Your browser doesn't support javascript.
loading
Rule-Based Identification of Individuals with Mild Cognitive Impairment or Alzheimer's Disease Using Clinical Notes from the United States Veterans Affairs Healthcare System.
Aguilar, Byron J; Miller, Donald; Jasuja, Guneet; Li, Xuyang; Shishova, Ekaterina; O'Connor, Maureen K; Nguyen, Andrew; Morin, Peter; Berlowitz, Dan; Zhang, Raymond; Monfared, Amir Abbas Tahami; Zhang, Quanwu; Xia, Weiming.
Afiliação
  • Aguilar BJ; Geriatric Research Education and Clinical Center, VA Bedford Healthcare System, 200 Springs Road, Bedford, MA, USA.
  • Miller D; Zuckerberg College of Health Sciences, University of Massachusetts Lowell, Lowell, MA, USA.
  • Jasuja G; Center for Healthcare Organization and Implementation, VA Bedford Healthcare System, Bedford, MA, USA.
  • Li X; Geriatric Research Education and Clinical Center, VA Bedford Healthcare System, 200 Springs Road, Bedford, MA, USA.
  • Shishova E; Zuckerberg College of Health Sciences, University of Massachusetts Lowell, Lowell, MA, USA.
  • O'Connor MK; Geriatric Research Education and Clinical Center, VA Bedford Healthcare System, 200 Springs Road, Bedford, MA, USA.
  • Nguyen A; Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA.
  • Morin P; Geriatric Research Education and Clinical Center, VA Bedford Healthcare System, 200 Springs Road, Bedford, MA, USA.
  • Berlowitz D; Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA.
  • Zhang R; Zuckerberg College of Health Sciences, University of Massachusetts Lowell, Lowell, MA, USA.
  • Monfared AAT; Alzheimer's Disease and Brain Health, Eisai Inc., Nutley, NJ, USA.
  • Zhang Q; Alzheimer's Disease and Brain Health, Eisai Inc., Nutley, NJ, USA.
  • Xia W; Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada.
Neurol Ther ; 12(6): 2067-2078, 2023 Dec.
Article em En | MEDLINE | ID: mdl-37747662
ABSTRACT

BACKGROUND:

Early identification of individuals with mild cognitive impairment (MCI) and Alzheimer's disease (AD) is a clinical and research imperative. Use of diagnostic codes for MCI and AD identification has limitations. We used clinical notes to supplement diagnostic codes in the Veterans Affairs Healthcare System (VAHS) electronic health records (EHR) to identify and establish cohorts of Veterans recorded with MCI or AD.

METHODS:

Targeted keyword searches for MCI ("Mild cognitive impairment;" "MCI") and AD ("Alz*") were used to extract clinical notes from the VAHS EHR from fiscal year (FY) 2010 through FY 2019. Iterative steps of inclusion and exclusion were applied until searches achieved a positive predictive value ≥ 80%. MCI and AD cohorts were identified via clinical notes and/or diagnostic codes (i.e., including Veterans recorded by "Notes Only," "Notes + Code," or "Codes Only").

RESULTS:

A total of 2,134,661 clinical notes from 339,007 Veterans met the iterative search criteria for MCI due to any cause and 4,231,933 notes from 572,063 Veterans met the iterative search criteria for AD. Over the 10-year study period, the number of clinical notes recording AD was generally stable, whereas the number for MCI more than doubled. More Veterans were identified for the MCI or AD cohorts via clinical notes than by diagnostic codes, particularly in the AD cohort. Among Veterans identified by having "Notes + Code" for MCI, the number first recorded by a code was lower than the number first recorded by a note until FY 2015 and then gradually became comparable after FY 2015. Among Veterans identified by having "Notes + Code" for AD, the number first recorded by a note was more than double the number first recorded by a code AD in each of the FYs.

CONCLUSIONS:

Clinical note-based identification captured more Veterans recorded with MCI and AD than diagnostic code-based identification.
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Neurol Ther Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Neurol Ther Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos