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Comparing staffing levels in the Online Survey Certification and Reporting (OSCAR) system with the Medicaid Cost
Bita A Kash1, Catherine Hawes, Charles D Phillips
1Department of Health Policy and Management, School of Rural Public Health, Texas A&M University Health Science Center, TAMU 1266, College Station, TX 77843, USA. bakash@srph.tamhsc.edu
Purpose:
This study had two goals: (a) to assess the validity of the Online Survey Certification and Reporting (OSCAR) staffing data by comparing them to staffing measures from audited Medicaid Cost Reports and (b) to identify systematic differences between facilities that over-report or underreport staffing in the OSCAR.
Design And Methods:
We merged the 2002 Texas Nursing Facility Cost Report, the OSCAR for Texas facilities surveyed in 2002, and the 2003 Area Resource File. We eliminated outliers in the OSCAR using three decision rules, resulting in a final sample size of 941 of the total of 1,017 non-hospital-based facilities. We compared OSCAR and Medicaid Cost Report staffing measures for three staff types. We examined differences between facilities that over-reported or underreported staffing levels in the OSCAR by using logistic regression.
Results:
Average staffing levels were higher in the OSCAR than in the Medicaid Cost Report data. The two sets of measures exhibited correlations ranging between 0.5 and 0.6. For-profit and larger facilities consistently over-reported registered nurse staffing levels. Factors associated with increased odds of over-reporting licensed vocational nursing or certified nursing assistant staffing were lower Medicare or Medicaid censuses and less market competition. Facility characteristics associated with over-reporting were consistent across different levels of over-reporting. Underreporting was much less prevalent.
Implications:
Certain types of facilities consistently over-report staffing levels. These reporting errors will affect the validity of consumer information systems, regulatory activities, and health services research results, particularly research using OSCAR data to examine the relationship between staffing and quality. Results call for a more accurate reporting system.
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