Evidence map›Paper›PMID 33550264›Full record

ArticleBMJ open2021

Identifying patterns of health care utilisation among physical elder abuse victims using Medicare data and legally adjudicated cases: protocol for case-control study using data linkage and machine learning.

Tony Rosen, Yuhua Bao, Yiye Zhang, Sunday Clark, Katherine Wen, Alyssa Elman, Philip Jeng, Elizabeth Bloemen, Daniel Lindberg, Richard Krugman and 5 more

Abstract read
In one paragraph

Article in BMJ open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. The Impact of Nurse Home-Visiting for Pregnant and Parenting Individuals with Previous Live Births.Prevention science : the official journal of the Society for Prevention Research · 2026
    Article
  3. Article
  4. Article
  5. Article
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

15 authors.

Tony RosenDepartment of Emergency Medicine, Weill Cornell Medicine/NewYork-Presbyterian Hospital, New York, New York, USA aer2006@med.cornell.edu.ORCID 0000-0001-6638-4121
Yuhua BaoDepartment of Health Policy & Research, Weill Cornell Medical College, New York, New York, USA.
Yiye ZhangDepartment of Health Policy & Research, Weill Cornell Medical College, New York, New York, USA.
Sunday ClarkDepartment of Emergency Medicine, Weill Cornell Medicine/NewYork-Presbyterian Hospital, New York, New York, USA.
Katherine WenDepartment of Policy Analysis and Management, Cornell University, Ithaca, New York, USA.
Alyssa ElmanDepartment of Emergency Medicine, Weill Cornell Medicine/NewYork-Presbyterian Hospital, New York, New York, USA.
Philip JengDepartment of Health Policy & Research, Weill Cornell Medical College, New York, New York, USA.
Elizabeth BloemenDepartment of Internal Medicine, University of Colorado School of Medicine, Aurora, Colorado, USA.
Daniel LindbergThe Kempe Center for the Prevention & Treatment of Child Abuse & Neglect, University of Colorado School of Medicine, Aurora, Colorado, USA.
Richard KrugmanThe Kempe Center for the Prevention & Treatment of Child Abuse & Neglect, University of Colorado School of Medicine, Aurora, Colorado, USA.
Jacquelyn CampbellJohn Hopkins University School of Nursing, John Hopkins University, Baltimore, Maryland, USA.
Ronet BachmanDepartment of Criminology, University of Delaware, Newark, Delaware, USA.
Terry FulmerJohn A Hartford Foundation, New York, New York, USA.
Karl PillemerDepartment of Policy Analysis and Management, Cornell University, Ithaca, New York, USA.
Mark LachsDivision of Geriatrics and Palliative Care, Weill Cornell Medicine/NewYork-Presbyterian Hospital, New York, New York, USA.

Funding

Pilot CoreP30AG022845 · NIA · WEILL MEDICAL COLL OF CORNELL UNIV · PI Manney Carrington Reid, ELAINE WETHINGTON · 2003 to 2026
$15.2M
Identifying Patterns of Health Care Utilization among Physical Elder Abuse Victims Using Medicare Data and Legally Adjudicated CasesR01AG060086 · NIA · WEILL MEDICAL COLL OF CORNELL UNIV · PI ROSEN, ANTHONY · 2018 to 2022
$2.2M
Identifying Injury Patterns and Forensic Biomarkers Diagnostic of Physical Elder AbuseK76AG054866 · NIA · WEILL MEDICAL COLL OF CORNELL UNIV · PI ROSEN, ANTHONY · 2016 to 2021
$1.1M
Outcome-driven Order Set Content Development, Management, and EvaluationK01LM013257 · NLM · WEILL MEDICAL COLL OF CORNELL UNIV · PI ZHANG, YIYE · 2019 to 2021
$541k
NIA NIH HHS K76 AG054866NIA NIH HHS P30 AG022845NIA NIH HHS R01 AG060086NLM NIH HHS K01 LM013257
6 · The paper itself

Abstract

introductionPhysical elder abuse is common and has serious health consequences but is under-recognised and under-reported. As assessment by healthcare providers may represent the only contact outside family for many older adults, clinicians have a unique opportunity to identify suspected abuse and initiate intervention. Preliminary research suggests elder abuse victims may have different patterns of healthcare utilisation than other older adults, with increased rates of emergency department use, hospitalisation and nursing home placement. Little is known, however, about the patterns of this increased utilisation and associated costs. To help fill this gap, we describe here the protocol for a study exploring patterns of healthcare utilisation and associated costs for known physical elder abuse victims compared with non-victims. METHODS AND ANALYSIS: We hypothesise that various aspects of healthcare utilisation are differentially affected by physical elder abuse victimisation, increasing ED/hospital utilisation and reducing outpatient/primary care utilisation. We will obtain Medicare claims data for a series of well-characterised, legally adjudicated cases of physical elder abuse to examine victims' healthcare utilisation before and after the date of abuse detection. We will also compare these physical elder abuse victims to a matched comparison group of non-victimised older adults using Medicare claims. We will use machine learning approaches to extend our ability to identify patterns suggestive of potential physical elder abuse exposure. Describing unique patterns and associated costs of healthcare utilisation among elder abuse victims may improve the ability of healthcare providers to identify and, ultimately, intervene and prevent victimisation. ETHICS AND DISSEMINATION: This project has been reviewed and approved by the Weill Cornell Medicine Institutional Review Board, protocol #1807019417, with initial approval on 1 August 2018. We aim to disseminate our results in peer-reviewed journals at national and international conferences and among interested patient groups and the public.

Indexed as

Elder AbuseAgedCase-Control StudiesChildHumansInformation Storage and RetrievalMachine LearningMedicarePatient Acceptance of Health CareUnited Statesgeriatric medicinehealth economicsprotocols & guidelines

Identifiers

PMID33550264
PMCPMC7925867

What OpenQuestion holds

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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.