Evidence map›Paper›PMID 33029550›Full record

ArticleGerontology & geriatric medicine

Free-Text Documentation of Dementia Symptoms in Home Healthcare: A Natural Language Processing Study.

Maxim Topaz, Victoria Adams, Paula Wilson, Kyungmi Woo, Miriam Ryvicker

Abstract read
In one paragraph

Article in Gerontology & geriatric medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 3 pooled it
–field-weighted citation impact
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

34 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  4. Article
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  7. Accelerating real-world prediction and research in Alzheimer's: The M3AD study.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
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  15. Applying natural language processing to understand symptoms among older adult home healthcare patients with urinary incontinence.Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing · 2025
    Article
  16. Article
  17. Using Natural Language Processing to Identify Home Health Care Patients at Risk for Diagnosis of Alzheimer's Disease and Related Dementias.Journal of applied gerontology : the official journal of the Southern Gerontological Society · 2024
    Article
  18. Prevalence of cognitive impairment in home health physical therapy.Journal of the American Geriatrics Society · 2024
    Article
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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

5 authors.

Maxim TopazColumbia University, New York, NY, USA.
Victoria AdamsVisiting Nurse Service of New York, New York, NY, USA.
Paula WilsonVisiting Nurse Service of New York, New York, NY, USA.
Kyungmi WooColumbia University, New York, NY, USA.
Miriam RyvickerVisiting Nurse Service of New York, New York, NY, USA.ORCID https://orcid.org/0000-0002-7339-080X

Funding

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 R21 AG065753
6 · The paper itself

Abstract

backgroundLittle is known about symptom documentation related to Alzheimer's disease and related dementias (ADRD) by home healthcare (HHC) clinicians.

objectiveThis study: (1) developed a natural language processing (NLP) algorithm that identifies common neuropsychiatric symptoms of ADRD in HHC free-text clinical notes; (2) described symptom clusters and hospitalization or emergency department (ED) visit rates for patients with and without these symptoms.

methodWe examined a corpus of -2.6 million free-text notes for 112,237 HHC episodes among 89,459 patients admitted to a non-profit HHC agency for post-acute care with any diagnosis. We used NLP software (NimbleMiner) to construct indicators of six neuropsychiatric symptoms. Structured HHC assessment data were used to identify known ADRD diagnoses and construct measures of hospitalization/ED use during HHC.

resultsNeuropsychiatric symptoms were documented for 40% of episodes. Common clusters included impaired memory, anxiety and/or depressed mood. One in three episodes without an ADRD diagnosis had documented symptoms. Hospitalization/ED rates increased with one or more symptoms present.

conclusionHHC providers should examine episodes with neuropsychiatric symptoms but no ADRD diagnoses to determine whether ADRD diagnosis was missed or to recommend ADRD evaluation. NLP-generated symptom indicators can help to identify high-risk patients for targeted interventions.

Indexed as

Alzheimer’s diseasedementiaelectronic health recordhome health carenatural language processing

Identifiers

PMID33029550
PMCPMC7520927

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.