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Construction and Use of Body Weight Measures from Administrative Data in a Large National Health System: A Systematic Review.
Annis, Ann; Freitag, Michelle B; Evans, Richard R; Wiitala, Wyndy L; Burns, Jennifer; Raffa, Susan D; Spohr, Stephanie A; Damschroder, Laura J.
Afiliação
  • Annis A; Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan, USA.
  • Freitag MB; College of Nursing, Michigan State University, East Lansing, Michigan, USA.
  • Evans RR; Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan, USA.
  • Wiitala WL; Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan, USA.
  • Burns J; Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan, USA.
  • Raffa SD; Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan, USA.
  • Spohr SA; National Center for Health Promotion and Disease Prevention, Veterans Health Administration, Durham, North Carolina, USA.
  • Damschroder LJ; Department of Psychiatry & Behavioral Sciences, Duke University School of Medicine, Durham, North Carolina, USA.
Obesity (Silver Spring) ; 28(7): 1205-1214, 2020 07.
Article em En | MEDLINE | ID: mdl-32478469
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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Temas: Geral Base de dados: MEDLINE Assunto principal: Peso Corporal / Pesos e Medidas Corporais / Bases de Dados Factuais / Programas Nacionais de Saúde Tipo de estudo: Guideline / Prognostic_studies / Systematic_reviews Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: Obesity (Silver Spring) Assunto da revista: CIENCIAS DA NUTRICAO / FISIOLOGIA / METABOLISMO Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Temas: Geral Base de dados: MEDLINE Assunto principal: Peso Corporal / Pesos e Medidas Corporais / Bases de Dados Factuais / Programas Nacionais de Saúde Tipo de estudo: Guideline / Prognostic_studies / Systematic_reviews Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: Obesity (Silver Spring) Assunto da revista: CIENCIAS DA NUTRICAO / FISIOLOGIA / METABOLISMO Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos