Practice Problem
The issue here is a deliberate fall of patients within the behavioral health facilities. These falls, even though they may not be fatal, present tremendous challenges for the safety and quality of patient health and care. An analysis of 4,176 incident reports on patient falls shows that 79.0% of falls were unattended by nurses, while 8.7% happened during direct nursing care (Takase, 2022). This implies a real problem for patient safety in the units related to behavioral health. The literature shed light on the role of meeting emotional needs to prevent deliberate falls, which is an indication of the necessity of active strategies that target the psychological demands of patients. It is necessary to acknowledge deliberate falls as indicators of unresolved mental health issues and insufficient staff-patient interactions within healthcare departments.
The goal for dealing with this issue is that patients will have high quality and safe treatment in behavioral health hospitals. Intentional falls not only inhibit the healing process but also hint at underlying psychological issues that need to be addressed (Takase, 2022). Through the use of appropriate measures such as prevention and compassion, healthcare providers can reduce the incidence of falls in a way that produces better patient health and care.
Analysis of Existing Evidence
The research on the factual data regarding intentional patient falls in behavioral health hospitals gives us a view of the aspects that are the causes of the occurrence of this malpractice. Numerous studies and health guidelines recognize intentional falls as a pervasive problem and the culprit in their occurrence within healthcare settings.
A study conducted by Takase (2022) was on the provocation of incident reports about patient falls, and a great deal was found out about the nature of such deliberate falls. A review of 4,176 incident reports showed that, nurses did not witness the majority of falls (79.0%), and it indicates a possible lack of surveillance and monitoring in nursing units of behavioral health units. Furthermore, about 8.7% of falls were reported due to direct nursing care. This implies that there is a need for improved patient supervision and support during these vital times through proper observation (Takase, 2022). This research thus not only stresses the need for maintaining environmental standards and assessing the risks in staffing but also strongly emphasizes the role of environmental factors in preventing intentional falls among patients.
The results from Seeherunwong et al. (2022) also indicated other patient-related factors that leave psychiatric patients vulnerable to intentional falls. We identified the factors responsible for falls as acute psychotic conditions and polypharmacy (Seeherunwong et al., 2022). These results demonstrate the complexity surrounding the fall prevention of intentional falls that necessitate multifaceted approaches that recognize patients’ unique attributes along with the environmental risks within healthcare settings.
Staffing concerns and patient-related factors were singled out as the main culprits of fall rates. A number of other studies have established that, as the patient-to-staff ratio increases, the chances of falls also increase, and this argues further for adequate staffing levels to guarantee the safety of the patients (Boot et al., 2023). This study endorses the employment of implemented staffing optimization strategies, which could help prevent accidental falls and ensure effective patient monitoring and support.
Besides, according to Jia et al. (2020), an expert interviewing with nurses demonstrated flaws in the current processes that are utilized to measure calculated falls. Falls that usually occur as an incident have a data source, which is the primary incident report. It is, however, challenging to have comprehensive data since staff workload restricts the full flow of information (Jia et al., 2020). The discovery shows, however, the need for the development of different data collection methods, including those of hospitals and patients’ feedback, in an attempt to get a wider view of the most significant factors that play a role in intentional falls.
Extensively, in the article of review by LeLaurin & Shorr (2019), the multivariate interplay of patient falls in healthcare institutions, mainly behavioral health hospitals, was analyzed. This review covered the complexity of patient characteristics, environment and medical professional practice influencing intentional falls, which were the subject of multiple studies and guidelines (LeLaurin & Shorr, 2019). The article highlighted the value of addressing risk factors such as environmental hazards and insufficient supervision which might be attributed to intentional falls by patients. Additionally, the review underscored.
Therefore, the existing research shows how multifaceted the establishment of intentional patient falls in behavioral health hospitals. It demands a comprehensive approach that covers patient-specific risk factors, ecologic factors as well as staffing conditions of healthcare establishments. Healthcare providers can refer to and utilize the synthesized findings from the multiple research studies and the clinical guidelines in order to design the intended interventions for fall prevention to improve patient safety and wellbeing.
Quality Improvement Process
For the quality improvement process, the Plan-Do-Study-Act (PDSA) Cycle is considered a practical solution to address behavioral health hospitals about going with intentional patient falls. This reinforcing and cyclical approach provides organizations with a rational approach to test small-scale changes, evaluate their effectiveness, and correct interventions (Boot et al., 2023). Healthcare units can promote patients’ safety and wellbeing by applying the PDSA Cycle to their patient care strategies to prevent intentional falls and to learn and revise their approaches. Unlike traditional approaches, the cyclical nature of the PDSA Cycle gives room for continuous learning and adjusting. Thus this method guarantees only evidence-based and patient-centered interventions.
Inclining the PDSA Cycle, the Lean Six Sigma model is an integral framework that combines the principles of Lean manufacturing and Six Sigma methodologies (Barr & Brannan, 2024). Lean Six Sigma is targeted to lower waste, reduce variations, and improve process efficiency. Therefore, it can be used to solve complicated issues like intentional patient falls. Through Lean Six Sigma principles utilization, healthcare organizations are able to optimize the health flows isolate the causes of falls, and then use specific interventions to decrease risk factors and improve performance.
One of the quality improvement tools that will certainly be applied as the process unfolds is the Failure Mode and Effects Analysis (FMEA). FMEA helps healthcare teams to be ahead of the curve in identifying failure modes inherent in processes, to assess their maximum impact on patient safety and to prioritize the interventions to prevent adverse events (Boot et al., 2023). Through FMEA, healthcare organizations could forecast and manage vulnerabilities in care delivery procedures, which may contribute to intentionally induced patient falls. This will help reduce the risks and improve the quality of behavioral health care.
In conclusion, preventing intentional patient falls in behavioral healthcare institutions necessitates a multifaceted view that takes into account patient susceptibilities, environmental conditions, and staffing issues. Through using the PDSA Cycle Lean Six Sigma approaches and FMEA tool, healthcare organizations can, therefore, use system-based approaches to better patient safety and wellness. Through the use of precise interventions and bacteria-free environments, healthcare professionals will decrease the number of intentional patient’ falls. They will significantly improve the quality of care in behavioral health facilities.
References
Barr, E., & Brannan, G. D. (2024). Quality Improvement Methods (LEAN, PDSA, SIX SIGMA). PubMed; StatPearls Publishing. https://www.ncbi.nlm.nih.gov/books/NBK599556
Boot, M., Allison, J., Maguire, J., & O’Driscoll, G. (2023). QI initiative to reduce the number of inpatient falls in an acute hospital Trust. BMJ Open Quality, 12(1), e002102. https://doi.org/10.1136/bmjoq-2022-002102
Jia, Q., Guo, Y., Wang, G., & Barnes, S. J. (2020). Big Data Analytics in the Fight against Major Public Health Incidents (Including COVID-19): A Conceptual Framework. International Journal of Environmental Research and Public Health, 17(17), 6161. https://doi.org/10.3390/ijerph17176161
LeLaurin, J. H., & Shorr, R. I. (2019). Preventing falls in hospitalized patients. Clinics in Geriatric Medicine, 35(2), 273–283. https://doi.org/10.1016/j.cger.2019.01.007
Seeherunwong, A., Thunyadee, C., Vanishakije, W., & Thanabodee-tummajaree, P. (2022). Staffing and patient-related factors affecting inpatient fall in a psychiatric hospital: a 5-year retrospective matched case–control study. International Journal of Mental Health Systems, 16(1). https://doi.org/10.1186/s13033-022-00514-1
Takase, M. (2022). Falls as the result of the interplay between nurses, patient and the environment: Using text-mining to uncover how and why falls happen. International Journal of Nursing Sciences, 10(1). https://doi.org/10.1016/j.ijnss.2022.12.003
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