RCM Best Practices in Healthcare

Philip Siegel

· 27 Aug 2021

RCM Best Practices in Healthcare

Revenue cycle management is the practice of capturing, managing and collecting patient service revenue. The revenue cycle itself, starts at the time of the appointment when a patient’s details are captured and ends when the vendor balance is completely settled. A typical revenue cycle management consists of various tasks and functions such as Patient Scheduling, Eligibility & Benefits Verification, Medical Coding, Charge & Demographic Entry, Payment Posting & Reconciliation, Payer Account Receivables Follow-Up and Denial Analysis.

Traditional revenue cycle management practices were almost entirely back-end processes that would begin only after the point-of-service. However, recent economic challenges and inefficiencies in the existing system have shifted the focus to the front-end management, particularly, in areas of patient access. More than half of the information on a bill is collected prior to or at the point-of-service and accessing it on the front-end only ensures its accuracy and validity. Effective revenue cycle management thus begins with effective data gathering. There are numerous technology-based solutions available in the market but the provider must look at ones that address the major aspects of patient access i.e. pre-visit eligibility verification, demographic verification, point-of-service insurance and collection workflow. In addition, the staff members should also be trained and educated in proper documentation practices, billing policies and procedures.

While gathering accurate information is the first critical step in revenue cycle management, making sure that the charge is posted (in a timely manner) with the right CPT and ICD-10 diagnosis codes forms the next. To ensure timely submission of clean claims it is always advisable to set benchmarks, like for instance, billing the claims within 48 hours from the date of service and conducting regular audits for coding and billing. The efforts of certified coders can be best supplemented with code-editing software to prepare the charges.

One should electronically file as much as possible but the key here is to follow-up and track down the submitted claims. A necessary yet often neglected procedure, the initial follow-up should occur no more than 15 days after the submission of claims and the subsequent follow-ups, every 7 days. The administrative costs and delays associated with billing patients can be reduced by offering options to receive and pay bills online.

As a rule of thumb, denied claims should ideally take less than 2 percent of the care provider’s net revenue. By monitoring the frequency and reason for denial, organizations can identify some real opportunities for improvement. Managing denials go hand-in-hand with the release of clean claims and preventing them is one of the basic elements of a highly functioning revenue cycle.

Hospitals across the country leak significant amounts of cash on a regular basis. A dollar not collected, has an unequivocal impact on principal projects, patient satisfaction and quality of care. A well-integrated revenue cycle management solution can thus improve the financial health of an organization by avoiding delays in payment, misplacing of information and errors.

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Top 4 Trends in Business Analytics

Companies stand to gain a greater ROI when they broaden and deepen their use of analytics. But in this expanding universe of data, traditional approaches (to analytics) might seem a tad too inadequate.

We take a look at few upcoming trends capable of impacting your intelligent data. Read on.

1. Visual Analytics– seeing is believable
Visual analytics can be seen as a combination of information visualization, data analytics and data transformation. Often deemed as a powerful means of understanding data, visual analytics makes an otherwise difficult-to-understand raw data easily comprehensible through visual representations and interaction techniques.

To get big insights out of big data, many organizations are implementing advanced data visualization with social network analysis capabilities. In its current evolution, visual analytics helps in representing relationships between different data sets in a more ‘dynamic’ way as opposed to ‘static’. A dynamic network is able to respond to changes (it can reflect the change that has happened, the sequence and the uncertainty) and also has the ability to integrate information from numerous “event-driven” information sources.

2. Business Intelligence (BI) and the Cloud
Cloud-based BI and analytics is set to take the world of analytics by storm. According to this report from Saugatuck Technology, cloud-based BI solutions will grow at a compound annual rate of 84 percent in the next two years and will be a major frontrunner in cloud-based solutions.

We can attribute this rise in popularity to a couple of reasons. Firstly, cloud-based BI platforms can store transactional information in an easy-to-understand format and users have the benefit of running reports, creating dashboards and performing other analytical operations. Secondly, businesses of all sizes can get granular insights from a mix of structured and unstructured data without having to expand their existing IT footprint or resources. In this way companies are able to store voluminous and rapidly-growing data and process it efficiently in real-time.

Cloud-based BI solutions work better when the company’s sales, financial, point-of-sale and social media data are effectively brought in together. The purpose is to provide a unified view of the organization’s business to enable better analysis and decision-making.

3. Mobile BI–BI on-the-go
Mobile users have become so accustomed to having their needs met by various mobile applications that it is not surprising to see similar experiences being created for a business environment as well.

The availability of high performance devices, the recent developments in the network infrastructure and the need to make faster and better decisions has propelled a surge in the adoption of mobile BI. With mobile BI, companies stand to gain better operational efficiency, real-time analytics and customer responsiveness. A recent Gartner report titled ‘Critical Capabilities for Mobile BI’, has even predicted that by 2013, 33 percent of BI functionality would take place via mobile devices.

When choosing a mobile BI solution, ubiquity, flexibility and security are factors of prime consideration. The dashboard should be able to perform the same way as it does on PCs and desktops and must also allow users build new reports on an ad-hoc basis.

4. Pervasive Analytics– when BI migrates to mainstream society
Consider the following scenarios: doctors being able to identify outbreaks from track reports of diseases, store managers replenishing out-of-stock products through point-of-sale data, customer service representatives having quick access to a customer’s credit history. These are a few classic examples of pervasive analytics where people on the ‘frontline’ are given access to some important data to make some important decisions.

So what is pervasive analytics? Pervasive analytics is a new wave of analytics in which anyone with a question can use data and BI to get the relevant answers. Like the examples above, it is about bringing business intelligence to individuals and empowering them with better decision-making abilities. Currently, there is a growing recognition among companies worldwide to make BI more ‘pervasively’ available throughout the organization.

To make this a possibility, the results of data warehousing and analytics must be directly embedded into the operational and transactional applications of the business. In addition, the company must also look at the degrees of training & non-executive involvement and data governance.

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