An Automated Malnutrition Screening Tool Using Routinely Collected Data for Older Adults in Long-Term Care: Development and Internal Validation of AutoMal
The AutoMal demonstrates excellent ability to differentiate malnutrition status. It makes automated identification of malnutrition possible by using 2 variables commonly found in electronic health records.
Authors
- Melanie Roberts
- Jonathan Foo (ORCID: https://orcid.org/0000-0003-4533-8307)
- Christian Osadnik (ORCID: https://orcid.org/0000-0001-9040-8007)
- Marie‐Claire O'Shea (ORCID: https://orcid.org/0000-0001-8226-7910)
- Judith Bauer (ORCID: https://orcid.org/0000-0002-3830-5147)
- Lauren Williams (ORCID: https://orcid.org/0000-0002-7860-0319)
Institutions
- Griffith University (AU)
- Monash University (AU)
Publication Details
- Journal
- Journal of the American Medical Directors Association
- Published
- 2024-09-08
- DOI
- https://doi.org/10.1016/j.jamda.2024.105252
- Primary Topic
- Nutrition and Health in Aging
- Type
- article
- Field-Weighted Citation Impact
- 0.00