Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-22T00:05:32.288Z Has data issue: false hasContentIssue false
  • English
  • Français

Development of a Scale to Identify the Fall-Prone Patient

Published online by Cambridge University Press:  29 November 2010

Janice M. Morse ,
Robert M. Morse  and
Suzanne J. Tylko
Janice M. Morse
Affiliation:
University of Alberta
Robert M. Morse
Affiliation:
University of Alberta
Suzanne J. Tylko
Affiliation:
University of Alberta
Get access Rights & Permissions [Opens in a new window]

Abstract

Patient falls are a serious problem, contributing to the morbidity and mortality of the elderly patient. This study reports on the development of the Morse Fall Scale. The scale consists of six scored items and discriminant analysis correctly classifies 80.5% of the patients. Validation of the scale by computer modeling was conducted. Data were randomly split and that analysis procedure repeated. Variables were obtained and weighted using half of these data, and these weights were tested on the remaining data. Similar results were obtained. Sensitivity of the scale was 78% and the positive predictive value, 10.3%. Conversely, specificity was 83% and the negative predictive value, 99.3%. Interrater reliability scores were r=.96. A prospective study in three clinical areas showed that the scale is sensitive to different patient conditions and to length of stay. Thus, the scale permits identification of the patient at risk of falling so that prevention strategies may be targeted to those individuals.

Résumé

Les chutes faites par les patients représentent un problème sérieux qui contribue à la morbidité et à la mortalité des patients âgés. L'étude actuelle rend compte de la mise au point du Morse Fall Scale. Cette échelle contient six items marqués et une analyse discriminate a répartit correctement 80,5% des patients. La justesse de cet outil a été prouvée au moyen d'un modèle calculé sur ordinateur. Les données ont été divisées au hasard et cette analyse a été répétée. Des variables ont été extraites et calculées en utilisant la moitié des données et ces valeurs ont ensuite été appliquées à l'autre moitié des données. Une forte ressemblance a alors été remarquée. La sensibilité de cette échelle s'est chiffrée à 78% et sa valeur prophétique positive à 10,3%. Le coefficient d'objectivité était de r = .96. Une enquête effeduée dans trois cliniques a démontré la sensibilité de l'échelle face aux différents états des patients et à la durée du séjour. Done il convient de conclure que l'échelle facilite l'identification des patients qui risquent de faire une chute, permettant ainsi aux responsables de formuler une stratégie de prévention conçue spécialement pour ces personnes.

Keywords

Patient fallsmeasurementpatient safety
Type
Articles
Information
Canadian Journal on Aging / La Revue canadienne du vieillissement , Volume 8 , Issue 4 , Winter/hiver 1989 , pp. 366 - 377
Copyright
Copyright © Canadian Association on Gerontology 1989

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Apgar, V. (1953). A proposal for a new method of evaluating the newborn infant. Current Perspectives in Anesthesia and Analgesia, 18, 260–267.Google Scholar
Arsenault, T.M. (1982). Slips and falls: Problem identification and resolution by the primary nurse. In Nursing Research: Advancing Clinical Practice for the 80's (pp. 386–396). Walnut Creek, CA: Symposia Medicus.Google Scholar
Dawes, R.M. (1979). The robust beauty of improper linear models in decision making. American Psychologist, 34, 571–582.CrossRefGoogle Scholar
Edelstein, R., & Merrill, R.A. Falls: A new solution for an old problem. Unpublished manuscript. St. Francis Memorial Hospital, San Francisco, 1983.Google Scholar
Fife, D.D., Solomon, P., & Stanton, M. (1984). A risk/falls program: Code orange for success. Nursing Management, 15, 50–53.Google ScholarPubMed
Innes, E.M., & Turnman, W.G. (1983). Evaluation of patient falls. Quality Review Bulletin, 9, 30–35.Google ScholarPubMed
Janken, J.K., Reynolds, B.A., & Swiech, K. (1986). Patient falls in the acute care setting: Identifying risk factors. Nursing Research, 35, 215–219.CrossRefGoogle ScholarPubMed
Kalchthaler, T., Bascon, R.A., & Quintos, V. (1978). Falls in the institutionalized elderly. Journal of American Geriatric Society, 16, 424–428.CrossRefGoogle Scholar
Lachenbruch, P.A. (1975). Discriminant analysis. London: Hafner Press.Google Scholar
Metropolitan Life Insurance Co. (1978). Statistical Bulletin, 59, 10–12.Google Scholar
Morris, E.V., & Isaacs, B. (1980). The prevention of falls in a geriatric hospital. Age Ageing, 9, 181–185.CrossRefGoogle Scholar
Morse, J.M. (1986). Computerized evaluation of a scale to identify the fall-prone patient. Canadian Journal of Public Health, 77, 21–25.Google ScholarPubMed
Morse, J.M., Black, C., Oberle, K., & Donahue, P. (1989). A prospective study to identify the fall-prone patient. Social Sciences & Medicine, 28, 81–86.CrossRefGoogle ScholarPubMed
Morse, J.M., Prowse, M., Morrow, N., & Federspeil, G. (1985). A retrospective analysis of patient falls. Canadian Journal of Public Health, 76, 116–118.Google ScholarPubMed
Morse, J.M., Tylko, S.J., & Dixon, H. (1987). Characteristics of the fall-prone patient. Gerontologist, 27, 516–522.CrossRefGoogle ScholarPubMed
Perry, B.C. (1982). Falls among the elderly: A review of methods and conclusions of epidemiologic studies. Journal of American Geriatric Society, 30, 367–372.CrossRefGoogle ScholarPubMed
Raz, T., & Baretich, M.F. (1987). Factors affecting the incidence of patient falls in hospitals. Medical Care, 25, 186–195.CrossRefGoogle ScholarPubMed
Tinetti, M.E., Williams, T.F., & Mayewski, R. (1986). Fall risk index for elderly patients based on number of chronic disabilities. American Journal of Medicine, 80, 429–434.CrossRefGoogle ScholarPubMed