Importance of Data Analytics in Revenue Cycle Billing
Revenue cycle billing is the crucial factor that keeps the financial health of a medical
organization up and running. Healthcare organizations invest millions of dollars in forming a good
team of billing professionals and revenue cycle leaders. While they create a massive supporting
pillar for healthcare organizations, data analytics balances the real issues that the RCM industry
faces. Investing in scientific data management and analytics tools has become as important as hiring
a group of experts. It is why more than 33% of the healthcare organizations in the USA have gone
completely digital with their RCM workflow.
Data analytics provide deep insights into the organization’s daily business with predicted trends
and functions of the future. The management can make better-informed decisions with the help of
these tools. It is why data science has acquired such an essential role in the healthcare financial
domain. This article will take you through the various steps of data collection in an RCM process
and how you can reap the benefits with the help of the proper analytical tools. Read on to know
more.
Steps of Data Collection in Revenue Cycle Billing
Revenue cycle billing is a comprehensive process with several steps involved, and there are specific
professionals assigned for each step. Here we have differentiated the three significant areas where
the billing team collects the data from the patient and processes it further.
Patient Registration Process:
Healthcare organizations collect 40% of the critical data during the
patient registration process
before the service is rendered, making it one of the most vital steps of the revenue cycle billing.
The billing team usually asks for the following details during this period:
Name of the patient
Address and contact details of the patient
Insurance information for multiple health plan providers, if any
Details of the clinical procedure that a physician referred to
Any documents of medical necessity that the provider has forwarded
The billing team uses this primary data to proceed with some of the crucial processes of RCM. The
details are used to verify the insurance information, apply for pre-authorization with the insurance
company, and estimate a fair price for the services to be rendered. They also prove to be beneficial
to plan financial counseling for the patient if they need any. Any error in data management during
this stage could result in claim denials in the future.
Medical Service
The billing team proceeds further with the charge capture process during the service. They take all
necessary equipment and procedural cost into account and register the corresponding codes to the
patient’s history. Since the code capture is vital for preparing the final bill, the data management
process needs to be accurate and updated. The method also mentions the details about what portion of
the bill is out-of-pocket and which part will be paid by the insurance company.
Patient Discharge Process
The medical bill is final at this stage of patient discharge, but there are still a lot of data that
needs to be checked for a clean claim to be processed. Experts say that the revenue cycle billing
team should be aware of the Discharged-Not-Final-Billed (DNFB), which lists services that have not
been billed. The data management tools need to have a smooth working functionality to differentiate
any errors that might have skewed the final bill for the patient. Any data mismatch during this
process could lead to claim denials and disrupt the cash flow for the hospital.
How does Data Management help in the process?
Superior data management tools help validate the collected data during the revenue cycle billing
process. The devices run the data through their system, scrub them for any minor errors, and
cross-check the collected information with the current data from the insurance company.
They are capable of combining loads of data from the Scheduling Database and Master Patient Index
(MPI) so that you do not face any trouble with duplication of claims. Their agility and smooth
functionality reduce the time consumed by the teams and increase efficiency.
The charge capture process includes several procedures
and needs close attention to detail to get it correct. That could become difficult for the billing
team in a hospital catering to hundreds of patients in a single day. Data analytics tools help to
keep your charge integrity intact by running them for any errors and intimidating you with the same.
The data analytics performs the most during the claim processing period. They run the claims by
comparing them with the historical data to give you accurate trends for collection management, days
in Accounts Receivables, denials management, and payer analysis.
Data Analytics Techniques
While you can customize your data reports according to your needs, data analytics follows three
basic techniques to give you different perspectives. All three are incredibly beneficial in helping
the management stay ahead of the curve.
Descriptive analytics takes into account the historical financial data of the organization and
compares the same with the current best practices of the revenue cycle billing industry. The results
are helpful in documenting any revenue leakage that might have occurred due to insurance issues, the
external market, or the internal operational workflows.
Predictive analytics, as per its name, ‘predicts’ any future trends in the revenue flow of the
organization. The tools use Machine Learning powered systems to mine the correct data and model it
according to the needs of the customizations. The trends can help the management tweak the current
revenue cycle billing process for the right optimization.
Prescriptive analytics helps the organization build a road map for the future. The data models show
each course of action and its possible outcome for the company. The suggestions are usually based on
the payer-provider collaboration in the past to predict how you can optimize your operational costs
and maximize your margins.
Data analytics is a growing industry with evolved tools coming up with each passing day. Make sure
you include the data management procedures in your upcoming workflow digitization journey to get the
best returns on investment.
We hope this article helped you understand the importance of data management in healthcare and how
analytics can help you optimize the revenue cycle billing. Please connect with us in the comment
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