Reliability, sensitivity, and specificity of the morse fall scale: A hospitalized population in Iran

Document Type : Original Article


1 Department of Health in Emergencies and Disasters, Shahid Beheshti University of Medical Sciences, Tehran, Iran

2 Behavioral Sciences Research Center, Life Style Institute; Department of Nursing Management, Nursing Faculty, Baqiyatallah University of Medical Sciences, Tehran, Iran

3 Department of Ergonomics, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran

4 Department of Occupational Health and Safety, School of Public Health and Safety; Workplace Health Promotion Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran

5 Department of Health in Emergencies and Disasters, School of Public Health and Safety; Workplace Health Promotion Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran



Background and Objectives: One of the important indicators of patient safety and quality of hospital care is the patient's fall. Patient falls are among the most crucial issues in the field of Never Events that will affect the health-care systems, and it is necessary to be considered to improve the safety of hospitalized patients. The present study was conducted to investigate the reliability, sensitivity, and specificity of the Morse Fall Scale (MFS) in Iran. Methods: In this prospective observational study, the reliability of the MFS was investigated through the inter-rater reliability. The researcher as the first evaluator and an experienced nurse as the second evaluator screened 180 patients in two educational hospitals in Tehran, Iran, between March and May 2021, using the access method with a MFS. The percentage of agreement of the evaluators was assessed using the Cohen's kappa coefficient, and sensitivity and specificity were assessed using the receiver operating characteristic curve. Results: The results showed that the percentages of agreement between the two assessors in the patient fall history index, in the index of secondary diagnoses, in the index of assistive devices, in the index of IV therapy and heparin lock, in the index of gait/transferring, and in the index of mental status were 0.869, 0.916, 0.871, 1.00, 0.898, and 0.815, respectively. The MFS reliability was obtained by an interclass correlation coefficient of 0.825, sensitivity of 66.7, and specificity of 81.6. Conclusion: The reliability, sensitivity, and specificity of the Morse scale are relatively favorable. Therefore, it is suggested that a patient fall screening scale be designed to measure all dimensions related to the correct assessment of the patient in terms of clinical conditions and nonclinical factors related to patient fall.


Aranda-Gallardo M, Morales-Asencio JM, Canca-Sanchez JC, Barrero-Sojo S, Perez-Jimenez C, Morales-Fernandez A, et al. Instruments for assessing the risk of falls in acute hospitalized patients: A systematic review and meta-analysis. BMC Health Serv Res 2013;13:122.  Back to cited text no. 1
Sung YH, Cho MS, Kwon IG, Jung YY, Song MR, Kim K, et al. Evaluation of falls by inpatients in an acute care hospital in Korea using the Morse Fall Scale. Int J Nurs Pract 2014;20:510-7.  Back to cited text no. 2
Miake-Lye IM, Hempel S, Ganz DA, Shekelle PG. Inpatient fall prevention programs as a patient safety strategy: A systematic review. Ann Intern Med 2013;158:390-6.  Back to cited text no. 3
Morse JM. Preventing Patient Falls. New York: Springer Publishing Company; 2008.  Back to cited text no. 4
National Database of Nursing Quality Indicators. (2013). Retrieved from  Back to cited text no. 5
Oliver D, Connelly JB, Victor CR, Shaw FE, Whitehead A, Genc Y, et al. Strategies to prevent falls and fractures in hospitals and care homes and effect of cognitive impairment: Systematic review and meta-analyses. BMJ 2007;334:82.  Back to cited text no. 6
Oliver D, Healey F, Haines TP. Preventing falls and fall-related injuries in hospitals. Clin Geriatr Med 2010;26:645-92.  Back to cited text no. 7
Moppett IK, Moppett SH. Surgical caseload and the risk of surgical Never Events in England. Anaesthesia 2016;71:17-30.  Back to cited text no. 8
Tingle J. Never events in the NHS. Br J Nurs 2018;27:166-7.  Back to cited text no. 9
Currie LM. Fall and injury prevention. Annu Rev Nurs Res 2006;24:39-74.  Back to cited text no. 10
Petridou ET, Kyllekidis S, Jeffrey S, Chishti P, Dessypris N, Stone DH. Unintentional injury mortality in the European Union: How many more lives could be saved? Scand J Public Health 2007;35:278-87.  Back to cited text no. 11
Hitcho EB, Krauss MJ, Birge S, Claiborne Dunagan W, Fischer I, Johnson S, et al. Characteristics and circumstances of falls in a hospital setting: A prospective analysis. J Gen Intern Med 2004;19:732-9.  Back to cited text no. 12
Halfon P, Eggli Y, Van Melle G, Vagnair A. Risk of falls for hospitalized patients: A predictive model based on routinely available data. J Clin Epidemiol 2001;54:1258-66.  Back to cited text no. 13
Chen JS, Simpson JM, March LM, Cameron ID, Cumming RG, Lord SR, et al. Risk factors for fracture following a fall among older people in residential care facilities in Australia. J Am Geriatr Soc 2008;56:2020-6.  Back to cited text no. 14
Healey F, Scobie S. The Third Report from the Patient Safety Observatory. Slips, Trips and Falls in Hospital. London: National Patient Safety Agency; 2007.  Back to cited text no. 15
Nyberg L, Gustafson Y. Using the Downton index to predict those prone to falls in stroke rehabilitation. Stroke 1996;27:1821-4.  Back to cited text no. 16
Morse JM, Morse RM, Tylko SJ. Development of a scale to identify the fall-prone patient. Can J Aging 1989;8:366-77.  Back to cited text no. 17
Oliver D, Britton M, Seed P, Martin FC, Hopper AH. Development and evaluation of evidence based risk assessment tool (STRATIFY) to predict which elderly inpatients will fall: Case-control and cohort studies. BMJ 1997;315:1049-53.  Back to cited text no. 18
Tinetti ME, Williams TF, Mayewski R. Fall risk index for elderly patients based on number of chronic disabilities. Am J Med 1986;80:429-34.  Back to cited text no. 19
Conley D, Schultz AA, Selvin R. The challenge of predicting patients at risk for falling: Development of the Conley Scale. Medsurg Nurs 1999;8:348-54.  Back to cited text no. 20
Hendrich A, Nyhuis A, Kippenbrock T, Soja ME. Hospital falls: Development of a predictive model for clinical practice. Appl Nurs Res 1995;8:129-39.  Back to cited text no. 21
Hendrich AL, Bender PS, Nyhuis A. Validation of the Hendrich II Fall Risk Model: A large concurrent case/control study of hospitalized patients. Appl Nurs Res 2003;16:9-21.  Back to cited text no. 22
Close J, Ellis M, Hooper R, Glucksman E, Jackson S, Swift C. Prevention of falls in the elderly trial (PROFET): A randomised controlled trial. Lancet 1999;353:93-7.  Back to cited text no. 23
Haidarpour DR, Rafiei S, Sadat SM, Mostofian F. Familiarity with the Basics of Clinical Governance. Tehran: Ministry of Health and Medical Education; 2011. p. 112.  Back to cited text no. 24
Shali M, Joolaee S, Vaskooi K, Bahrani N. Assessing the patient falls in hospitals affiliated to Tehran university of medical sciences. Iran J Nurs 2016;29:1-12.  Back to cited text no. 25
Ebadi A, Sharifnia SH, Zareiyan A. Instrument Development in Health Sciences. Tehran: Jameh Negar; 2019.  Back to cited text no. 26
Nassar N, Helou N, Madi C. Predicting falls using two instruments (the Hendrich Fall Risk Model and the Morse Fall Scale) in an acute care setting in Lebanon. J Clin Nurs 2014;23:1620-9.  Back to cited text no. 27
Chow SK, Lai CK, Wong TK, Suen LK, Kong SK, Chan CK, et al. Evaluation of the Morse Fall Scale: Applicability in Chinese hospital populations. Int J Nurs Stud 2007;44:556-65.  Back to cited text no. 28
de Urbanetto JS, Creutzberg M, Franz F, Ojeda BS, da Gustavo AS, Bittencourt HR, et al. Morse Fall Scale: Translation and transcultural adaptation for the Portuguese language. Rev Esc Enferm USP 2013;47:569-75.  Back to cited text no. 29
Munro BH. Statistical Methods for Health Care Research. USA. England.Argentina.Hong Kong.Australia.japan: Lippincott Williams & Wilkins; 2005.  Back to cited text no. 30
Bouldin EL, Andresen EM, Dunton NE, Simon M, Waters TM, Liu M, et al. Falls among adult patients hospitalized in the United States: Prevalence and trends. J Patient Saf 2013;9:13-7.  Back to cited text no. 31
Ghanbary A, Salehi Dehno N, Moslemi Haghighi F, Torabi M. The prevalence and correlates of falling down in the older adults over 55 years in Shiraz. Iran J Ageing 2013;8:64-70.  Back to cited text no. 32
McClish DK. Analyzing a portion of the ROC curve. Med Decis Making 1989;9:190-5.  Back to cited text no. 33
Safari S, Baratloo A Elfil M, Negida A. Evidence based emergency medicine; Part 5: Receiver operating characteristic curve and area under the curve. Emerg (Tehran) 2016;4:111-3.  Back to cited text no. 34
Kumar R, Indrayan A. Receiver operating characteristic (ROC) curve for medical researchers. Indian Pediatr 2011;48:277-87.  Back to cited text no. 35
Urbanetto JS, Pasa TS, Bittencout HR, Franz F, Rosa VP, Magnago TS. Analysis of risk prediction capability and validity of Morse Fall Scale Brazilian version. Rev Gaucha Enferm 2017;37:e62200.  Back to cited text no. 36
Bóriková I, Tomagová M, Miertová M, Žiaková K. Predictive value of the morse fall scale. Cent Eur J Nurs Midwifery 2017;8:588-95.  Back to cited text no. 37
Watson BJ, Salmoni AW, Zecevic AA. The use of the Morse Fall Scale in an acute care hospital. Clin Nurs Stud 2016;4:32.  Back to cited text no. 38
Kim EA, Mordiffi SZ, Bee WH, Devi K, Evans D. Evaluation of three fall-risk assessment tools in an acute care setting. J Adv Nurs 2007;60:427-35.  Back to cited text no. 39