revenue cycle analytics Archives

Yashica Chopra
January 26, 2025
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Revenue Cycle Management in Healthcare: Your 2025 Playbook

RCM is a key process in the healthcare sector and impacts revenue and patient management. Here, we’ll discuss the top practices to enhance revenue cycle management in healthcare and the role of RCM analytics in the industry. There is an increase in demand for big data analytics in the healthcare industry to handle the increasing generation of new data every day. Technology has become an integral part of the industry for effectively managing large data volumes and providing data-driven decision-making analytics. Different types of services, like patient management, revenue cycle management, financial management, data management, etc., are offered by data analytics companies to help healthcare centers streamline their internal processes. RCM analytics is similar to healthcare analytics but focuses on the financial aspect of the business. Statistics show that the global healthcare analytics market was $44.8 billion in 2024 and is projected to reach $284.5 billion by 2035 at a CAGR (compound annual growth rate) of 18.3%. RCM, aka revenue cycle management, is one of the core functions in the healthcare sector. Setting up a comprehensive RCM system can reduce the risk of errors in patient data, reduce claim denials by insurance companies, and increase patient satisfaction with the healthcare center. In this blog, we’ll explore the role of RCM analytics and the best practices to follow when adopting the process. What is Revenue Cycle Management? Revenue cycle management is managing the revenue cycle in a healthcare center. A revenue cycle can be broadly classified into three stages – patient registration, preparing to claim insurance, and collecting the payment. These are further divided into multiple steps. But what is the use of RCM in medical billing? RCM combines various tasks and departments to create a pathway for the patient’s journey with the hospital. From the time the patient arrives at the hospital and asks for an appointment to the final bill payment after the treatment ends (and any other revisits), RCM ensures the patient’s data is accurately collected, recorded, stored, and shared with relevant parties to provide medical treatment and manage insurance/ payment for the services provided. RCM analysis minimizes the risk of mismanagement of these functions and increases overall efficiency. What is an Example of RCM? Let’s say, a patient with an ear infection visits the hospital for treatment. The front office staff will gather the patient’s details and give an appointment with the specialist. The report (tests and medication) recommended by the specialist has to be updated in the patient’s file. If surgery is necessary, the patient’s insurance details are collected so that the insurance company can contact them and file a claim to reimburse the expenses. When the patient goes home, the bill is settled by tallying the claim amount with the bill amount. The patient pays the balance, if any, to end the transaction. These are a series of tasks performed by different people over a period. With revenue cycle management in medical billing, these can be streamlined and accelerated using technology. Effective RCM enhances patient satisfaction while reducing the stress on hospital staff. What are the 12 Steps of the RCM Cycle? Now that you know what the revenue cycle process is, let’s look at the various stages of revenue cycle management. 8 Top RCM Practices to Follow in 2025 To get the best of RCM analytics, the healthcare center should follow the industry-wide best practices and be open to accepting new technology and modern processes. 1. Invest in Technology In a world where technology gives a business a competitive edge, not utilizing it can lead to chaos and decline. Considering the complex stages of revenue cycle management, healthcare RCM analytics include a range of tools and technologies. For example, a data warehouse has to be set up (on-premises or cloud) to store all the data in a central database. This data warehouse is integrated with input sources to collect patient data and connected with AI tools for data analytics and data visualization dashboards. More third-party integrations can be added to send the details to insurance companies for claim submissions. Invoice generation and payment management software are also integrated with the data warehouse to create an interconnected RCM system that provides real-time information to the hospital staff. 2. Collect Patient Data Early Patients are a key part of the healthcare system. Collecting all the necessary information about the patient will create a better profile and lead to more effective treatment. Similarly, asking patients about their insurance details right during the initial registration will allow the hospital to get the required pre-authorization for claim submission. Instead of waiting until bill generation, ask for the information when they register the first time. By storing this data in the central repository, the staff can access it whenever necessary. The claims can be submitted quickly, and patients can be informed in advance about any extra payments they would have to make if the insurance payout doesn’t cover the entire bill amount. 3. Optimize Patient Registration Process Collecting patient data upfront is the first step. This information has to be verified to avoid complications later on. For example, a simple clerical mistake in adding the insurance policy number can result in claim denial and loads of paperwork. Verifying the insurance details as soon as possible will prevent such delays and decrease the claim denial rate. Similarly, RCM performance analytics can be used to optimize the registration process and simplify it for the patients. After all, people don’t want to fill out a dozen applications just to get an appointment with a doctor. Identify the bottlenecks in patient registration and eliminate unwanted steps. Keep the forms straightforward but also include enough fields to collect the required information. 4. Aggregate Patient Data (Digitally) Digitalizing the process ensures patient records are moved to the data warehouse and can be accessed by doctors and admin whenever necessary. This is also important to process insurance claims as the details should be shared with the insurer. Thankfully, today’s revenue cycle management technology is advanced and

Yashica Chopra
January 15, 2025
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Inhouse vs Outsourced RCM Analytics – The Ideal Choice in Healthcare?

Revenue cycle management (RCM) is managing patient data, claims, and payments from start to finish. Here, we’ll discuss the role of RCM analytics in healthcare and determine the differences between in-house and outsourced analytics services. The healthcare industry deals with many administrative and financial tasks. From patient applications to transactions with insurance companies, the processes can be complex and time-consuming. This is one of the reasons why billing takes so much time in hospitals, causing more delays and frustration for the administrators and patients. Fortunately, RCM provides an effective solution for this. To improve things, RCM analytics identifies the root cause of delays and helps streamline the entire process. But what is RCM? What does RCM stand for? RCM is Revenue Cycle Management, the process of identifying, collecting, and managing payments from patients of the healthcare center. It is necessary for patient management and financial management. The RCM market is expected to grow at a CAGR of 12.2% between 2025 and 2032 to reach $342.6 billion by 2032. Revenue cycle management (RCM) software streamlines and automates revenue cycle management. So, what is RCM software, and how does it work? RCM software is similar to medical billing software that tracks the patient’s case from initial registration to discharge. It is used to calculate the final payment, insurance payouts, etc. It also maintains a proper record of each patient with ID. However, healthcare establishments face many problems in medical billing and RCM. RCM analytics provides a reliable solution for these issues. But should a hospital opt for in-house billing or outsource the task? Let’s find answers to these questions and more! RCM Challenges in Healthcare Before we explore the differences between how in-house RCM and outsourced analytics work, let’s first understand the challenges of healthcare RCM analytics. Human Error The hospital staff is often overworked and stressed due to the extensive responsibilities they handle. By asking them to manually manage patient registrations and payments, there’s a high risk of human error or a wrong entry. Complex Process The roles and responsibilities of front-end and back-end employees are different. RCM has to effectively bridge the gap to minimize confusion, incorrect information, delays, etc. The process is just too complex and stressful without using the latest technology. Missing and Outdated Data With the administration fragmented into individual departments, there’s a risk of patient data missing from files. For example, if someone forgets to mention the information about the patient’s insurance in a report, it could lead to a series of confusion and miscommunication. RCM data management through modern data warehousing services can solve this problem. Changing Regulations The regulations in the healthcare and insurance industries can change, resulting in confusion among patients and administrative departments. It could be something as simple as a hospital not having a tie-up with a certain insurer, leading to more paperwork and exploring alternate options. Patient Volume Hospitals are among the busiest places on earth. Unfortunately, this puts excessive pressure on the staff to work around the clock. The high patient volume directly translates to tons of paperwork, reports, and bills. Using RCM software and data analytics helps handle this high volume. Fraud Detection The hospital staff also has to deal with fraudulent transactions and wrong insurance claims. Manually investigating each claim is exhausting. What if they can detect and predict such activities proactively? RCM analysis can be used for fraud detection to identify potential frauds in the early stages. In-house vs. Outsourced RCM Analytics in Healthcare: Which One to Choose RCM analytics can help healthcare businesses overcome various challenges they face in managing patient data and claims. But should they develop an in-house RCM analytics model or outsource RCM analytics to a third-party service provider? Which method is more effective? In-House RCM Let’s first check out what in-house RCM analytics in healthcare and medical billing actually are. In-house RCM is also called medical billing. The entire setup is managed by the hospital staff with little or no input from service providers. The service provider might build the RCM analytics model and hand over the responsibility to the hospital staff. This gives the business more control over the process but also increases workload. Advantages of In-house RCM Disadvantages of In-house RCM Outsourced RCM Analytics Outsourced RCM analytics are offered by third-party companies that handle all the responsibilities of setting up the analytical model, creating integrations between different systems within the establishment, and managing the central repository with patients’ details. What is outsourced RCM analysis in healthcare and medical billing? It is an interconnected approach to setting up a comprehensive and robust management system on a cloud platform to streamline and automate financial management in the healthcare center. A single interface or platform like the Power BI dashboard can be used by various departments like the front desk, billing, clinical, etc., to access patient data and update the records in real-time. It is a collaborative model aimed at boosting overall efficiency, performance, and revenue for the business. Advantages of Outsourced RCM Analytics Disadvantages of Outsourced RCM Analytics What are the 12 Steps of RCM? Data analytics companies offer nearshore and offshore RCM analytics services in the healthcare industry. They set up RCM analytics to streamline the twelve steps of revenue cycle management, manage patient data, track claims, and increase ROI. They start by identifying the KPIs to measure and improve the establishment’s financial health. What is a KPI in RCM? KPI stands for Key Performance Indicator, a metric used to measure if the RCM cycle is aligned with the hospital’s vision and objectives and is delivering the required results. The twelve steps of revenue cycle management in medical billing are as follows: Fortunately, hospitals can manage all these steps by investing in the latest revenue cycle management technology and partnering with analytics service providers to maintain the system. This reduces the pressure on hospital employees and enhances patient experience. It also maximizes efficiency and increases reimbursements by limiting denials. Conclusion Depending on the business’s mission, vision, and objectives, RCM

Yashica Chopra
June 28, 2024
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A Comprehensive Guide to Revenue Cycle Analytics- All You Need to Know

Revenue cycle analytics is the process of analyzing the revenue cycle data to derive actionable insights for decision-making. Here, we’ll discuss the role of data analytics in revenue cycle management and how it can help a business generate more revenue and become successful. Revenue is one of the core factors a business should consider. After all, how long can an establishment function if it doesn’t generate income while incurring expenditure? Many organizations have processes set for revenue cycle management to determine their finances and returns. Reports show that the revenue cycle management market is expected to touch $1.209 trillion by 2030. Additionally, statistics show that the global big data market is expected to reach $90 billion by 2025 and $103 billion by 2027. Almost every industry is investing in big data analytics and business intelligence tools to derive real-time insights and streamline its businesses. But what is a revenue cycle? What role does revenue cycle analytics play in an organization? How can a business effectively use business analytics and big data to derive advanced analytical insights from revenue cycles? Let’s find out in this blog! What is Revenue Cycle Analytics? Revenue cycle analytics is the process of analyzing the revenue streams of your business to identify weak areas and find suitable solutions to address them. The aim is to effectively increase the business income and optimize the entire revenue generation process by relying on meaningful insights derived from analyzing large amounts of business data. You can use several data points and parameters to track, measure, and analyze the revenue cycle in your organization. What is a Revenue Cycle Analyst? A revenue cycle analyst is the person who is responsible for optimizing the revenue cycle in your business. Their responsibilities include the following: The analyst has to determine and track various revenue cycle metrics, share the reports with decision-makers, offer actionable recommendations, and assist the top management in making efficient and proactive decisions to boost business revenue. Typically, businesses look for data analysts with experience in the finance and accounting industries, as well as economics and statistics. What is the Revenue Cycle Process? A revenue cycle contains multiple recurring steps necessary to complete an accounting process to record the revenue generated by the business. This involves tracking transactions like sales, returns, claims, offers, etc. Revenue cycle assessment helps establish financial stability in your business and find more ways for growth. It can boost your revenue and profits by evaluating various business processes and offering insights about how to increase overall efficiency. It also has a role in enhancing customer satisfaction with your business. The revenue cycle process starts with the order placed by a customer and ends when the payment is received. It repeats for every order by every customer. The following are the elements found in the revenue cycle process: Why Use Data Analytics in Revenue Analysis? Revenue analysis is done by the finance and accounting department to help your business make correct investment decisions. However, traditional methods are time-consuming and have certain limitations. By using data analytics, you can take advantage of the latest technology to streamline and automate the analysis of revenue. This saves time and provides real-time insights to decision-makers in different departments and all verticals. Reduce Costs One of the main reasons for using data analytics for revenue management is the cost. Every business wants to cut costs and find ways to generate more returns from the investment. Analytics derives insights by analyzing large datasets in a quick time. It can provide reports about which areas to work on and how to plug the leaks to prevent revenue drain. Enhance Revenue While reducing costs is vital, increasing your revenue is equally important. Wouldn’t it be beneficial if you could find more revenue sources for your business? This can lead to greater profits. Revenue cycle analytics can identify ways to generate more revenue. Moreover, the analytics run continuously, allowing you to regularly improve your financial position. Improve Cash Flow When you analyze historical data using advanced tools, you can uncover trends/patterns and correlations that cannot be detected through traditional methods. This provides a clearer picture of the cash inflow and outflow channels. You can forecast the requirements in advance and plan accordingly to prevent last-minute roadblocks. Determine the Price How do you set the pricing for your products and services? Many factors come into the picture, like competitors’ rates, industry standards, your investments, time taken, resources consumed, quality, etc., by using data analytics to manage the revenue cycle, you can accurately price your offerings and bring more flexibility and transparency to the entire process. Streamline Internal Processes Revenue cycle analytics is not limited to making financial decisions. It can also help streamline other internal processes to increase overall efficiency and performance. For example, automation is a great investment choice and gives high returns. It can be implemented in all departments to save time and allow employees to focus on the core aspects of the job. Prevent Revenue Leaks Revenue leaks are a concern for many businesses. Missed payments, extra charges, fines, dues, double orders, cancelations, etc., can drain your revenue over time. While the payments may be small, they add up and can impact your revenue. Revenue cycle management analytics helps identify such leaks and can plug them into by automating workflows. Risk Mitigation Financial decisions are always considered a risk. Additionally, fraudulent transactions, false claims, and other issues can lead to losses. By analyzing revenue cycles using data analytics and business intelligence tools, you can find effective means to minimize such risks. Moreover, by partnering with reputed managed analytics service providers, you can ensure you comply with the industry and regional standards/ regulations. How Can Big Data Analytics be Used in the Revenue Cycle? Big data analytics in the revenue cycle can help your business in many ways. Streamline Claims The insurance and healthcare industries often deal with claims which are complicated, confusing, and stressful. The procedure can be simplified and streamlined through data analytics