By - October 5, 2017

Catching ACA Data Errors Early

Before printing 1095-C forms or submitting them to the IRS all employee data should be reviewed to ensure that the statements provide an accurate reflection of employees’ histories. Although time can be spent reviewing measurement periods and affordability calculations, if those determinations are being created based on inaccurate employment dates, benefit dates, or other critical data, then the work done is ultimately useless.

Some of the issues might be caught in a thorough review of the 1095-C forms themselves, but some would not. Furthermore, since the forms can only be generated at the end of the year once final data has been collected, it is likely a more valuable use of resources to review any problems earlier in the year, before it is time to print forms and when adjustments can still be made to the information.

Incorrect Dates

We’ve identified several common data errors that persist across our customers. For example, one of the top errors is benefits and employment dates that are stored in the HRIS/benefits systems and seem illogical or are not chronological. These often occur due to employees being rehired after a period of non-employment, job changes, or changes in benefits eligibility.

For example, we might see an employee with a hire date on one day, with the benefits start date 4 months earlier. That begs the question, how could someone be covered before they were hired? In addition to the 1095-C form incorrectly representing this individual as covered under medical benefits before employment even started, there is a second concern. If the hire date  is incorrect, that would also push the employee into an incorrect measurement period where some of the hours worked would not be considered and the results would be inaccurate.

This is a case of problematic employee data that can skew the results printed on the final 1095-C form. Reviewing the data early, and consistently can catch these problems before they get printed on your employees’ tax forms.

Take a look at the following to see some other common data errors we see and think about whether they apply to your data: ACA Data Quality Checklist: Common Errors to Avoid.

 

If you need help with ACA Compliance & Reporting, Contact Us.

Tags: ,

Categorized in: