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Search All Research Studies
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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 5 of 5 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
Shipe ME, Baechle JJ, Deppen SA
Modeling the impact of delaying surgery for early esophageal cancer in the era of COVID-19.
Surgical society guidelines have recommended changing the treatment strategy for early esophageal cancer during the novel coronavirus (COVID-19) pandemic. Delaying resection can allow for interim disease progression, but the impact of this delay on mortality is unknown. The COVID-19 infection rate at which immediate operative risk exceeds benefit is unknown. In this study, the investigators sought to model immediate versus delayed surgical resection in a T1b esophageal adenocarcinoma.
AHRQ-funded; HS026122.
Citation: Shipe ME, Baechle JJ, Deppen SA .
Modeling the impact of delaying surgery for early esophageal cancer in the era of COVID-19.
Surg Endosc 2021 Nov;35(11):6081-88. doi: 10.1007/s00464-020-08101-6..
Keywords: COVID-19, Cancer, Surgery, Shared Decision Making, Risk
Nair D, Malhotra S, Lupu D
Challenges in communication, prognostication and dialysis decision-making in the COVID-19 pandemic: implications for interdisciplinary care during crisis settings.
This paper uses case vignettes to highlight challenges in communication, prognostication, and medical decision-making that have been exacerbated by the COVD-19 pandemic for patients with kidney disease. The authors include best practice recommendations to mitigate those issues and conclude with implications for interdisciplinary models of care in crisis settings. Concerns about certain biomarkers, demographics, and medical comorbidities that can predict an increased risk for mortality among patients with COVID-19 and kidney disease are discussed, because there may be communication barriers related to physical exposure and conservation of personal protective equipment with those at-risk patients.
AHRQ-funded; HS026395.
Citation: Nair D, Malhotra S, Lupu D .
Challenges in communication, prognostication and dialysis decision-making in the COVID-19 pandemic: implications for interdisciplinary care during crisis settings.
Curr Opin Nephrol Hypertens 2021 Mar 1;30(2):190-97. doi: 10.1097/mnh.0000000000000689..
Keywords: COVID-19, Dialysis, Kidney Disease and Health, Shared Decision Making, Clinician-Patient Communication, Communication, Chronic Conditions
Shipe ME, Beeghly-Fadiel A, Deppen SA
Modeling the impact of delaying bariatric surgery due to COVID-19: a decision analysis.
In this study, the investigators developed a decision analysis model to evaluate risks and benefits of delaying scheduled bariatric surgery during the novel coronavirus disease (COVID-19) pandemic. Their base case was a 45-year-old female with diabetes and a body mass index of 45 kg/m(2). They compared immediate with delayed surgery after 6 months to allow for COVID-19 prevalence to decrease. The investigators found that immediate and delayed bariatric surgeries after 6 months resulted in similar 20-year overall survival.
AHRQ-funded; HS026122.
Citation: Shipe ME, Beeghly-Fadiel A, Deppen SA .
Modeling the impact of delaying bariatric surgery due to COVID-19: a decision analysis.
Obes Surg 2021 Mar;31(3):1387-91. doi: 10.1007/s11695-020-05054-6..
Keywords: Obesity: Weight Management, Obesity, COVID-19, Surgery, Shared Decision Making
Abrams EM, Shaker M, Oppenheimer J
The challenges and opportunities for shared decision making highlighted by COVID-19.
This article discusses the challenges and opportunities for shared decision making (SDM) that have been emphasized more recently due to the COVID-19 pandemic. It has changed how clinicians deliver care due to the need for social distancing and health service reallocation. It is causing clinicians to reevaluate common practices and enhance effectiveness of their management strategies.
AHRQ-funded; HS024599.
Citation: Abrams EM, Shaker M, Oppenheimer J .
The challenges and opportunities for shared decision making highlighted by COVID-19.
J Allergy Clin Immunol Pract 2020 Sep;8(8):2474-80.e1. doi: 10.1016/j.jaip.2020.07.003.
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Keywords: Shared Decision Making, COVID-19, Healthcare Delivery, Patient and Family Engagement, Patient-Centered Healthcare