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 (3)
- Burnout (1)
- (-) Clinical Decision Support (CDS) (8)
- Diagnostic Safety and Quality (1)
- Electronic Health Records (EHRs) (4)
- Electronic Prescribing (E-Prescribing) (1)
- Healthcare Delivery (1)
- (-) Health Information Technology (HIT) (8)
- Hospitals (2)
- Medical Errors (2)
- Medication (4)
- Medication: Safety (2)
- (-) Patient Safety (8)
- Quality Indicators (QIs) (1)
- Quality Measures (1)
- Quality of Care (1)
- Shared Decision Making (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 8 of 8 Research Studies DisplayedCo Z, Holmgren AJ, Classen DC
The tradeoffs between safety and alert fatigue: data from a national evaluation of hospital medication-related clinical decision support.
This study evaluated the overall performance of hospitals that used the Computerized Physician Order Entry Evaluation Tool in 2017 and 2018 and compared performances for fatal orders and nuisance orders each year. The authors evaluated 1599 hospitals that took the test by using their overall percentage scores along with the percentage of fatal orders appropriately alerted on and the percentage of nuisance orders incorrectly alerted on. Overall hospital scores improved from 58.1% in 2017 to 66.2% in 2018. Fatal order performance improved slightly from 78.8% to 83.0%, but there no very little change in nuisance order performance (89.0% to 89.7%). Conclusions were that perhaps hospitals are not targeting the deadliest orders first and some hospitals may be achieving higher scores by over-alerting. This has the potential to cause clinician burnout and even worsen patient safety.
AHRQ-funded; HS023696.
Citation: Co Z, Holmgren AJ, Classen DC .
The tradeoffs between safety and alert fatigue: data from a national evaluation of hospital medication-related clinical decision support.
J Am Med Inform Assoc 2020 Aug;27(8):1252-58. doi: 10.1093/jamia/ocaa098..
Keywords: Medication: Safety, Medication, Patient Safety, Clinical Decision Support (CDS), Shared Decision Making, Burnout, Hospitals, Health Information Technology (HIT), Quality of Care
Classen DC, Holmgren AJ, Co Z
National trends in the safety performance of electronic health record systems from 2009 to 2018.
This study examined trends in the safety performance of electronic health records (EHRs) in hospitals from 2009 to 2018. The Leapfrog Health IT Safety Measure test was administered by the Leapfrog Group from July 2018 to December 1, 2019. Overall mean performance scores increased from 53.9% in 2009 to 65.6% in 2018. Mean hospital scores for categories representing basic clinical decision support increased from 69.8% in 2009 to 85.6% in 2018. Advanced decision clinical support also increased from 29.5% in 2009 to 46.1%. These results showed great improvement, but there is still substantial safety risk in current hospital EHR systems.
AHRQ-funded; HS023696.
Citation: Classen DC, Holmgren AJ, Co Z .
National trends in the safety performance of electronic health record systems from 2009 to 2018.
JAMA Netw Open 2020 May;3(5):e205547. doi: 10.1001/jamanetworkopen.2020.5547..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Hospitals, Patient Safety, Quality Measures, Clinical Decision Support (CDS), Quality Indicators (QIs)
Meyer AND, Giardina TD, Spitzmueller C
Patient perspectives on the usefulness of an artificial intelligence-assisted symptom checker: cross-sectional survey study.
This study examined patients’ experiences using an artificial intelligence (AI)-assisted online symptom checker and their doctors’ reactions to that use. From March 2 through March 15, 2018 an online survey was conducted of US users of the Isabel Symptom Checker within 6 months of their use. The majority of users were women, white, and had a mean age of 48. Overall, patients had a positive experience with the symptom checker and felt they would use it again (91.4%). About 48% discussed the findings with their physician and felt about 40% of their physicians were interested. Patients who had previously experienced diagnostic errors were more likely to use the symptom checker to determine if they should seek care.
AHRQ-funded; HS025474; HS027363.
Citation: Meyer AND, Giardina TD, Spitzmueller C .
Patient perspectives on the usefulness of an artificial intelligence-assisted symptom checker: cross-sectional survey study.
J Med Internet Res 2020 Jan 30;22(1):e14679. doi: 10.2196/14679..
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT), Diagnostic Safety and Quality, Patient Safety
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
Lambert 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
Nguyen BP, Reese T, Decker S
Implementation of clinical decision support services to detect potential drug-drug interaction using clinical quality language.
The authors report on the implementation and evaluation of CDS Services which represent potential drug-drug interactions knowledge with Clinical Quality Language (CQL). Their suggested solution is based on emerging standards including CDS Hooks, FHIR, and CQL. They selected two use cases, implemented them with CQL rules, and tested them.
AHRQ-funded; HS023826; HS025984.
Citation: Nguyen BP, Reese T, Decker S .
Implementation of clinical decision support services to detect potential drug-drug interaction using clinical quality language.
Stud Health Technol Inform 2019 Aug 21;264:724-28. doi: 10.3233/shti190318..
Keywords: Clinical Decision Support (CDS), Adverse Drug Events (ADE), Medication, Adverse Events, Patient Safety, Health Information Technology (HIT)
Liang C, Miao Q, Kang H
Leveraging patient safety research: efforts made fifteen years since To Err Is Human.
The present study sought to explore the associations between federal incentives of patient safety research and the outcomes from 1995 to 2014, in which two historical events - the release of To Err Is Human and the American Recovery and Reinvestment Act - were considered in the analysis. They concluded that their findings suggested a positive outcome in patient safety research.
AHRQ-funded; HS022895.
Citation: Liang C, Miao Q, Kang H .
Leveraging patient safety research: efforts made fifteen years since To Err Is Human.
Stud Health Technol Inform 2019 Aug 21;264:983-87. doi: 10.3233/shti190371..
Keywords: Patient Safety, Medical Errors, Adverse Events, Clinical Decision Support (CDS), Health Information Technology (HIT)
Powers EM, Shiffman RN, Melnick ER
Efficacy and unintended consequences of hard-stop alerts in electronic health record systems: a systematic review.
Clinical decision support (CDS) hard-stop alerts-those in which the user is either prevented from taking an action altogether or allowed to proceed only with the external override of a third party-are increasingly common but can be problematic. To understand their appropriate application, the investigators explored 3 key questions: (1) To what extent are hard-stop alerts effective in improving patient health and healthcare delivery outcomes? (2) What are the adverse events and unintended consequences of hard-stop alerts? (3) How do hard-stop alerts compare to soft-stop alerts?
AHRQ-funded; HS024332.
Citation: Powers EM, Shiffman RN, Melnick ER .
Efficacy and unintended consequences of hard-stop alerts in electronic health record systems: a systematic review.
J Am Med Inform Assoc 2018 Nov;25(11):1556-66. doi: 10.1093/jamia/ocy112..
Keywords: Clinical Decision Support (CDS), Electronic Health Records (EHRs), Health Information Technology (HIT), Healthcare Delivery, Patient Safety