Evidence map›Paper›PMID 32139320›Full record

SynthesisDisability and health journal2020

Identifying reproductive-aged women with physical and sensory disabilities in administrative health data: A systematic review.

Hilary K Brown, Adele Carty, Susan M Havercamp, Susan Parish, Yona Lunsky

Abstract readSystematic Review
In one paragraph

Synthesis in Disability and health journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Outcomes in patients with and without disability admitted to hospital with COVID-19: a retrospective cohort study.CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne · 2022
    Article
  9. Article
  10. 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

5 authors.

Hilary K BrownInterdisciplinary Centre for Health & Society, University of Toronto Scarborough, Toronto, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, Canada; Women's College Research Institute, Women's College Hospital, Toronto, Canada. Electronic address: hk.brown@utoronto.ca.
Adele CartyDalla Lana School of Public Health, University of Toronto, Toronto, Canada.
Susan M HavercampCenter for Psychiatry and Behavioral Health, Wexner Medical Center, Ohio State University, Columbus, OH, United States.
Susan ParishCollege of Health Professions, Virginia Commonwealth University, Richmond, VA, United States.
Yona LunskyDepartment of Psychiatry, University of Toronto, Toronto, Canada; Centre for Addiction & Mental Health, Toronto, Canada.

Funding

Pregnancy in Women with Disabilities: Using Novel Methods to Characterize RiskR01HD092326 · NICHD · UNIVERSITY OF TORONTO · PI BROWN, HILARY, LUNSKY, YONA · 2017 to 2020
$590k
NICHD NIH HHS R01 HD092326
6 · The paper itself

Abstract

backgroundWomen with disabilities experience significant health disparities. A barrier to progress in addressing these disparities is the lack of population-based data on their health outcomes, which are needed to plan health care delivery systems. Administrative health data are increasingly being used to measure the health of entire populations, but these data may only capture impairment and not activity and participation restrictions.

objectiveWe conducted a systematic review to identify and appraise existing literature on the development and validation of algorithms to identify reproductive-aged women with physical and sensory disabilities in administrative health data.

methodsWe searched Medline, EMBASE, CINAHL, PsycINFO, and Scopus from inception to April 2019 for studies of the development and/or validation of algorithms using diagnostic, procedural, or prescription codes to identify physical and sensory disabilities in administrative health data. Study and algorithm characteristics were extracted and quality was assessed using standardized instruments.

resultsOf 14,073 articles initially identified, we reviewed 6 articles representing 2 unique algorithms. One algorithm aimed to correlate diagnoses, procedure codes, and prescriptions with ability to access routine care as an indicator of functional limitation. The other algorithm used diagnostic and procedure codes to identify use of mobility-assistive devices to measure functional limitation. Only one algorithm was validated against self-reported disability.

conclusionsOur findings underscore the need to strengthen current methods to identify disability in administrative health data, including linkage with other sources of information on functional limitations, so that population-based data can be used to optimize health care for women with disabilities.

Indexed as

AdultAlgorithmsFemaleHealthcare DisparitiesHealth StatusHumansMovement DisordersPersons with DisabilitiesSelf ReportSensation DisordersUnited StatesAlgorithmsDatabasesDisabled personsRegistries

Identifiers

PMID32139320
PMCPMC7387197

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.