A new algorithm to build bridges between two patient-reported health outcome instruments: the MOS SF-36® and the VR-12 Health Survey

Qual Life Res. 2018 Aug;27(8):2195-2206. doi: 10.1007/s11136-018-1850-3. Epub 2018 Apr 19.

Abstract

Purpose: To develop bridging algorithms to score the Veterans Rand-12 (VR-12) scales for comparability to those of the SF-36® for facilitating multi-cohort studies using data from the National Cancer Institute Surveillance, Epidemiology, and End Results Program (SEER) linked to Medicare Health Outcomes Survey (MHOS), and to provide a model for minimizing non-statistical error in pooled analyses stemming from changes to survey instruments over time.

Methods: Observational study of MHOS cohorts 1-12 (1998-2011). We modeled 2-year follow-up SF-36 scale scores from cohorts 1-6 based on baseline SF-36 scores, age, and gender, yielding 100 clusters using Classification and Regression Trees. Within each cluster, we averaged follow-up SF-36 scores. Using the same cluster specifications, expected follow-up SF-36 scores, based on cohorts 1-6, were computed for cohorts 7-8 (where the VR-12 was the follow-up survey). We created a new criterion validity measure, termed "extensibility," calculated from the square root of the mean square difference between expected SF-36 scale averages and observed VR-12 item score from cohorts 7-8, weighted by cluster size. VR-12 items were rescored to minimize this quantity.

Results: Extensibility of rescored VR-12 items and scales was considerably improved from the "simple" scoring method for comparability to the SF-36 scales.

Conclusions: The algorithms are appropriate across a wide range of potential subsamples within the MHOS and provide robust application for future studies that span the SF-36 and VR-12 eras. It is possible that these surveys in a different setting outside the MHOS, especially in younger age groups, could produce somewhat different results.

Keywords: Extensibility; SF-36; VR-12.

Publication types

  • Observational Study

MeSH terms

  • Aged
  • Algorithms*
  • Cohort Studies
  • Female
  • Health Surveys / methods*
  • Humans
  • Male
  • Medicare
  • Patient Reported Outcome Measures*
  • Quality of Life / psychology*
  • United States
  • Veterans / psychology*
  • Virtual Reality