Are you endeavoring to assure the proficiency and sustainability of your lab practice? How can you leverage predictive analytics to enhance the performance of the revenue cycle? For this, you must have to get familiar with predictive data analytics. With predictive analytics, a healthcare provider can boost revenue cycle performance and drive good savings. It is a game-changer in the RCM as it can be utilized to rectify concerns and forecast revenue for better business growth.
The derived insights help you to proactively address problems with payers that are holding payments, streamline revenue cycle workflow, and educate clinicians/employees on best practices. Before moving further, dig deeper to understand the concept of the predictive data analytics role in revenue cycle management and its significance.
Significance of Data Analytics
Everybody wants convenient, affordable, engaging, and equitable healthcare. You can do more with data if you have integrated systems and fully managed analytical solutions in place. Without the data-driven headaches, you can get closer to your data-driven vision with each passing day.
With data analysis, you can recognize the revenue cycle management breakdowns that are putting a deep impact on the financial sustainability of your healthcare business. You can use data-driven findings to address and predict the issues as it is the next step in the evolution of healthcare. The right predictive analytic partner will improve efficiency or accuracy and will bring these latest healthcare trends to your attention. You become able to enhance care quality while diminishing costs.
Predictive Data Analytics_ The Future of Healthcare
It helps determine what has a high probability of occurring in the future using forecasting and modeling techniques. Medical specialty professionals, physicians, healthcare stakeholders, researchers, and medical practices can provide the best possible care for the individual patient by using those predictions.
Predictive analytics uses a variety of modeling techniques from conventional to advanced methods. For providing the possible robust prediction, the advanced lab billing solutions along with innovative tools can help you achieve maximum precision. Here are the following best approaches that can help medical practices leverage predictive analytics to boost their revenue cycle performance.
Review Payer-Specific Payment Behavior
With the help of predictive analytics, you become able to identify how long a specific claim will take to get you paid after reviewing payer-specific behavior. It is a strategy that provides a high degree of accuracy and helps you predict the date of remittance for claims.
Predict Claim Denials
Predictive analysis helps you to determine which claims are denied before they occur. In this way, you become able to increase clean claim rates and correct claims before submission. Medical practitioners also use these analytics to shift their staff’s attention to high-value rejections that have a strong chance of returning.
Identify Changes In Payer Rules
The emerging ability of predictive data analytics is to anticipate changes in payer rules before a claim is delayed or denied along with applying payer-specific rules and coding edits for claims adjudication. Nowadays, this entire procedure still needs experts who comprehend the claims edits’ intricacies to determine the next steps and evaluate these alerts.
Tackle Revenue Cycle Challenges With Predictive Data Analytics
The healthcare RCM is continuously evolving due to its dynamic form. That’s the reason healthcare providers are tending to face diverse challenges that range from failure to have certain policies in place to billing errors. It is integral for a lab practice to find ways that can light their ways to improve their organization’s revenue stream. Below are some pain points associated with the healthcare RCM and some solutions to tackle them for reducing future financial troubles.
Incompetent Medical Billing Process
Mistakes in the billing process shock patients with a huge debt that they cannot pay and hurt practices to the tune of tens of millions of dollars. Lab practices must ensure that they are not leaving the uncollected revenue on the table and patients are aware of out-of-pocket expenses. They must ensure their patient satisfaction so next time whenever their patients need care they don’t seek care from other facilities. At the point of service, a few providers know how to collect from patients while various have not mastered the art of collecting the maximum revenue amount from their patients.
According to a survey, ‘’85% of practices say that collecting payments from patients once they had left the physician’s office is one of the most difficult tasks.’’ If healthcare providers are currently experiencing the highest amount of bad debt, they try to reduce it at or before the point of service. They must devise more streamlined methods for collecting from patients and develop a better understanding of patient responsibility if they really want to maintain financial stability in a changing landscape.
The right predictive analytics partners will bring the latest trends to your attention in their earliest stage and provide you with a competitive medical billing process in place. They will assure you will receive payments without further delays. It is also helpful for a medical professional to recruit well-trained and efficient medical billing staff. Who understand the integrity and significance of data that they deal with on a regular basis.
Lack of Staff Training
If the medical staff doesn’t have sufficient training they wouldn’t be able to capture patient data accurately and bill correctly. They must know how to capture the demographic information of patients on the front-end and be responsible for billing needs. The accurate data starts with patient registration/schedule if you see it from a revenue cycle perspective. When you have a skilled team your claims can be filed and collected in the most effective or efficient possible manner. They provide the groundwork and save a healthcare organization money in the long run that might be spent on time-consuming and costly staff training.
It can lead to unnecessary spending when coding errors equate to medical errors. For instance, a report stated that in New Jersey 23 hospitals paid $499,999 penalties for medical errors due to the failure of coding staff for staying updated with the latest guidelines about medical coding. Moreover, if medical coders want to contribute to the bottom line, they need to stay sharp with the new set of skills because the new coding transition of ICD-10 may be less or more complete. In order to learn how to code efficiently, the coding staff must complete four-hour increments with a 60-hour long training. An experienced medical billing and coding staff uses predictive analytics to make the whole process of billing more efficient as well as reduce billing errors.
Outdated Technology Challenges
Many lab practices remain heavily dependent on the manual follow-up work and processing of claims. Because they lack the infrastructure and capital to invest in advanced technologies. According to a McKinsey report, ‘’Financial clearance activity like authorization requirements and overall administrative burden for medical practice increases. Authorization request volume annually rose by 15% and grew from 24 million to 32 million between 2013-2015. Physician and staff process 37 authorization each week and spent 16.4 hours/week on authorization activities in 2016.’’
In addition to this, this also contributes to the growth in rejections, according to the report and they have to wait for a long time to get a response to their authorization request. However, insightful analytics enable healthcare providers to get the knowledge they need for sustaining the organization’s financial health and effectively utilize smart solutions for managing their revenue cycle operations.
However, insightful analytics enable healthcare providers to get the knowledge they need for sustaining the organization’s financial health and effectively utilize smart solutions for managing their revenue cycle operations.
Conclusion
Predictive data analytics enable transparency into areas such as denial trends, staff productivity, revenue cycle metrics, and physician productivity. A highly transparent environment assists you to drive improved financial outcomes and data-driven decision-making.
It is important to take measures to assure you are getting actionable insights as you formulate a predictive analytics game plan. Work with a proficient professional in revenue cycle analysis to identify trends your lab business has not worked with or uncovered yet. Laboratory Billings is a trusted lab billing company in the US. Our dedicated experts help you use predictive analytics to solve the revenue cycle business challenge while strengthening financial performance.[/vc_column_text][/vc_column][/vc_row]
