Evaluating Cognitive Impairment in a Large Health Care System: The Cognition in Primary Care Program.

Alzheimer’s disease cognitive dysfunction continuing medical education dementia early detection of disease mild cognitive impairment primary care

Journal

Journal of Alzheimer's disease : JAD
ISSN: 1875-8908
Titre abrégé: J Alzheimers Dis
Pays: Netherlands
ID NLM: 9814863

Informations de publication

Date de publication:
27 Apr 2024
Historique:
medline: 3 5 2024
pubmed: 3 5 2024
entrez: 3 5 2024
Statut: aheadofprint

Résumé

The prevalence of Alzheimer's disease and related disorders (ADRD) is rising. Primary care providers (PCPs) will increasingly be required to play a role in its detection but lack the training to do so. To develop a model for cognitive evaluation which is feasible in primary care and evaluate its implementation in a large health system. The Cognition in Primary Care Program consists of web-based training together with integrated tools built into the electronic record. We implemented the program among PCPs at 14 clinics in a large health system. We (1) surveyed PCPs to assess the impact of training on their confidence to evaluate cognition, (2) measured the number of cognitive assessments they performed, and (3) tracked the number of patients diagnosed with mild cognitive impairment (MCI). Thirty-nine PCPs completed the training which covered how to evaluate cognition. Survey response rate from those PCPs was 74%. Six months after the end of the training, they reported confidence in assessing cognition (mean 4.6 on 5-point scale). Cognitive assessments documented in the health record increased from 0.8 per month before the training to 2.5 in the six months after the training. Patients who were newly diagnosed with MCI increased from 4.2 per month before the training to 6.0 per month in the six months after the training. This model for cognitive evaluation in a large health system was shown to increase cognitive testing and increase diagnoses of MCI. Such improvements are essential for the timely detection of ADRD.

Sections du résumé

Background UNASSIGNED
The prevalence of Alzheimer's disease and related disorders (ADRD) is rising. Primary care providers (PCPs) will increasingly be required to play a role in its detection but lack the training to do so.
Objective UNASSIGNED
To develop a model for cognitive evaluation which is feasible in primary care and evaluate its implementation in a large health system.
Methods UNASSIGNED
The Cognition in Primary Care Program consists of web-based training together with integrated tools built into the electronic record. We implemented the program among PCPs at 14 clinics in a large health system. We (1) surveyed PCPs to assess the impact of training on their confidence to evaluate cognition, (2) measured the number of cognitive assessments they performed, and (3) tracked the number of patients diagnosed with mild cognitive impairment (MCI).
Results UNASSIGNED
Thirty-nine PCPs completed the training which covered how to evaluate cognition. Survey response rate from those PCPs was 74%. Six months after the end of the training, they reported confidence in assessing cognition (mean 4.6 on 5-point scale). Cognitive assessments documented in the health record increased from 0.8 per month before the training to 2.5 in the six months after the training. Patients who were newly diagnosed with MCI increased from 4.2 per month before the training to 6.0 per month in the six months after the training.
Conclusions UNASSIGNED
This model for cognitive evaluation in a large health system was shown to increase cognitive testing and increase diagnoses of MCI. Such improvements are essential for the timely detection of ADRD.

Identifiants

pubmed: 38701141
pii: JAD231200
doi: 10.3233/JAD-231200
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Barak Gaster (B)

Department of Medicine, University of Washington, Seattle, WA, USA.

Monica Zigman Suchsland (MZ)

Department of Family Medicine, University of Washington, Seattle, WA, USA.

Annette L Fitzpatrick (AL)

Department of Family Medicine, University of Washington, Seattle, WA, USA.

Joshua M Liao (JM)

Department of Medicine, University of Washington, Seattle, WA, USA.

Basia Belza (B)

School of Nursing, University of Washington, Seattle, WA, USA.

Amy P Hsu (AP)

Department of Medicine, University of Washington, Seattle, WA, USA.

Sarah McKiddy (S)

School of Nursing, University of Washington, Seattle, WA, USA.

Christina Park (C)

Department of Epidemiology, University of Washington, Seattle, WA, USA.

Benjamin S Olivari (BS)

National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, USA.

Angad P Singh (AP)

Department of Family Medicine, University of Washington, Seattle, WA, USA.

Jaqueline Raetz (J)

Department of Family Medicine, University of Washington, Seattle, WA, USA.

Classifications MeSH