National Healthcare Quality and Disparities Report
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Search All Research Studies
AHRQ Research Studies Date
Topics
- Adverse Events (1)
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- Clinical Decision Support (CDS) (2)
- Dementia (1)
- (-) Elderly (12)
- Electronic Health Records (EHRs) (4)
- (-) Emergency Department (12)
- Falls (4)
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- (-) Health Information Technology (HIT) (12)
- Home Healthcare (1)
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- Long-Term Care (3)
- Neurological Disorders (2)
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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 12 of 12 Research Studies DisplayedHaimovich AD, Shah MN, Southerland LT
Automating risk stratification for geriatric syndromes in the emergency department.
This study discussed using automated risk stratification to implement screening programs for geriatric syndromes in the emergency department (ED). This method would reduce significant workloads at a time of record-breaking ED patient volumes, staff shortages, and hospital boarding crises. The authors defined the concept of automated risk stratification and screening using existing electronic health record (EHR) data. They discussed progress made in three potential use cases in the ED: falls, cognitive impairment, and end-of-life and palliative care; emphasizing the importance of linking automated screening with systems of healthcare delivery. They found that research progress and operational deployment vary by use case, ranging from deployed solutions in falls screening to algorithmic validation in cognitive impairment and end-of-life care, but should still be considered a potential solution.
AHRQ-funded; HS027735.
Citation: Haimovich AD, Shah MN, Southerland LT .
Automating risk stratification for geriatric syndromes in the emergency department.
J Am Geriatr Soc 2024 Jan; 72(1):258-67. doi: 10.1111/jgs.18594..
Keywords: Elderly, Emergency Department, Risk, Health Information Technology (HIT)
Hekman DJ, Cochran AL, Maru AP
Effectiveness of an emergency department-based machine learning clinical decision support tool to prevent outpatient falls among older adults: protocol for a quasi-experimental study.
This article described a research protocol for evaluating the effectiveness of an automated screening and referral intervention tool for patients receiving falls risk intervention. The study will attempt to quantify the impact of a machine learning (ML) clinical decision support intervention on patient behavior and outcomes. The primary analysis will obtain referral completion rates from different emergency departments. The findings will inform ongoing discussion on the use of ML and artificial intelligence to augment medical decision-making.
AHRQ-funded; HS027735.
Citation: Hekman DJ, Cochran AL, Maru AP .
Effectiveness of an emergency department-based machine learning clinical decision support tool to prevent outpatient falls among older adults: protocol for a quasi-experimental study.
JMIR Res Protoc 2023 Aug 3; 12:e48128. doi: 10.2196/48128..
Keywords: Clinical Decision Support (CDS), Emergency Department, Health Information Technology (HIT), Elderly, Falls
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)
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
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)
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)
Gillespie SM, Wasserman EB, Wood NE
High-intensity telemedicine reduces emergency department use by older adults with dementia in senior living communities.
Individuals with dementia have high rates of emergency department (ED) use for acute illnesses. In this study, the investigators evaluated the effect of a high-intensity telemedicine program that delivered care for acute illnesses on ED use rates for individuals with dementia residing in senior living communities (SLCs; independent and assisted living).
AHRQ-funded; HS018047.
Citation: Gillespie SM, Wasserman EB, Wood NE .
High-intensity telemedicine reduces emergency department use by older adults with dementia in senior living communities.
J Am Med Dir Assoc 2019 Aug;20(8):942-46. doi: 10.1016/j.jamda.2019.03.024..
Keywords: Elderly, Telehealth, Health Information Technology (HIT), Dementia, Neurological Disorders, Healthcare Delivery, Chronic Conditions, Emergency Department, Healthcare Utilization
Patterson BW, Repplinger MD, Pulia MS
Using the Hendrich II Inpatient Fall Risk Screen to predict outpatient falls after emergency department visits.
This study examined the utility of using the Hendrich II Inpatient Fall Risk Screen to predict outpatient falls in elderly patients after emergency department (ED) visits. Individuals aged 65 and older seen in the ED from January 2013 to September 30, 2015 participated in the study. The Hendrich II screen was found to correlate with outpatient falls, but it is likely it would have little utility as a stand-alone fall screen. When the screen was combined with other potential confounders or predictors, the screen performed much better.
AHRQ-funded; HS024558.
Citation: Patterson BW, Repplinger MD, Pulia MS .
Using the Hendrich II Inpatient Fall Risk Screen to predict outpatient falls after emergency department visits.
J Am Geriatr Soc 2018 Apr;66(4):760-65. doi: 10.1111/jgs.15299..
Keywords: Elderly, Falls, Risk, Emergency Department, Electronic Health Records (EHRs), Health Information Technology (HIT), Prevention, Patient Safety, Adverse Events
Gillespie SM, Shah MN, Wasserman EB
Reducing emergency department utilization through engagement in telemedicine by senior living communities.
High-intensity telemedicine has been shown to reduce the need for emergency department (ED) care for older adult senior living community (SLC) residents with acute illnesses. In this study, the investigators evaluated the effect of SLC engagement in a telemedicine program on ED use rates. The investigators concluded that individuals residing in more engaged SLCs experienced a greater decrease in ED use compared with subjects residing in less engaged SLCs or those without access to high-intensity telemedicine for acute illnesses.
AHRQ-funded; HS018047.
Citation: Gillespie SM, Shah MN, Wasserman EB .
Reducing emergency department utilization through engagement in telemedicine by senior living communities.
Telemed J E Health 2016 Jun;22(6):489-96. doi: 10.1089/tmj.2015.0152..
Keywords: Elderly, Emergency Department, Health Information Technology (HIT), Healthcare Utilization, Patient and Family Engagement, Telehealth
Shah MN, Wasserman EB, Wang H
High-intensity telemedicine decreases emergency department use by senior living community residents.
The authors evaluated the effect on emergency departrment use of a high-intensity telemedicine program that provides acute illness care for senior living community (SLC) residents. They found that high-intensity telemedicine significantly reduced emergency department use among SLC residents without increasing other utilization or mortality.
AHRQ-funded; HS018047.
Citation: Shah MN, Wasserman EB, Wang H .
High-intensity telemedicine decreases emergency department use by senior living community residents.
Telemed J E Health 2016 Mar;22(3):251-8. doi: 10.1089/tmj.2015.0103.
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Keywords: Elderly, Telehealth, Health Information Technology (HIT), Emergency Department, Healthcare Utilization, Long-Term Care
Shah MN, Wasserman EB, Gillespie SM
High-intensity telemedicine decreases emergency department use for ambulatory care sensitive conditions by older adult senior living community residents.
The aim of this study was to assess the effect of a high-intensity telemedicine program for senior living community (SLC) residents on the rate of Emergency department (ED) visits for ambulatory care sensitive conditions (ACSCs). It found that providing acute illness care by high-intensity telemedicine to older adults residing in SLCs significantly decreases the rate of ED use for ACSCs over 1 year.
AHRQ-funded; HS018047.
Citation: Shah MN, Wasserman EB, Gillespie SM .
High-intensity telemedicine decreases emergency department use for ambulatory care sensitive conditions by older adult senior living community residents.
J Am Med Dir Assoc 2015 Dec;16(12):1077-81. doi: 10.1016/j.jamda.2015.07.009..
Keywords: Elderly, Telehealth, Health Information Technology (HIT), Emergency Department, Healthcare Utilization, Long-Term Care
Shah MN, Morris D, Jones CM
A qualitative evaluation of a telemedicine-enhanced emergency care program for older adults.
The purpose of this study was to document the experiences of patients, their caregivers, healthcare personnel, and staff members with a program that provides telemedicine-enhanced emergency care to older adults residing in senior living communities (SLCs) and to delineate perceived barriers and facilitators. The authors concluded that telemedicine-enhanced emergency care is an acceptable method of providing emergency care to older adults in SLCs.
AHRQ-funded; HS018047.
Citation: Shah MN, Morris D, Jones CM .
A qualitative evaluation of a telemedicine-enhanced emergency care program for older adults.
J Am Geriatr Soc 2013 Apr;61(4):571-6. doi: 10.1111/jgs.12157..
Keywords: Elderly, Telehealth, Health Information Technology (HIT), Emergency Department, Healthcare Delivery, Long-Term Care