics

• Net Days in Accounts Receivable (A/R): This measures how long it takes to collect payments after a patient visit. It’s best to keep this under 50 days, ideally between 30 and 40 days. The longer it takes, the higher the Cost to Collect because staff must spend more time following up.
• Clean Claim Rate: This shows the percent of claims accepted the first time without error. A rate of 90% or higher is good, with 95% as a common goal. More clean claims mean less rework and fewer costs.
• Bad Debt Ratio: This ratio shows how much revenue is lost because payments were not received. Higher amounts suggest problems like poor patient screening or unclear billing, which increase costs and lost revenue.
• Cash Collection as a Percentage of Net Patient Services Revenue: This shows how well billed services turn into actual cash. Numbers near 100% mean good revenue collection. Values between 90%-95% may need extra checks.
• Denial Rate: This is the percent of claims denied by payers. More denials mean more work to fix errors and bill patients again, which raises costs.

Using Cost to Collect with these other measurements helps healthcare leaders find weak points in their billing and collection systems. These might include problems with approvals, billing accuracy, patient payments, or follow-ups.

The Impact of Rising Costs and Workforce Challenges

Healthcare providers in the U.S. face growing labor costs and worker shortages. These raise collection costs if work output does not increase along with pay.
Patients also have to pay more out-of-pocket because of insurance plans with high deductibles. This increases the amount patients owe both during and after care. When patients cannot pay, bad debt and charity care amounts go up, making collections harder.
Reports show that bad debts have grown compared to past years. To avoid losing revenue, healthcare providers need efficient billing and collection processes. Controlling costs and working efficiently are key to staying financially stable.

Enhancing Cost to Collect Through AI and Workflow Automation

Healthcare groups can lower Cost to Collect and improve revenue cycle work by using artificial intelligence (AI) and automation technology. For example, companies specializing in phone automation help manage patient communications better and reduce the workload.
Here is how AI and automation help with Cost to Collect and revenue cycle tasks:

• Improved Patient Engagement: AI systems can send appointment reminders and check insurance automatically. They also help with financial counseling. This can increase early payments and lower bad debt. Early contact with patients reduces claim denials.
• Front-Office Phone Automation: Automation handles calls about scheduling, questions, and payments. This lowers the work for office staff and reduces related costs.
• Faster Claim Resolution: AI can find errors in claims before sending them in. This improves clean claim rates and cuts denial rates. Fewer denied claims mean less rework and lower collection expenses.
• Analytics and Reporting: AI reports on key metrics in real time. This helps leaders spot problems like rising collection times or denial rates early and act quickly.
• Operational Efficiency: Automation helps standardize tasks like processing claims and posting payments. This keeps work consistent and cuts human errors.

Healthcare providers that use AI and automation often see lower collection costs because of better tasks and faster payments. This is very helpful for small and medium-sized practices which have limited staff and many tasks to handle daily.

Selecting and Monitoring KPIs for Operational Efficiency

Healthcare leaders should pick performance measures that match their goals and needs. Along with Cost to Collect, tracking technology use, patient financial engagement, and how often claims are resolved right away can help improve results.
Regularly comparing these measures to industry standards lets providers see how they perform compared to others. This helps find areas needing attention.
Good KPI tracking helps providers control costs and improve patient experience. For example, using AI to communicate better with patients encourages them to pay promptly, which lowers bad debt and collection costs.