Evidence map›Paper›PMID 35339240›Full record

ArticleAcademic pediatrics2022

Enhancing Quality Measurement With Clinical Information: A Use Case of Body Mass Index Change Among Children Taking Second Generation Antipsychotics.

Tianyao Huo, Qian Li, Michelle I Cardel, Regina Bussing, Almut G Winterstein, Dominick J Lemas, Hongzhi Xu, Jennifer Woodard, Kamila Mistry, Sarah Scholle and 2 more

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Academic pediatrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.6field-weighted citation impact, top 33% of its field
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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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

12 authors at 3 institutions in 2 countries.

Tianyao HuoDepartment of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida (T Huo, Q Li, MI Cardel, DJ Lemas, H Xu, J Woodard, KE Muller, and EA Shenkman), Gainesville, Fla. Electronic address: thuo@ufl.edu.
Qian LiDepartment of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida (T Huo, Q Li, MI Cardel, DJ Lemas, H Xu, J Woodard, KE Muller, and EA Shenkman), Gainesville, Fla.
Michelle I CardelDepartment of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida (T Huo, Q Li, MI Cardel, DJ Lemas, H Xu, J Woodard, KE Muller, and EA Shenkman), Gainesville, Fla; WW International, Inc (MI Cardel), New York, NY.
Regina BussingDepartment of Psychiatry, College of Medicine, University of Florida (R Bussing), Gainesville, Fla.
Almut G WintersteinDepartment of Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida (AG Winterstein), Gainesville, Fla.
Dominick J LemasDepartment of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida (T Huo, Q Li, MI Cardel, DJ Lemas, H Xu, J Woodard, KE Muller, and EA Shenkman), Gainesville, Fla.
Hongzhi XuDepartment of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida (T Huo, Q Li, MI Cardel, DJ Lemas, H Xu, J Woodard, KE Muller, and EA Shenkman), Gainesville, Fla.
Jennifer WoodardDepartment of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida (T Huo, Q Li, MI Cardel, DJ Lemas, H Xu, J Woodard, KE Muller, and EA Shenkman), Gainesville, Fla.
Kamila MistryAgency for Healthcare Research and Quality (K Mistry), Rockville, Md.
Sarah ScholleNational Committee for Quality Assurance (S Scholle), Washington, DC.
Keith E MullerDepartment of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida (T Huo, Q Li, MI Cardel, DJ Lemas, H Xu, J Woodard, KE Muller, and EA Shenkman), Gainesville, Fla.
Elizabeth A ShenkmanDepartment of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida (T Huo, Q Li, MI Cardel, DJ Lemas, H Xu, J Woodard, KE Muller, and EA Shenkman), Gainesville, Fla.
University of Florida · USAgency for Healthcare Research and Quality · USNational Committee for Quality Assurance · US

Funding

Using social networks to map and evaluate team science across CTSA hubsUL1TR001427 · NCATS · UNIVERSITY OF FLORIDA · PI MITCHELL, DUANE A. · 2015 to 2024
$37.2M
National Collaborative for Innovation in Quality Measurement: Implementing and Improving (NCINQ II)U18HS025296 · AHRQ · NATIONAL COMMITTEE FOR QUALITY ASSURANCE · PI SCHOLLE, SARAH H. · 2016 to 2016
$2.7M
The Child Health Quality (CHeQ) Partnership ProgramU18HS025298 · AHRQ · UNIVERSITY OF FLORIDA · PI SHENKMAN, ELIZABETH A. · 2016 to 2019
$2.6M
Methods and Software for Lifecourse Epidemiology Data and Sample Size AnalysisR01GM121081 · NIGMS · UNIVERSITY OF COLORADO DENVER · PI DABELEA, DANA, GLUECK, DEBORAH HELEN · 2016 to 2019
$2.6M
Human milk metabolomics and microbe-host interactions associated with pediatric obesityK01DK115632 · NIDDK · UNIVERSITY OF FLORIDA · PI LEMAS, DOMINICK JOSEPH · 2019 to 2023
$831k
Acceptance-Based Therapy Weight Loss Intervention for Adolescents: A Pilot, Randomized Controlled TrialK01HL141535 · NHLBI · UNIVERSITY OF FLORIDA · PI CARDEL, MICHELLE · 2018 to 2020
$455k
AHRQ HHS U18 HS025296AHRQ HHS U18 HS025298NCATS NIH HHS UL1 TR001427NHLBI NIH HHS K01 HL141535NIDDK NIH HHS K01 DK115632NIGMS NIH HHS R01 GM121081
6 · The paper itself

Abstract

objectiveWe sought to examine the extent to which body mass index (BMI) was available in electronic health records for Florida Medicaid recipients aged 5 to 18 years taking Second-Generation Antipsychotics (SGAP). We also sought to illustrate how clinical data can be used to identify children most at-risk for SGAP-induced weight gain, which cannot be done using process-focused measures.

methodsElectronic health record (EHR) data and Medicaid claims were linked from 2013 to 2019. We quantified sociodemographic differences between children with and without pre- and post-BMI values. We developed a linear regression model of post-BMI to examine pre-post changes in BMI among 4 groups: 1) BH/SGAP+ children had behavioral health conditions and were taking SGAP; 2) BH/SGAP- children had behavioral health conditions without taking SGAP; 3) children with asthma; and 4) healthy children.

resultsOf 363,360 EHR-Medicaid linked children, 18,726 were BH/SGAP+. Roughly 4% of linked children and 8% of BH/SGAP+ children had both pre and post values of BMI required to assess quality of SGAP monitoring. The percentage varied with gender and race-ethnicity. The R

conclusionMeeting the 2030 Centers for Medicare and Medicaid Services goal of digital monitoring of quality of care will require continuing expansion of clinical encounter data capture to provide the data needed for digital quality monitoring. Using linked EHR and claims data allows identifying children at higher risk for SGAP-induced weight gain.

Indexed as

Antipsychotic AgentsAdolescentAgedBody Mass IndexChildChild, PreschoolHumansMedicaidMedicareUnited StatesWeight GainAntipsychotic Agentsdigital quality measuresmetabolic monitoringquality measurementrace-ethnicityrurality

Identifiers

PMID35339240
PMCPMC9092621
OpenAlexW4220871254

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.