Trouble at the back end? Look at the front end: if your registration data error rate is high, your front end may need help

Healthcare Financial Management, March, 2006 by Richelle Fleischer, Donald Bertch

Missing primary care physician's name, incorrect format of subscriber identification number, minor listed as guarantor. Over the past decade, most health systems have installed electronic bill scrubber software to identify registration data quality problems such as these. The goal: to ensure claims are as clean as possible before being submitted. However, registration data correction occurs on the first day after the bill has dropped out of discharged-not-final-billed hold status (typically on day four or five). Once a claim has dropped into the hillers' queue, the clock is ticking to get that claim out the door as quickly as possible. Re-involving the registrar at this point will slow cash flow and increase days in accounts receivable.

Patient access and patient accounting often struggle over the quality of patient data. Patient accounting feels victimized by poor registration data quality, which this department has to correct. Patient access needs examples of registration errors to use in staff training, but providing these examples on a timely and ongoing basis would require considerable time and effort by patient accounting. Then, too, patient access staff feels that some of the examples that are provided do not represent the greater problem. Thus, the two departments get stuck at an impasse with no clear resolution.

First-Generation Solution: The Manual CIA Process

One solution is the manual registration-data quality audit, which involves the use of resources such as a quality assurance analyst, spreadsheet software, and copies of face sheets and insurance cards. A list of registration fields that affect claims being paid, contractual adjustments being applied correctly, and guarantor statements going to the right address is created. Using copies of resources, a QA analyst reviews each identified field in the registration record against the documents provided. Using this manual process, one FTE can review approximately 100 to 150 registrations per day. In many cases, one FTE will not be able to review 100 percent of registrations.

The analyst then documents the registration errors found. Using a database or spreadsheet makes it easier to build reports and search and sort for specific registrations or types of errors. The documentation should store certain vital data, including the account number, registration date/time, registration employee ID, financial class, patient type, field name, corrected value, and type of error. The documentation of errors is essential in identifying problem areas and training needs for registration staff. Error documentation also can be used to conduct a productivity analysis of registration staff and set up benchmarks and rewards for improvement of performance and morale.

This process works but is time-consuming.

Next Generation Solution: Registration Scrubber Software

Registration QA systems attempt to automate much of the review process and provide standardized reporting. The systems let users build edits or rules against the registration fields that will automatically flag potential errors. These edits need to be flexible and intuitive to find the large array of potential problems that can exist in one registration. The rules allow users to automatically check for required fields, the character length of the field, the value of the field, and the value against a specific format (e.g., field must start with three letters and nine numbers or any specific letter or number), and to compare the value in one field against that of another field in the record. These rules also need to be flexible enough to apply only in particular situations, e.g., a specific insurance plan or financial class.

The systems also validate the guarantor address used to mail statements to self-pay patients, thereby reducing the number of statements returned with a bad address and improving timely payments. Using these automated error-checking procedures, the systems can then build work lists for QA analysts to quickly and efficiently review the accounts. The work lists are customizable to allow analysts to focus first on accounts that have been flagged with errors based on the rules and then, if time permits, move to other accounts.

The QA systems come with many standard reports to show analysts the errors and their cause. They allow analysts to see the error percentages broken out by patient type, financial class, and insurance plans and provide additional detail and show the registration employees' errors. The systems provide a way to benchmark or gauge productivity of each registration employee and separate new employees from veterans. The report systems allow users to save reports in multiple formats, e-mail them to colleagues, or work with the data further.

Taking Action

Sensitizing staff from the CFO to patient access employees regarding this issue has triggered an enormous effort to define standards, train staff, implement a review process, and build measurement reports and databases to assess the seriousness of the problem and whether efforts to improve are having a positive impact. In many hospitals, establishing a QA process has resulted in a significant increase in hours spent completing a manual audit or QA review. In addition, spreadsheets and databases are built and fed manually to ensure that the error data are tracked and reported. For processes that are better than average, users may even have management reports and a method for providing feedback to patient access employees.