National Healthcare Quality and Disparities Report
Latest available findings on quality of and access to health care
Data
- Data Infographics
- Data Visualizations
- Data Tools
- Data Innovations
- All-Payer Claims Database
- Healthcare Cost and Utilization Project (HCUP)
- Medical Expenditure Panel Survey (MEPS)
- AHRQ Quality Indicator Tools for Data Analytics
- State Snapshots
- United States Health Information Knowledgebase (USHIK)
- Data Sources Available from AHRQ
Search All Research Studies
AHRQ Research Studies Date
AHRQ Research Studies
Sign up: AHRQ Research Studies Email updates
Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 3 of 3 Research Studies DisplayedLambert BL, Galanter W, Liu KL
Automated detection of wrong-drug prescribing errors.
Investigators assessed the specificity of an algorithm designed to detect look-alike/sound-alike (LASA) medication prescribing errors in electronic health record (EHR) data. They found that automated detection of LASA medication errors is feasible and can reveal errors not currently detected by other means. Additionally, real-time error detection is not possible with the current system. They suggested that further development should replicate their analysis in other health systems and on a larger set of medications and should decrease clinician time spent reviewing false-positive triggers by increasing specificity.
AHRQ-funded; HS021093.
Citation: Lambert BL, Galanter W, Liu KL .
Automated detection of wrong-drug prescribing errors.
BMJ Qual Saf 2019 Nov;28(11):908-15. doi: 10.1136/bmjqs-2019-009420..
Keywords: Adverse Drug Events (ADE), Adverse Events, Clinical Decision Support (CDS), Electronic Health Records (EHRs), Health Information Technology (HIT), Medical Errors, Medication, Patient Safety
Adelman JS, Applebaum JR, Schechter CB
Effect of restriction of the number of concurrently open records in an electronic health record on wrong-patient order errors: a randomized clinical trial.
This study assessed whether the belief that having only 1 electronic health record (EHR) open at a time as opposed to 4 will reduce the number of wrong-patient orders by clinicians. A randomized clinical trial was conducted with 3356 clinicians in a large New York Health system from October 2015 to April 2017. Outcomes from emergency department, inpatient, and outpatient settings showed that there seemed to be no difference in the number of wrong-patient order errors. However, most clinicians in the unrestricted group placed orders with a single-record open anyway which limited the power of the study.
AHRQ-funded; HS023704.
Citation: Adelman JS, Applebaum JR, Schechter CB .
Effect of restriction of the number of concurrently open records in an electronic health record on wrong-patient order errors: a randomized clinical trial.
JAMA 2019 May 14;321(18):1780-87. doi: 10.1001/jama.2019.3698..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Healthcare Delivery, Medical Errors, Patient Safety
Pohl JM, Tanner C, Hamilton A
Medication safety after implementation of a commercial electronic health record system in five safety-net practices: a mixed methods approach.
This study, conducted in five safety-net practices, examined the impact of implementing a commercial electronic health records system on medication safety. The authors found 130 "true" drug-drug interaction (DDI) pairs, representing 149,087 visits and 62 providers, with the largest DDI categories being related to antihypertensive medications, which are often prescribed together. They found no significant differences between physicians and nurse practitioners on the rate of DDI pairs.
AHRQ-funded; HS017191.
Citation: Pohl JM, Tanner C, Hamilton A .
Medication safety after implementation of a commercial electronic health record system in five safety-net practices: a mixed methods approach.
J Am Assoc Nurse Pract 2014 Aug;26(8):438-44. doi: 10.1002/2327-6924.12089.
.
.
Keywords: Medication: Safety, Medication, Electronic Health Records (EHRs), Health Information Technology (HIT), Adverse Drug Events (ADE), Adverse Events, Medical Errors, Patient Safety