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
Topics
- Brain Injury (1)
- Caregiving (1)
- Clinical Decision Support (CDS) (4)
- Clinician-Patient Communication (1)
- Communication (1)
- COVID-19 (1)
- Critical Care (1)
- Diagnostic Safety and Quality (1)
- Elderly (1)
- Electronic Health Records (EHRs) (3)
- (-) Emergency Department (9)
- Emergency Medical Services (EMS) (1)
- Falls (1)
- (-) Health Information Technology (HIT) (9)
- Hospitalization (1)
- Implementation (1)
- Newborns/Infants (1)
- Nursing (1)
- Outcomes (1)
- Patient-Centered Healthcare (2)
- Patient and Family Engagement (1)
- Risk (1)
- (-) Shared Decision Making (9)
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 9 of 9 Research Studies DisplayedHinson 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
Jacobsohn GC, Leaf M, Liao F
Collaborative design and implementation of a clinical decision support system for automated fall-risk identification and referrals in emergency departments.
The authors used a collaborative and iterative approach to design and implement an automated clinical decision support system (CDS) for Emergency Department (ED) providers to identify and refer older adult ED patients at high risk of future falls. The system was developed using collaborative input from an interdisciplinary design team and integrated seamlessly into existing ED workflows. A key feature of development was the unique combination of patient experience strategies, human-centered design, and implementation science, which allowed for the CDS tool and intervention implementation strategies to be designed simultaneously. Challenges included: usability problems, data inaccessibility, time constraints, low appointment availability, high volume of patients, and others. The study concluded that using the collaborative, iterative approach was successful in achieving all project goals, and could be applied to other cases.
AHRQ-funded; HS024558.
Citation: Jacobsohn GC, Leaf M, Liao F .
Collaborative design and implementation of a clinical decision support system for automated fall-risk identification and referrals in emergency departments.
Healthc 2022 Mar;10(1):100598. doi: 10.1016/j.hjdsi.2021.100598..
Keywords: Elderly, Clinical Decision Support (CDS), Shared Decision Making, Falls, Risk, Emergency Department, Health Information Technology (HIT)
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)
Aronson PL, Politi MC, Schaeffer P
Development of an app to facilitate communication and shared decision-making with parents of febrile infants ≤ 60 days old.
This study’s aim was to develop and test a tool to engage parents of febrile infants 60 days or less of age evaluated in the emergency department (ED). The tool was designed to improve communication between parents and healthcare providers and to support shared decision-making (SDM) about whether to perform a lumbar puncture (LP) for infants 29 to 60 days of age. The authors conducted a multi-phase development and testing process including individual, semi-structured interviews with parents and clinicians; design of a “storyboard” of the tool with design impression testing; development of a software application prototype called e-Care; and usability testing of e-Care using qualitative assessment and the System Usability Scale (SUS). The authors interviewed 27 parents and 23 clinicians. After the interviews, they developed separate versions of e-Care for infants aged 28 days or less and 29 to 60 days of age in both English and Spanish. e-Care is divided into 4 sections: 1) homepage; 2) why testing is done; 3) what tests are done; and 4) what happens after testing. The mean SUS score given by parents and clinicians was 90.3 representing “excellent” usability.
AHRQ-funded; HS026006.
Citation: Aronson PL, Politi MC, Schaeffer P .
Development of an app to facilitate communication and shared decision-making with parents of febrile infants ≤ 60 days old.
Acad Emerg Med 2021 Jan;28(1):46-59. doi: 10.1111/acem.14082..
Keywords: Clinician-Patient Communication, Communication, Newborns/Infants, Caregiving, Shared Decision Making, Patient and Family Engagement, Emergency Department, Health Information Technology (HIT)
Carayon P, Hoonakker P, Hundt AS
Application of human factors to improve usability of clinical decision support for diagnostic decision-making: a scenario-based simulation study.
This study used a scenario-based simulation to compare a human factor (HF)-based clinician decision support (CDS) with a web-based CDS (MDCalc) for clinicians to diagnose pulmonary embolism (PE) in the emergency department. A total of 32 emergency physicians participated using both CDS types. Emergency physicians made more appropriate diagnoses decisions with the PE-Dx CDS (94%) than with the web-based CDS (84%). Experimental tasks were also performed faster (average 96 seconds per scenario versus 117 seconds). They also reported lower workload and higher satisfaction with the HF-based CDS.
AHRQ-funded; HS024342; HS024558; HS022086.
Citation: Carayon P, Hoonakker P, Hundt AS .
Application of human factors to improve usability of clinical decision support for diagnostic decision-making: a scenario-based simulation study.
BMJ Qual Saf 2020 Apr;29(4):329-40. doi: 10.1136/bmjqs-2019-009857..
Keywords: Clinical Decision Support (CDS), Shared Decision Making, Health Information Technology (HIT), Diagnostic Safety and Quality, Emergency Department
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
Hinson JS, Martinez DA, Cabral S
Triage performance in emergency medicine: a systematic review.
The authors synthesized existing emergency department (ED) triage literature by using a framework that enables performance comparisons and benchmarking across triage systems, with respect to clinical outcomes and reliability. They found that a substantial proportion of ED patients who die post-encounter or who are critically ill are not designated as high acuity at triage. They suggested that the opportunity exists to improve interrater reliability and triage performance in identifying patients at risk of adverse outcome.
AHRQ-funded; HS023641.
Citation: Hinson JS, Martinez DA, Cabral S .
Triage performance in emergency medicine: a systematic review.
Ann Emerg Med 2019 Jul;74(1):140-52. doi: 10.1016/j.annemergmed.2018.09.022..
Keywords: Emergency Department, Shared Decision Making, Critical Care, Outcomes, Health Information Technology (HIT)
Mistry B, Stewart De Ramirez S, Kelen G
Accuracy and reliability of emergency department triage using the emergency severity index: an international multicenter assessment.
This study assessed the accuracy and variability of triage score assignment by emergency department (ED) nurses using the Emergency Severity Index (ESI) in 3 countries. It found that the concordance of nurse-assigned ESI score with reference standard was universally poor and variability was high. Although the ESI is the most popular ED triage tool in the United States and is increasingly used worldwide, its findings point to a need for more reliable ED triage tools.
AHRQ-funded; HS023641.
Citation: Mistry B, Stewart De Ramirez S, Kelen G .
Accuracy and reliability of emergency department triage using the emergency severity index: an international multicenter assessment.
Ann Emerg Med 2018 May;71(5):581-87.e3. doi: 10.1016/j.annemergmed.2017.09.036.
.
.
Keywords: Shared Decision Making, Emergency Department, Emergency Medical Services (EMS), Health Information Technology (HIT), Nursing
Melnick ER, Hess EP, Guo G
Patient-centered decision support: formative usability evaluation of integrated clinical decision support with a patient decision aid for minor head injury in the emergency department.
The study’s objective was to formatively evaluate an electronic tool that not only helps clinicians at the bedside to determine the need for CT use based on the Canadian CT Head Rule but also promotes evidence-based conversations between patients and clinicians regarding patient-specific risk and patients' specific concerns. It concluded that the Concussion or Brain Bleed app is a useful and usable final product integrating clinical decision support with a patient decision aid.
AHRQ-funded; HS021271.
Citation: Melnick ER, Hess EP, Guo G .
Patient-centered decision support: formative usability evaluation of integrated clinical decision support with a patient decision aid for minor head injury in the emergency department.
J Med Internet Res 2017 May 19;19(5):e174. doi: 10.2196/jmir.7846.
.
.
Keywords: Brain Injury, Shared Decision Making, Emergency Department, Health Information Technology (HIT), Patient-Centered Healthcare