It is no secret that a high-performing revenue cycle department is the most important factor in determining the financial success of any healthcare organization. Without a healthy revenue cycle, there is little chance of long-term survival.
To achieve the greatest revenue cycle outcomes that translate into the highest level of reimbursement, you must set up workflow processes that allow you to make continuous improvements and that adhere to best practices. In addition, measuring quality at every step of the claim journey is crucial to maximizing revenue potential.
The best way to accomplish these objectives in today’s current healthcare environment is to use predictive analytics along with artificial intelligence (AI) to assist your current revenue cycle team. Doing so allows you to identify problems within the revenue cycle processes and issues with payer behavior. It also helps you to measure the performance of the work being done.
What’s at stake if you don’t use AI and analytics?
In 2017, HFMA published a report that stated that, out of $3 trillion in claims that were filed, $262 billion ended up as denied and unpaid. (1) In 2021, HFMA reported that denial rates had climbed another 20% since the 2017 data was originally published. That is a total of almost $315 billion in denials and unpaid claims.
Furthermore, HFMA has stated that if a claim denies with the first pass there is less than a 40% chance it will be paid on the second submission. Put another way, up to 60% of your claims are likely to remain unpaid if the claim is not paid with the first submission!
Most of the leading health plans are using claims data to automate the process of routine claims. Doing so allows them to have their claims teams focus on complex claims that require human expertise and judgment. It also helps insurers to quickly identify potential fraud or any other potential threats.
Providers who follow the lead of insurers and make the change to using data analytics and AI in their own revenue cycle processes can expect to also benefit from the use of predictive modeling that shows past patterns and current trending, and help management make better-informed decisions for the future.
3 types of analytics you must start using today
When used in combination with AI found in EHR software, there are numerous types of analytics that can be used in business to answer a variety of questions. The “intelligence” of AI tabulates values into data sets that can then indicate specific events such as the reason why a claim is being denied or which diagnosis code requires a prior authorization. AI then probes more deeply into the analysis of the data using machine learning algorithms. In healthcare, the three types of analytics that are most useful are descriptive, predictive, and prescriptive analytics.
Descriptive analytics looks at what has happened in the past by reviewing historical financial and revenue cycle data. From that data, you can draw comparisons and discover patterns. The results help find any potential revenue leakage and identify if such leaks are occurring due to insurance issues or within the internal operational workflows.
Predictive analytics uses both current and historical data to help in predicting what revenue flow trends are likely to happen in the future. This type of analytics allows you to gain insight into what could happen next.
Prescriptive analytics also makes predictions about future outcomes and is used to help an organization determine what should happen and how to build a roadmap for a desired future state. The data models show the potential outcomes for the company based on which course of action it chooses. From there, you can determine the best way forward for your organization.
By using analytics and AI in your revenue cycle workflows, you are able to gain actionable insights into:
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Your team’s past and current activities, including both individual and group performance
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How to improve the patient experience
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Actions you can take to create your organization’s desired future state
Taken together, these insights can help you improve your revenue stream and financial cash flow.
(1) HFMA, 2022, April. Improve cash flow and cost of reworking denials with the efficientC claim scrubber technology. HFMA.org
