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J Am Med Dir Assoc. 2012 Feb;13(2):188.e7-188.e12. doi: 10.1016/j.jamda.2011.04.021. Epub 2011 Jun 16.

Scope and severity index: a metric for quantifying nursing home survey deficiency number, scope, and severity adjusted for the state-related measurement bias.

Author information

1
University of Wisconsin, Madison, WI, USA. antonova.jenya@gmail.com

Abstract

OBJECTIVES:

To develop a metric (scope and severity index [SSI]) to measure nursing home deficiency number, scope, and severity adjusted for the state-related bias and to test its convergent and predictive validity.

DESIGN:

We assigned scope and severity weights to each level of scope and severity (A-L). SSI was calculated as a sum of all weights per survey which was further corrected for the state-level bias by dividing by the state average number of health deficiencies and multiplying by the national average number of health deficiencies. Data source - National Online Survey, Certification, and Reporting system.

SETTING:

All Medicare/Medicaid-certified skilled nursing facilities.

MEASUREMENTS:

We correlated SSI with nursing home staffing levels (convergent validity) and denial of payment for new admissions (predictive validity).

RESULTS:

The expert panel reached agreement on the scope and severity weights: Level A = 5, B = 10, C = 15, D = 20, E = 30, F = 40, G = 35, H = 50, I = 65, J = 55, K = 75, and L = 100 points. Scope and severity per deficiency was positively correlated with the number of deficiencies in that survey. SSI contained almost no state-related bias, but yet related state-level variability. It demonstrated strong face, convergent, and predictive validity.

CONCLUSIONS:

SSI rendered a valuable metric to conduct quantitative analyses of nursing home deficiency number, scope, and severity across states. Future research should investigate the positive relationship between scope and severity of deficiencies and their number. Better understanding and correction of other factors introducing systematic bias to the survey results (e.g. regional impact) can further improve the accuracy of survey result evaluation.

PMID:
21683661
DOI:
10.1016/j.jamda.2011.04.021
[Indexed for MEDLINE]
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