Health systems are awash in data. Not only are there many different sources, but the formats – even for “standard processes” – vary from vendor to vendor, system to system. While this data is necessary and can be incredibly useful, many health systems are struggling to leverage data due to the challenges in healthcare, especially when systems merge or combine.
Multiple electronic health record (EHR) systems, differing payers, multiple payment data sources, variations of standard electronic data interchange (EDI) files and lack of tools to harness the data all contribute to inefficiency, higher costs, and absence of an effective way to make the data actionable. Not only is the data difficult to manage, these factors also make it difficult for health systems to manage their revenue cycles, costing systems time and money.
Many health systems utilize multiple information technology (IT) systems combined with different vendors to gather data. According to a HIMSS Analytics study, 41 percent of hospitals said they used their EHR with two or more other vendors for revenue cycle management (RCM). While you may think “the more the merrier,” that is not the case when it comes to healthcare technology. The more systems you have, the harder it is for them to work together and gather the data accurately for reporting.
Too many disparate systems are a huge hurdle for hospitals trying to leverage their analytics. The HIMSS study also discovered that 76 percent of hospitals surveyed stated that denials are the biggest challenge they face with RCM. Lack of visibility across multiple IT systems are a huge contributor to this challenge. Along with multiple systems comes staff that will need to maintain and manage the systems leading to more complexity.
Of the hospitals surveyed in the HIMSS study who were having troubles with denials, 72.5 percent of respondents were using their EHR alongside three or more other RCM systems to manage their revenue cycle. In order to improve their revenue cycle, the focus needs to be on creating continuity across the hospital footprint and make it easier to leverage data.
Another factor contributing to the challenge of leveraging data is the variation of payers flowing into health systems. The majority of hospitals work with both public health programs, such as Medicare and Medicaid, as well as private insurers. Each of these payers has its own set of procedures and forms for billing as well as collecting payments. Additionally, some billing procedures are conducted electronically while others are still paper driven, adding an additional layer of difficulty. A study conducted by the BMC Health Services Research estimated that 80 percent of billing-related costs in the United States are due to managing the added complexity.
EDI allows healthcare systems to exchange data in a standardized and secure manner among healthcare professionals and patients. While healthcare claims and payments leverage “standard” EDI formats, such as the 837, 835, and 820, the version of the format that is used varies greatly. Each version can leverage some of the needed data differently. Data that relates to payments and claims sits outside of the EDI system and has its own set of formats, making it incredibly hard for the healthcare system to get all the information in one place to produce a “single version” of the truth (i.e. the bill). Each EHR has its own “standard” for the format and handling of these various files as well.
This challenge is amplified when two health systems merge and have multiple EHRs. In order to understand billing compliance, denials, or patient responsibility, these disparate sources need to be brought together to create a single, normalize view of the data and then have tools that analyze the data and make it actionable.
Healthcare systems are not in the business of mapping data fields, standardizing them, and applying data sciences to identify patterns. Bringing the data together is the first step, then you need to be able to model it, identify actions, and interface that back into the health systems’ workflow. With multiple employees scattered across various sites, it makes it difficult to standardize and optimize this data to reduce costs, improve compliance, reduce denials, and understand a patient’s propensity to pay. These are all core to revenue cycle operations, and are better left to RCM experts.
The multitude of data and information flowing throughout health systems is only useful when it is accurately obtained and understood. Gaining an understanding and harnessing this valuable data can take healthcare to the next level. Bringing sources and data together will allow health systems to leverage their current operations to lower costs, improve billing compliance, reduce denials, and improve collection rates with patients.
Combining forces with an RCM or payment processing company will ensure your billing process is compliant and compatible with your EHR, which contributes to a faster payment turnaround and greater patient satisfaction.