The healthcare industry is currently undergoing a data-driven metamorphosis that has completely transformed the way this industry functions. As it continues to witness a massive influx of a stream of data that is shaping new trends and standards, more and more healthcare organizations are increasingly adopting the use of data analytics to gain better and more reliable insights, pattern visibility, and predictions from this explosive amount of medical data.
However, most organizations still fail to unlock the full potential of big data in healthcare revenue cycle management as they struggle to effectively leverage data analytics to drive change in their practice. In this article, we will review how finding and analyzing trends acquired from big data sources could be used to help healthcare practices improve efficiency within their revenue cycle.
The Need for Big Data In Healthcare
In today’s competitive healthcare environment, organizations’ cash flows are declining rapidly and profit margins are getting tighter than ever. According to a survey conducted by the AMGA Medical Group in 2017 using financial data from 49 organizations, healthcare organizations suffered an increase in the operating loss per physician from 10% in 2016 to 17.5% of the net revenue. This illustrates the need for a better method of operations by healthcare practices that could restructure their revenue cycle towards a more efficient and productive approach.
Problems such as incorrect ICD-10 coding, manual data entry errors, and overburdened financial support staff could lead to several operational challenges in your revenue cycle. However, most of these challenges can be avoided by the use of big data in healthcare that can streamline the revenue cycle and financial operations of an organization to ultimately improve patient communication and profitability. This is why the need for big data in the healthcare revenue cycle will only continue to grow, especially as more organizations opt for value-based care.
The Use of Big Data to Solve Revenue Cycle Management Challenges
Practices are increasingly investing in the implementation of a data-driven healthcare revenue cycle to fill the gaps in their cycle that could be costing them a lot of money. The use of big data in healthcare allows practices to gain actionable insights, which is used to make better decisions that can lead to critical improvements in their operations and financial health.
Big data healthcare solutions combined with machine-learning algorithms offer providers valuable insights into their performance metrics that can be used to improve their workflow management. With big data, organizations can also develop and track key performance indicators which allow the providers to assess the efficiency and accuracy of their billing staff. This motivates the human components of the revenue cycle to optimize their workflows and offers healthcare providers visibility into which members of the staff are handling claims productively and whose workflows are not beneficial to the organization. This can help practices make crucial decisions about staffing, which can help avoid unnecessary labor costs.
Organizations that have created a data-driven culture for the use of big data analytics in their healthcare practice have the potential to quickly pinpoint errors and inaccuracies and predict problems within their procedures. This allows them to quickly mitigate these problems before they can escalate into larger issues that could be more costly in the long term.
Additionally, using big data in healthcare systems is crucial to aligning the clinical and financial experience a patient receives. It is imperative that the patient receives the same level of comfort with their billing experience as their clinical care. Adopting data-driven claims and billing management systems can go a long mile towards ensuring patient satisfaction.
Benefits of Big Data in Healthcare Revenue Cycle Management
As integrated systems and independent practices alike continue to face greater cost pressures and increased volumes of revenue leakages, it is vital, now more than ever, that these practices harness the large amounts of medical data available to improve their financial standings.
A more holistic approach to healthcare revenue cycle management by means of the use of big data can enable practices to progress by adding more context to insurance claims as well as identifying areas of improvement. This ultimately sets them up for success, minimizes the loss of their time and resources, and creates a stronger revenue cycle.
Let’s take a closer look at the benefits of big data analytics in healthcare revenue cycle management.
Reduces Insurance Denials
Some of the most critical parts of the revenue cycle such as the registration of patients and insurance verification can be made much more accurate with the implementation of big data analytical tools. However, the most important part of the cycle that is significantly improved by the integration of big data in healthcare is reimbursement claims. Healthcare providers can use it to submit accurate claims for payments to ensure compliance and reduce the chances of rejections.
Providers can also make use of predictive modeling to anticipate which claims are likely to be rejected and can reduce claims rejection rates by allowing for a more accurate coding system. The data can also be used to identify any missing information from the claims and reveal ways to improve the payment collection process. Data analytics also gives providers 360-degree visibility into their claims, which can be used to determine the cause for any denials received in order to avoid similar rejections in the future.
Renegotiation of Unfavorable Payer Contracts
With the help of data analytics, patient care organizations get a more comprehensive understanding of how much their services are costing them and how much they are earning in return. This makes it possible for providers to review their contracts with their payers and assess whether these contracts are benefitting their revenue cycle or not.
Big data analytics allow providers to come to the negotiating table with undeniable and applicable data to support why a renegotiation should be made so that the terms of these contracts can then be renegotiated for more favorable ones.
Not only are big data healthcare solutions making significant strides in clinical trials and patient treatment, but they are also revolutionizing the financial side of the healthcare system for the better. Automation of the revenue cycle management system with the assistance of big data in healthcare can play an instrumental role in streamlining a healthcare organization’s financial processes, allowing physicians to focus on what matters the most – providing the best care possible to their patients.