A Managerial Approach to Investigate Fall Risk in a Rehabilitation Hospital
Source abstract
Abstract
Among the issues on which health directions focus, fall risk is one of major importance since it affects patients hospitalized in both acute and rehabilitative hospitals. In this context, few publications have proposed a managerial approach aimed at (a) investigating several factors related to falls and (b) trying to acquire more knowledge and comprehension when analyzing the data collected. Consequently, this paper pursues such objectives by investigating data related to falls (and the recurrence of falls) registered in a rehabilitation hospital within the years 2020 and 2021. A multidisciplinary team (clinical staff and engineers) registered 238 first falls, and descriptive statistics were used to analyze the fall-related anamnestic and clinical data. Then, appropriate statistical analyses were used to compare the same data—this time distinguishing fallers/recurrent fallers—and, again, descriptive statistics were used to analyze the consequences of falls. The statistical analyses allowed us to gain insights into the fall mechanisms, the main places in which falls took place, the impacts of drugs, and fall consequences (e.g., the potential extra costs for the hospital). Moreover, the Morse and Stratify risk tools, state of consciousness, and fall containment measures were proven to be statistically significant features for distinguishing fallers and recurrent fallers, and they may be further investigated to define more accurate preventive measures within rehabilitation hospitals.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Balance, Gait, and Falls Prevention · Context-Aware Activity Recognition Systems · Stroke Rehabilitation and Recovery
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy
Istituti Clinici Scientifici Maugeri IRCCS, Via Generale Bellomo 73/75, 70124 Bari, Italy
Istituti Clinici Scientifici Maugeri, Piazza della Chiesa 4, 74025 Marina di Ginosa, Italy
Department of Engineering, University of Sannio, Piazza Roma 21, 82100 Benevento, Italy
References (59)
Show source-provided references
1. World Health Organization (2007). WHO Global Report on Falls Prevention in Older Age.
2. Preventing Falls and Fall-Related Injuries in Hospitals10.1016/j.cger.2010.06.005 ↗
3. Health Care Utilization and Costs in a Medicare Population by Fall Status10.1097/00005650-199808000-00006 ↗
4. Development and evaluation of evidence based risk assessment tool (STRATIFY) to predict which elderly inpatients will fall: Case-control and cohort studies10.1136/bmj.315.7115.1049 ↗
5. Report on the Japanese Orthopaedic Association’s 3-year project observing hip fractures at fixed-point hospitals10.1007/s00776-005-0998-1 ↗
6. Falls risk prediction tools for hospital inpatients: Do they work?
7. Falls in English and Welsh hospitals: A national observational study based on retrospective analysis of 12 months of patient safety incident reports10.1136/qshc.2007.024695 ↗
8. Fall Risk Assessment Scales: A Systematic Literature Review10.3390/nursrep11020041 ↗
9. Development of a Scale to Identify the Fall-Prone Patient10.1017/S0714980800008576 ↗
10. Fall Risk Assessment Tools–Validity Considerations and a Recommended Approach10.4081/itjm.2019.1196 ↗
11. Fanti, M.P., and Ukovich, W. (2014, January 16–19). Discrete Event Systems Models and Methods for Different Problems in Healthcare Management. Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA), Barcelona, Spain.10.1109/ETFA.2014.7005031 ↗
12. Discrete-Event Simulation in Healthcare Settings: A Review10.3390/modelling3040027 ↗
13. Vázquez-Serrano, J.I., Peimbert-García, R.E., and Cárdenas-Barrón, L.E. (2021). Discrete-Event Simulation Modeling in Healthcare: A Comprehensive Review. Int. J. Environ. Res. Public Health, 18.10.3390/ijerph182212262 ↗
14. Ponsiglione, A.M., Romano, M., and Amato, F. (2021, January 6–9). A Finite-State Machine Approach to Study Patients Dropout from Medical Examinations. Proceedings of the IEEE 6th International Forum on Research and Technology for Society and Industry (RTSI), Naples, Italy.10.1109/RTSI50628.2021.9597264 ↗
15. Ricciardi, C., Cesarelli, G., Ponsiglione, A.M., Tommasi, G.D., Cesarelli, M., Romano, M., Improta, G., and Amato, F. (2022, January 26–28). Combining simulation and machine learning for the management of healthcare systems. Proceedings of the IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE), Rome, Italy.10.1109/MetroXRAINE54828.2022.9967526 ↗
16. A Framework for Developing Generalisable Discrete Event Simulation Models of Hospital Emergency Departments10.1016/j.ejor.2021.12.033 ↗
17. Franck, T., Augusto, V., Xie, X., Gonthier, R., and Achour, E. (2015, January 6–9). Performance Evaluation of an Integrated Care for Geriatric Departments Using Discrete-Event Simulation. Proceedings of the Winter Simulation Conference (WSC), Huntington Beach, CA, USA.10.1109/WSC.2015.7408257 ↗
18. Decision Support for Resource Optimization Using Discrete Event Simulation in Rehabilitation Hospitals
19. Optimal Planning of Health Services through Genetic Algorithm and Discrete Event Simulation: A Proposed Model and Its Application to Stroke Rehabilitation Care10.1177/23814683221134098 ↗
20. Improta, G., Donisi, L., Bossone, E., Vallefuoco, E., Ponsiglione, A.M., and Amato, F. (2022, January 17–18). Discrete Event Simulation to Improve Clinical Consultations in a Rehabilitation Cardiology Unit. Proceedings of the E-Health and Bioengineering Conference (EHB), Iasi, Romania.10.1109/EHB55594.2022.9991285 ↗
21. Discrete Event Simulation-Based Resource Modelling in Health Technology Assessment10.1007/s40273-017-0533-1 ↗
22. Evaluation of a New Endobronchial Double Lumen Tube with Integrated Camera: A Hospital Based HTA Experience
23. A Review on Existing Health Technology Assessment (HTA) Methodologies
24. Yock, P.G., Zenios, S., Makower, J., Brinton, T.J., Kumar, U.N., Watkins, F.T.J., Denend, L., Krummel, T.M., and Kurihara, C.Q. (2015). Biodesign: The Process of Innovating Medical Technologies, Cambridge University Press. [2nd ed.].10.1017/CBO9781316095843 ↗
25. Needs-Based Innovation in Cardiovascular Medicine: The Stanford Biodesign Process10.1016/j.jacbts.2016.06.011 ↗
26. Innovation in Hemodialysis: Using the Biodesign Process to Identify Unmet Needs
27. Stanford’s Biodesign Innovation Program: Teaching Opportunities for Value-Driven Innovation in Surgery10.1016/j.surg.2019.10.012 ↗
28. Examining Fall Risk Assessment in Geriatric Rehabilitation Settings Using Translational Research10.1097/rnj.0000000000000259 ↗
29. Lean Six Sigma in Healthcare10.1111/j.1945-1474.2006.tb00596.x ↗
30. Lean Six Sigma in a Hospital10.1504/IJSSCA.2006.011566 ↗
31. McDermott, O., Antony, J., Bhat, S., Jayaraman, R., Rosa, A., Marolla, G., and Parida, R. (2022). Lean Six Sigma in Healthcare: A Systematic Literature Review on Motivations and Benefits. Processes, 10.10.3390/pr10101910 ↗
32. Lean Six Sigma in the Healthcare Sector: A Systematic Literature Review10.1016/j.matpr.2021.05.534 ↗
33. Integrating DMAIC Approach of Lean Six Sigma and Theory of Constraints toward Quality Improvement in Healthcare10.1515/reveh-2019-0003 ↗
34. Define, Measure, Analyze, Improve, Control (DMAIC) Methodology as a Roadmap in Quality Improvement10.36401/JQSH-22-X2 ↗
35. Tetteh, E.G., and Uzochukwu, B.M. (2015). Lean Six Sigma Approaches in Manufacturing, Services, and Production, IGI Global. [1st ed.].10.4018/978-1-4666-7320-5 ↗
36. A Health Technology Assessment between Two Pharmacological Therapies through Six Sigma: The Case Study of Bone Cancer10.1108/TQM-01-2020-0013 ↗
37. DMAIC Approach for the Reduction of Healthcare-Associated Infections in the Neonatal Intensive Care Unit of the University Hospital of Naples ‘Federico II’
38. Application of DMAIC Cycle and Modeling as Tools for Health Technology Assessment in a University Hospital10.1155/2021/8826048 ↗
39. Health Technology Assessment through Six Sigma Methodology to Assess Cemented and Uncemented Protheses in Total Hip Arthroplasty
40. Ricciardi, C., Gubitosi, A., Vecchione, D., Cesarelli, G., De Nola, F., Ruggiero, R., Docimo, L., and Improta, G. (2022). Comparing Two Approaches for Thyroidectomy: A Health Technology Assessment through DMAIC Cycle. Healthcare, 10.10.3390/healthcare10010124 ↗
41. DMAIC in Improving Patient Care Processes: Challenges and Facilitators in Context of Healthcare10.1016/j.ifacol.2022.09.628 ↗
42. Cesarelli, G., Petrelli, R., Ricciardi, C., D’Addio, G., Monce, O., Ruccia, M., and Cesarelli, M. (2021). Reducing the Healthcare-Associated Infections in a Rehabilitation Hospital under the Guidance of Lean Six Sigma and DMAIC. Healthcare, 9.10.3390/healthcare9121667 ↗
43. Reducing patients’ falls rate in an Academic Medical Center (AMC) using Six Sigma “DMAIC” approach10.1108/IJHCQA-03-2016-0030 ↗
44. 20 Lean six-sigma significantly reduces hospital patient falls by 40% & falls with injury by 72%
45. Correlation between fall risk increasing drugs (FRIDs) and fall events at a rehabilitation hospital
46. An analysis of fall incidence rate and risk factors in an inpatient rehabilitation unit: A retrospective study10.1080/10749357.2020.1774723 ↗
47. Predictive validity of the Hendrich fall risk model II in an acute geriatric unit10.1016/j.ijnurstu.2010.09.002 ↗
48. Casa Colina Fall Risk Assessment Scale—Revised: Predicting Falls in Inpatient Rehabilitation Facilities
49. Valutazione di due strumenti di misura del rischio di cadute dei pazienti
50. Predicting falls using two instruments (the Hendrich Fall Risk Model and the Morse Fall Scale) in an acute care setting in Lebanon10.1111/jocn.12278 ↗
51. Evaluation of three fall-risk assessment tools in an acute care setting10.1111/j.1365-2648.2007.04419.x ↗
52. Castellini, G., Demarchi, A., Lanzoni, M., and Castaldi, S. (2007). Fall prevention: Is the STRATIFY tool the right instrument in Italian Hospital inpatient? A retrospective observational study. BMC Health Serv. Res., 17.10.1186/s12913-017-2583-7 ↗
53. (2023, March 18). La Prevenzione Delle Cadute in Ospedale. Available online: https://www.regione.toscana.it/documents/10180/603668/La+prevenzione+delle+cadute+in+ospedale.pdf/96a548bc-23e5-4eea-b7ea-665f30bfb2fe.
54. Understanding the Relationship between Walking Aids and Falls in Older Adults10.1519/JPT.0000000000000031 ↗
55. Risk factors for geriatric patient falls in rehabilitation hospital settings: A systematic review10.1177/0269215511400639 ↗
56. Falls prevention: Identification of predictive fall risk factors10.1016/j.apnr.2015.05.007 ↗
57. Patterns and Predictors of Inpatient Falls and Fall-Related Injuries in a Large Academic Hospital10.1086/502500 ↗
58. Characteristics of Falls and Recurrent Falls in Residents of an Aging in Place Community: A Case-Control Study10.1016/j.apnr.2019.151190 ↗
59. Characteristics and Circumstances of Falls in a Hospital Setting10.1111/j.1525-1497.2004.30387.x ↗