Evidence map›Paper›PMID 38556756›Full record

ArticleJournal of applied gerontology : the official journal of the Southern Gerontological Society2024

Using Natural Language Processing to Identify Home Health Care Patients at Risk for Diagnosis of Alzheimer's Disease and Related Dementias.

Miriam Ryvicker, Yolanda Barrón, Jiyoun Song, Maryam Zolnoori, Shivani Shah, Julia G Burgdorf, James M Noble, Maxim Topaz

Open access · greenAbstract read
In one paragraph

Article in Journal of applied gerontology : the official journal of the Southern Gerontological Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
3.5field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Applying the Brief Interview for Mental Status in a Diverse Home Health Patient Population.Journal of the American Medical Directors Association · 2026
    Article
  5. Accelerating real-world prediction and research in Alzheimer's: The M3AD study.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
  6. Article
  7. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 1 country.

Miriam RyvickerCenter for Home Care Policy & Research, VNS Health, New York, NY, USA.ORCID 0000-0002-7339-080X
Yolanda BarrónCenter for Home Care Policy & Research, VNS Health, New York, NY, USA.ORCID 0000-0002-7064-937X
Jiyoun SongUniversity of Pennsylvania School of Nursing, Philadelphia, PA, USA.
Maryam ZolnooriColumbia University School of Nursing, New York, NY, USA.
Shivani ShahCenter for Home Care Policy & Research, VNS Health, New York, NY, USA.
Julia G BurgdorfCenter for Home Care Policy & Research, VNS Health, New York, NY, USA.ORCID 0000-0002-3356-1897
James M NobleColumbia University Medical Center, New York, NY, USA.ORCID 0000-0003-0648-6702
Maxim TopazCenter for Home Care Policy & Research, VNS Health, New York, NY, USA.
VNS Health · USColumbia University · USColumbia University Irving Medical Center · USUniversity of Pennsylvania · US

Funding

Research Education CoreP30AG066462 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI PHILIP L DE JAGER · 2020 to 2026
$30.1M
Nurses' documentation of patient diagnoses, symptoms and interventions for home care patients with Alzheimer's Disease and related dementias: A natural language processing studyR21AG065753 · NIA · VISITING NURSE SERVICE OF NEW YORK · PI RYVICKER, MIRIAM, TOPAZ, MAXIM · 2020 to 2021
$474k
NIA NIH HHS P30 AG066462NIA NIH HHS R21 AG065753
6 · The paper itself

Abstract

This study aimed to: (1) validate a natural language processing (NLP) system developed for the home health care setting to identify signs and symptoms of Alzheimer's disease and related dementias (ADRD) documented in clinicians' free-text notes; (2) determine whether signs and symptoms detected via NLP help to identify patients at risk of a new ADRD diagnosis within four years after admission. This study applied NLP to a longitudinal dataset including medical record and Medicare claims data for 56,652 home health care patients and Cox proportional hazard models to the subset of 24,874 patients admitted without an ADRD diagnosis. Selected ADRD signs and symptoms were associated with increased risk of a new ADRD diagnosis during follow-up, including: motor issues; hoarding/cluttering; uncooperative behavior; delusions or hallucinations; mention of ADRD disease names; and caregiver stress. NLP can help to identify patients in need of ADRD-related evaluation and support services.

Indexed as

Natural Language ProcessingAgedAged, 80 and overDatasets as TopicHumansLongitudinal StudiesMaleMedicareProportional Hazards ModelsReproducibility of ResultsUnited StatesAlzheimer’s diseasedementiahome health carenatural language processing

Identifiers

PMID38556756
PMCPMC11368608
OpenAlexW4393363863

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.