Between skyrocketing labor and supply costs, tightening payer restrictions, and unfavorable government regulations, provider groups struggle to recoup revenue earned.
Posted just this month, MGMA’s Datadive “Missing Pieces for Revenue Recovery in the Post-Pandemic Era” raises the alarm that surging labor and supply expenses in a time when total encounters have dropped will ratchet up the pressure on provider revenue for yet another year. Over 89% of medical groups surveyed reported their operating expenses increased this year so far.
“Doing more with less doesn’t always leave you with a better bottom line,” the report shares. “This painful reality has intensified as post-pandemic staffing shortages linger, and elevated expenses put pressure on medical group, hospital, and health system finances.”
Today, many forward-thinking providers, managed service organizations, and hospitals are leveraging revenue cycle analytics software. Healthcare leaders agree that it’s a powerful strategy for measuring revenue cycle effectiveness and ultimately maximizing revenue. Here, you’ll find how revenue cycle analytics software helps providers limit labor costs, reduce denials and underpayments, and recover more in aging accounts receivable. These steps optimize the revenue cycle, enhancing EBITDA.
What is revenue cycle analytics software?
Revenue cycle analytics software consists of:
- Statistical analysis for performing complex calculations
- Automated solutions for identifying patterns and trends
- Data visualization tools
These features interact to deliver an in-depth look into the financial health and performance of medical practices.
Imagine presenting documented data rendered in easily understandable graphics to your team. The trends and patterns there justify your revenue cycle decisions. When a team member asks a question, you turn to the data rather than defending your opinion or sharing your experience (that others may not have had).
Most likely, you’re already paying to track and document the data found in your EHR/EMR, practice management, and billing systems. Revenue cycle analytics software turns this data into insights and insights into powerful plans. It has proven to increase workflow efficiency and practice profitability, reduce costs, and enhance patient satisfaction. It also helps you to track RCM metrics to enhance financial performance and patient satisfaction.
How does revenue cycle analytics software improve provider revenue?
Given the many places where money changes hands during the patient journey, practice groups can lose track of just which of their processes and workflows leak the most revenue.
Revenue cycle analytics software finds these revenue leakage points and even provides insights as to why they occur. Common sources of inefficiency are coding, lack of up-front patient pay estimates, and prior authorization and claim denials.
When the revenue cycle analytics software pinpoints sources of revenue leakage, you can analyze the reasons behind it. Revenue improves once these issues are rectified.
For instance, revenue lost during patient access could reflect a high prior authorizations denial rate. The revenue cycle management team can explore whether prior authorizations issues stem from their physicians falling short on proving medical necessity, staff making clerical errors, or coders using retired or incorrect codes. With the root cause determined, you can then create a plan to rectify the issues. Clearly, these three scenarios involve different team members (clinical, clerical, coders), and distinct process breakdowns. After the new, repaired process is implemented, the revenue cycle analytics software can track and measure improvements.
You can start by addressing areas where most revenue leakage is occurring, and then move on to other areas. For instance, should the software reveal that certain surgeries are not recouping the revenue expected, you can analyze charge capture to find common missed charges. (The Healthcare Financial Management Association reports that the average hospital loses up to 1 percent of its net charges due to missed charges.) Comparing all charges a procedure typically involves to those your team actually charged reveals every charge that should have been included.
Working revenue leakage areas one at a time like this may take some time, but the improvement in revenue integrity lasts for years to come.
While most think of revenue cycle analytics software as benefiting the provider, healthcare leaders are increasingly reporting that efficient operations and a positive financial experience fuel patient satisfaction, too. And of course, it takes satisfied patients to keep provider revenue rising (think: return visits and referrals). An Accenture survey reveals that 64% of patients intend to switch providers if their expectations are not met.
Patients have positive experiences when they can get in to see their doctors within a reasonable time period. Revenue cycle analytics software can reveal scheduling bottlenecks that need to be broken so that patients can get in as soon as possible.
Prior Authorization Approvals
Patients also have positive experiences when their prior authorizations come in approved on the first submission. Waiting on a prior authorization appeal that was triggered due to lack of documentation or a coding error only causes frustration. As mentioned above, revenue cycle analytics software pinpoints the common errors payers report in a provider's prior authorizations. Rectifying these errors improves patient outcomes because they are seen faster.
Patients also appreciate providers that ease the financial end of their relationship. Soaring healthcare costs and patient healthcare financial responsibility (along with rising inflation) have deepened financial barriers to care. According to a recent report from the Kaiser Family Foundation, 41% of Americans currently face medical debt.
As more patients struggle with affordability, they appreciate providers who can work with them on payment. The predictive analytics feature of some revenue cycle analytics software solutions can pinpoint the patients with the highest likelihood of delaying payments or even failing to pay. With this information, providers can reach out to this population to set up payment plans, or even help them find insurance eligibility they may not have known they have. Yep. Revenue cycle analytics software does that too.
When 90% of patients say a good financial experience underlies their decision to return to a provider, it behooves providers to shore up their payment systems. Revenue cycle analytics can help.
Improved Payer Contract Terms
Prescriptive and comparative analytics can help organizations compare reimbursements and benefits in their contracts, giving them the data to negotiate better terms. With the average provider group juggling 16 to 20 different payers, the ability for one staff member to know just which offers the best overall packages is almost impossible.
Insights derived from contract data put these answers right in front of providers, giving them the confidence to press payers for more favorable reimbursements for themselves AND better benefits for their patients–the whole reason for becoming a provider in the first place!
Revenue cycle analytics isn’t just about historical data. When predictive analytics is implemented, it can identify potential risks before revenue is lost. It does use historical data, but in this case, it uses AI and ML to project trends or what’s coming.
With these potentially harmful trends outlined, you can then apply prescriptive analytics to suggest how best to address them. Predictive analytics uses outcomes from the past to prescribe the best steps to take to avoid predicted coding and billing errors, patient scheduling delays, or prior authorization and claims denials.
With this information, the provider can review coding protocols or prior authorization and claims workflows to find errors.
For example, if the data indicates a high number of future claim denials, a healthcare organization can preemptively review its claim submission process to reduce these denials.
Performance Benchmarking and Improvement Mapping
With your most dire internal revenue issues addressed, it’s time to improve revenue integrity by comparing your operations with those of other healthcare organizations as well as industry standards. This is where comparative analytics comes in.
Comparative analytics uses a database of industry benchmarks and competitor data to evaluate data on provider and system performance, risk factors, environmental factors, and patient populations. Using this information, you can establish your baseline data and map a path for future improvements. Use this data to justify performance-enhancement initiatives to your team and win their buy-in.
Data and insights revenue cycle analytics software delivers
RCM analytics software offers healthcare providers valuable insights to improve financial performance, streamline operations, and enhance patient services. Let's take a closer look at the various types of data and insights it delivers. Examples follow each instance.
Patient Financial Data includes information regarding patient payments, insurance coverage, and outstanding balances. Analytics can offer valuable insights into patient payment behavior patterns and the effectiveness of collection strategies.
- For instance, an analysis might reveal that a significant number of patients delay payments beyond 60 days. Offering early payment incentives or online payment options could improve collection times.
Claim Denial and Underpayment Data obtained from claims analytics reveals common reasons for denied claims, the departments or procedures most affected, and the financial impact of these denials. Additionally, it helps identify underpaid claims.
- For example, if data shows a high percentage of orthopedic surgery claims are denied due to coding errors, the hospital might consider additional training for the coding team or exploring a computer-assisted coding solution.
Payer Performance Data includes information about the performance of various insurance payers, such as denial rates, payment timeliness, underpayments, and adherence to contracts.
- For example, if an insurance company consistently pays less than the contracted rate, a hospital can use this data to renegotiate the contract or decide whether to continue working with that payer.
Coding and Billing Data involves data on coding accuracy, charge capture, and billing practices. All help identify revenue leakage or inefficiencies in the billing process.
- For instance, if a provider group identifies recurrent missed charges in one department, it can implement a charge capture tool to ensure proper billing for all services rendered.
Operational Data comprises information on the efficiency of revenue cycle processes, such as claims processing time, collection times, and staff productivity.
- For example, if the data shows an increase in the average days in accounts receivable (A/R), the billing department may need to re-evaluate their follow-up processes with payers.
Revenue and Profitability Data includes high-level financial data like revenue, costs, profit margins, and key financial ratios, providing an overall view of the organization's financial health.
- If a specific specialty consistently generates lower margins than expected, the healthcare provider may need to consider investing in equipment or staff to increase profitability.
Patient Access Data encompasses data related to patient registration, insurance verification, and benefit eligibility, which can help identify issues in the patient access process that lead to claim denials or payment delays.
- If a significant number of claims are denied due to insurance eligibility issues, automating the insurance verification process at the time of patient registration may be beneficial.
Contract Management Data helps organizations understand the financial implications of different contracts and identify opportunities for renegotiation.
- For example, if an analytics tool reveals that certain payer contracts consistently result in lower payments, the healthcare provider can use this data during contract renegotiation to advocate for more favorable terms.
Patient Satisfaction Data includes feedback and survey data pertaining to the patient's financial experience, which can be utilized to improve overall patient satisfaction.
- If patients are rating the waiting room experience low, providers may want to retrain reception staff, install televisions with helpful health information, or find ways to speed intake.
How does revenue cycle analytics software work?
While every medical practice has an EHR, as well as revenue collection, claims and billing systems in place, not every practice employs processes or technology to analyze the effectiveness of its revenue collection. Data comes in from many sources, mostly the EHR, and your billing and practice management systems. Once collected, this data is moved to a unified repository–typically a data warehouse–where it’s then properly formatted and qualified in preparation for analysis.
After the data is formatted and unified, revenue cycle analytics software uses statistical analysis, data mining, and machine learning algorithms to analyze it. The analysis is then distilled into various reports defined by predetermined metrics of interest. The software displays these reports in a dashboard in a way that reveals trends, inefficiencies, and improvement opportunities.
Types of revenue cycle analytics software
Software vendors prioritize the types of analytics they include in their products based on the client problems they’re trying to solve. Some include all of the following analytics types. Others feature just a few. Read through to determine which has the most potential for improving your revenue.
Descriptive Analytics Software is one of the most basic, ubiquitously available analytics types. This algorithm draws conclusions about the past using historical data. For instance, providers may analyze the number of denied claims in the past to identify common reasons for denials and find solutions.
Diagnostic Analytics Software analyzes data to determine the causes behind specific events. In revenue cycle management, it involves investigating why certain claims were denied or why a particular month had lower revenue.
Contract and Payer Analytics Software helps organizations assess the financial performance of their payer contracts. It aids in identifying problematic contracts, underpayments, and trends for negotiating more favorable terms.
Comparative Analytics Software compares a healthcare organization’s revenue cycle performance to similar organizations, identifying areas of underperformance and opportunities for improvement.
Predictive Analytics Software utilizes statistical algorithms and machine learning techniques to anticipate future outcomes based on historical data. In revenue cycle management, it can predict payment delays or identify patients likely to have trouble paying their bills.
Prescriptive Analytics Software employs advanced tools to recommend courses of action. It assists in making informed decisions about revenue cycle management processes, such as approaching a patient about an unpaid bill or optimizing claims submissions.
Real-Time Analytics Software involves analyzing data as it enters the system, allowing for timely identification of potential issues with new claims before submission to the insurer.
Now that you know the subcategories of revenue cycle analytics software, you can talk intelligently with vendors, ensuring the product you select matches your needs.
Key features of revenue cycle analytics software
A range of companies have developed software to analyze the provider revenue cycle. While each may target a specific market and varying use cases, most share these common features.
Comprehensive data management includes automated data capture, normalization, and validation to ensure easy access to necessary information and tracking of revenue cycle performance indicators.
Accurate Business Intelligence
The software should flag anomalies, identify trends, and offer precise reports and dashboards. Robust business intelligence tools help identify areas for improvement and optimize financial processes.
The software should allow for customizable configurations that align with unique healthcare organization needs. This includes defining performance indicators, billing rules, and automated workflows. Customization optimizes performance and tailors the software to specific requirements.
Robust Security Features
With increasing cyber threats, the software must have robust security measures to protect sensitive data. It should maintain HIPAA compliance, offer role-based security access, and have data backup and recovery features to ensure data privacy and integrity.
Revenue cycle analytics software companies understand that most provider staff, given their heavy healthcare responsibilities, require a user-friendly interface that’s easy to navigate and locate information without requiring specialized training. An intuitive interface ensures access to data and informed decision-making across the organization.
Get Visibility into Your Revenue Cycle Performance with MD Clarity
The long-term financial stability of any healthcare organization has always been directly correlated with the integrity of its revenue cycle. Revenue cycle analytics software is a crucial tool for streamlining processes, reducing billing errors, improving patient satisfaction, and speeding up reimbursement.
MD Clarity’s tools show where your organization is leaking revenue. From patient collections to payer contract performance, you can find your best opportunities for revenue recovery. Get a demo to see how MD Clarity restores revenue to provider groups and management service organizations.