National Healthcare Quality and Disparities Report
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Search All Research Studies
AHRQ Research Studies Date
Topics
- Autism (1)
- Care Management (1)
- (-) Children/Adolescents (6)
- (-) Clinical Decision Support (CDS) (6)
- Diagnostic Safety and Quality (1)
- Ear Infections (1)
- Electronic Health Records (EHRs) (2)
- Health Information Technology (HIT) (5)
- Obesity (2)
- Obesity: Weight Management (1)
- Practice Patterns (2)
- Primary Care (1)
- Quality Improvement (1)
AHRQ Research Studies
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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 6 of 6 Research Studies DisplayedDugan TM, Mukhopadhyay S, Carroll A
Machine learning techniques for prediction of early childhood obesity.
This study aimed to predict childhood obesity after age two, using only data collected prior to the second birthday by a clinical decision support system called CHICA. It demonstrated that data from a production clinical decision support system can be used to build an accurate machine learning model to predict obesity in children after age two.
AHRQ-funded; HS020640; HS018453; HS017939.
Citation: Dugan TM, Mukhopadhyay S, Carroll A .
Machine learning techniques for prediction of early childhood obesity.
Appl Clin Inform 2015 Aug 12;6(3):506-20. doi: 10.4338/aci-2015-03-ra-0036.
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Keywords: Children/Adolescents, Obesity, Health Information Technology (HIT), Clinical Decision Support (CDS), Children/Adolescents
Bauer NS, Carroll AE, Saha C
Computer decision support changes physician practice but not knowledge regarding autism spectrum disorders.
This study examined whether adding an autism module promoting adherence to clinical guidelines to an existing computer decision support system (CDSS) changed physician knowledge and self-reported clinical practice. It found that a CDSS module to improve primary care management of ASD in pediatric practice led to significant improvements in physician-reported use of validated screening tools to screen for ASDs.
AHRQ-funded; HS018453.
Citation: Bauer NS, Carroll AE, Saha C .
Computer decision support changes physician practice but not knowledge regarding autism spectrum disorders.
Appl Clin Inform 2015;6(3):454-65. doi: 10.4338/aci-2014-09-ra-0084.
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Keywords: Health Information Technology (HIT), Practice Patterns, Clinical Decision Support (CDS), Children/Adolescents, Autism
Fiks AG, Zhang P, Localio AR
Adoption of electronic medical record-based decision support for otitis media in children.
The authors characterized adoption of an otitis media clinical decision support (CDS) system, the impact of performance feedback on adoption, and the effects of adoption on guideline adherence. The performance feedback increased CDS adoption, but additional strategies are needed to integrate CDS into primary care workflows.
AHRQ-funded; HS017042
Citation: Fiks AG, Zhang P, Localio AR .
Adoption of electronic medical record-based decision support for otitis media in children.
Health Serv Res. 2015 Apr;50(2):489-513. doi: 10.1111/1475-6773.12240..
Keywords: Children/Adolescents, Clinical Decision Support (CDS), Ear Infections, Electronic Health Records (EHRs), Health Information Technology (HIT)
Hendrix KS, Downs SM, Carroll AE
Pediatricians' responses to printed clinical reminders: does highlighting prompts improve responsiveness?
The authors tested whether selectively highlighting clinical decision support prompts in yellow would improve physicians' responsiveness. They found that highlighting reminder prompts did not increase physicians' responsiveness. They suggested possible explanations and offer alternative strategies to increasing physician responsiveness to prompts.
AHRQ-funded; HS020640; HS018453; HS017939.
Citation: Hendrix KS, Downs SM, Carroll AE .
Pediatricians' responses to printed clinical reminders: does highlighting prompts improve responsiveness?
Acad Pediatr 2015 Mar-Apr;15(2):158-64. doi: 10.1016/j.acap.2014.10.009.
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Keywords: Clinical Decision Support (CDS), Children/Adolescents, Primary Care, Practice Patterns, Quality Improvement
Shaikh U, Berrong J, Nettiksimmons J
Impact of electronic health record clinical decision support on the management of pediatric obesity.
The investigators assessed the impact of electronic health record-based clinical decision support in improving the diagnosis and management of pediatric obesity. They found a statistically significant increase in the diagnosis of overweight/obesity, scheduling of follow-up appointments, frequency of ordering recommended laboratory investigations, and assessment and counseling for nutrition and physical activity.
AHRQ-funded; HS018567.
Citation: Shaikh U, Berrong J, Nettiksimmons J .
Impact of electronic health record clinical decision support on the management of pediatric obesity.
Am J Med Qual 2015 Jan-Feb;30(1):72-80. doi: 10.1177/1062860613517926.
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Keywords: Care Management, Children/Adolescents, Clinical Decision Support (CDS), Diagnostic Safety and Quality, Electronic Health Records (EHRs), Health Information Technology (HIT), Obesity, Obesity: Weight Management
Gilbert AL, Downs SM
Medical legal partnership and health informatics impacting child health: interprofessional innovations.
This article describes the interprofessional nature of the Medical Legal Partnership ( MLP) model itself, illustrates the work that was done to craft this innovative health informatics approach to implementing MLP, and demonstrates how pediatricians social workers and attorneys may work together to improve child health outcomes.
AHRQ-funded; HS020640.
Citation: Gilbert AL, Downs SM .
Medical legal partnership and health informatics impacting child health: interprofessional innovations.
J Interprof Care 2015;29(6):564-9. doi: 10.3109/13561820.2015.1029066..
Keywords: Health Information Technology (HIT), Children/Adolescents, Clinical Decision Support (CDS)