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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 4 of 4 Research Studies DisplayedWang SV, Maro JC, Baro E
Data mining for adverse drug events with a propensity score-matched tree-based scan statistic.
In this study, the investigators propose a method that combines tree-based scan statistics with propensity score-matched analysis of new initiator cohorts, a robust design for investigations of drug safety. They subsequently conducted plasmode simulations to evaluate performance. The authors suggest that TreeScan with propensity score matching shows promise as a method for screening and prioritization of potential adverse events.
AHRQ-funded; HS022193.
Citation: Wang SV, Maro JC, Baro E .
Data mining for adverse drug events with a propensity score-matched tree-based scan statistic.
Epidemiology 2018 Nov;29(6):895-903. doi: 10.1097/ede.0000000000000907..
Keywords: Adverse Drug Events (ADE), Adverse Events, Patient Safety, Medication, Medication: Safety, Data, Research Methodologies
Fong A, Adams KT, Gaunt MJ
Identifying health information technology related safety event reports from patient safety event report databases.
The objective of this paper was to identify health information technology (HIT) related events from patient safety event (PSE) report free-text descriptions. A difference-based scoring approach was used to prioritize and select model features. A feature-constraint model was developed and evaluated to support the analysis of PSE reports. The feature-constraint model provides a method to identify HIT-related patient safety hazards using a method that is applicable across healthcare systems with variability in their PSE report structures.
AHRQ-funded; HS023701.
Citation: Fong A, Adams KT, Gaunt MJ .
Identifying health information technology related safety event reports from patient safety event report databases.
J Biomed Inform 2018 Oct;86:135-42. doi: 10.1016/j.jbi.2018.09.007..
Keywords: Health Information Technology (HIT), Patient Safety, Adverse Events, Data
Goss FR, Lai KH, Topaz M
A value set for documenting adverse reactions in electronic health records.
In this study, the investigators developed a value set for encoding adverse reactions using a large dataset from one health system, enriched by reactions from 2 large external resources. This integrated value set included clinically important severe and hypersensitivity reactions. The work contributed a value set, harmonized with existing data, to improve the consistency and accuracy of reaction documentation in electronic health records, providing the necessary building blocks for more intelligent clinical decision support for allergies and adverse reactions.
AHRQ-funded; HS022728.
Citation: Goss FR, Lai KH, Topaz M .
A value set for documenting adverse reactions in electronic health records.
J Am Med Inform Assoc 2018 Jun;25(6):661-69. doi: 10.1093/jamia/ocx139..
Keywords: Adverse Drug Events (ADE), Adverse Events, Electronic Health Records (EHRs), Medication, Data, Health Information Technology (HIT), Patient Safety
Eisler L, Huang G, Lee KM
Identification of perioperative pulmonary aspiration in children using quality assurance and hospital administrative billing data.
This study aims to identify the incidence of and risk factors for perioperative aspiration in children using quality assurance data supplemented by administrative billing records, and to examine the utility of billing data as a supplementary data source. The investigators found that International Classification of Diseases, Ninth Revision codes for aspiration used as a secondary data source were nonspecific for perioperative aspiration, but when combined with record review yielded a 30% increase in identified cases of aspiration over quality assurance data alone.
AHRQ-funded; HS022941.
Citation: Eisler L, Huang G, Lee KM .
Identification of perioperative pulmonary aspiration in children using quality assurance and hospital administrative billing data.
Paediatr Anaesth 2018 Mar;28(3):218-25. doi: 10.1111/pan.13319..
Keywords: Adverse Events, Children/Adolescents, Data, Pneumonia, Respiratory Conditions