The power of information: Leveraging data to maximize efficiency and revenue to improve your bottom line

It is no surprise that accurate payer, patient, and provider data has a direct impact on lab revenue. Currently, many laboratory information systems focus on revenue problems at an episodic level, limiting their ability to analyze and solve the larger revenue issues and obtain the insights needed to transform their bottom line. Additionally, obtaining, storing, and normalizing this big picture data is made difficult due to the multiple data sources involved.

Equipped with the tools necessary to harness a holistic view of data, laboratories can pinpoint areas of improvement, streamline efficiency, and improve client and patient satisfaction – ultimately resulting in increased revenue and an improved bottom line.

The current and future impact of data on laboratories   

For several years, progressive laboratories have been searching for tools that provide a broader view of their operational and financial performance. This is mainly because they are looking to combat hurdles such as margin compression, staff shortages, and processing errors. One major issue with laboratory data today is duplication causing inconsistencies and inaccuracies. For example, data is often entered and stored into multiple third-party systems such as an electronic health record (EHR), health information system, billing system, etc. Laboratories need to create a source of certainty where they work to cleanse and fix any and all errors, thereby creating accurate data. While accessing this precise big picture data across all entities solves many of the current struggles laboratories are facing, its potential impact is at a much larger scale.

The lab of the future revolves around accurate data. As the world of healthcare IT becomes more advanced, laboratories will struggle to compete without a big-picture perspective. This type of information has the power to transform laboratories – streamlining efficiency, enhancing compliance, and improving both provider and patient satisfaction. To get there, labs need to work toward removing data from silos, structuring it, and leveraging it to make better decisions.

Types of data most important to lab revenue

Payer data: Inaccurate or missing payer data causes untimely collections, denials, or patient and provider dissatisfaction due to inaccurate billing. Accessing accurate payer data helps labs with reporting and negotiating contracts, as well as strategically managing their business.

Patient data: Inaccurate or missing patient data causes a host of downstream errors and inefficiencies including negative impacts to provider and patient relationships and on lab revenue. Once inaccurate data becomes accurate data, it directly impacts the bottom line leading to faster revenue. By accessing clean patient identity data, labs can avoid duplication errors and improve efficiency and patient care.

Test/specimen data: Accuracy is especially important when it comes to test or specimen data. Ensuring correct collection dates and times are recorded, checking for duplications, and timely management of errors and rejections are all vital to maximizing efficiency, thereby improving lab revenue.

Concrete impact of leveraging accurate data

While it is clear that labs should prioritize receiving and delivering accurate information, the real impact that data has on the day-to-day may be less evident without seeing it first-hand. Below are three examples of labs who have leveraged clean data to resolve obstacles and increase revenue.

Missing insurance information is a common laboratory struggle. This particular lab utilized machine learning insurance tools to automate mapping to the laboratory insurance codes. By doing so, this lab was able to reduce unnecessary manual data entry and speed up adjudication, closing gaps and increasing revenue.

This next last lab was struggling with incorrect insurance eligibility information due to verification happening at the back end. This was causing claim denials either because eligibility had expired, or service was not covered by the patient’s plan. By simply moving eligibility verification to the front end, this lab saw fewer denials and needs for corrections. This is a classic example of how thinking about data proactively rather than retroactively can have an immediate impact on a laboratory’s bottom line.

In this last example, a nationwide laboratory was struggling with denials because insurance was requiring encounter notes to be submitted with each and every claim. By embracing new interoperability capabilities, this laboratory was able to pull information directly from EHRs, ensuring accurate and efficient information. This resulted in drastically cutting down on phone calls, faxes, and office visits. In addition, this lab saw significantly less insurance denials and holds, while increasing operational efficiency.

How to access accurate data and use it efficiently and effectively

The root of missing revenue in labs is due to fixing data inaccuracies at the most expensive point: when the data is furthest away from the provider and testing has been performed. Laboratories need to proactively gather information in advance and utilize modern technology to correct data.

Gathering accurate information starts the moment a laboratory onboards a provider. By taking a close look at the ordering and accessioning process, laboratories can proactively get ahead of inaccuracies that may occur down the line. This type of effective and timely management is key, but it’s not the only precaution labs should take.

Because there are so many additional steps involved in the recording and transferring of information, the possibility of error is high without an integrated laboratory solution. Utilizing robust and scalable technology makes all of the difference in supporting business and clinical goals, eliminating workflow challenges, and maximizing revenue. Laboratories should look for data normalization tools that provide some of the following capabilities:

  • Demographic, insurance, and clinical data on demand
  • End-to-end orders and results interfaces with providers
  • Insurance eligibility verification
  • Across platform compendium management

As stated, the future of the laboratory industry is data centric. By having a holistic view of data, your business will be able to take strategic and measured steps to increase revenue while also ensuring that efficient practices throughout your operation are met. Setting a solid foundation of data accuracy doesn’t just help your lab in the short-term, more importantly, it will set you up for future success and growth.