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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 DisplayedBoxley C, Fujimoto M, Ratwani RM
A text mining approach to categorize patient safety event reports by medication error type.
This study examined whether natural language processing can be used to better categorize medication related patient safety event reports. A total of 3,861 medication related patient safety event reports that were previously annotated using a consolidated medication error taxonomy were used to develop three models using the following algorithms: (1) logistic regression, (2) elastic net, and (3) XGBoost. The models were tested and performance was analyzed. The authors found the XGBoost model performed best across all medication error categories. 'Wrong Drug', 'Wrong Dosage Form or Technique or Route', and 'Improper Dose/Dose Omission' categories performed best across the three models. In addition, they identified five words most closely associated with each medication error category and which medication error categories were most likely to co-occur.
AHRQ-funded; HS026481.
Citation: Boxley C, Fujimoto M, Ratwani RM .
A text mining approach to categorize patient safety event reports by medication error type.
Sci Rep 2023 Oct 26; 13(1):18354. doi: 10.1038/s41598-023-45152-w..
Keywords: Health Information Technology (HIT), Patient Safety, Medication, Medication: Safety, Adverse Drug Events (ADE), Adverse Events
Zhang J, Kummerfield E, Hultman G
Application of causal discovery algorithms in studying the nephrotoxicity of remdesivir using longitudinal data from the EHR.
Researchers analyzed the role of remdesivir in the mechanism and optimal treatment of the development of acute kidney injury (AKI) in the setting of COVID. Applying causal discovery machine learning techniques, they built multifactorial causal models of COVID-AKI; risk factors and renal function measures were represented in a temporal sequence using longitudinal data from Electronic Health Records. Their results indicated a need for assessment of renal function on second- and third-day use of remdesivir, and also showed that remdesivir may pose less risk to AKI than existing conditions of chronic kidney disease.
AHRQ-funded; HS024532.
Citation: Zhang J, Kummerfield E, Hultman G .
Application of causal discovery algorithms in studying the nephrotoxicity of remdesivir using longitudinal data from the EHR.
AMIA Annu Symp Proc 2023 Apr 29; 2022:1227-36..
Keywords: COVID-19, Electronic Health Records (EHRs), Health Information Technology (HIT), Medication, Adverse Drug Events (ADE), Adverse Events
Taft T, Rudd EA, Thraen I
"Are we there yet?" Ten persistent hazards and inefficiencies with the use of medication administration technology from the perspective of practicing nurses.
The objectives of this study were to characterize persistent hazards and inefficiencies in inpatient medication administration, to explore cognitive attributes of medication administration tasks, and to discuss strategies to reduce technology-related hazards. Researchers interviewed nurses at two urban US health systems. Persistent safety hazards and inefficiencies related to medication administration technology were organized around the perception-action cycle (PAC) cycle. The researchers concluded that errors may persist in medication administration despite successful deployment of Bar Code Medication Administration and Electronic Medication Administration Record. Opportunities to improve would require a deeper understanding of high-level reasoning in medication administration.
AHRQ-funded; HS025136.
Citation: Taft T, Rudd EA, Thraen I .
"Are we there yet?" Ten persistent hazards and inefficiencies with the use of medication administration technology from the perspective of practicing nurses.
J Am Med Inform Assoc 2023 Apr 19; 30(5):809-18. doi: 10.1093/jamia/ocad031..
Keywords: Medication, Electronic Prescribing (E-Prescribing), Health Information Technology (HIT), Patient Safety, Adverse Drug Events (ADE), Medical Errors, Medication: Safety
Grauer A, Rosen A, Applebaum JR
Examining medication ordering errors using AHRQ network of patient safety databases.
Research on the impact of Computerized Physician Order Entry (CPOE) systems on drug order inaccuracies has shown inconsistent results, with CPOE not reliably preventing such mistakes. The study utilized the Network of Patient Safety Databases (NPSD) from the Agency for Healthcare Research and Quality (AHRQ) to explore the frequency and degree of harm associated with reported events during the ordering stage, and to classify them by error type.
The researchers conducted a retrospective analysis of reported safety incidents provided by healthcare systems associated with patient safety organizations from June 2010 to December 2020. All errors related to medication and other substance orders reported to the NPSD using the common format v1.2 during this period were assessed. The researchers grouped and categorized the prevalence of reported medication order errors by error type, harm levels, and demographic data. The study found that during the study period, 12,830 mistakes were reported. Incorrect dosage accounted for 3,812 errors (29.7%), followed by incorrect medicine 2,086 (16.3%), and incorrect duration 765 (6.0%). Out of 5,282 incidents that affected the patient and had a known severity level, 12 resulted in fatalities, 4 led to severe harm, 45 caused moderate harm, 341 led to minor harm, and 4,880 resulted in no harm. The study concluded that the most frequently reported and damaging types of medication order errors were incorrect dose and incorrect medication orders.
The researchers conducted a retrospective analysis of reported safety incidents provided by healthcare systems associated with patient safety organizations from June 2010 to December 2020. All errors related to medication and other substance orders reported to the NPSD using the common format v1.2 during this period were assessed. The researchers grouped and categorized the prevalence of reported medication order errors by error type, harm levels, and demographic data. The study found that during the study period, 12,830 mistakes were reported. Incorrect dosage accounted for 3,812 errors (29.7%), followed by incorrect medicine 2,086 (16.3%), and incorrect duration 765 (6.0%). Out of 5,282 incidents that affected the patient and had a known severity level, 12 resulted in fatalities, 4 led to severe harm, 45 caused moderate harm, 341 led to minor harm, and 4,880 resulted in no harm. The study concluded that the most frequently reported and damaging types of medication order errors were incorrect dose and incorrect medication orders.
AHRQ-funded; HS026121.
Citation: Grauer A, Rosen A, Applebaum JR .
Examining medication ordering errors using AHRQ network of patient safety databases.
J Am Med Inform Assoc 2023 Apr 19; 30(5):838-45. doi: 10.1093/jamia/ocad007..
Keywords: Medication, Adverse Drug Events (ADE), Adverse Events, Medical Errors, Patient Safety, Electronic Prescribing (E-Prescribing), Health Information Technology (HIT), Medication: Safety