Improving Previsit Processess to Maximize Postvisit Collections
As most of us know, poor previsit processes create havoc on a practice’s ability to post, bill, and collect for services rendered (Petaschnick J. Health Care Collector. 2007;20:1,10-12). A previsit process that is laden with errors, variation, and waste will result in an increase not only in denials and lost revenue, but also in cost associated with catching and correcting errors on the back end.
Previsit processes also can be tied directly to patient satisfaction. Perhaps the most obvious is the dissatisfaction that arises when charges are denied as a result of incorrect billing (Lloyd J. Receivables Report. 2011;26: 1,10). Dissatisfaction can be compounded when patients experience anxiety and worry associated with a lack of understanding about their out-of- pocket liability before they have received services. Because the financial obligation for oncology patients continues to grow, patients now are seeking alternatives and options, both medically and financially.
To decrease the cost of collections and to meet the patient’s expectation to be educated fully about their financial liability, Kansas City Cancer Center, a multispecialty oncology and hematology practice with 7 primary sites of service in the Kansas City metro area, evaluated its previsit processes to incorporate a complete, accurate, and timely verification of benefits before rendering services.
Identifying the Problems
In the winter of 2009, Kansas City Cancer Center practice leadership identified a clear opportunity to decrease the number of denied claims. Upon closer examination, they found that 3 of the top 5 denial codes resulted directly from a failure to collect and/or verify the appropriate information at the time of preregistration. These denial codes included: Services Covered by Another Payer, Services Not Covered by This Payer, and Coverage Termed.
To evaluate the preregistration process in more detail, the practice assembled a cross-functional team and created a standard definition of “complete preregistration”: collecting 100% of the following data elements before the date of service, with 100% accuracy, 100% of the time:
- Patient name (first, middle, last)
- Date of birth
- Primary and secondary policy and group numbers
- Plan addresses
- Subscriber demographics (name, date of birth, gender, Social Security number, and employer).
Next, the practice measured how well this standard was being met. By counting both missing and inaccurate data, the team calculated a defect rate of 52%. This deficiency was causing work to be duplicated in the form of error correction and time spent locating missing information. In addition, there consistently were defects that made it downstream, which resulted in denials and additional replicated work.
At this point, they set out to determine the root causes of the incomplete preregistrations in order to apply the most effective solutions. They identified variation in process between multiple sites of service; excessive touches or hand-offs without clearly defined roles, responsibilities, or accountability; use of inadequate or outdated paper forms resulting in missing, inaccurate, or illegible information; and simple errors in obtaining and recording data elements such as group numbers, insurance plans, dates of birth, subscriber information, and plan numbers.
To address the flaws in the processes, the practice developed a centralized team of preregistration liaisons (PRLs) to complete accurate and timely preregistrations for all new patients. After a patient is scheduled at any location (most new patient appointments are scheduled by the patient’s referring office), a PRL contacts the patient within 48 hours to obtain his or her address, phone number, emergency contacts, insurance information, and other pertinent demographics. While on the phone, the PRL answers any questions regarding the upcoming visit, such as directions to the clinic or information about the provider or practice.
The PRL then contacts the insurance company to verify benefits, including deductibles, copays, and coinsurance. This information is scanned into the practice management system for access by the site of service. After the treatment has been ordered, the process is picked up by the clinic’s financial counselor, who educates the patient about his or her potential liability and identifies payment assistance if needed.
With the development of this new team and processes, the preregistration defect rate ultimately decreased from 52% to 2%, which the practice continues to maintain today. By identifying an opportunity for improvement, defining quality from the customer’s perspective, collecting data, and targeting root causes, practices can make improvements to their previsit processes that will decrease costs, increase revenue, and maintain patient satisfaction.