National Healthcare Quality and Disparities Report
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AHRQ Research Studies Date
Topics
- Adverse Events (2)
- Care Coordination (1)
- Care Management (1)
- Children/Adolescents (4)
- Clinical Decision Support (CDS) (3)
- Communication (1)
- COVID-19 (1)
- Critical Care (1)
- Diagnostic Safety and Quality (1)
- Elderly (4)
- (-) Electronic Health Records (EHRs) (35)
- (-) Emergency Department (35)
- Emergency Medical Services (EMS) (4)
- Falls (2)
- Healthcare Delivery (3)
- Healthcare Utilization (1)
- Health Information Exchange (HIE) (3)
- Health Information Technology (HIT) (30)
- Home Healthcare (1)
- Hospitalization (2)
- Hospital Readmissions (1)
- Hospitals (3)
- Implementation (1)
- Kidney Disease and Health (1)
- Medical Errors (1)
- Medication (2)
- Mortality (1)
- Neurological Disorders (1)
- Nursing (1)
- Outcomes (1)
- Patient-Centered Healthcare (1)
- Patient-Centered Outcomes Research (1)
- Patient Safety (5)
- Prevention (1)
- Provider (2)
- Provider: Health Personnel (1)
- Provider: Physician (3)
- Quality Improvement (2)
- Quality Measures (1)
- Quality of Care (4)
- Registries (2)
- Risk (4)
- Rural Health (1)
- Screening (1)
- Sepsis (2)
- Shared Decision Making (3)
- Simulation (1)
- Teams (1)
- Telehealth (1)
- Trauma (2)
- Workflow (3)
- Workforce (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 25 of 35 Research Studies DisplayedMoy AJ, Cato KD, Withall J
Using time series clustering to segment and infer emergency department nursing shifts from electronic health record log files.
Clinical shifts are an essential unit of work recognized in clinical settings and may function as a primary unit of analysis in the study of documentation burden. The purpose of this proof- of-concept study was to investigate the feasibility of a new approach utilizing time series clustering to segment and infer clinician shifts from electronic health record (HER) log files. The researchers recorded 33,535,585 events between April-June 2021 and computationally identified 43,911 potential shifts among 2,285 emergency department nurses. On average, shifts were 10.6±3.1 hours in duration. Researchers classified the shifts based on type: day, evening, night; and length: 12-hour, 8-hour, other. The preliminary results of the study found that unsupervised clustering methods may be a feasible approach for quickly identifying clinician shifts.
AHRQ-funded; HS028454.
Citation: Moy AJ, Cato KD, Withall J .
Using time series clustering to segment and infer emergency department nursing shifts from electronic health record log files.
AMIA Annu Symp Proc 2023 Apr 29; 2022:805-14..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Emergency Department, Workforce
Moy AJ, Hobensack M, Marshall K
Understanding the perceived role of electronic health records and workflow fragmentation on clinician documentation burden in emergency departments.
This study’s goal was to understand the perceived role of electronic health records (EHR) and workflow fragmentation on clinician documentation burden in the emergency department (ED). The authors conducted semistructured interviews with a national sample of US prescribing providers and registered nurses who actively practice in the adult ED setting and use Epic Systems' EHR. They recruited 12 prescribing providers and 12 registered nurses. Six themes were found related to EHR factors perceived to contribute to documentation burden including lack of advanced EHR capabilities, absence of EHR optimization for clinicians, poor user interface design, hindered communication, increased manual work, and added workflow blockages, and five themes associated with cognitive load. The relationship between workflow fragmentation and EHR documentation burden brought up two themes: underlying sources and adverse consequences.
AHRQ-funded; HS028454.
Citation: Moy AJ, Hobensack M, Marshall K .
Understanding the perceived role of electronic health records and workflow fragmentation on clinician documentation burden in emergency departments.
J Am Med Inform Assoc 2023 Apr 19; 30(5):797-808. doi: 10.1093/jamia/ocad038..
Keywords: Electronic Health Records (EHRs), Workflow, Health Information Technology (HIT), Emergency Department
Hinson JS, Klein E, Smith A
Multisite implementation of a workflow-integrated machine learning system to optimize COVID-19 hospital admission decisions.
This study’s objective was to develop, implement, and evaluate an electronic health record (EHR) embedded clinical decision support (CDS) system that leveraged machine learning (ML) to estimate short-term risk for clinical deterioration in patients with or under investigation for COVID-19. The system translates model-generated risk for critical care needs within 24 hours and inpatient care needs within 72 hours into rapidly interpretable COVID-19 Deterioration Risk Levels made viewable within ED clinician workflow. A retrospective cohort of 21,452 ED patients who visited one of five ED study sites was used to derive ML models and were prospectively validated in 15,670 ED visits that occurred before (n = 4322) or after (n = 11,348) CDS implementation. Model performance and numerous patient-oriented outcomes including in-hospital mortality were measured across study periods. ML model performance was excellent under all conditions. AUC ranged from 0.85 to 0.91 for prediction of critical care needs and 0.80-0.90 for inpatient care needs. Total mortality was unchanged across study periods but was reduced among high-risk patients after the implementation.
AHRQ-funded; HS026640.
Citation: Hinson JS, Klein E, Smith A .
Multisite implementation of a workflow-integrated machine learning system to optimize COVID-19 hospital admission decisions.
NPJ Digit Med 2022 Jul 16;5(1):94. doi: 10.1038/s41746-022-00646-1..
Keywords: COVID-19, Clinical Decision Support (CDS), Health Information Technology (HIT), Implementation, Electronic Health Records (EHRs), Emergency Department, Shared Decision Making
Yadgir SR, Engstrom C, Jacobsohn GC
Machine learning-assisted screening for cognitive impairment in the emergency department.
Researchers developed and evaluated an automated screening tool to identify a subset of patients at high risk for cognitive impairment (CI). Using the Blessed Orientation Memory Concentration (BOMC) test, administered in the emergency department, they found that an algorithm based on electronic health record data can define a subset of patients at higher risk for CI. They recommended that incorporating such an algorithm into a screening workflow could allow screening efforts and resources to be focused where they have the most impact.
AHRQ-funded; HS024558.
Citation: Yadgir SR, Engstrom C, Jacobsohn GC .
Machine learning-assisted screening for cognitive impairment in the emergency department.
J Am Geriatr Soc 2022 Mar;70(3):831-37. doi: 10.1111/jgs.17491..
Keywords: Neurological Disorders, Screening, Emergency Department, Electronic Health Records (EHRs), Health Information Technology (HIT), Elderly
Pruitt ZM, Howe JL, Hettinger AZ
Emergency physician perceptions of electronic health record usability and safety.
Investigators sought to identify emergency physicians' perceived electronic health record (EHR) usability and safety strengths and shortcomings across major EHR vendor products. They found that the 3 most commonly discussed usability topics were Workflow Support (shortcoming), Visual Display (strength), and Data Entry. Fourteen cross-hospital/cross-vendor themes, 6 vendor-specific themes, and 4 hospital-specific themes emerged as well.
AHRQ-funded; HS025136.
Citation: Pruitt ZM, Howe JL, Hettinger AZ .
Emergency physician perceptions of electronic health record usability and safety.
J Patient Saf 2021 Dec 1;17(8):e983-e87. doi: 10.1097/pts.0000000000000849..
Keywords: Emergency Department, Electronic Health Records (EHRs), Health Information Technology (HIT), Patient Safety
Chartash D, Sharifi M, Emerson B
Documentation of shared decisionmaking in the emergency department.
Patient-centered communication and shared decision making is a vital element of clinical practice, but little is known about its impact or value in the emergency department (ED) setting. The researchers of this study developed a natural language processing tool using regular expressions to identify shared decision making, patient-centered communications, and to describe visit-, site-, and temporal-level patterns within a large health system. The study took place in two parts: part 1 was the development and validation of the natural language processing tool, and part 2 was a retrospective analysis of shared decision making and patient discussion using the processing tool to assess ED physician and advanced practitioner documentation from 2013 to 2020. Compared to chart review of 600 ED notes, the accuracy rates of the natural language processing tool were 96.7% and 88.9% respectively. Between 2013 to 2020 the researchers observed greater likelihood of shared decision-making documentation among physicians vs advanced practice providers, higher likelihood among female vs male patients, and lower likelihood of shared decision-making in Black patients compared with White patients. The researchers also found that patient discussion and shared decision-making were associated with higher levels of commercial insurance status and level of triage. The study concluded that a natural language processing tool was developed, validated, and utilized to identify incidences of shared decision making from ED documentation, with the researchers finding multiple possible factors which contribute to variation in shared decision making.
AHRQ-funded; HS025701.
Citation: Chartash D, Sharifi M, Emerson B .
Documentation of shared decisionmaking in the emergency department.
Ann Emerg Med 2021 Nov;78(5):637-49. doi: 10.1016/j.annemergmed.2021.04.038..
Keywords: Shared Decision Making, Emergency Department, Patient-Centered Healthcare, Electronic Health Records (EHRs), Health Information Technology (HIT)
Wang X, Blumenthal HJ, Hoffman D
Modeling patient-related workload in the emergency department using electronic health record data.
Understanding and managing clinician workload is important for clinician (nurses, physicians and advanced practice providers) occupational health as well as patient safety. Efforts have been made to develop strategies for managing clinician workload by improving patient assignment. The goal of the current study was to use electronic health record (EHR) data to predict the amount of work that individual patients contributed to clinician workload (patient-related workload).
AHRQ-funded; HS022542.
Citation: Wang X, Blumenthal HJ, Hoffman D .
Modeling patient-related workload in the emergency department using electronic health record data.
Int J Med Inform 2021 Jun;150:104451. doi: 10.1016/j.ijmedinf.2021.104451..
Keywords: Emergency Department, Electronic Health Records (EHRs), Health Information Technology (HIT), Provider: Physician
Enayati M, Sir M, Zhang X
Monitoring diagnostic safety risks in emergency departments: protocol for a machine learning study.
This study’s objective will be to identify variables associated with diagnostic errors in emergency departments using large-scale EHR data and machine learning techniques. It will use trigger algorithms with electronic health record (EHR) data repositories to generate a large data set of records that are labeled trigger-positive or trigger-negative, depending on if they meet certain criteria. This study will be conducted by 2 academic medical centers with affiliated community hospitals.
AHRQ-funded; HS027363; HS026622.
Citation: Enayati M, Sir M, Zhang X .
Monitoring diagnostic safety risks in emergency departments: protocol for a machine learning study.
JMIR Res Protoc 2021 Jun 14;10(6):e24642. doi: 10.2196/24642..
Keywords: Emergency Department, Diagnostic Safety and Quality, Patient Safety, Risk, Electronic Health Records (EHRs), Health Information Technology (HIT)
Korach ZT, Gradwohl S, Messinger A
Unsupervised clinical relevancy ranking of structured medical records to retrieve condition-specific information in the emergency department.
Investigators compared knowledge-based and unsupervised statistical methods for ranking electronic health record (EHR) information by relevancy to a chief complaint of chest or back pain among emergency department patients. They found that a fully unsupervised statistical method can provide a reasonably accurate, low-effort, and scalable means for situation-specific ranking of clinical information within the EHR.
AHRQ-funded; HS024541.
Citation: Korach ZT, Gradwohl S, Messinger A .
Unsupervised clinical relevancy ranking of structured medical records to retrieve condition-specific information in the emergency department.
Int J Med Inform 2021 May;149:104410. doi: 10.1016/j.ijmedinf.2021.104410.
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Keywords: Emergency Department, Electronic Health Records (EHRs), Health Information Technology (HIT)
Patel VL, Denton CA, Soni HC
Physician workflow in two distinctive emergency departments: an observational study.
In this study, the investigators characterized physician workflow in two distinctive emergency departments (ED). Physician practices mediated by electronic health records (EHR) were explored within the context of organizational complexity for the delivery of care. The investigators concluded that 1.) the nature of the clinical practice and EHR-mediated workflow reflected the ED work practices; 2.) physicians in more complex organizations may be less efficient because of the fragmented workflow- however these effects could be mitigated by effort distribution through team communication, which affords inherent safety checks.
AHRQ-funded; HS022670.
Citation: Patel VL, Denton CA, Soni HC .
Physician workflow in two distinctive emergency departments: an observational study.
Appl Clin Inform 2021 Jan;12(1):141-52. doi: 10.1055/s-0040-1722615..
Keywords: Emergency Department, Workflow, Healthcare Delivery, Electronic Health Records (EHRs), Health Information Technology (HIT)
Patterson BW, Jacobsohn GC, Maru AP
Comparing strategies for identifying falls in older adult emergency department visits using EHR data.
This study compared seven different strategies for identifying falls in older adult emergency department (ED) visits using electronic health record (EHR) data. This retrospective cohort study used randomly selected data from 500 ED visits by patients 65 and older at an academic medical center from December 2016 to April 2017. The seven strategies tested were: Chief complaint (CC), ICD codes, Restrictive ICD codes, Broad ICD codes, Combined approaches, Natural language processing (NLP), and Manual abstraction (gold standard). When compared with manual chart review, NLP was found to be the most accurate fall identification strategy, followed by a combination of a restrictive ICD code-based definition with CC.
AHRQ-funded; HS024558.
Citation: Patterson BW, Jacobsohn GC, Maru AP .
Comparing strategies for identifying falls in older adult emergency department visits using EHR data.
J Am Geriatr Soc 2020 Dec;68(12):2965-67. doi: 10.1111/jgs.16831..
Keywords: Elderly, Falls, Emergency Department, Electronic Health Records (EHRs), Health Information Technology (HIT)
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
Topaz M, Woo K, Ryvicker M
Home healthcare clinical notes predict patient hospitalization and emergency department visits.
About 30% of home healthcare patients are hospitalized or visit an emergency department (ED) during a home healthcare (HHC) episode. Novel data science methods are increasingly used to improve identification of patients at risk for negative outcomes. The aim of the study was to identify patients at heightened risk hospitalization or ED visits using HHC narrative data (clinical notes).
AHRQ-funded; HS027742.
Citation: Topaz M, Woo K, Ryvicker M .
Home healthcare clinical notes predict patient hospitalization and emergency department visits.
Nurs Res 2020 Nov/Dec;69(6):448-54. doi: 10.1097/nnr.0000000000000470..
Keywords: Elderly, Home Healthcare, Emergency Department, Hospitalization, Risk, Electronic Health Records (EHRs), Health Information Technology (HIT)
Martinez DA, Levin SR, Klein EY
Early prediction of acute kidney injury in the emergency department with machine-learning methods applied to electronic health record data.
Researchers analyzed routinely collected emergency department (ED) data and developed prediction models with capacity for early identification of ED patients at high risk for acute kidney injury. They found that machine learning applied to routinely-collected ED data identified ED patients at high risk for acute kidney injury up to 72 hours before they met diagnostic criteria. They recommended further prospective evaluation.
AHRQ-funded; HS027793.
Citation: Martinez DA, Levin SR, Klein EY .
Early prediction of acute kidney injury in the emergency department with machine-learning methods applied to electronic health record data.
Ann Emerg Med 2020 Oct;76(4):501-14. doi: 10.1016/j.annemergmed.2020.05.026..
Keywords: Kidney Disease and Health, Emergency Department, Electronic Health Records (EHRs), Health Information Technology (HIT)
Scott HF, Colborn KL, Sevick CJ
Development and validation of a predictive model of the risk of pediatric septic shock using data known at the time of hospital arrival.
The purpose of this observational cohort study was to derive and validate a model of risk of septic shock among children with suspected sepsis, using data known in the electronic health record at hospital arrival. The investigators concluded that their model estimated the risk of septic shock in children at hospital arrival earlier than existing models. They indicate it leveraged the predictive value of routine electronic health record data through a modern predictive algorithm and suggest it has the potential to enhance clinical risk stratification in the critical moments before deterioration.
AHRQ-funded; HS025696.
Citation: Scott HF, Colborn KL, Sevick CJ .
Development and validation of a predictive model of the risk of pediatric septic shock using data known at the time of hospital arrival.
J Pediatr 2020 Feb;217:145-51.e6. doi: 10.1016/j.jpeds.2019.09.079..
Keywords: Children/Adolescents, Sepsis, Emergency Department, Hospitals, Risk, Electronic Health Records (EHRs), Health Information Technology (HIT)
Horng S, Joseph JW, Calder S
Assessment of unintentional duplicate orders by emergency department clinicians before and after implementation of a visual aid in the electronic health record ordering system.
The purpose of this cohort study was to determine whether a simple visual aid was associated with a reduction in duplicate ordering of tests and medications. An interrupted time series model was used to analyze a series of consecutive patients who visited the emergency department of a large volume academic hospital. The researchers conclude that passive visual cues that provided just-in-time decision support were associated with reductions in unintentional duplicate orders for laboratory and radiology tests but not in unintentional duplicate medication orders.
AHRQ-funded; HS024288.
Citation: Horng S, Joseph JW, Calder S .
Assessment of unintentional duplicate orders by emergency department clinicians before and after implementation of a visual aid in the electronic health record ordering system.
JAMA Netw Open 2019 Dec 2;2(12):e1916499. doi: 10.1001/jamanetworkopen.2019.16499..
Keywords: Electronic Health Records (EHRs), Emergency Department, Health Information Technology (HIT), Patient-Centered Outcomes Research, Medication
Cochran AL, Rathouz PJ, Kocher KE
A latent variable approach to potential outcomes for emergency department admission decisions.
The authors sought to provide a general framework to evaluate admission decisions from electronic healthcare records. They estimated that while admitting a patient with higher latent needs reduced the 30-day risk of revisiting the emergency department or later being admitted through the emergency department by over 79%, admitting a patient with lower latent needs actually increased these 30-day risks by 3.0% and 7.6%, respectively.
AHRQ-funded; HS024160.
Citation: Cochran AL, Rathouz PJ, Kocher KE .
A latent variable approach to potential outcomes for emergency department admission decisions.
Stat Med 2019 Sep 10;38(20):3911-35. doi: 10.1002/sim.8210..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Emergency Department, Clinical Decision Support (CDS), Shared Decision Making, Hospitalization
Wang X, Kim TC, Hegde S
Design and evaluation of an integrated, patient-focused electronic health record display for emergency medicine.
This study used work-centered usability methods to evaluate an integrated patient-focused status display designed to support ED clinicians' communication and situation awareness regarding a patient's health status and progress through their ED plan of care. The display design was informed by previous studies we conducted examining the information and cognitive support requirements of ED providers and nurses. The investigators concluded that participants' subjective ratings of usability, usefulness, and support for cognitive objectives were encouraging.
AHRQ-funded; HS022542.
Citation: Wang X, Kim TC, Hegde S .
Design and evaluation of an integrated, patient-focused electronic health record display for emergency medicine.
Appl Clin Inform 2019 Aug;10(4):693-706. doi: 10.1055/s-0039-1695800..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Emergency Department
Patterson BW, Pulia MS, Ravi S
Scope and influence of electronic health record-integrated clinical decision support in the emergency department: a systematic review.
This systematic review examined the scope and influence of electronic health record-integrated clinical decision support (CDS) technologies implemented in hospital emergency departments. A literature search was conducted using 4 databases from the inception of these CDS systems through January 2018. Out of 2,558 potential studies identified, 42 met inclusion criteria. Common uses for CDS technologies included medication and radiology ordering practices, and more comprehensive systems supporting diagnosis and treatment for specific diseases. The majority of studies (83%) reported positive effects on outcomes, with most studies using a pre-post experimental design (76%). The authors concluded that although most studies show positive effects of CDS technologies, many of the studies were small and poorly controlled.
AHRQ-funded; HS024342; HS024558; HS022086.
Citation: Patterson BW, Pulia MS, Ravi S .
Scope and influence of electronic health record-integrated clinical decision support in the emergency department: a systematic review.
Ann Emerg Med 2019 Aug;74(2):285-96. doi: 10.1016/j.annemergmed.2018.10.034..
Keywords: Clinical Decision Support (CDS), Electronic Health Records (EHRs), Health Information Technology (HIT), Emergency Department
Kimmel HJ, Brice YN, Trikalinos TA
Real-time emergency department electronic notifications regarding high-risk patients: a systematic review.
In this study, the authors systematically reviewed evidence on the feasibility and efficacy of real-time electronic notifications about patients at high risk of emergency department (ED) recidivism. They concluded that real-time electronic notifications of ED providers regarding patients at high risk of ED recidivism are feasible and may help reduce resource utilization and costs. The authors indicate that large knowledge gaps remain regarding patient- and provider-centered outcomes.
AHRQ-funded; HS022998.
Citation: Kimmel HJ, Brice YN, Trikalinos TA .
Real-time emergency department electronic notifications regarding high-risk patients: a systematic review.
Telemed J E Health 2019 Jul;25(7):604-18. doi: 10.1089/tmj.2018.0117..
Keywords: Emergency Department, Electronic Health Records (EHRs), Health Information Technology (HIT), Hospital Readmissions
Durojaiye AB, Levin S, Toerper M
Evaluation of multidisciplinary collaboration in pediatric trauma care using EHR data.
This study electronic health record (EHR) data to compare usage patterns from pediatric trauma patients with minor injuries at a Level I pediatric trauma center. The data was used to compare demographics, clinical and network characteristics, and emergency department (ED) length of stay (LOS). Three distinct groups were compared: fully connected, partially connected, and disconnected. The fully connected group had a decreased ED LOS compared with the partially connected group.
AHRQ-funded; HS023837.
Citation: Durojaiye AB, Levin S, Toerper M .
Evaluation of multidisciplinary collaboration in pediatric trauma care using EHR data.
J Am Med Inform Assoc 2019 Jun;26(6):506-15. doi: 10.1093/jamia/ocy184..
Keywords: Children/Adolescents, Trauma, Electronic Health Records (EHRs), Health Information Technology (HIT), Emergency Department, Healthcare Utilization
Bond WF, Barker LT, Cooley KL
A simple low-cost method to integrate telehealth interprofessional team members during in situ simulation.
This article describes the integration of remote telehealth electronic intensive care unit (eICU) personnel into in situ simulations with rural emergency department (ED) care teams and the technical challenges of creating shared awareness of the patient's condition and the care team's progress among the care team, the eICU, and those running the simulation. The purpose of the simulations was to introduce telehealth technology and new processes of engaging the eICU via telehealth during sepsis care in rural EDs; development of the scenarios included experts in sepsis, telehealth, and emergency medicine. A shared in situ simulation clinical actions observational checklist was created using an off-the-shelf survey software program. The checklist was completed during the simulations by an onsite observer, and shared with the eICU team via teleconferencing software to and cue eICU nurse engagement. Staff from the two EDs were engaged and an eICU nurse participated in debriefing via the telehealth video system.
AHRQ-funded; HS024027.
Citation: Bond WF, Barker LT, Cooley KL .
A simple low-cost method to integrate telehealth interprofessional team members during in situ simulation.
Simul Healthc 2019 Apr;14(2):129-36. doi: 10.1097/sih.0000000000000357..
Keywords: Critical Care, Electronic Health Records (EHRs), Emergency Department, Health Information Technology (HIT), Rural Health, Simulation, Teams, Telehealth
Durojaiye AB, McGeorge N, Kristen W
Characterizing the utilization of the problem list for pediatric trauma care.
The EHR problem list has the potential to support care coordination among the multidisciplinary care team that cares for pediatric trauma patients. To realize this potential, the need exists to ensure appropriate utilization by formulating acceptable usage and management policy. In this regard, understanding the prevailing utilization pattern is pivotal. To this end, in this study, the investigators analyzed EHR in tandem with trauma registry data at a Level I pediatric trauma center.
AHRQ-funded; HS023837.
Citation: Durojaiye AB, McGeorge N, Kristen W .
Characterizing the utilization of the problem list for pediatric trauma care.
AMIA Annu Symp Proc 2018 Dec 5;2018:404-12..
Keywords: Care Coordination, Children/Adolescents, Electronic Health Records (EHRs), Emergency Department, Health Information Technology (HIT), Hospitals, Registries, Trauma
Denton CA, Soni HC, Kannampallil TG
Emergency physicians' perceived influence of EHR use on clinical workflow and performance metrics.
In this article, the authors investigated the perceived effects of electronic health record (EHR) use on clinical workflow and meaningful use (MU) performance metrics. The investigators concluded that physicians' perception of EHRs was likely to influence their practices. They suggested that with negative perceptions of EHR usability problems, positive aspects of EHR use, including the influence on MU performance metrics, may be overridden.
AHRQ-funded; HS022670.
Citation: Denton CA, Soni HC, Kannampallil TG .
Emergency physicians' perceived influence of EHR use on clinical workflow and performance metrics.
Appl Clin Inform 2018 Jul;9(3):725-33. doi: 10.1055/s-0038-1668553..
Keywords: Electronic Health Records (EHRs), Emergency Department, Health Information Technology (HIT), Workflow, Provider: Physician, Provider
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