National Healthcare Quality and Disparities Report
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Topics
- Adverse Events (4)
- Arthritis (2)
- Cardiovascular Conditions (1)
- Children/Adolescents (1)
- Data (1)
- Dementia (1)
- Diagnostic Safety and Quality (4)
- (-) Electronic Health Records (EHRs) (30)
- Emergency Department (2)
- Evidence-Based Practice (4)
- Healthcare-Associated Infections (HAIs) (3)
- Healthcare Delivery (1)
- Health Information Technology (HIT) (29)
- Health Systems (1)
- Heart Disease and Health (1)
- Hospitalization (1)
- Hospitals (3)
- Imaging (1)
- Implementation (1)
- Injuries and Wounds (2)
- Learning Health Systems (1)
- Medical Errors (1)
- Mortality (1)
- Neurological Disorders (2)
- Outcomes (1)
- Patient-Centered Healthcare (1)
- Patient-Centered Outcomes Research (2)
- Patient Safety (6)
- Payment (1)
- Prevention (1)
- Primary Care (4)
- Primary Care: Models of Care (1)
- Provider Performance (2)
- (-) Quality Improvement (30)
- Quality Indicators (QIs) (3)
- Quality Measures (3)
- (-) Quality of Care (30)
- Registries (1)
- Sepsis (2)
- Surgery (5)
- Tools & Toolkits (2)
- Trauma (1)
- Urinary Tract Infection (UTI) (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 25 of 30 Research Studies DisplayedBradford A, Shofer M, Singh H
AHRQ Author: Shofer M, Singh H
Measure Dx: implementing pathways to discover and learn from diagnostic errors.
This paper discusses Measure Dx, a new AHRQ resource that translates knowledge from diagnostic measurement research into actionable recommendations. This resource guides healthcare organizations to detect, analyze, and learn from diagnostic safety events as part of a continuous learning and feedback cycle. The goal of Measure Dx is to advance new frontiers in reducing preventable diagnostic harm to patients.
AHRQ-authored; AHRQ-funded; 233201500022I; HS027363.
Citation: Bradford A, Shofer M, Singh H .
Measure Dx: implementing pathways to discover and learn from diagnostic errors.
Int J Qual Health Care 2022 Sep 10;34(3). doi: 10.1093/intqhc/mzac068..
Keywords: Diagnostic Safety and Quality, Patient Safety, Quality Improvement, Quality of Care, Electronic Health Records (EHRs), Health Information Technology (HIT), Health Systems, Learning Health Systems
Zhu Y, Simon GJ, Wick EC
Applying machine learning across sites: external validation of a surgical site infection detection algorithm.
Surgical complications have tremendous consequences and costs. Complication detection is important for quality improvement, but traditional manual chart review is burdensome. Automated mechanisms are needed to make this more efficient. The purpose of the study was to understand the generalizability of a machine learning algorithm between sites; automated surgical site infection (SSI) detection algorithms developed at one center were tested at another distinct center.
AHRQ-funded; HS024532.
Citation: Zhu Y, Simon GJ, Wick EC .
Applying machine learning across sites: external validation of a surgical site infection detection algorithm.
J Am Coll Surg 2021 Jun;232(6):963-71.e1. doi: 10.1016/j.jamcollsurg.2021.03.026..
Keywords: Healthcare-Associated Infections (HAIs), Surgery, Adverse Events, Diagnostic Safety and Quality, Electronic Health Records (EHRs), Health Information Technology (HIT), Quality Improvement, Quality of Care
Griffey 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
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
Kang SK, Garry K, Chung R
Natural language processing for identification of incidental pulmonary nodules in radiology reports.
The authors developed natural language processing (NLP) to identify incidental lung nodules (ILNs) in radiology reports for assessment of management recommendations using the electronic health records for patients who underwent chest CT before and after implementation of a department-wide dictation macro of the Fleischner Society recommendations. They concluded that NLP reliably automates identification of ILNs in unstructured reports, pertinent to quality improvement efforts for ILN management.
AHRQ-funded; HS024376.
Citation: Kang SK, Garry K, Chung R .
Natural language processing for identification of incidental pulmonary nodules in radiology reports.
J Am Coll Radiol 2019 Nov;16(11):1587-94. doi: 10.1016/j.jacr.2019.04.026..
Keywords: Imaging, Diagnostic Safety and Quality, Health Information Technology (HIT), Electronic Health Records (EHRs), Quality Improvement, Quality of Care
Knierim KE, Hall TL, Dickinson LM
Primary care practices' ability to report electronic clinical quality measures in the EvidenceNOW Southwest Initiative to Improve Heart Health.
The objective of this study was to determine how quickly primary care practices can report electronic clinical quality measures (eCQMs) and to identify the practice characteristics associated with faster reporting. Examining the EvidenceNOW Southwest initiative, the researchers’ results showed that the time to report eCQMs varied by measure and practice type, with very few practices reporting quickly. Additional support for practices to succeed in new programs that require eCQM reporting was recommended.
AHRQ-funded; HS023904.
Citation: Knierim KE, Hall TL, Dickinson LM .
Primary care practices' ability to report electronic clinical quality measures in the EvidenceNOW Southwest Initiative to Improve Heart Health.
JAMA Netw Open 2019 Aug 2;2(8):e198569. doi: 10.1001/jamanetworkopen.2019.8569..
Keywords: Primary Care, Quality Indicators (QIs), Quality Measures, Quality Improvement, Quality of Care, Heart Disease and Health, Cardiovascular Conditions, Patient-Centered Outcomes Research, Evidence-Based Practice, Electronic Health Records (EHRs), Health Information Technology (HIT)
Dalal AK, Fuller T, Garabedian P
Systems engineering and human factors support of a system of novel EHR-integrated tools to prevent harm in the hospital.
This study examined systems engineering and human factors support of a system of novel electronic health record (EHR)-integrated tools for patient safety in the hospital. The authors established a Patient Safety Learning Laboratory of 2 core and 3 individual project teams to introduce a suite of digital health tools integrated with their EHR to identify, assess, and mitigate threats to patient safety. They identified 7 themes regarding use of 12 systems engineering and human factors over the 4-year project.
AHRQ-funded; HS023535.
Citation: Dalal AK, Fuller T, Garabedian P .
Systems engineering and human factors support of a system of novel EHR-integrated tools to prevent harm in the hospital.
J Am Med Inform Assoc 2019 Jun;26(6):553-60. doi: 10.1093/jamia/ocz002..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Patient Safety, Hospitals, Quality Improvement, Quality of Care
Colborn KL, Bronsert M, Hammermeister K
Identification of urinary tract infections using electronic health record data.
Using the American College of Surgeons National Surgical Quality Improvement Program UTI status of patients who underwent an operation at the University of Colorado Hospital, the investigators sought to develop an algorithm for identifying UTIs using data from the electronic health record. The investigators concluded that a model with 14 predictors from the electronic health record identifies UTIs well, and it could be used to scale up UTI surveillance or to estimate the impact of large-scale interventions on UTI rates.
AHRQ-funded; HS026019.
Citation: Colborn KL, Bronsert M, Hammermeister K .
Identification of urinary tract infections using electronic health record data.
Am J Infect Control 2019 Apr;47(4):371-75. doi: 10.1016/j.ajic.2018.10.009..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Quality of Care, Quality Improvement, Surgery, Urinary Tract Infection (UTI)
Simon KC, Yucus C, Castle J
Building of EMR tools to support quality and research in a memory disorders clinic.
This article describes the development of a customized EMR toolkit that standardizes patient data collection with hundreds of discrete fields, supports Best Practices for treating patients with memory disorders, and also supports practice-based research. The toolkit was successfully implemented to support Best Practices in the care of patients with memory disorders. Applications are also discussed. Data collection is ongoing, but the authors anticipate that the toolkit will generate data that allows for descriptive and hypothesis-driven research as well as quality improvement among patients seen in memory clinics.
AHRQ-funded; HS024057.
Citation: Simon KC, Yucus C, Castle J .
Building of EMR tools to support quality and research in a memory disorders clinic.
Front Neurol 2019 Mar 7;10:161. doi: 10.3389/fneur.2019.00161..
Keywords: Dementia, Electronic Health Records (EHRs), Health Information Technology (HIT), Neurological Disorders, Quality of Care, Quality Improvement, Tools & Toolkits
Liu LH, Choden S, Yazdany J
Quality improvement initiatives in rheumatology: an integrative review of the last 5 years.
Researchers reviewed recent quality improvement initiatives in the field of rheumatology to identify common strategies and themes leading to measurable change. Their review demonstrated common solutions, particularly involving leveraging health IT and workflow redesign. Electronic health record (EHR)-based interventions were most successful when reinforced with provider education, reminders, and performance feedback. Structured models such as the learning collaborative may help disseminate successful initiatives across practices.
AHRQ-funded; HS025638.
Citation: Liu LH, Choden S, Yazdany J .
Quality improvement initiatives in rheumatology: an integrative review of the last 5 years.
Curr Opin Rheumatol 2019 Mar;31(2):98-108. doi: 10.1097/bor.0000000000000586..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Quality of Care, Quality Improvement
Shah T, Patel-Teague S, Kroupa L
Impact of a national QI programme on reducing electronic health record notifications to clinicians.
In this study, the investigators evaluated the impact of a national, multicomponent, quality improvement (QI) programme designed to reduce low-value EHR notifications. The investigators found that, based on prior estimates on time to process notifications, this national QI programme potentially saved 1.5 hours per week per PCP to enable higher value work. The investigators also found that the number of daily notifications remained high, suggesting the need for additional multifaceted interventions and protected clinical time to help manage them.
AHRQ-funded; HS022087.
Citation: Shah T, Patel-Teague S, Kroupa L .
Impact of a national QI programme on reducing electronic health record notifications to clinicians.
BMJ Qual Saf 2019 Jan;28(1):10-14. doi: 10.1136/bmjqs-2017-007447..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Quality Indicators (QIs), Quality Improvement, Quality of Care, Primary Care, Primary Care: Models of Care
Dowding D, Merrill J, Russell D
Using feedback intervention theory to guide clinical dashboard design.
The provision of feedback to clinicians and organizations on the quality of care they provide is thought to influence clinician and organizational behavior leading to care improvements. Clinical Dashboards use data visualization techniques to provide feedback to individuals on their performance compared to quality metrics. In this paper the authors outline a theoretical approach to the design of a clinical dashboard; Feedback Intervention Theory (FIT).
AHRQ-funded; HS023855.
Citation: Dowding D, Merrill J, Russell D .
Using feedback intervention theory to guide clinical dashboard design.
AMIA Annu Symp Proc 2018 Dec 5;2018:395-403..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Provider Performance, Quality of Care, Quality Improvement
Colin NV, Cholan RA, Sachdeva B
Understanding the impact of variations in measurement period reporting for electronic clinical quality measures.
The purpose of the study was to understand the impact of varying measurement period on the calculation of electronic Clinical Quality Measures (eCQMs). Variations in measurement periods were associated with variation in performance between clinics for 3 of the 4 eCQMs, but did not have significant differences when calculated within clinics. Variations from standard measurement periods may reflect poor data quality and accuracy.
AHRQ-funded; HS023908.
Citation: Colin NV, Cholan RA, Sachdeva B .
Understanding the impact of variations in measurement period reporting for electronic clinical quality measures.
eGEMS 2018 Jul 19;6(1):17. doi: 10.5334/egems.235..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Quality Measures, Quality Improvement, Quality of Care
Dowding D, Merrill JA
The development of heuristics for evaluation of dashboard visualizations.
Heuristic evaluation is used in human-computer interaction studies to assess the usability of information systems. This article develops a heuristic evaluation checklist that can be used to evaluate systems that produce information visualizations. The authors suggest that a checklist of usability heuristics for evaluating information visualization systems can contribute to assuring high quality in electronic data systems developed for health care.
AHRQ-funded; HS023855.
Citation: Dowding D, Merrill JA .
The development of heuristics for evaluation of dashboard visualizations.
Appl Clin Inform 2018 Jul;9(3):511-18. doi: 10.1055/s-0038-1666842..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Provider Performance, Quality of Care, Quality Improvement
Hemler JR, Hall JD, Cholan RA
Practice facilitator strategies for addressing electronic health record data challenges for quality improvement: EvidenceNOW.
In this paper, the authors describe the strategies facilitators use to help practices perform quality improvement (QI) when complete or accurate performance data are not available. The investigators found facilitators faced practice-level EHR data challenges, such as a lack of clinical performance data, partial or incomplete clinical performance data, and inaccurate clinical performance data.
AHRQ-funded; HS023940.
Citation: Hemler JR, Hall JD, Cholan RA .
Practice facilitator strategies for addressing electronic health record data challenges for quality improvement: EvidenceNOW.
J Am Board Fam Med 2018 May-Jun;31(3):398-409. doi: 10.3122/jabfm.2018.03.170274..
Keywords: Electronic Health Records (EHRs), Quality Improvement, Evidence-Based Practice, Health Information Technology (HIT), Primary Care, Quality of Care
Austrian JS, Jamin CT, Doty GR
Impact of an emergency department electronic sepsis surveillance system on patient mortality and length of stay.
The goal of this study was to determine if an electronic health record (EHR) based sepsis alert system could improve quality of care and clinical outcomes for patients with sepsis. A patient-level, interrupted time series study of emergency department patients with severe sepsis or septic shock was conducted, with an intervention introduced at the approximate mid-point--a system of interruptive sepsis alerts triggered by abnormal vital signs or laboratory results. Mean length of stay for patients with sepsis decreased significantly following the introduction of the alert, but the alert system had no effect on mortality or other clinical or process measures. The researchers conclude that a more sophisticated algorithm for sepsis identification is needed to improve outcomes.
AHRQ-funded; HS023683.
Citation: Austrian JS, Jamin CT, Doty GR .
Impact of an emergency department electronic sepsis surveillance system on patient mortality and length of stay.
J Am Med Inform Assoc 2018 May;25(5):523-29. doi: 10.1093/jamia/ocx072..
Keywords: Electronic Health Records (EHRs), Emergency Department, Health Information Technology (HIT), Hospitals, Mortality, Outcomes, Quality Improvement, Quality of Care, Sepsis
Cohen DJ, Dorr DA, Knierim K
Primary care practices' abilities and challenges in using electronic health record data for quality improvement.
Federal value-based payment programs require primary care practices to conduct quality improvement activities, informed by the electronic reports on clinical quality measures that their electronic health records (EHRs) generate. This study concluded that the current state of EHR measurement functionality may be insufficient to support federal initiatives that tie payment to clinical quality measures.
AHRQ-funded; HS023940.
Citation: Cohen DJ, Dorr DA, Knierim K .
Primary care practices' abilities and challenges in using electronic health record data for quality improvement.
Health Aff 2018 Apr;37(4):635-43. doi: 10.1377/hlthaff.2017.1254.
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Keywords: Electronic Health Records (EHRs), Primary Care, Quality Improvement, Quality of Care, Health Information Technology (HIT), Payment
Bhise V, Sittig DF, Vaghani V
An electronic trigger based on care escalation to identify preventable adverse events in hospitalised patients.
Researchers refined the methods of the Institute of Healthcare Improvement's Global Trigger Tool application and leveraged electronic health record data to improve detection of preventable adverse events, including diagnostic errors. In the studied sample, preventable adverse events were identified, including adverse drug events, patient falls, procedure-related complications, and hospital-associated infections. The authors concluded that such e-triggers can help overcome limitations of currently available methods to detect preventable harm in hospitalized patients.
AHRQ-funded; HS022087; HS023602.
Citation: Bhise V, Sittig DF, Vaghani V .
An electronic trigger based on care escalation to identify preventable adverse events in hospitalised patients.
BMJ Qual Saf 2018 Mar;27(3):241-46. doi: 10.1136/bmjqs-2017-006975..
Keywords: Adverse Events, Electronic Health Records (EHRs), Health Information Technology (HIT), Hospitalization, Hospitals, Patient Safety, Prevention, Quality of Care, Quality Improvement, Quality Indicators (QIs)