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Fall Risk Among Older Adults : = Major Risk Factors, Primary Assessment Tools, and the Influence of Medications.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Fall Risk Among Older Adults :/
其他題名:
Major Risk Factors, Primary Assessment Tools, and the Influence of Medications.
作者:
Jensen, Marie Roseann.
面頁冊數:
1 online resource (61 pages)
附註:
Source: Masters Abstracts International, Volume: 84-11.
Contained By:
Masters Abstracts International84-11.
標題:
Health sciences. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30426148click for full text (PQDT)
ISBN:
9798379501679
Fall Risk Among Older Adults : = Major Risk Factors, Primary Assessment Tools, and the Influence of Medications.
Jensen, Marie Roseann.
Fall Risk Among Older Adults :
Major Risk Factors, Primary Assessment Tools, and the Influence of Medications. - 1 online resource (61 pages)
Source: Masters Abstracts International, Volume: 84-11.
Thesis (M.A.)--University of the Pacific, 2023.
Includes bibliographical references
Fall risk among older adult is a worldwide public health problem. As the older adult population is continuing to increase, addressing this issue is critical. Several fall risk assessment tools have been designed to help predict various risk factors. Among these assessment tools is the Hendrich II Fall Risk Model (HIIFRM). This tool uses evidence-based risk factors including mental status, sex, functional status, and whether the patient is taking antileptics and/or benzodiazepines. The purpose of this paper is to validate the HFRM, explore additional variables that increase the likelihood of falling including both past falls and the number of prescription medications a patient is taking. Our findings validate the HFRM; with each additional point on the HFRM score, holding all other explanatory variables constant, the odds of having multiple previous fall-related admissions increased by 38.3% (P < 0.001). The strongest predictor of future falls was previous falls. With confounders held constant, each additional previous fall predicted a 3.9-fold increase in the odds of experiencing a future fall (p < 0.001; 95% CI of OR: 3.131 to 4.961). When looking at prescription medications, for each additional increase in prescription medications, we observe a 11.8% increase in the number of falls experienced during the tracking period (p<0.001; 95% CI of IRR: 1.084 to 1.170). Although a validated tool, our research indicates additional variables that could enhance its effectiveness.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023
Mode of access: World Wide Web
ISBN: 9798379501679Subjects--Topical Terms:
3168359
Health sciences.
Subjects--Index Terms:
Fall riskIndex Terms--Genre/Form:
542853
Electronic books.
Fall Risk Among Older Adults : = Major Risk Factors, Primary Assessment Tools, and the Influence of Medications.
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Fall risk among older adult is a worldwide public health problem. As the older adult population is continuing to increase, addressing this issue is critical. Several fall risk assessment tools have been designed to help predict various risk factors. Among these assessment tools is the Hendrich II Fall Risk Model (HIIFRM). This tool uses evidence-based risk factors including mental status, sex, functional status, and whether the patient is taking antileptics and/or benzodiazepines. The purpose of this paper is to validate the HFRM, explore additional variables that increase the likelihood of falling including both past falls and the number of prescription medications a patient is taking. Our findings validate the HFRM; with each additional point on the HFRM score, holding all other explanatory variables constant, the odds of having multiple previous fall-related admissions increased by 38.3% (P < 0.001). The strongest predictor of future falls was previous falls. With confounders held constant, each additional previous fall predicted a 3.9-fold increase in the odds of experiencing a future fall (p < 0.001; 95% CI of OR: 3.131 to 4.961). When looking at prescription medications, for each additional increase in prescription medications, we observe a 11.8% increase in the number of falls experienced during the tracking period (p<0.001; 95% CI of IRR: 1.084 to 1.170). Although a validated tool, our research indicates additional variables that could enhance its effectiveness.
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