Mitigate Medical Billing Challenges with Intelligent Data Capture Solutions
The healthcare industry deals with large volumes of billing records for patients daily. Many healthcare providers suffer from inefficient or inaccurate billing, putting negative pressure on their revenue cycle.
The revenue cycle of a healthcare provider starts from the time a patient registers and ends when the final bill is either paid by the patient or sent for an insurance claim. Delays in the accounts receivable process, claims processing, or rejection of claims by the insurance company, negatively affect RCM (revenue cycle management).
Optimizing RCM is a key concern for healthcare providers to stay profitable, provide high-quality patient care, and deliver positive patient health outcomes.
The accuracy and efficiency of medical billing processes thus become a focal point for healthcare institutions.
Challenges in medical billing and coding
Healthcare organizations must ensure that crucial information is properly captured in each step of the revenue cycle.
Challenges like manual billing errors, incorrect or insufficient patient information and medical coding inaccuracies produce blocks in the revenue cycle—healthcare providers who tackle these proactively ensure a smooth revenue cycle.
Let's look at these challenges in more detail:
Bad quality of patient data
The first step in the healthcare revenue cycle is when a patient walks into a healthcare institution, and front-end staff collect initial patient information. It is vital to collect sufficient and accurate demographic data, medical history records, and insurance-related information during the patient registration process. Importantly, front-end staff must verify the patient's health insurance status and coverage. They must clearly establish insurance eligibility at this point as this information becomes the basis for further billing, payments, claims and reimbursements. When such data is not correctly entered into the provider's billing system, it can lead to future revenue cycle complications.
Overcharges in medical bills
Financial services provider NerdWallet found that 63% of American adults surveyed indicated receiving medical bills that cost more than expected.
According to a NerdWallet survey of American adults conducted by Harris Poll, 49% of Medicare medical claims contain medical billing errors. These claims result in 26.4% overpayment for the care provided. 57% of consumers say they have received confusing medical bills. Incorrect billing or overcharging patients leads to messed-up accounts and reflects poor RCM.
Inaccuracies in medical coding
Medical coding refers to assigning the correct code to describe the type of service a patient will receive. It involves converting healthcare diagnosis, procedures, medical services, and equipment into universal medical alphanumeric codes. Medical coders ensure that these codes are correctly applied during the medical billing process. Any errors in abstracting the information from the physician's transcription notes, lab or radiology reports, or mistakes in assigning the correct codes can create problems with claims processing and lead to insurance denials.
According to The Practice Management Institute, incorrectly coded claims resulted in $6.7 billion in improper Medicare payments.
Moving from paper-based billing to digitization and automation
You may be surprised that the healthcare industry embraces the latest technology and procedures in treating diseases and medical conditions—but when it comes to internal processes such as billing and payments, primitive paper still rules the scene!
A survey from the Medical Group Management Association and Navicure found that 77% of group practices still do paper-based billing.
Digitization in medical billing can help reduce healthcare fraud and errors.
A move to digital can bring significant benefits to the healthcare industry.
How intelligent data capture benefits the medical billing process
The healthcare billing system is highly document-dependent and ridden with manual tasks, making it time-consuming, inefficient and prone to errors.
The first step is to digitize all paper-based billing processes, convert paper to digital, and achieve high-quality data that is accurate and readily available at the click of a button.
Advanced intelligent capture software automatically identifies keywords or phrases in all types of documents, including those containing machine print, handprint and cursive handwriting.
Machine learning and Natural Language Processing (NLP) enable data capture platforms to automatically recognize and extract data from medical documents for proper coding and billing.
Paper records such as medical records, physician notes and billing documents are scanned as image files. These can include both structured and unstructured data.
At Revolution Data Systems (RDS), we implement and service OpenText Intelligent Capture—a platform that uses advanced machine learning technology to sort and classify all your medical documents. It automatically recognizes new content, whether it is an email, attachment, or scanned records. In addition, it is smart enough to recognize key information contained in the documents or images, such as a vendor name or key code or invoice number. It recognizes this text, checks it against its trusted data sources and automatically adds it appropriately in the metadata. Intelligent document processing speeds up medical billing. The process involves the following steps:
Collect all medical documents, including medical records, physician notes and billing documents.
Intelligent data capture extracts data from paper documents and integrates it with major process workflows.
Intelligent Data Processing (IDP) automates medical bill coding for the accurate generation of invoices.
Combine the data into centralized repositories and automatically generate weekly and consolidated bills to reap significant savings that can be passed on to customers.
Automated data capture in medical billing has clear advantages
It brings down invoice and claims processing costs
It reduces the chances of internal or external fraud
It reduces errors in billing
It provides transparency for consumers into the healthcare process
RDS offers intelligent data capture and data extraction solutions that enable medical practitioners to deliver accurate and quality healthcare services. Efficient document scanning and automated data attribution of all medical documents are critical. Making this data interoperable between existing systems such as an ERP or an HMIS is also of utmost importance.
Talk to RDS to implement medical billing automation using advanced and integrated solutions for document scanning, intelligent capture and data extraction. Talk to our OpenText expert consultants to understand how to reduce costs, improve revenue cycle management, and ultimately help physicians address patients more effectively!