Construction and Use of Body Weight Measures from Administrative Data in a Large National Health System: A Systematic Review.

Published

Journal Article

OBJECTIVE: Administrative data are increasingly used in research and evaluation yet lack standardized guidelines for constructing measures using these data. Body weight measures from administrative data serve critical functions of monitoring patient health, evaluating interventions, and informing research. This study aimed to describe the algorithms used by researchers to construct and use weight measures. METHODS: A structured, systematic literature review of studies that constructed body weight measures from the Veterans Health Administration was conducted. Key information regarding time frames and time windows of data collection, measure calculations, data cleaning, treatment of missing and outlier weight values, and validation processes was collected. RESULTS: We identified 39 studies out of 492 nonduplicated records for inclusion. Studies parameterized weight outcomes as change in weight from baseline to follow-up (62%), weight trajectory over time (21%), proportion of participants meeting weight threshold (46%), or multiple methods (28%). Most (90%) reported total time in follow-up and number of time points. Fewer reported time windows (54%), outlier values (51%), missing values (34%), or validation strategies (15%). CONCLUSIONS: A high variability in the operationalization of weight measures was found. Improving methods to construct clinical measures will support transparency and replicability in approaches, guide interpretation of findings, and facilitate comparisons across studies.

Full Text

Duke Authors

Cited Authors

  • Annis, A; Freitag, MB; Evans, RR; Wiitala, WL; Burns, J; Raffa, SD; Spohr, SA; Damschroder, LJ

Published Date

  • July 2020

Published In

Volume / Issue

  • 28 / 7

Start / End Page

  • 1205 - 1214

PubMed ID

  • 32478469

Pubmed Central ID

  • 32478469

Electronic International Standard Serial Number (EISSN)

  • 1930-739X

Digital Object Identifier (DOI)

  • 10.1002/oby.22790

Language

  • eng

Conference Location

  • United States