The statistical validity of nursing home survey findings

J Am Med Dir Assoc. 2011 Nov;12(9):675-7. doi: 10.1016/j.jamda.2010.12.011. Epub 2011 Mar 21.

Abstract

Objectives: The Medicare nursing home survey is a high-stakes process whose findings greatly affect nursing homes, their current and potential residents, and the communities they serve. Therefore, survey findings must achieve high validity. This study looked at the validity of one key assessment made during a nursing home survey: the observation of the rate of errors in administration of medications to residents (med-pass).

Design: Statistical analysis of the case under study and of alternative hypothetical cases.

Setting: A skilled nursing home affiliated with a local medical school.

Participants: The nursing home administrators and the medical director.

Intervention: Observational study.

Measurements: The probability that state nursing home surveyors make a Type I or Type II error in observing med-pass error rates, based on the current case and on a series of postulated med-pass error rates.

Results: In the common situation such as our case, where med-pass errors occur at slightly above a 5% rate after 50 observations, and therefore trigger a citation, the chance that the true rate remains above 5% after a large number of observations is just above 50%. If the true med-pass error rate were as high as 10%, and the survey team wished to achieve 75% accuracy in determining that a citation was appropriate, they would have to make more than 200 med-pass observations. In the more common situation where med pass errors are closer to 5%, the team would have to observe more than 2000 med-passes to achieve even a modest 75% accuracy in their determinations.

Conclusion: In settings where error rates are low, large numbers of observations of an activity must be made to reach acceptable validity of estimates for the true rates of errors. In observing key nursing home functions with current methodology, the State Medicare nursing home survey process does not adhere to well-known principles of valid error determination. Alternate approaches in survey methodology are discussed.

MeSH terms

  • Bias
  • Health Care Surveys / standards*
  • Health Care Surveys / statistics & numerical data
  • Health Facility Administrators
  • Humans
  • Medicare / statistics & numerical data
  • Medication Errors / trends
  • Reproducibility of Results*
  • Skilled Nursing Facilities*
  • United States