The Morse scale is not enough to prevent falls when applied in solitary. Although the tool has proven some degree of effectiveness in preventing falling of hospitalized patients, it needs a supplementary tool for more efficiency. A tool that can be used to supplement the Morse scale is Stratify. The use of a supplemented Morse scale has a high likelihood of decreasing the high fall rates. Instead of using the fall screening tool solely for prediction purposes, measures should be put in place to ensure that the fall screening tools are used for additional assessment as well as proactive fall prevention. When the tools are used this way, it is possible to conduct the screening immediately after admission and then come up with the initial plans for preventing falls. Once the potential risks are identified, the supplementary tools can be used to mitigate each of the identified risk. The nursing assessment can be used to refine the plan continuously when the patient is still in the hospital. The ideal time for implementing the plan should be immediately after the admission of the patient. Addressing all the possible risk factors requires a comprehensive risk assessment tool.
Implementing the supplemented Morse scale and stratify should be preceded by screening the risk of falling. The identified risk factors should be addressed by developing a personalized plan. The best way to come up with the plan is bringing both the family and the patient on board. In most cases, a mistake is made by advocating for interventions based on the patient’s risk of fall. The based way to implement the intervention is tailoring the intervention on the basis of patient-specific risk factors such as cognitive impairment and gait disturbance. According to Harrington et al. (2010), when the fixed-effects model is used, Stratify exhibits more specificity compared to the Morse scale. However, the specificity of Stratify reduces upon the use of the random-effects model. Considering the fixed-effects model, the Morse scale exhibits a higher Youden index compared to Stratify. The use of the random-effects model, however, does not show any significant difference between the two tools. In this case, none of the two tools is absolute effective when used in solitary. A supplementary implementation of the two tools ensures combined elements that, in turn, enhance the success in reducing the cases of falls in hospitalized patients.
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Regular implementation of a good fall prevention strategy requires communicating the risk factors of the patient as well as the intended plan to the family, patient, and the health care team. The direct care team members, such as patient care assistants and nurses should be recruited to reinforce the supplementary plan implementation. Many types of research have been carried out to compare the sensitivity as well as specificity of both Stratify and Morse Fall Scale. Although both tools have been validated with high degree accuracy, their accuracy is compromised when used or tested outside the original validation setting (Castellini, Demarchi, Lanzoni & Castaldi, 2017). In this case, fall-risk assessment tools cannot be used outside of their validation settings. Patient falls result from the interaction of different fall risk factors. In the same regard, addressing the problem would require multidisciplinary tools. Stratify and Morse Fall scale are the two tools that have been developed based on a rigorous design. The two tools have also been validated in different clinical settings. In this regard, the best way to reduce or do away with patient falls is by implementing the two tools jointly.
References
Castellini, G., Demarchi, A., Lanzoni, M., & Castaldi, S. (2017). Fall prevention: is the STRATIFY tool the right instrument in Italian Hospital inpatient? A retrospective observational study. BMC Health Services Research , 17 (1). doi: 10.1186/s12913-017- 2583-7
Harrington, L., Luquire, R., Vish, N., Winter, M., Wilder, C., Houser, B., Pitcher, E., Qin, H. (2010). Meta-analysis of fall risk assessment tools in hospitalized adults. The Journal of Nursing Administration, 40 (11), 483-488. doi: 10.1097/NNA.0b013e3181f88fbd
