Our purpose-built software can help you find the best way to improved insights, higher revenue, and accurate benchmark data.
Emergency departments (EDs) run on adrenaline, but they also run on data! ED billing is complex and prone to high error rates, making it an ideal target for a strategic data solution that can identify outliers and provide clinical data to document and support appropriate coding.
For EDs to accurately charge for services, they must code the care given, according to the services provided to the patient. This system, called evaluation and management or E/M services, is regulated by the Centers for Medicare & Medicaid Services (CMS).
Medical coders use a physician’s documentation of a visit to determine correct billing codes. This intricate system has many rules and specifications, which leaves it open to errors at all points of the process, particularly in busy EDs, where documentation is not always a top priority for clinicians. But when it comes to medical records “if you didn’t document it, you didn’t do it,” because coders must take the chart at face value only.
Medical coders assign Current Procedural Terminology (CPT) codes that best define the patient type, setting of service, and level of E/M service performed. This ensures that cases are billed correctly, both to Medicare and Medicaid, as well as private insurance. Level of E/M service is further divided into three elements that must be present to select the applicable E/M service: history, examination, and medical decision making. Less frequently, visits involve counseling or coordination of care, and level of care can be better determined by provider time spent.
Within the E/M elements — history, examination, and medical decision making — there are many subcategories defined. For example, there are four types of history, with required elements that define them. A process that at first sounds simple can quickly become complicated.
While EMR systems help guide documentation for clinicians, a large portion of it is in narrative form. Narrative documentation is more prone to error than discrete data fields. According to CMS, 80% of the improper payments were due to incorrect coding, and 5% were due to insufficient documentation.
Medical Coding Errors
In its 2019 Improper Payment Data report, CMS said that CPT code 99223 is the most frequently miscoded claim, with an average error rate of 24.1% nationwide, resulting in about $443 million in improper payments in 2019.
Upcoding errors expose a facility to regulatory scrutiny and denials. Downcoding errors represent lost revenue for services rendered, and operational inefficiency. Both can have unfortunate consequences for hospital emergency departments.
But when clinical data is used to supplement billing data, it’s easier to identify missed billing opportunities, for example, encounters coded as E/M less than level 4 where advanced imaging was ordered. Partnering with a purpose-built emergency medicine data analytics solution — can provide clinical data to coders in a convenient format as part of their workflow, which improves coding productivity and accuracy. This approach also offers the potential to provide the necessary data to determine encounter MIPS inclusion/exclusion criteria at the same time, without needing to dig through EHR charts manually.
The Road to Improvement
Higher coding accuracy benefits hospitals by reducing denials, improving audits and regulatory findings, avoiding possible penalties, and providing accurate data for estimation of future revenue. Many EDs do not realize that they have a problem until it is revealed by an audit or an unexplained drop in revenue. Quality monitoring with accurate data is essential to quickly spot outliers and avoid costly surprises.
One example of how data can be used to drive E/M coding improvement is by segmenting coding profiles by individual providers. This data can then be compared to outside benchmarks, and to department peers. If patterns vary from expected outcomes, then greater scrutiny may reveal opportunity for improvement at the provider level.
The department as a whole can also be compared to data from like-sized departments with similar demographics to look for inconsistencies. Data can be evaluated over time to assess changes in the department or evaluate the success of education and improvement plans.
ED leaders depend on accurate data for informed decision-making. d2i can provide data on both ESI levels and E/M coding, revealing important relationships about triage accuracy, coding accuracy, and overall acuity levels of a department. This information can be used to determine best staffing patterns and for improving department efficiency.
With the right data analytics partner that understands ED coding, it’s never been easier to find your way to improved insights, higher revenue, and accurate benchmark data.