Norm-based Interpretation Guidelines (NBIG), a state-of-the-art service developed by QualityMetric,
supports comparisons of results obtained by clients using any of the SF™ Generic Health Surveys with representative
population-based norms and results from the published literature. NBIG draws on QualityMetric's repository of the more
than 5,000 clinical trials and outcomes research studies with SF measures published since 1988, and a number of general
population databases. NBIG can be queried easily to find norms for the SF-36®, SF-36v2™ SF-12®, SF-12v2™,
and SF-8™ Health Surveys, as well as computerized adaptive scores on DYNHA®. NBIG norms, adjusted for participant group characteristics (age, gender, diagnosis, and severity), provide a method for interpreting the meaning of SF scores in comparison with scores for a standardized sample with similar characteristics.
NBIG takes norm-based scoring (NBS) to the next level, further facilitating interpretation and comparison of clinical
trials and outcomes research data. A simple linear transformation of data originally scored on a 0-100 scale,
NBS algorithms score scales that have a mean of 50 and a standard deviation of 10 in the general 1998 US population.
Thus, on all scales, any score less than 50 falls below the general population mean, and each point represents 1/10th
of a standard deviation. Using NBS algorithms, scores on all eight SF health domain profile scales and the two component
summary measures are directly comparable. General population and disease group norms serve as reference points or
benchmarks for applications such as estimating disease burden and evaluating treatment benefit.
