2006 OPEN FORUM Abstracts
SIMPLE SPREADSHEETS AUTOMATE BILLING IN LONG TERM CARE
Teresa A. Volsko,
MHHS, RRT, FAARC, Sherrie Christman, CRT
Advanced Health
Systems, Inc. Hudson, Ohio
The purpose of this study is to evaluate the use of an Excel
spreadsheet, programmed to perform data calculations and look up Medicaid
billing codes for a respiratory service provider in the long term care
environment. We hypothesize that the use of a programmed spreadsheet will
reduce billing errors, enhance revenue capture and save staff time.
Methods: Patient name, pay status and
hours of oxygen use were collected on a weekly basis for residents in 6
randomly selected Ohio based skilled nursing homes from January 1, 2006 - March
31, 2006. The total hours of oxygen use for each patient was calculated on a
monthly basis and converted to cubic feet in order to determine the appropriate
Medicaid billing modifier in one of two methods. First, the monthly sum of the
hours of oxygen use and conversion to cubic feet for each patient were
calculated by hand using a battery powered calculator. Staff used a reference
table to look up the appropriate Medicaid billing modifier, and then
transcribed the code onto a worksheet.
The identical data were typed into an Excel spreadsheet that was
programmed to perform the aforementioned calculations and automatically assign
the Medicaid modifier. The times associated with the hand calculated process
and the automated processes were collected and entered into SPSS 9.0 for
Windows for analysis. Error rates were calculated and expressed as a
percentage. Payment error dollar amounts were determined. Mean times associated
with processing billing data with each system were compared by Student's
T-test. Statistical significance was established at p < 0.05.
Results: Data from 596 patients were
collected. Hand calculated process resulted in a 6% error rate. Eleven or 31%
of the billing errors affected Medicaid payment rate, 45% of which would have
resulted in Medicaid overpaying the provider. The balance or 55% of the billing
errors would have resulted in underpayment to the DME provider. There were no
errors with the spreadsheet system. Time data are displayed in the table below:
| Hand | Computer | p value | |
| Calculation time for hour usage, conversion to cubic feet and assignment of modifier. Total (min) mean (± SD) Time/patient | 505 28.06 (± 21.3) 0.8 | 107 5.94 (± 3.9) 0.2 | 0.0038 - - |
A time-savings of 6.6 hours in staff time were realized for
the study period. This translates to an annual savings of 26.4 hours.
Conclusions: DME providers can use
easily programmable spreadsheets to automate the billing process, and reduce
staff time as well as billing errors to third party payers.