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Search All Research Studies
Topics
- Behavioral Health (1)
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- (-) Clinical Decision Support (CDS) (6)
- (-) Elderly (6)
- Emergency Department (2)
- Falls (3)
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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 6 of 6 Research Studies DisplayedHekman 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
Kagarmanova A, Sparkman H, Laiteerapong N
Improving the management of chronic pain, opioid use, and opioid use disorder in older adults: study protocol for i-cope study.
This article describes a protocol for an upcoming study on the planned implementation and evaluation of I-COPE (Improving Chicago Older Adult Opioid and Pain Management through Patient-centered Clinical Decision Support and Project ECHO®) to improve care for older adults with chronic pain, opioid use, and opioid use disorder (OUD). The study will be implemented in 35 clinical sites across the metropolitan Chicago area for patients aged ≥ 65 with chronic pain, opioid use, or OUD who receive primary care at one of the clinics. I-COPE includes the integration of patient-reported data on symptoms and preferences, clinical decision support tools and shared decision making into routine primary care. Primary care providers will be trained on the tools through web-based videos and an optional Project ECHO® course, entitled "Pain Management and OUD in Older Adults." A framework called RE-AIM will be used to assess the I-COPE implementation. Outcomes considered effective include an increased variety of recommended pain treatments, decreased prescriptions of higher-risk pain treatments, and decreased patient pain scores. Outcomes will be evaluated at 6 and 12 months after implementation, and PCPs participating in Project ECHO® will be evaluated on changes in knowledge, attitudes, and self-efficacy using pre- and post-course surveys.
AHRQ-funded; HS027910.
Citation: Kagarmanova A, Sparkman H, Laiteerapong N .
Improving the management of chronic pain, opioid use, and opioid use disorder in older adults: study protocol for i-cope study.
Trials 2022 Jul 27;23(1):602. doi: 10.1186/s13063-022-06537-w..
Keywords: Elderly, Pain, Chronic Conditions, Opioids, Medication, Substance Abuse, Behavioral Health, Clinical Decision Support (CDS), Shared Decision Making, Health Information Technology (HIT)
Rice H, Garabedian PM, Shear K
Clinical decision support for fall prevention: defining end-user needs.
The purpose of this study was to identify patient and primary care staff needs for development of a tool that will generate clinical decision support (CDS) to prevent falls and injuries in older adults. Community-dwelling patients aged 60 and over and primary care clinic staff were eligible to participate in the study; all were affiliated with the University of Florida Health Archer Family Health Care primary care clinic and the Brigham & Women's Hospital-affiliated primary care clinics. Through qualitative interviews with patients (n=18) and primary care clinic staff (n=24) user needs were identified and then categorized into the following themes: evidence-based safe exercises; expert guidance; individualized resources; in-person assessment of patient condition; motivational tools; patient understanding of fall risk; personal support networks; systematic communication and workload burden. The study concluded that personalized, actionable, and evidence-based clinical decision support may be able to address some of the many gaps that exist in fall prevention management in older adults.
AHRQ-funded; HS027557.
Citation: Rice H, Garabedian PM, Shear K .
Clinical decision support for fall prevention: defining end-user needs.
Appl Clin Inform 2022 May;13(3):647-55. doi: 10.1055/s-0042-1750360..
Keywords: Elderly, Falls, Prevention, Clinical Decision Support (CDS), Shared Decision Making, Health Information Technology (HIT)
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)
Campbell NL, Holden RJ, Tang Q
Multicomponent behavioral intervention to reduce exposure to anticholinergics in primary care older adults.
This study tested the effectiveness of a multicomponent behavioral intervention to reduce the use of high-risk anticholinergic medications in primary care older adults. Ten primary care clinics within Eskenazi Health in Indianapolis were selected to test the intervention. The intervention included provider- and patient-focused components. The provider-focused component was a computerized decision support system alerting the presence of a high-risk anticholinergic and offering dose- and indication-specific alternatives; while the patient-focused component was a story-based video providing education and modeling an interaction with a healthcare provider. The intervention occurred from April 2019 through March 2020. A total of 552 older adults had primary care visits during the study period. Only 3 out of 259 provider-focused alerts led to a medication change. Of the 276 staff alerts, 4.7% were confirmed to activate the patient-focused intervention.
AHRQ-funded; P30HS024384.
Citation: Campbell NL, Holden RJ, Tang Q .
Multicomponent behavioral intervention to reduce exposure to anticholinergics in primary care older adults.
J Am Geriatr Soc 2021 Jun;69(6):1490-99. doi: 10.1111/jgs.17121..
Keywords: Elderly, Medication, Primary Care, Clinical Decision Support (CDS), Shared Decision Making
Yin MT, Shiau S, Rimland D
Fracture prediction with modified-FRAX in older HIV-infected and uninfected men.
The authors investigated considering HIV as a cause of secondary osteoporosis when calculating FRAX, a clinical fracture risk calculator, in HIV-infected individuals. They found that modified-FRAX underestimated the fracture rates more in older HIV-infected than in otherwise similar uninfected men. and they recommend further studies to determine how to risk stratify for screening and treatment in older HIV-infected individuals.
AHRQ-funded; HS018372.
Citation: Yin MT, Shiau S, Rimland D .
Fracture prediction with modified-FRAX in older HIV-infected and uninfected men.
J Acquir Immune Defic Syndr 2016 Aug 15;72(5):513-20. doi: 10.1097/qai.0000000000000998.
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Keywords: Clinical Decision Support (CDS), Elderly, Injuries and Wounds, Human Immunodeficiency Virus (HIV), Risk