National Healthcare Quality and Disparities Report
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Search All Research Studies
AHRQ Research Studies Date
Topics
- Adverse Drug Events (ADE) (2)
- Adverse Events (2)
- Clinical Decision Support (CDS) (1)
- Communication (1)
- Diabetes (1)
- Electronic Health Records (EHRs) (1)
- (-) Electronic Prescribing (E-Prescribing) (6)
- Health Information Technology (HIT) (5)
- Medical Errors (3)
- (-) Medication (6)
- Medication: Safety (3)
- Patient Adherence/Compliance (1)
- Patient Safety (5)
- Provider (1)
- Provider: Clinician (1)
- Risk (2)
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 DisplayedIqbal AR, Parau CA, Kazi S
Identifying electronic medication administration record (eMAR) usability issues from patient safety event reports.
This study investigated the contribution of usability challenges associated with the electronic medication administration record (eMAR) to medication errors using patient safety event reports (PSEs). The authors analyzed free-text descriptions of 849 medication-related PSEs selected from 2.3 million reports. Specific health IT components, usability challenge categories, and nuanced usability themes that contributed to each PSE were identified by coders. Usability challenges included workflow support, alerting, and display/visual clutter.
AHRQ-funded; HS025136.
Citation: Iqbal AR, Parau CA, Kazi S .
Identifying electronic medication administration record (eMAR) usability issues from patient safety event reports.
Jt Comm J Qual Patient Saf 2021 Dec;47(12):793-801. doi: 10.1016/j.jcjq.2021.09.004..
Keywords: Electronic Prescribing (E-Prescribing), Health Information Technology (HIT), Medication, Medical Errors, Patient Safety
King CR, Abraham J, Fritz BA
Predicting self-intercepted medication ordering errors using machine learning.
Current approaches to understanding medication ordering errors rely on relatively small manually captured error samples. These approaches are resource-intensive, do not scale for computerized provider order entry (CPOE) systems, and are likely to miss important risk factors associated with medication ordering errors. Previously, the investigators described a dataset of CPOE-based medication voiding accompanied by univariable and multivariable regression analyses. In this paper, they updated the analysis using machine learning (ML) models to predict erroneous medication orders and identify its contributing factors.
AHRQ-funded; HS025443.
Citation: King CR, Abraham J, Fritz BA .
Predicting self-intercepted medication ordering errors using machine learning.
PLoS One 2021 Jul 14;16(7):e0254358. doi: 10.1371/journal.pone.0254358..
Keywords: Medication, Medical Errors, Adverse Drug Events (ADE), Adverse Events, Medication: Safety, Patient Safety, Electronic Prescribing (E-Prescribing), Health Information Technology (HIT)
Kandaswamy S, Pruitt Z, Kazi S
Clinician perceptions on the use of free-text communication orders.
The aim of this study was to investigate (1) why ordering clinicians use free-text orders to communicate medication information; (2) what risks physicians and nurses perceive when free-text orders are used for communicating medication information; and (3) how electronic health records (EHRs) could be improved to encourage the safe communication of medication information. The investigators concluded that clinicians' use of free-text orders as a workaround to insufficient structured order entry can create unintended patient safety risks.
AHRQ-funded; HS025136; HS024755.
Citation: Kandaswamy S, Pruitt Z, Kazi S .
Clinician perceptions on the use of free-text communication orders.
Appl Clin Inform 2021 May;12(3):484-94. doi: 10.1055/s-0041-1731002..
Keywords: Electronic Prescribing (E-Prescribing), Health Information Technology (HIT), Electronic Health Records (EHRs), Medication: Safety, Medication, Patient Safety, Communication, Provider: Clinician, Provider, Risk
Abraham J, Galanter WL, Touchette D
Risk factors associated with medication ordering errors.
This study’s goal was to collect data on “voided” orders in computerized order entry systems for medication to 1) identify the nature and characteristics of medication ordering errors; 2) investigate the risk factors associated with these errors and; 3) explore potential strategies to mitigate these risk factors. Data was collected using clinician interviews and surveys within 24 hours of the voided order and using chart reviews. During the 16-month study period 1074 medication orders were voided, with 842 being true medication errors. A total of 22% reached the patient, with at least a single administration, but without causing patient harm. Interviews were conducted on 355 voided orders (33%). Errors were associated with multiple factors not just a single risk factor. The causal contributors included a combination of technological-, cognitive-, environment-, social-, and organization-level factors.
AHRQ-funded; HS025443.
Citation: Abraham J, Galanter WL, Touchette D .
Risk factors associated with medication ordering errors.
J Am Med Inform Assoc 2021 Jan 15;28(1):86-94. doi: 10.1093/jamia/ocaa264..
Keywords: Medication: Safety, Electronic Prescribing (E-Prescribing), Medication: Safety, Medication, Medical Errors, Adverse Drug Events (ADE), Adverse Events, Risk, Health Information Technology (HIT), Patient Safety
Powers C, Gabriel MH, Encinosa W
AHRQ Author: Encinosa W
Meaningful use stage 2 e-prescribing threshold and adverse drug events in the Medicare Part D population with diabetes.
The authors investigated whether physicians who meet the meaningful use stage 2 threshold for e-prescribing (50 percent of prescriptions e-prescribed) have lower rates of ADEs among their diabetic patients. They found that physician e-prescribing to Medicare beneficiaries was associated with reduced risk of ADEs among their diabetes patients, as were several prescriber and panel characteristics.
AHRQ-authored
Citation: Powers C, Gabriel MH, Encinosa W .
Meaningful use stage 2 e-prescribing threshold and adverse drug events in the Medicare Part D population with diabetes.
J Am Med Inform Assoc 2015 Sep;22(5):1094-8. doi: 10.1093/jamia/ocv036..
Keywords: Electronic Prescribing (E-Prescribing), Diabetes, Medication, Patient Safety
Pevnick JM, Li N, Asch SM
Effect of electronic prescribing with formulary decision support on medication tier, copayments, and adherence.
The researchers evaluated whether formulary decision support (FDS) could reduce patient medication costs, and thereby improve adherence. In the studied population, interruptive FDS shifted prescribing toward preferred tier medications, but these medications were only minimally less expensive for patients. Thus, FDS did not significantly increase adherence.
AHRQ-funded; HS016391.
Citation: Pevnick JM, Li N, Asch SM .
Effect of electronic prescribing with formulary decision support on medication tier, copayments, and adherence.
BMC Med Inform Decis Mak 2014;14:79. doi: 10.1186/1472-6947-14-79..
Keywords: Electronic Prescribing (E-Prescribing), Medication, Patient Adherence/Compliance, Clinical Decision Support (CDS), Health Information Technology (HIT)