Some management techniques take advantage of basic receivables-system information to monitor charge capture and forecast future exam caseloads. The models shown here use real data; a complex hospital-based practice was purposely chosen, with a trend line of January 2008 through August 2009. To understand the power of today’s receivables systems, consider that it took approximately two minutes to write the extraction query for these models, and the compilation took 30 seconds. This covers individual days spanning 19 months. A larger date range would, theoretically, build a more normalized population, but this practice made a significant change in coverage that affected hospital volumes after January 1, 2008.
No strong math background is needed to follow basic statistical techniques. The database extraction was exported to a standard spreadsheet program for modification to produce tables. The receivables-database program can produce statistics; however, in the absence of this feature, the raw data can be exported either to a spreadsheet or to a database program that has statistical functions to produce the same results.
The exam patterns seen for different days of the week can be used by the practice or its receivables vendor to monitor exam capture quickly. The same data can be used in forecasting.
Table 1 illustrates what the total extraction looks like. A month with a national holiday was chosen to meet a requirement of the analysis.
|Table 1: Extraction Example: July 2009|
Fridays are highlighted because Independence Day for 2009 fell on a Saturday, but was observed on the preceding Friday. Note how different the volume can be on a day that is a national or regional holiday. It more closely mirrors weekend volumes, which principally come from emergency-department patients. July 2009 was also chosen because it is outside the population reflected in the monitoring statistics (January 2008 through June 2009). There is an important reason for this, stemming from the inherent delay between the date of service for an exam and the date that it is posted to the receivables system. It can take up to 90 days to capture all exams fully for a given day. Therefore, July 2009 will offer a good opportunity to test actual capture against prior averages. Table 2 illustrates the statistics pertaining to July 2009 matched against those for the full range of dates.
|Table 2: Basic statistics on Table 1 data, versus entire population|
1/2008 TO 6/2009
The 31 days of July 2009 are organized by day of the week, with a special designation for a holiday falling on a weekday. The average is obtained by summing the exams per day, and then dividing by the number of days. The SD, or standard deviation, is the square root of the variance, and the variance is a measure of the database spread; it is the average of the distances from the mean, squared. These dispersion values help test the credibility of future results.