Accounts receivable is a critical metric for every organization, but I have found in my experience in the healthcare industry there exists a strong focus on this particular metric all the way up to the executive level. Considering that we know what our data point will be (AR) we will now have to determine how we would like to visualize this information. For this scenario the aging may be grouped by 0-30 Days, 31-60 Days, 61-90 Days, and 90+ Days. Further, the grouping levels may be Provider, Service Department, Insurance Company, Payer Group, Date, Specialty etc…
Figure 1 shows an example of how an aging bucket (0 – 30 Days) may be designed to display this information grouped on Payer Group.
Figure 2 shows an example of how an aging bucket (0 – 30 Days) may be designed to display this information grouped on Provider.
This concept could be designed into a full solution representing every view of the previously mentioned groups by each aging bucket; however, the purpose of this blog entry is simply to have a brief overview to generate thought among the iDashboards User Community.
Thoughts and Questions are always welcome!
Zach Breimayer– Technical Consultant, iDashboards