National Healthcare Quality and Disparities Report
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- Adverse Events (1)
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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 10 of 10 Research Studies DisplayedGriffey RT, Schneider RM, Todorov AA
The emergency department trigger tool: validation and testing to optimize yield.
Researchers validated the emergency department trigger tool (EDTT) in an independent sample and compared record selection approaches to optimize yield for quality improvement. In this single-site study of the EDTT, they observed high levels of validity in trigger selection, yield, and representativeness of adverse events, with yields that are superior to estimates for traditional approaches to adverse event detection. Record selection using weighted triggers outperformed a trigger count threshold approach and far outperformed random sampling from records with at least one trigger. They concluded that the EDTT is a promising efficient and high-yield approach for detecting all-cause harm to guide quality improvement efforts in the emergency department.
AHRQ-funded; HS025052.
Citation: Griffey RT, Schneider RM, Todorov AA .
The emergency department trigger tool: validation and testing to optimize yield.
Acad Emerg Med 2020 Dec;27(12):1279-90. doi: 10.1111/acem.14101..
Keywords: Emergency Department, Electronic Health Records (EHRs), Health Information Technology (HIT), Medical Errors, Adverse Events, Patient Safety, Quality Improvement, Quality of Care
Scott HF, Brilli RJ, Paul R
Evaluating pediatric sepsis definitions designed for electronic health record extraction and multicenter quality improvement.
The purpose of this study was to describe the Children's Hospital Association's Improving Pediatric Sepsis Outcomes sepsis definitions and to evaluate the definition using a published framework. The investigators concluded that the Improving Pediatric Sepsis Outcomes Sepsis definitions demonstrated feasibility for large-scale data abstraction. When operationalized, these definitions enabled multicenter identification and data aggregation, indicating practical utility for quality improvement.
AHRQ-funded; HS025696.
Citation: Scott HF, Brilli RJ, Paul R .
Evaluating pediatric sepsis definitions designed for electronic health record extraction and multicenter quality improvement.
Crit Care Med 2020 Oct;48(10):e916-e26. doi: 10.1097/ccm.0000000000004505..
Keywords: Children/Adolescents, Electronic Health Records (EHRs), Health Information Technology (HIT), Sepsis, Quality Improvement, Quality of Care
Bucher BT, Shi J, Ferraro JP
Portable automated surveillance of surgical site infections using natural language processing: development and validation.
The authors presented the development and validation of a portable natural language processing (NLP) approach for automated surveillance of surgical site infections (SSIs). Patient clinical text notes from EHRs following surgical procedures from two independent healthcare systems were abstracted. The authors found that automated surveillance of SSIs can be achieved using NLP of clinical notes with high sensitivity and specificity.
AHRQ-funded; HS025776.
Citation: Bucher BT, Shi J, Ferraro JP .
Portable automated surveillance of surgical site infections using natural language processing: development and validation.
Ann Surg 2020 Oct;272(4):629-36. doi: 10.1097/sla.0000000000004133..
Keywords: Surgery, Healthcare-Associated Infections (HAIs), Electronic Health Records (EHRs), Health Information Technology (HIT), Quality Improvement, Quality of Care
Bronsert M, Singh AB, Henderson WG
Identification of postoperative complications using electronic health record data and machine learning.
Investigators developed a machine learning algorithm for identifying patients with one or more complications using data from the electronic health record (EHR). They concluded that using machine learning on EHR postoperative data linked to American College of Surgeons National Surgical Quality Improvement Program outcomes data, a model with 163 predictors from the EHR identified complications well at their institution.
AHRQ-funded; HS026019.
Citation: Bronsert M, Singh AB, Henderson WG .
Identification of postoperative complications using electronic health record data and machine learning.
Am J Surg 2020 Jul;220(1):114-19. doi: 10.1016/j.amjsurg.2019.10.009..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Surgery, Quality Improvement, Quality of Care, Diagnostic Safety and Quality
Homco J, Carabin H, Nagykaldi Z
Validity of medical record abstraction and electronic health record-generated reports to assess performance on cardiovascular quality measures in primary care.
The purpose of this study was to compare observed performance scores measured using 2 imperfect reference standard data sources with misclassification-adjusted performance scores obtained using bayesian latent class analysis. Using aspirin, blood pressure, and smoking performance data from the Healthy Hearts for Oklahoma Project, researchers found that extracting information for the same individuals using different data sources generated different performance score estimates. Recommendations included further research to identify the sources of these differences.
AHRQ-funded; HS023919.
Citation: Homco J, Carabin H, Nagykaldi Z .
Validity of medical record abstraction and electronic health record-generated reports to assess performance on cardiovascular quality measures in primary care.
JAMA Netw Open 2020 Jul;3(7):e209411. doi: 10.1001/jamanetworkopen.2020.9411..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Cardiovascular Conditions, Quality Measures, Quality of Care, Primary Care, Provider Performance, Evidence-Based Practice
Rudin RS, Friedberg MW, Shekelle P
Getting value from electronic health records: research needed to improve practice.
Electronic health records (EHRs) are now widely adopted in the United States, but health systems have barely begun using them to deliver high-value care. This article describes 4 potential benefits of EHR-based research: improving clinical decisions, supporting triage decisions, enabling collaboration among the care team (including patients), and increasing productivity via automation of tasks.
AHRQ-funded; HS024067.
Citation: Rudin RS, Friedberg MW, Shekelle P .
Getting value from electronic health records: research needed to improve practice.
Ann Intern Med 2020 Jun 2;172(11 Suppl):S130-s36. doi: 10.7326/m19-0878..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Quality Improvement, Quality of Care, Healthcare Delivery
Tignanelli CJ, Silverman GM, Lindemann EA
Natural language processing of prehospital emergency medical services trauma records allows for automated characterization of treatment appropriateness.
Incomplete prehospital trauma care is a significant contributor to preventable deaths. Current databases lack timelines easily constructible of clinical events. Temporal associations and procedural indications are critical to characterize treatment appropriateness. Natural language processing (NLP) methods present a novel approach to bridge this gap. In this study, the investigators sought to evaluate the efficacy of a novel and automated NLP pipeline to determine treatment appropriateness from a sample of prehospital EMS motor vehicle crash records.
AHRQ-funded; HS026379.
Citation: Tignanelli CJ, Silverman GM, Lindemann EA .
Natural language processing of prehospital emergency medical services trauma records allows for automated characterization of treatment appropriateness.
J Trauma Acute Care Surg 2020 May;88(5):607-14. doi: 10.1097/ta.0000000000002598.
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Keywords: Trauma, Injuries and Wounds, Electronic Health Records (EHRs), Health Information Technology (HIT), Quality Improvement, Quality of Care
Businger AC, Fuller TE, Schnipper JL
Lessons learned implementing a complex and innovative patient safety learning laboratory project in a large academic medical center.
This paper describes the challenges, recommendations and lessons learned while developing and implementing a Patient Safety Learning Laboratory (PSLL) project, which is comprised of a suite of HIT tools integrated with a newly implemented Electronic Health Record (EHR) vendor system in the acute care setting of a large academic medical center. The PSLL Administrative Core engaged stakeholders and study personnel throughout all phases of the project. Challenges to implementation included stakeholder engagement, project scope and complexity, technology and governance, and team structure. Some changes were implemented during the trial and others were labeled as lessons learned for future iterative interventions. A willingness to think outside of current workflows and processes to change health system culture around adverse event prevention was one of the keys to success.
AHRQ-funded; HS023535.
Citation: Businger AC, Fuller TE, Schnipper JL .
Lessons learned implementing a complex and innovative patient safety learning laboratory project in a large academic medical center.
J Am Med Inform Assoc 2020 Feb;27(2):301-07. doi: 10.1093/jamia/ocz193.
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Keywords: Patient Safety, Implementation, Health Information Technology (HIT), Quality Improvement, Quality of Care, Patient-Centered Healthcare, Electronic Health Records (EHRs), Evidence-Based Practice
Gandrup J, Li J, Izadi Z
Three quality improvement initiatives and performance of rheumatoid arthritis disease activity measures in electronic health records: results from an interrupted time series study.
This study evaluated the effect of 3 HIT initiatives on the performance of rheumatoid arthritis (RA) disease activity measures and outcomes in an academic rheumatology clinic. The three initiatives implemented to facilitate performance of the Clinical Disease Activity Index (CDAI) were: 1) an EHR flowsheet to input scores, 2) peer performance reports, and 3) an EHR Smartform including a CDAI calculator. Data from 995 patients with 8,040 encounters between 2012 and 2017 was included. Electronic capture of CDAI scores increased from 0% to 64%. Peer performance reporting and the SmartForm kept performance stable. Physician satisfaction increased after SmartForm implementation.
AHRQ-funded; HS025638.
Citation: Gandrup J, Li J, Izadi Z .
Three quality improvement initiatives and performance of rheumatoid arthritis disease activity measures in electronic health records: results from an interrupted time series study.
Arthritis Care Res 2020 Feb;72(2):283-91. doi: 10.1002/acr.23848..
Keywords: Arthritis, Electronic Health Records (EHRs), Health Information Technology (HIT), Quality Improvement, Quality of Care
Liss DT, Peprah YA, Brown T
Using electronic health records to measure quality improvement efforts: findings from a large practice facilitation initiative.
This study described primary care practices' ability to obtain measures with reporting periods aligning with a large quality improvement initiative. Facilitators reported barriers to data collection such as practices lacking optional EHR features, and EHRs' inability to produce reporting periods across two calendar years. The authors conclude that EHR vendors' compliance with federal reporting requirements is not necessarily sufficient to support real-world quality improvement work. They recommended improvements in the flexibility and usability of EHRs' quality measurement functions, particularly for smaller practices.
AHRQ-funded; HS023921.
Citation: Liss DT, Peprah YA, Brown T .
Using electronic health records to measure quality improvement efforts: findings from a large practice facilitation initiative.
Jt Comm J Qual Patient Saf 2020 Jan;46(1):11-17. doi: 10.1016/j.jcjq.2019.09.006..
Keywords: Patient-Centered Outcomes Research, Evidence-Based Practice, Electronic Health Records (EHRs), Health Information Technology (HIT), Quality Improvement, Quality of Care