NURS FPX 6016 Assessment 2 Quality Improvement Initiative Evaluation

Quality Improvement Initiative Evaluation 

After Mr. John’s fall, Springer General Hospital made him do a QI exercise. Case falls are a major safety issue in hospitals. Reports say that falls are one of the most common causes of injury, longer stays in the hospital, and higher death rates. Feng et al. (2022) say that hospitals see about 134 million adverse events every year, which cause 2.6 million deaths, many of which could have been avoided.

Springfield General Hospital employs easy-to-use, evidence-based fall prevention protocols to reduce the number of falls. These include regular threat assessments for cascade, staff training, communication between different departments, and the use of technology like bed alarms and Electronic Health Records (EHR) alerts for patients who are at risk. Mr. John was involved in the incident. He said he felt dizzy, but he wasn’t checked again for his fall risk.

The evaluation for NURS FPX 6016 Assessment 2 focuses on quality improvement initiatives. 

He tried to walk without help after waiting too long for someone to answer his call light. This led to a fall that could have been avoided with better communication, stricter adherence to fall prevention protocols, and quicker actions. The QI program at Springfield General will use tools that have been proven to work, like the Morse Fall Scale, to figure out how many falls there will be and make them less likely to happen. Still, staff members will have to admit that nurses and physical therapists need to keep getting training to stop cascade, and technology—like bed warnings and alerts from real-time EHR—will be used to help spot cases that are at risk of cascade early on.

One of the program’s main points is that staff alarm fatigue can lower the effectiveness of these technologies. Also, the sanitarium could not clearly see how these measures affected all areas because some units were not using the new tools that were put in place to reduce falls. These gaps in perpetration and prostrating resistance to reporting adverse events out of fear of losing their jobs will determine how well this action works. With these changes, the QI action at Springfield General Hospital will greatly reduce the number of fall-related incidents, improve patient safety, and create a better environment for care for both patients and healthcare workers.

Evaluation of the Success of the Quality Improvement Initiative 

The QI action was evaluated using public metrics and outcome measures, such as a fall rate of 3.44 falls per 1,000 case bed days, which is a standard benchmark for fall prevention performance (Venema et al., 2019). By comparing its fall rate to this standard, Springfield General can see how well its fall-prevention protocols work. Other interventions include using the Morse Fall Scale to figure out how likely a patient is to fall, training staff and making sure they obey the rules, and using technology like bed warnings and Electronic Health Record (EHR) warnings.

These help keep track of progress and ensure that safety rules are followed. The more harmonious use of the Morse Fall Scale, the thorough training of staff, and the successful integration of technology are all examples of this action that have worked well. These factors have made it easier to determine threat factors, which has led to faster response times and a drop in the number of falls to 2.9 per 1,000 case bed days. There are a few hypotheticals that support the success evaluation: falls are reported directly, with the labor force feeling safe to do so; fall-forestallment protocols, including the Morse Fall Scale, are slightly applied across all units; the technology in place (bed admonitions, EHR cautions) is functional and has been integrated into workflows effectively; and the staff entered acceptable training and are following protocols. To find out how the QI action affected the drop in fall-related incidents and how it supports Springfield General’s core values, like safety, case-centered care, and constant improvement, we need to think of similar situations.

Interprofessional Participants & Actions 

An interprofessional team helped improve quality improvement (QI) projects at Springfield General Hospital, which helped stop cascades. Nurses, physical therapists, and doctors all had important roles to play in the hallway, each bringing their own unique perspective to the job. Nurses played a key role in finding patients who were at risk and putting in place fall-prevention measures, such as using the Morse Fall Scale (Baumann et al., 2022) to do regular fall-risk assessments.

Physical therapists also helped by using specialized treatments to improve mobility and strength in the cases, which probably helps prevent falls. Doctors were able to provide information about drugs and health problems that could make the cases more likely to fall than others. The input and feedback from these healthcare professionals were essential for regular meetings and discussions about how technologies like bed admonitions and EHR cautions work. Their combined efforts improved communication, made treatment adherence more consistent, and timed interventions around the cascade, which led to a noticeable drop in cascade rates (Baumann et al., 2022).

NURS FPX 6016 Assessment 2: Evaluation of Quality Improvement Initiative 

Despite these milestones, certain questions and knowledge gaps remained unaddressed. For example, even though the integration of technology (like bed warnings and EHR warnings) was mostly successful, concerns about alarm fatigue among staff came up, which could have affected their responsiveness (Baumann et al., 2022). Nurses said that the frequency of warnings sometimes made them less sensitive, which made it harder to prioritize important warnings. The Morse Fall Scale is widely utilized; however, certain platoon members are skeptical about its comprehensive consideration of all factors contributing to fall risk, particularly for individuals with intricate medical histories. New training on the craft of fall threat and more information on how different groups of patients respond to different forestallment strategies would have given a better overall picture of how the action affected people. More awareness among staff in all departments and styles could have led to better technology integration and better use of assessment tools, which could have led to even more fall-prevention practices (Baumann et al., 2022).

Additional Recommended Indicators and Protocols 

To enhance and broaden the outcomes of the fall-forestallment QI at Springfield General Hospital, the following new guidelines and protocols should be considered: Case-centered outgrowth measures, designed for case satisfaction assessments specifically focused on fall prevention and safety protocols, would provide enhanced feedback regarding the perceived care of the cases and the sanitarium’s fall prevention initiatives (Dykes et al., 2020). Furthermore, checking to see if nannies and staff are happy with the fall-forestallment rules could help find out which parts of the staff need more help or training. The sanitarium should also investigate what happened after each fall to see if there were any missed chances to help and any problems with communication and following protocols. Similar reviews could identify specific areas that require improvement. Moreover, the incorporation of mobility shadowing technology akin to wearable bias or stir detectors may enhance the real-time surveillance of case movements and empower staff to intervene prior to the occurrence of cascades, particularly for cases that are unlikely to seek assistance promptly (Cooper et al., 2021).

NURS FPX 6016 Assessment 2 Quality Improvement Initiative 

Using technology, predictive analytics, and machine literacy models, patient data is broken down into smaller pieces. This data may include drug history, vital signs, and mobility. Such analysis makes it easier to find cases that are at risk of cascade increases and to adjust prevention measures to fit each person’s needs (Thapa et al., 2022). Even so, the accompanying suggestions could significantly impact case outcomes, but they have both advantages and disadvantages. Adding more outcome measures, like reviews after a fall and checks on patient satisfaction, would make fall-prevention evaluations more complete. However, it would also make administrative work harder and require more resources for collecting and analyzing data. Combining mobility-tracking technology with predictive analytics would make it possible to see things in real time based on data, but its implementation would require a lot of money to buy new technologies and train staff. There is also the risk of giving staff too much important data or relying too much on technology instead of their judgment (Raubal et al., 2021). Therefore, it’s important to achieve a balance between the beneficial things about the technology and protocol and the ability to carry out the crime and hire people.

Conclusion 

In conclusion, the interprofessional team at Springfield General Hospital made satisfactory progress on the fall-forestallment QI action. Some important goals were met, such as improving communication and following protocols, but there is still room for improvement in areas like reducing alarm fatigue and improving threat assessment tools. Adding case-centered measures, mobility shadowing, and prophetic analytics could help even more, but these technologies need to be carefully integrated to avoid attracting staff. To make the action as positive as possible, staff and cases will need to keep giving feedback. To keep lowering fall rates and making patients safer, you need to achieve a balance between being creative and being practical.

NURS FPX 6016 Assessment 2 Quality Improvement Initiative Evaluation 

Feng, T., Zhang, X., Tan, L., Su, Y., & Liu, H. (2022). Near-miss organizational literacy in nursing within a tertiary sanitarium The study was conducted using a mixed-styles approach. BMC Nursing, 21(1). https://doi.org/10.1186/s12912-022-01071-1 

Raubal, M., Bucher, D., & Martin, H. (2021). The study focuses on the use of geosmartness as a substantiated and sustainable approach to urban mobility. The Urban Book Series, 59–83. https://doi.org/10.1007/978-981-15-8983-6_6

Thapa, R., Garikipati, A., Shokouhi, S., Hurtado, M., Barnes, G., Hoffman, J., Calvert, J., Katzmann, L., Mao, Q., & Das, R. (2022). Predicting falls in long-term care installations: A machine literacy study. JMIR Aging, 5(2), e35373. https://doi.org/10.2196/35373

Venema, D. M., Skinner, A. M., Nailon, R., Conley, D., High, R., & Jones, K. J. (2019). Case and system factors associated with unassisted and pernicious cascades in hospitals This was an experimental study. The study was published in BMC elders, volume 19, issue 1. https://doi.org/10.1186/s12877-019-1368-8