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Revenues may soon improve for hospitals and healthcare organizations. Since the COVID-19 pandemic, patients have been receiving care remotely and practicing social distancing. It makes sense to consider making the most out of your revenue cycle management system.
Revenue cycle management (RCM) software helps to track billable activities of patients from appointment booking through the end of the payment process. The technology used in RCM software is robust to streamline medical billing and financial procedures, thus enhancing revenue streams and reducing any financial errors.
Patient Access and Experience
Patient experience is now one of the key issues impacting the healthcare industry. There is a huge information deficit in the area of patient payments.
Patients ask “How much should I pay from my pocket?” The answer has been surprisingly difficult to find. Patients must get quick and easy access to information about services performed and corresponding charges; the amount expected to be paid by their insurance company; and the out-of-pocket expenses they are expected to bear. It is important to include the aspect of the No Surprises Act, which complicates the situation for both providers and patients.
We anticipate patient access and experience to improve with new technologies that can project the costs they need to bear, improved omnichannel information availability, and improved payment plans. Patient financial services will go through a much-needed overhaul.
Prior-Authorization and Eligibility Verification
While great tech exists for information interchange, prior authorization and eligibility verification tech adoption have lagged because of a lack of standardized documentation and information exchange protocols. With clearinghouses now modernizing, there is new hope for API-driven information exchanges.
Autonomous Coding
Automation tech is seeing increasing adoption, and there is a general perception that coding, billing, and accounts receivable problems will be solved through automation. Artificial Intelligence, Machine Learning, and Robotic Process Automation technologies provide great promise to lower labor costs. Medical coding is becoming data-driven and autonomous with improved standardization through ICD-11 and a better combination of virtual scribing, Universal Medical Language Systems (UMLS), OCR, and natural language processing (NLP). While these are still early days, coding tech is yet to prove effective in finding discharges not fully coded (DNFC) and arresting revenue leakage.
A/R, Denial Management, and Appeals Filing
Accounts Receivable (A/R) status has moved from calls to portals. We see increasing relevance for chatbots using conversational artificial intelligence (AI) in A/R and denial management filing. Data structures can now power customized appeals filing as well.
Focus on the Front-End
Most revenue cycle leaders agree that they need to solve revenue cycle issues in the front-end rather than elongate the cycle and wait to address them in the back end. They recognize that they need to link prior authorization, revenue integrity, clinical documentation improvement, and denial management to accelerate their revenue cycle. The ability to quickly identify denial issues, determine root causes, and develop solutions to reduce these denials through an iterative model that focuses on denial prevention is considered the key to addressing revenue cycle issues.
Underpayment and Analytics
The Hospital revenue cycle is fraught with underpayment issues. Contract analysis and underpayment identification can help arrest underpayments. As the shift to more branded, national healthcare practices happens, performance analytics becomes a critical business function. Practice-specific analytics using standard measures and Key Performance Indicators or KPIs will enable accurate views of performance and drive corrective action.
Labor and staffing complexities can be alleviated by automating repetitive tasks, enabling current and new staff to focus on more core duties. This is one way that healthcare can become more efficient and increase its operation margins. Outputs from these technologies are able to create interoperable data that can be sent and ingested into multiple systems for better analytics.
