National Healthcare Quality and Disparities Report
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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.
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1 to 2 of 2 Research Studies DisplayedMueller KL, Naganathan S, Griffey RT
Counseling on Access to Lethal Means-Emergency Department (CALM-ED): a quality improvement program for firearm injury prevention.
The authors evaluated the feasibility of the Counseling on Access to Lethal Means intervention in the Emergency Department (CALM-ED) by non-physician personnel. Their quality improvement study was conducted in an urban, academic ED with over 90,000 annual patient visits, and considered adult patients who were discharged after presenting to the ED with a suicidal crisis. They found that an ED-based CALM quality-improvement intervention was feasible for implementation by non-physician personnel and was well received by patients and families. They concluded that the intervention has the potential to help saves lives at times of suicide crisis.
AHRQ-funded; HS025052.
Citation: Mueller KL, Naganathan S, Griffey RT .
Counseling on Access to Lethal Means-Emergency Department (CALM-ED): a quality improvement program for firearm injury prevention.
West J Emerg Med 2020 Aug 20;21(5):1123-30. doi: 10.5811/westjem.2020.5.46952.
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Keywords: Emergency Department, Injuries and Wounds, Prevention, Quality Improvement, Quality of Care, Domestic Violence, Behavioral Health
Tignanelli CJ, Silverman GM, Lindemann EA
Natural language processing of prehospital emergency medical services trauma records allows for automated characterization of treatment appropriateness.
Incomplete prehospital trauma care is a significant contributor to preventable deaths. Current databases lack timelines easily constructible of clinical events. Temporal associations and procedural indications are critical to characterize treatment appropriateness. Natural language processing (NLP) methods present a novel approach to bridge this gap. In this study, the investigators sought to evaluate the efficacy of a novel and automated NLP pipeline to determine treatment appropriateness from a sample of prehospital EMS motor vehicle crash records.
AHRQ-funded; HS026379.
Citation: Tignanelli CJ, Silverman GM, Lindemann EA .
Natural language processing of prehospital emergency medical services trauma records allows for automated characterization of treatment appropriateness.
J Trauma Acute Care Surg 2020 May;88(5):607-14. doi: 10.1097/ta.0000000000002598.
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Keywords: Trauma, Injuries and Wounds, Electronic Health Records (EHRs), Health Information Technology (HIT), Quality Improvement, Quality of Care