Evidence map›Paper›PMID 35505552›Full record

Observational studyWorld neurosurgery2022

Statistical Approaches for Quantifying the Quality of Neurosurgical Care.

Sharon-Lise T Normand, Katya Zelevinsky, Haley K Abing, Marcela Horvitz-Lennon

Abstract readObservational Study
In one paragraph

Observational study in World neurosurgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

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

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

  1. Pooled it
  2. 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

4 authors.

Sharon-Lise T NormandDepartment of Health Care Policy, Harvard Medical School, Boston, Massachusetts, USA; Department of Biostatistics, Harvard Chan School of Public Health, Boston, Massachusetts, USA. Electronic address: sharon@hcp.med.harvard.edu.
Katya ZelevinskyDepartment of Health Care Policy, Harvard Medical School, Boston, Massachusetts, USA.
Haley K AbingDepartment of Health Care Policy, Harvard Medical School, Boston, Massachusetts, USA.
Marcela Horvitz-LennonRAND Corporation, Boston, Massachusetts, USA; Cambridge Health Alliance, Cambridge, Massachusetts, USA.

Funding

Improving Minority Health by Monitoring Medicaid Quality, Disparities and ValueR01MD012428 · NIMHD · RAND CORPORATION · PI HORVITZ-LENNON, MARCELA V, NORMAND, SHARON-LISE TERESA · 2017 to 2020
$3.2M
Improving Value of Publicly Funded Mental Health CareR01MH106682 · NIMH · RAND CORPORATION · PI HORVITZ-LENNON, MARCELA V, NORMAND, SHARON-LISE TERESA · 2016 to 2019
$2.6M
An In-Depth Investigation of Racial & Ethnic Disparities in Schizophrenia CareR01MH087488 · NIMH · RAND CORPORATION · PI HORVITZ-LENNON, MARCELA V, NORMAND, SHARON-LISE TERESA · 2010 to 2012
$1.6M
NIMHD NIH HHS R01 MD012428NIMH NIH HHS R01 MH087488NIMH NIH HHS R01 MH106682
6 · The paper itself

Abstract

backgroundQuantifying quality of health care can provide valuable information to patients, providers, and policy makers. However, the observational nature of measuring quality complicates assessments.

methodsWe describe a conceptual model for defining quality and its implications about the data collected, how to make inferences about quality, and the assumptions required to provide statistically valid estimates. Twenty-one binary or polytomous quality measures collected from 101,051 adult Medicaid beneficiaries aged 18-64 years with schizophrenia from 5 U.S. states show methodology. A categorical principal components analysis establishes dimensionality of quality, and item response theory models characterize the relationship between each quality measure and a unidimensional quality construct. Latent regression models estimate racial/ethnic and geographic quality disparities.

resultsMore than 90% of beneficiaries filled at least 1 antipsychotic prescription and 19% were hospitalized for schizophrenia during a 12-month observational period in our multistate cohort with approximately 2/3 nonwhite beneficiaries. Four quality constructs emerged: inpatient, emergency room, pharmacologic/ambulatory, and ambulatory only. Using a 2-parameter logistic model, pharmacologic/ambulatory care quality varied from -2.35 to 1.26 (higher = better quality). Black and Latinx beneficiaries had lower pharmacologic/ambulatory quality compared with whites. Race/ethnicity modified the association of state and pharmacologic/ambulatory care quality in latent regression modeling. Average quality ranged from -0.28 (95% confidence interval, -2.15 to 1.04) for blacks in New Jersey to 0.46 [95% confidence interval, -0.89 to 1.40] for whites in Michigan.

conclusionsBy combining multiple quality measures using item response theory models, a composite measure can be estimated that has more statistical power to detect differences among subjects than the observed mean per subject.

Indexed as

Antipsychotic AgentsBlack or African AmericanAdultEthnicityHumansMedicaidUnited StatesWhite PeopleAntipsychotic AgentsItem response theory modelLatent constructLatent regression modelSchizophrenia

Identifiers

PMID35505552
PMCPMC9074098

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.