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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 DisplayedVenema DM, Skinner AM, Nailon R
Patient and system factors associated with unassisted and injurious falls in hospitals: an observational study.
Unassisted falls are more likely to result in injury than assisted falls. However, little is known about risk factors for falling unassisted. Furthermore, rural hospitals, which care for a high proportion of older adults, are underrepresented in research on hospital falls. This study identified risk factors for unassisted and injurious falls in rural hospitals.
AHRQ-funded; HS021429.
Citation: Venema DM, Skinner AM, Nailon R .
Patient and system factors associated with unassisted and injurious falls in hospitals: an observational study.
BMC Geriatr 2019 Dec 11;19(1):348. doi: 10.1186/s12877-019-1368-8..
Keywords: Falls, Injuries and Wounds, Patient Safety, Elderly, Risk, Hospitals, Adverse Events
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.
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
Aspinall SL, Springer SP, Zhao X
Central nervous system medication burden and risk of recurrent serious falls and hip fractures in Veterans Affairs nursing home residents.
This study investigated the association between taking central nervous system (CNS) medications with the risk of serious falls and hip fractures. Study participants were residents at a Veterans Health Administration (VHA) Community Living Center (CLC) between July 1, 2005 and June 30, 2009. This was a nested case-control study. The investigators concluded that there was a higher risk in those residents receiving 3.0 or more daily CNS medications.
AHRQ-funded; HS023779.
Citation: Aspinall SL, Springer SP, Zhao X .
Central nervous system medication burden and risk of recurrent serious falls and hip fractures in Veterans Affairs nursing home residents.
J Am Geriatr Soc 2019 Jan;67(1):74-80. doi: 10.1111/jgs.15603..
Keywords: Elderly, Falls, Injuries and Wounds, Long-Term Care, Medication, Nursing Homes, Patient Safety, Risk
Waters TM, Chandler AM, Mion LC
Use of International Classification of Diseases, Ninth Revision, Clinical Modification, codes to identify inpatient fall-related injuries.
The researchers compared falls and fall-related injuries that a fall evaluator or hospital incident report identified with injuries identified according to discharge ICD-9-CM codes for the same set of inpatient episodes of care. They found that the CMS-targeted ICD-9-CM codes used to identify fall-related injuries in claims data do not always detect the most-serious falls.
AHRQ-funded; HS020627.
Citation: Waters TM, Chandler AM, Mion LC .
Use of International Classification of Diseases, Ninth Revision, Clinical Modification, codes to identify inpatient fall-related injuries.
J Am Geriatr Soc 2013 Dec;61(12):2186-91. doi: 10.1111/jgs.12539..
Keywords: Falls, Elderly, Patient Safety, Inpatient Care, Adverse Events