Falls occur frequently and repeatedly among nursing home residents and account for 20% of total deaths from falls in the age group of 65 and older. Although auto-alert systems have been developed to detect and report falls of the elderly in the community, fewer have been developed for the nursing home setting due to the unique challenges in this setting. This paper analyzes the human-factors challenges in fall prevention in nursing homes through interviews, observations, and work analysis. Implications and guidelines for developing fall prevention technologies for nursing homes are discussed. A fall-prediction and notification system is proposed.
Get full access to this article
View all access options for this article.
References
1.
Centers for Disease Control and Prevention, National Center for Injury Prevention and Control. Web–based Injury Statistics Query and Reporting System (WISQARS)
2.
AmbroseA. F.PaulG.HausdorffJ. M. (2013). Risk factors for falls among older adults: A review of the literature. Maturitas, 75(1), 51-61.
3.
JinZ.LiB.AliH.LiH. (in preparation). Developing a Fall Prediction System Using EMG and Gyroscope for Nursing Home Residents.
4.
KerrK. M.WhiteJ. A.BarrD. A.MollanR. A. B. (1997). Analysis of the sit-stand-sit movement cycle in normal subjects. Clinical Biomechanics, 12(4), 236-245.
5.
KellyK. E.PhillipsC. L.CainK. C.PolissarN. L.KellyP. B. (2002). Evaluation of a nonintrusive monitor to reduce falls in nursing home patients. Journal of the American Medical Directors Association, 3(6), 377-382.
6.
KosseN. M.BrandsK.BauerJ. M.HortobagyiT.LamothC. J. C. (2013). Sensor technologies aiming at fall prevention in institutionalized old adults: A synthesis of current knowledge. International Journal of Medical Informatics, 82(9), 743-752.
7.
LiH.AliH. B. (2015). Human Factors Considerations in the Design of Falls Prevention Technologies for Nursing Homes: A Case Study. In Proceedings of the 2015 International Symposiumm on Human Factors and Ergonomics in Health Care. Santa Monica, CA: Human Factors and Ergonomics Society.
8.
NajafiB.AminianK.LoewF.BlancY.RobertP. A. (2002). Measurement of stand-sit and sit-stand transitions using a miniature gyroscope and its application in fall risk evaluation in the elderly. IEEE Transactions on Biomedical Engineering, 49(8), 843-851.
9.
PingY.XiaohuaW. (2012). Risk factors for accidental falls in the elderly and intervention strategy. Journal of Medical Colleges of PLA, 27(5), 299-305.
10.
RubensteinL. Z.JosephsonK. R.RobbinsA. S. (1994). Falls in the nursing home. Annals of Internal Medicine, 121(6), 442.
11.
TinettiM. E.GordonC.SogolowE.LapinP.BradleyE. H. (2006). Fall-risk evaluation and management: Challenges in adopting geriatric care practices. Gerontologist, 46(6), 717-725.
12.
RubensteinL. Z.RobbinsA. S.SchulmanB.L.RosadoJ.OsterweilD.JosephsonK. R. (1988). Falls and instability in the elderly. Journal of the American Geriatric Society, 36, 266-278.
13.
SterkeC. S.van BeeckE. F.LoomanC. W. N.KressigR. W.van der CammenT. J. M. (2012). An electronic walkway can predict short-term fall risk in nursing home residents with dementia. Gait & Posture, 36(1), 95-101.
14.
TideiksaarR.FeinerC. F.MabyJ. (1993). Falls prevention: the efficacy of a bed alarm system in an acute-care setting. The Mount Sinai Journal of Medicine, 60(6), 522-527.
15.
ZimmermanD.AntonovaE. (2006). Human Factors and Ergonomics in Nursing Homecare. In Handbook of Human Factors and Ergonomics in Healthcare and Patient Safety, 899-920.
