Evidence map›Paper›PMID 39349066›Full record

ArticleJournal of the American Medical Directors Association2024

Detecting Agitated Behaviors in Nursing Home Residents With Dementia Using Electronic Medical Records.

Hyunkyung Yun, Vincent Mor, Christopher Santostefano, Ellen McCreedy

Abstract read
In one paragraph

Article in Journal of the American Medical Directors Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Hyunkyung YunDepartment of Health Services, Policy and Practice, School of Public Health, Brown University, Providence, RI, USA. Electronic address: hyunkyung_yun@brown.edu.
Vincent MorDepartment of Health Services, Policy and Practice, School of Public Health, Brown University, Providence, RI, USA; Center for Gerontology and Healthcare Research, School of Public Health, Brown University, Providence, RI, USA; Center for Long-Term Care Quality and Innovation, School of Public Health, Brown University, Providence, RI, USA.
Christopher SantostefanoCenter for Gerontology and Healthcare Research, School of Public Health, Brown University, Providence, RI, USA.
Ellen McCreedyDepartment of Health Services, Policy and Practice, School of Public Health, Brown University, Providence, RI, USA; Center for Gerontology and Healthcare Research, School of Public Health, Brown University, Providence, RI, USA; Center for Long-Term Care Quality and Innovation, School of Public Health, Brown University, Providence, RI, USA.

Funding

Training Core (I)U54AG063546 · NIA · BROWN UNIVERSITY · PI Vincent Mor · 2019 to 2026
$125.9M
NIA NIH HHS U54 AG063546
6 · The paper itself

Abstract

objectivesAgitated behaviors (behaviors) are common in nursing home (NH) residents with Alzheimer's disease and related dementias (ADRD). Pragmatic trials of behavior management interventions rely on routinely collected Minimum Data Set (MDS) data to evaluate study outcomes, despite known underreporting. We describe a method to augment MDS-based behavioral measures with structured and unstructured data from NH electronic medical records (EMR).

designRepeated cross-sectional analyses of EMR data from a single multistate NH corporation. SETTING AND

participantsLong-stay residents (at least 90 days in NH) with ADRD from January 2020 through August 2022.

methodsQuarterly and annual assessments of NH residents with ADRD during the study period were identified. For MDS, any behavior was defined as a score of 1 or higher on the Agitated and Reactive Behavior Scale. For structured EMR data, any behavior was defined as increased resident agitation, verbal aggression, or physical aggression on the Interventions to Reduce Acute Care Transfers, Change in Condition form (INTERACT). For unstructured EMR data, any behavior was defined using keyword searches of free-text orders.

resultsA total of 77,936 MDS assessments for 19,705 long-stay residents with ADRD in 322 NHs were identified; 14.8% (SD 35.6) of residents had behaviors per month using MDS alone, 16.2% (SD 36.9) using MDS and INTERACT, and 18.6% (SD 38.9) using MDS, INTERACT, and orders. Supplementing MDS with EMR data increased behavior identification by 3.8 percentage points (a 25.7% relative increase). Less than 0.5% had behaviors noted in all 3 sources consistently across study months. CONCLUSIONS AND IMPLICATIONS: Using EMR data increased detectable behaviors vs the MDS alone. The 3 sources captured different types of behaviors and using them together may be a more comprehensive identification strategy. These results are important for better targeting of interventions and allocation of resources to improve the quality of life for NH residents with ADRD-related behaviors.

Indexed as

DementiaElectronic Health RecordsNursing HomesPsychomotor AgitationAgedAged, 80 and overCross-Sectional StudiesFemaleHumansMaledementiaelectronic health recordsNeuropsychiatric symptomsnursing homespragmatic trials

Identifiers

PMID39349066
PMCPMC11606745

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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.