The Science Journal of the American Association for Respiratory Care

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.

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