Evidence map›Paper›PMID 38114962›Full record

ArticleBMC women's health2023

The Carolina hysterectomy cohort (CHC): a novel case series of reproductive-aged hysterectomy patients across 10 hospitals in the US south.

Zakiya M Haji-Noor, Joacy G Mathias, Theo Gabriel Beltran, Lauren G Anderson, Mollie E Wood, Annie Green Howard, Sharon Peacock Hinton, Kemi M Doll, Whitney R Robinson

Abstract read
In one paragraph

Article in BMC women's health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. 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

9 authors.

Zakiya M Haji-Noor *Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Joacy G Mathias *Division of Women's Community and Population Health and Department of Obstetrics Gynecology, Duke University School of Medicine, Durham, North, Carolina, USA.
Theo Gabriel BeltranDepartment of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Lauren G AndersonDivision of Women's Community and Population Health and Department of Obstetrics Gynecology, Duke University School of Medicine, Durham, North, Carolina, USA.
Mollie E WoodDepartment of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Annie Green HowardDepartment of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Sharon Peacock HintonDepartment of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Kemi M DollDepartment of Obstetrics & Gynecology, University of Washington School of Medicine, Seattle, WA, USA.
Whitney R RobinsonDepartment of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. whitney.robinson489@duke.edu.

Funding

Re-Entry Supplement: Investigation of Oral Microbial Enzymes for the Detection and Treatment of Periodontal DiseaseUL1TR002489 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BUSE, JOHN BERNARD, SHAHEEN, NICHOLAS J · 2018 to 2022
$48.6M
North Carolina Translational & Clinical Sciences Institute (NC TraCS)UL1TR001111 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BUSE, JOHN BERNARD, CAREY, TIMOTHY S · 2013 to 2017
$43.9M
North Carolina Translational and Clinical Sciences Institute (NC TraCS)UM1TR004406 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI NICHOLAS J SHAHEEN · 2023 to 2026
$37.5M
Science CoreP2CHD065563 · NICHD · DUKE UNIVERSITY · PI James Moody · 2015 to 2026
$5.7M
Racial Differences in Treatment with Hysterectomy: a Multilevel InvestigationR01MD011680 · NIMHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ROBINSON, WHITNEY RAGAN · 2017 to 2021
$3.3M
NCATS NIH HHS UL1 TR001111NCATS NIH HHS UL1 TR002489NCATS NIH HHS UM1 TR004406NICHD NIH HHS P2C HD065563NIMHD NIH HHS R01 MD011680
6 · The paper itself

Abstract

backgroundHysterectomy is a common surgery among reproductive-aged U.S. patients, with rates highest among Black patients in the South. There is limited insight on causes of these racial differences. In the U.S., electronic medical records (EMR) data can offer richer detail on factors driving surgical decision-making among reproductive-aged populations than insurance claims-based data. Our objective in this cohort profile paper is to describe the Carolina Hysterectomy Cohort (CHC), a large EMR-based case-series of premenopausal hysterectomy patients in the U.S. South, supplemented with census and surgeon licensing data. To demonstrate one strength of the data, we evaluate whether patient and surgeon characteristics differ by insurance payor type.

methodsWe used structured and abstracted EMR data to identify and characterize patients aged 18-44 years who received hysterectomies for non-cancerous conditions between 10/02/2014-12/31/2017 in a large health care system comprised of 10 hospitals in North Carolina. We used Chi-squared and Kruskal Wallis tests to compare whether patients' socio-demographic and relevant clinical characteristics, and surgeon characteristics differed by patient insurance payor (public, private, uninsured).

resultsOf 1857 patients (including 55% non-Hispanic White, 30% non-Hispanic Black, 9% Hispanic), 75% were privately-insured, 17% were publicly-insured, and 7% were uninsured. Menorrhagia was more prevalent among the publicly-insured (74% vs 68% overall). Fibroids were more prevalent among the privately-insured (62%) and the uninsured (68%). Most privately insured patients were treated at non-academic hospitals (65%) whereas most publicly insured and uninsured patients were treated at academic centers (66 and 86%, respectively). Publicly insured and uninsured patients had higher median bleeding (public: 7.0, uninsured: 9.0, private: 5.0) and pain (public: 6.0, uninsured: 6.0, private: 3.0) symptom scores than the privately insured. There were no statistical differences in surgeon characteristics by payor groups.

conclusionThis novel study design, a large EMR-based case series of hysterectomies linked to physician licensing data and manually abstracted data from unstructured clinical notes, enabled identification and characterization of a diverse reproductive-aged patient population more comprehensively than claims data would allow. In subsequent phases of this research, the CHC will leverage these rich clinical data to investigate multilevel drivers of hysterectomy in an ethnoracially, economically, and clinically diverse series of hysterectomy patients.

Indexed as

Insurance CoverageSurgeonsAdultFemaleHospitalsHumansHysterectomyInsurance, HealthMedically UninsuredUnited StatesCase seriesCohort profileElectronic medical recordEpidemiologyHealth disparityHysterectomyReproductive health

Identifiers

PMID38114962
PMCPMC10729499

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