The revenue cycle management function has come a long way for companies with a recent paradigm shift in thinking from a cost centre to a profit centre view. Unfortunately, this shift in mindset has not led to an industry breakthrough solution. In a survey conducted by ISG, 97% of  companies reported they struggle with optimising the workforce, asset, productivity, or growth. Each level has a correlation with the revenue cycle function, which contributes to an industry average of 15–25% of overall operating costs (i.e. a large population of DME companies continue to operate at 25–35% revenue cycle costs).

Although companies are adapting to cope with revenue cycle issues, the size of the canvas has expanded beyond focusing on just the following:

• 100% accurate inputs at the order-entry stage leading to a clean claim submission.
• 100% adherence to the eligibility criteria based on medical necessity established by the physician before dispensing the products.
• Timely collections of required documents before billing to avoid timely filing denials.
• Understanding of payer/product rules for accurately determining required documents to avoid complete or partial denial.

The industry has used a combination of process and technology to tackle these factors with varying degrees of success. However, the desired end state seems to be as elusive as when we began this journey. Now we are forced to ask why. The answer begins with recalibrating the set of variables we need to monitor:

• The shift in the payer mix due to demographic factors, such as an increase in aged population
• Product mix changes as result of sales strategies and the resulting swing on pricing
• Onslaught of regulatory audits warranting increased scrutiny of processes and appeals have grown more than 150% over the last three years as a result of high claim rejections

These factors are playing a larger role in affecting providers that struggle with razor-thin margins, competitive bidding, and unfavourable contracts dictated by the payers.

To achieve a genuine view on the actual reasons, a three-step method must be used:

• Use data analytics to understand historical trends.
• Assemble a revenue projection blueprint design. The model maps the order from inflow to cash yield. Predictions from each process phase are compared to actual performance to identify where the stoppage in flow is occurring; and
• Form a “line of sight” team from core business operations to review process performance, identify opportunities, and tactically align initiatives to improve results.

This approach generates insights that link the cash shortfalls to unsuspected sources unlike the usual ones, such as productivity, timely filing limits, ageing, delay in follow-ups, ineffective collection practices, etc. Cash was down not because the collections team was less effective, but because the average value of a cash payment had dropped. The sales team was meeting the overall volume goal, but the team was selling lower-priced items. This product shift had a cascading effect, triggering a negative impact on the payer mix.

An unexpected variation in product sales brought an unexpected shift in who was buying the product, the purchaser base. The new trend was sales to payers with reduced contract pricing and, ultimately, a lower value per order.

As an outcome, companies can create a well-defined model on which to base probabilities versus random targets. This model equips a company’s leadership with certifiable triggers for evaluating cash results.

Conclusion

The way to the future for DME companies to constantly stay on top will depend on their agility to respond, which comes from the power of smart intelligent processes achieved through the following:

1. Investing in data infrastructure that supports information exchange among payers and providers.
2. Including payer, product mix, and sales effectiveness in the list of process metrics.
3. Establishing a measurement system that tracks metrics and reports all performance indicators in the entire RCM value chain, including sales.
4. Building a forecasting model built on predictive analytics principles using historical data to act as an alert too.

Regardless of what you decide is the best for your company and understanding the importance of RCM checklist as a function of your success is a key. Contact us for more information.

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