National Healthcare Quality and Disparities Report
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AHRQ Research Studies Date
Topics
- Adverse Drug Events (ADE) (2)
- Adverse Events (2)
- Clinical Decision Support (CDS) (1)
- Communication (1)
- Electronic Health Records (EHRs) (2)
- (-) Electronic Prescribing (E-Prescribing) (6)
- Health Information Technology (HIT) (6)
- Medical Errors (3)
- Medication (6)
- Medication: Safety (4)
- Opioids (1)
- Patient Safety (5)
- Practice Patterns (1)
- Provider (2)
- Provider: Clinician (2)
- Provider: Physician (1)
- Risk (2)
- Shared Decision Making (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 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
Everson J, Cheng AK, Patrick SW
Association of electronic prescribing of controlled substances with opioid prescribing rates.
The purpose of this study was to assess the association between use of electronic prescribing of controlled substances (EPCS) and trends in opioid prescribing. Results suggested that an increased use of EPCS was not associated with decreased opioid prescribing or a decrease in the amount prescribed and may have been associated with a small increase in opioid prescribing. Recommendations included levers to ensure that EPCS is integrated with outside data and that information is actively used to inform prescribing decisions.
AHRQ-funded; HS026395.
Citation: Everson J, Cheng AK, Patrick SW .
Association of electronic prescribing of controlled substances with opioid prescribing rates.
JAMA Netw Open 2020 Dec;3(12):e2027951. doi: 10.1001/jamanetworkopen.2020.27951..
Keywords: Electronic Prescribing (E-Prescribing), Health Information Technology (HIT), Opioids, Medication, Practice Patterns, Provider: Physician, Provider: Clinician, Provider
Holmgren AJ, Co Z, Newmark L
Assessing the safety of electronic health records: a national longitudinal study of medication-related decision support.
The authors tested how well EHRs prevented medication errors with the potential for patient harm. Data from a national, longitudinal sample of 1527 hospitals in the US from 2009-16 who took a safety performance assessment test using simulated medication orders was used. The authors found that hospital medication order safety performance improved over time. They conclude that intentional quality improvement efforts appear to be a critical part of high safety performance and may indicate the importance of a culture of safety.
AHRQ-funded; HS023696.
Citation: Holmgren AJ, Co Z, Newmark L .
Assessing the safety of electronic health records: a national longitudinal study of medication-related decision support.
BMJ Qual Saf 2020 Jan;29(1):52-59. doi: 10.1136/bmjqs-2019-009609..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Patient Safety, Medication, Electronic Prescribing (E-Prescribing), Medication: Safety, Clinical Decision Support (CDS), Shared Decision Making