By: Paige Cerulli
Professional insights: Olga Khabinskaya
Technology and data are transforming the healthcare industry, and that includes the medical billing field. The increasing use of big data analytics can enhance medical billing accuracy in many ways, offering significant benefits to medical practices. Whether you’re been in medical billing for decades or are just beginning your career, learning to use and embrace big data analytics may help you do your job better and more efficiently, making you an asset to the practice.
How big data analytics can improve medical billing accuracy
The term “big data analytics” refers to collecting, processing and analyzing large amounts of data. That data can then be used to identify trends and provide insights that can help a medical practice optimize its operations. As big data is implemented in the medical billing process, it’s poised to help practices improve accuracy in several ways.
Olga Khabinskaya, Director of Billing at WCH Service Bureau, explained that there are many advantages to using big data analytics. “Big data analytics enhances billing accuracy by allowing us to pull critical information from various sources, such as a patient’s eligibility, plan benefits and service eligibility,” she said. “By analyzing clinical visits, pharmacy prescriptions, diagnostic testing and laboratory work from electronic medical records (EMRs) and other healthcare data sources, we can ensure claims are coded correctly. This creates a more transparent billing process and reduces claim denials by utilizing the correct CPT codes and including all relevant diagnosis codes.”
Big data analytics can create increased accuracy, which supports and empowers medical billers and coders. Increased accuracy makes for reduced errors and improved productivity and efficiency. Since medical billers and coders can be more accurate with big data analytics support, they can reduce income loss for practices. With fewer errors to correct, billers and coders can focus on new tasks rather than spending extra time addressing errors. The result is a more professionally run and streamlined billing operation, which can boost staff morale and satisfaction, too.
In fact, the increased accuracy afforded by big data analytics can affect many other medical billing elements, making big data a key addition to the industry. Here are some of the most essential ways big data analytics affects accuracy and efficiency:
Medical billing and compliance
Medical practices must continuously meet strict compliance and regulatory requirements, such as meeting Health Insurance Portability and Accountability Act (HIPAA) and International Classification of Diseases (ICD) requirements and billing guidelines. “Big data analytics helps by identifying patterns in claims data that may indicate compliance risks, such as incorrect coding or billing for non-covered services,” explained Khabinskaya.
“Additionally, real-time data analysis allows billing professionals to ensure documentation supports claims, reducing the risk of audits and penalties.” Avoiding audits can save medical practices substantial time and money. JB Martin Law estimates that during a healthcare audit, a practice may pay hundreds or thousands of dollars to attorneys or consultants who review their records and implement changes. The audit process can limit staff productivity and require staff retraining, so it’s ideal to ensure that the practice stays compliant from the start.
Patient billing experience
Since big data analytics can improve medical billing accuracy, they can improve the overall patient billing experience. Khabinskaya noted that analytics can reduce errors and improve billing transparency, creating a more streamlined experience. “By integrating data from different healthcare systems, facilities can ensure that patient bills are accurate and reflect all relevant services,” she said. “Predictive analytics can also be used to forecast patient financial responsibility, allowing facilities to proactively communicate expected costs to patients and provide payment plan options where necessary.”
Improving the patient experience can increase overall patient satisfaction and ensure that a patient’s touchpoints with the billing office are positive ones. Using predictive analytics to communicate expected cost can help a practice stand out from others, indicating that staff are dedicated to supporting patients and to putting in extra work to deliver an optimum experience. Given the increase of healthcare consumerism, in which patients are demanding higher quality service from healthcare providers, creating an enjoyable and positive patient experience is more important now than ever before.
Improved billing accuracy may bolster a practice’s patient retention rates, which can have a significant impact on the practice’s bottom line. According to Forbes, patient retention may deliver a decent return on investment, in part because a practice’s existing patients have a 60% to 70% probability of visiting the practice for services. That probability is just 5% to 20% for new patients. Additionally, patients who are happy with a practice may become a source of referrals, driving up the practice’s number of new patients without the practice having to invest in marketing or patient acquisition.
Revenue cycle management
The medical revenue cycle—or the process of efficiently billing patients and third-party providers for services and then collecting revenue—is a challenge to manage. According to Khabinskaya, predictive analytics can help practices to optimize their revenue cycle management. Using analytics, a practice can identify trends in claim denials and inefficiencies in billing workflows, and then they can work to correct those issues.
“By analyzing past billing data, healthcare facilities can forecast cash flow, improve collections and reduce claim rejections,” she said. “This ultimately leads to faster reimbursements, improved financial health for providers and better resource allocation within the organization.”
Fraud identification and prevention
Fraud is a pressing concern in medical billing, and quickly identifying fraud can help protect practices against significant losses. The National Health Care Anti-Fraud Association estimates that tens of billions of dollars are lost due to medical fraud each year. Estimates of exact fraud amounts range significantly. On the low end, 3% of total health care expenditures may be lost to fraud, but on the higher end, the estimate is as much as 10% of expenditures, meaning more than $300 billion is lost to fraud each year.
“By analyzing large datasets, facilities can detect unusual billing patterns, such as duplicate claims or services that were never rendered,” said Khabinskaya. “Machine learning models can flag anomalies in billing behaviors and help providers take proactive measures to prevent fraudulent activity. This not only protects the organization but also ensures compliance with insurance regulations.”
Additional benefits of big data analytics
In addition to enhanced medical billing accuracy, big data analytics offers other benefits. According to Khabinskaya, big data analytics are helpful with financial forecasting, resource management and optimizing payer negotiations. “It can identify payer trends, helping facilities adjust their billing strategies to maximize reimbursements,” she noted. “Additionally, data-driven insights enable providers to improve patient care by identifying gaps in treatment and ensuring services are billed correctly the first time.”
Challenges in implementing big data analytics in medical billing
While big data analytics can enhance billing accuracy and offers several other benefits, there are still some challenges to its adaptation that practices will need to navigate.
Big data needs to be compliant with HIPAA regulations; it must protect patient personal information against data breaches. Medical practices need to ensure that any data and programs they use meet these regulations.
More and more, cybersecurity is a major concern anytime patient data is used. Cybersecurity breaches are common and incredibly expensive in the healthcare industry. According to Healthcare Dive, the healthcare industry is the most expensive industry for responding to and recovering from data breaches, and the average cost of a healthcare data breach in 2024 was $9.8 million. Given the threat and cost of potential cybersecurity breaches, medical practices need to implement top-notch cybersecurity practices to protect patient data. Additionally, they need to maintain and update those practices to ensure they can resist advancing and evolving attacks.
For big data analytics to be effective and valuable, practices need to have access to quality, standardized data. If data is inconsistent or incomplete, it can lead to inaccuracies or an underperformance. Practices must strategically gather and manage data to get optimum results when using it for billing and other analytics.
Looking forward in the medical billing and coding industry
Big data has already had a transformative effect on the healthcare industry, and thanks to its use, practices have a valuable tool at their disposal. In addition to big data, other technologies, like artificial intelligence (AI), machine learning and blockchain technology are impacting the industry with predictive billing outcomes, increased efficiency, improved security and reduced fraud.
A practice that embraces this new technology is poised to benefit in several ways. “As technology advances, integrating these analytics into daily billing operations will become essential for improving efficiency, reducing errors, and ensuring compliance,” said Khabinskaya. “Healthcare facilities that leverage big data effectively will benefit from increased accuracy, streamlined processes and ultimately, better financial outcomes.”
