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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 3 of 3 Research Studies DisplayedPatterson BW, Jacobsohn GC, Shah MN
Development and validation of a pragmatic natural language processing approach to identifying falls in older adults in the emergency department.
This study examined development and validation of a pragmatic natural language processing (NLP) approach to identify fall risk in older adults after emergency department (ED) visits. A single center retrospective review using data from 500 emergency department provider notes on older adults age 65 and older were random selected for analysis. The NLP algorithm successfully identified falls in ED notes with over 90% precision, and looks promising to reduce labor-intensive manual abstraction.
AHRQ-funded; HS024558.
Citation: Patterson BW, Jacobsohn GC, Shah MN .
Development and validation of a pragmatic natural language processing approach to identifying falls in older adults in the emergency department.
BMC Med Inform Decis Mak 2019 Jul 22;19(1):138. doi: 10.1186/s12911-019-0843-7..
Keywords: Adverse Events, Elderly, Emergency Department, Falls, Risk, Patient Safety
Patterson BW, Engstrom CJ, Sah V
Training and interpreting machine learning algorithms to evaluate fall risk after emergency department visits.
This study examined the potential of using machine learning algorithms to evaluate fall risk after an emergency department (ED) visit. They compared several machine learning methodologies for creation of a risk stratification algorithm to predict the outcome of a return visit for a fall within 6 months of an ED visit.
AHRQ-funded; HS024558; HS024342.
Citation: Patterson BW, Engstrom CJ, Sah V .
Training and interpreting machine learning algorithms to evaluate fall risk after emergency department visits.
Med Care 2019 Jul;57(7):560-66. doi: 10.1097/mlr.0000000000001140..
Keywords: Adverse Events, Elderly, Emergency Department, Falls, Risk, Patient Safety
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