Evidence map›Paper›PMID 30094823›Full record

Observational studyJournal of the American Geriatrics Society2018

Long-Term Nursing Home Entry: A Prognostic Model for Older Adults with a Family or Unpaid Caregiver.

Jennifer L Wolff, John Mulcahy, David L Roth, Irena S Cenzer, Judith D Kasper, Jin Huang, Kenneth E Covinsky

Open access · greenAbstract readObservational Study
In one paragraph

Observational study in Journal of the American Geriatrics Society, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
11.1field-weighted citation impact, top 2% 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

30 citing papers in PubMed, 46 citations in OpenAlex.

  1. Perceived Control, Cognitive Training, and Incident Alzheimer's Disease and Related Dementias in the ACTIVE Study.The journals of gerontology. Series B, Psychological sciences and social sciences · 2025
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  16. Drivers of Long-Term Care Considerations by Persons With Cognitive Impairment.Journal of applied gerontology : the official journal of the Southern Gerontological Society · 2021
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Jennifer L WolffDepartment of Health Policy and Management, Bloomberg School of Public Health.
John MulcahyDepartment of Health Policy and Management, Bloomberg School of Public Health.
David L RothCenter on Aging and Health, Division of Geriatric Medicine and Gerontology, School of Medicine, Johns Hopkins University, Baltimore, Maryland.
Irena S CenzerDivision of Geriatric Medicine, University of California, San Francisco, San Francisco, California.
Judith D KasperDepartment of Health Policy and Management, Bloomberg School of Public Health.
Jin HuangCenter on Aging and Health, Division of Geriatric Medicine and Gerontology, School of Medicine, Johns Hopkins University, Baltimore, Maryland.
Kenneth E CovinskyDivision of Geriatric Medicine, University of California, San Francisco, San Francisco, California.
Johns Hopkins University · USUniversity of California, San Francisco · USJohns Hopkins Medicine · US

Funding

The National Health and Trends StudyU01AG032947 · NIA · JOHNS HOPKINS UNIVERSITY · PI VICKI A. FREEDMAN, JENNIFER ANN SCHRACK · 2008 to 2026
$169.4M
Prognostic Significance of Family Caregiver Factors for Older Adult Health EventsR01AG047859 · NIA · JOHNS HOPKINS UNIVERSITY · PI WOLFF, JENNIFER L. · 2015 to 2018
$1.5M
NIA NIH HHS R01 AG047859NIA NIH HHS R01AG047859NIA NIH HHS U01 AG032947NIA NIH HHS U01AG032947
6 · The paper itself

Abstract

objectivesTo comprehensively examine factors associated with long-term nursing home (NH) entry from 6 domains of older adult and family caregiver risk from nationally representative surveys and develop a prognostic model and a simple scoring system for use in risk stratification.

designRetrospective observational study.

settingNational Long-Term Care Surveys 1999 and 2004 and National Health and Aging Trends Study 2011 and linked caregiver surveys.

participantsCommunity-living older adults receiving help with self-care disability and their primary family or unpaid caregiver (N=2,676). MEASUREMENTS: Prediction of long-term NH entry (>100 days or ending in death) by 24 months follow up, ascertained from Minimum Data Set assessments and dates of death from Medicare enrollment files. Risk factors were measured from survey responses.

resultsIn total, 16.1% of older adults entered a NH. Our final model and risk scoring system includes 7 independent risk factors: older adult age (1 point/5 years), living alone (5 points), dementia (3 points), 3 or more of 6 self-care activities (2 points), caregiver age (45-64: 1 point, 65-74: 2 points, ≥75: 4 points), caregiver help with money management (2 points), and caregiver report of moderate (2 points) or high (4 points) strain. Using this model, participants were assigned to risk quintiles. Long-term NH entry was 7.0% in the lowest quintile (0-6 points), 20.4% in the middle 3 quintiles (7-14 points), and 30.9% in the highest quintile (15-22 points). The model was well calibrated and demonstrated moderate discrimination (c-statistic=0.670 in the original data, c-statistic=0.647 in bootstrapped samples, c-statistic=0.652 using the point-scoring system).

conclusionWe developed a prognostic model and simple scoring system that may be used to stratify risk of long-term NH entry of community-living older adults. Our model may be useful for population health and policy applications.

Indexed as

Models, StatisticalAgedAged, 80 and overCaregiversFemaleGeriatric AssessmentHomes for the AgedHumansIndependent LivingLong-Term CareMaleMedicareMiddle AgedNursing HomesPrognosisRetrospective Studiesdisabilitynursing home entryrisk prediction

Identifiers

PMID30094823
PMCPMC6181771
OpenAlexW2887029781

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.