KnE Life Sciences

ISSN: 2413-0877

The latest conference proceedings on life sciences, medicine and pharmacology.

Risk Factors for Cognitive Impairment after Ischemic Stroke

Published date: Dec 05 2018

Journal Title: KnE Life Sciences

Issue title: The 2nd International Conference on Hospital Administration (The 2nd ICHA)

Pages: 152–160

DOI: 10.18502/kls.v4i9.3567

Authors:
Abstract:

A fall can be defined as ’an event that results in a person coming to rest inadvertently on the ground or floor or other lower level (Matarese & Ivziku, 2016). Falls can be caused by many factors. Millions of patient falls in hospitals are recorded (Lynn et al., 2014). Patient falls impact either the patients or the hospitals. It is a challenge for healthcare organization to reduce negative impact of patient falls. This article aims to describe tools used by hospitals to prevent patient falls, by reviewing systematically the literatures found in ProQuest and SCOPUS database. This systematic review refers to the protocol of PRISMA. Literatures were gathered from ‘ProQuest’ and ‘SCOPUS’ electronic databases. Prevention of patient falls can, generally, be divided in two
main sections; while the first section is early detection, the second is interventions (Smith et al., 2016). The early detection of patient falls is further divided into two sections, fall-risk screening and fall-risk assessment (Matarese & Ivziku, 2016). Various screening tools have been developed to identify patients at risk of falls in
hospitals. The following falls risk-screening tools are frequently used: the St Thomas risk assessment tool in falling elderly inpatients (STRATIFY); the Conley scale; the Morse Fall scale; the Falls Risk Assessment Tool (FRAT); and the NPSA scale (Matarese & Ivziku, 2016). There are several paediatric screening tools, such as General Risk Assessment for Paediatric Inpatient Falls (Graf-PIF), CHAMPS, Cummings scale, Children’s National Medical Center (CNMC) scale, and the Humpty Dumpty Fall Scale (Murray et al., 2016). The NICE guideline recommends including the following factors in the hospital’s multifactorial falls risk-assessment tool: cognitive and visual impairment, continence problems, a history of falls, mobility problems, medications, balance and
postural problems, health problems, and syncope syndrome (Matarese & Ivziku, 2016). In addition to screening and assessment tools, there are many intervention tools used by hospitals to prevent patient falls, such as using remote video monitoring in hospitals for reducing falls (Votruba et al., 2016), using certain footwears, and
using fall-reduction projects, consider measuring effect on nursing staff time, staffing ratios on budget, or changes in patient mobility as a result of the initiative (Cumbler et al., 2013). Falls are unintended accidents to the patients in hospital that happen frequently. It is a challenge for healthcare organizations to reduce negative
impacts of patient falls. There are some tools used by hospitals to prevent patient falls.


Keywords: patient falls prevention, STRATIFY, Conley, Morse, FRAT, NPSA, Graf-PIF, CHAMPS, Cumming, CNMC, Humpty Dumpty, NICE

References:

[1] Matarese, M. (2015). Systematic review of fall risk screening tools for older patients in acute hospitals. Journal of Advanced Nursing, vol. 71, no. 6, pp. 1198–1209.


[2] Lynn, M. R., Jones, C. B., and Mandelkehr, L. (2014). Factors Contributing to Falls in Hospitalized Patients: Post-fall Aggregate Analysis.


[3] Votruba, L. (2016). Video monitoring to reduce falls and patient companion costs for adult inpatients - ProQuest. Nursing Economic$, vol. 34, no. 4, pp. 185–189.


[4] Smith, M. I. (2016). Predicting falls and when to intervene in older people: A multilevel logistical regression model and cost analysis, D. Zhu (ed.). PLoS One, vol. 11, no. 7.


[5] Murray, B., Vess, E., Edlund, J. (2016). Implementing a pediatric fall prevention policy and program - ProQuest. Pediatric Nursing, vol. 42, no. 5, pp. 256–259.


[6] Oliver, D. (1997). Development and evaluation of evidence based risk assessment tool (STRATIFY) to predict which elderly inpatients will fall: Case-control and cohort studies. BMJ, vol. 315, no. 7115, pp. 1049–1053.


[7] Morse, J. M., Tylko, S. J., and Dixon, H. A. (1987). Characteristics of the fall-prone patient. Gerontologist.


[8] Nandy, S. (2004). Development and preliminary examination of the predictive validity of the Falls Risk Assessment Tool (FRAT) for use in primary care. Journal of Public Health, vol. 26, no. 2, pp. 138–148.


[9] Chari, S. R. (2016). Point prevalence of suboptimal footwear features among ambulant older hospital patients: Implications for fall prevention. Australian Health Review, vol. 40, no. 4, p. 399.


[10] Cumbler, E. U. (2013). Inpatient falls: Defining the problem and identifying possible solutions. Part II: Application of quality improvement principles to hospital falls. The Neurohospitalist, vol. 3, no. 4, pp. 203–208.

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