Accuracy is a problem across the entire revenue cycle
But what are the implications of accuracy issues? Customer problems, billing issues, client satisfaction, and wasted labor are just to name a few. This is true for both the front and back-end of the revenue cycle.
However, few hospitals and revenue cycle vendors have perspective on just how big of an issue it is.
The Front-End Registration Challenge
Registration stands out as a primary area of accuracy challenges for the front-end. For example, a patient misidentified during registration can cause downstream billing issues, duplicate records, and even litigation if the wrong procedure is completed on a patient.
- HIMSS estimates that 8-14% of medical records are marred with incorrect information that ties to an incorrect patient identity.
- The average cost to correct a duplicate record is estimated at around $100.
- Identification errors can result in duplicate tests being run on the patient to verify results. Research has shown the average cost associated with repeated medical care due to patient misidentification at over $1,000 per instance.
- Misidentification is a contributor to 35% of all medical claims that are denied — an estimated loss of $17.4 million per hospital each year according to The Ponemon Institute.
As bad as that sounds, accuracy is just as big of a problem on the back-end.
Back-End Revenue Cycle Use Cases: Accuracy Failures
Once the claims are submitted and adjudicated, payments and remits are generated by the payer. Assuming the claim data had patient errors and some clinical data errors, that means downstream payments and remittance data can be incorrect as well.
Accuracy Use Case Failure #1:
An EOB/EOP file is received with incorrect account information that does not match the correct patient account (or in some cases patient ID). The inaccurate data requires excessive manual labor to correct the issue, resulting in A/R days creeping higher. If the EOB data extraction process is not reliable, this causes misposting of data.
Accuracy Use Case Failure 2:
If an incorrect APC or DRG code is billed, the claim becomes a high risk for denial and additional, highly-manual work is required to correct the billing and appeal the denied claim, slowing down productivity across the revenue cycle.
Accuracy Use Case Failure 3:
If a claim is posted with inaccurate adjustment codes and a provider doesn’t catch the issue, healthcare providers risk over- and underpayment. Plus, patients could be directly impacted financially as they could end up being asked to pay more than obligated or receive multiple, confusing bills when the inaccuracy is identified and corrected.
Many of the administrative errors are generated from human processes, such as data entry and posting. No matter where the function is based, i.e. at provider, billing company, lockbox provider, it must have strong controls for accuracy. See white paper, “Why Posting Errors are the Norm in EOB Processing.”
The Impact on Vendors
Accurate data not only impacts patients but reimbursements and internal efficiencies as well. In the age of population health, accuracy of both clinical and claims data is necessary for hospitals and health systems to achieve their population health management goals — it’s worth noting that claims data has historically been favored in population health because of its structured nature, availability, and the fact that it spans a patient’s entire continuum of care.
This is an invaluable and strategic resource that more providers should be taking advantage of. However, the merge between clinical and administrative data is where the most value is realized.
Providers and revenue cycle vendors should look towards technologies like AI and deep learning to solve accuracy issues. AI can deliver accuracy levels that exceed 99% per field and dramatically reduce data entry and correction time, minimize accuracy issues, facilitate straight-through processing and limit bottlenecks across the system.
Watch this three-minute video to see how OrboGraph leverages AI & deep learning technologies electronifies paper- & PDF-originated EOBs/EOPs to achieve straight-through processing for providers and revenue cycle vendors.