NUR 633 Module 7 Milestone Three Example

Milestone Three: Implementing and Evaluating Integrated Fall Risk Alerts on 6 West

[Student Name]

Southern New Hampshire University

NUR 633: Informatics and Communication Technology

Milestone Three

[Instructor Name]

[Date]

The organization, setting and figures below are a composite written as a model document. No real employer, client, colleague or patient is described.

Milestone Three: Implementing and Evaluating Integrated Fall Risk Alerts on 6 West

Many clinical technology projects are designed well and implemented poorly. A system goes live on a Monday morning, training consists of a slide deck, night staff meet it for the first time at 2 a.m. and within weeks nurses have found ways around it. This milestone plans the implementation and evaluation of the integrated fall alert system designed for 6 West. It argues that phased rollout, testing with the people who will use the system at night, training that respects shift work and evaluation built on the systems' own data give the design its best chance of reducing falls.

What Is Being Implemented

Four pieces go live together, each answering one of the Milestone Two requirements. When a nurse charts a high fall risk score, the chart now tells the call platform, and the patient's room is marked as high risk. If that patient triggers a bed sensor, the alert travels to the pocket devices of the nurse and assistant who own the room, names the room and the risk and, if no one responds within a minute, climbs to the charge nurse. Sensors start at a middle setting rather than the most sensitive one, and a nurse raises them only for a stated reason. Finally, each high-risk patient gets an individual prevention plan on the whiteboard, reviewed with the patient and family in the way the Fall TIPS trial tested (Dykes et al., 2010).

Anticipating Barriers

The Consolidated Framework for Implementation Research asks planners to look for trouble in five places: at the change being introduced, at pressures from beyond the hospital's walls, at the hospital's own culture and resources, at the individuals expected to work differently and at the rollout process itself (Damschroder et al., 2009). Working through each area for 6 West turns up specific risks. The innovation is only moderately complex, but pocket alerts could feel like one more interruption. Inside the organization, nights are thinly staffed and two night nurses are in their first year. Among the people, some remember the 2022 staffing pilot that quietly disappeared and may expect the same again. And the rollout depends on an interface team that is also serving three other projects. Every item on that list is answered somewhere in the plan below.

Phased Rollout

The rollout runs over 16 weeks in four phases. In weeks one to four, the interface team builds the flag and badge routing in the test environment, and bed sensor defaults are changed on four beds. In weeks five to eight, eight night nurses and two nursing assistants run scripted scenarios in the test environment and on the four beds: a high-risk patient standing, a low-risk patient rolling over, an unacknowledged alarm escalating to the charge nurse and a badge out of battery. Problems found are fixed before go-live. In weeks nine and ten, the full system goes live on half the unit, the east hall, while the west hall continues current practice, which provides a short comparison and limits disruption. In weeks eleven to sixteen, the system extends to the whole unit, with a formal review at week sixteen.

Super Users and Training

Each shift will have at least one super user, a staff nurse or nursing assistant with extra training who supports colleagues at go-live. A mixed methods study of super users during an electronic record rollout concluded that the behaviors that mattered were being proactive, explaining the reasons behind actions, framing the change positively and sharing information freely, and that units where super users behaved this way showed greater improvement in clinicians' proficiency with the system (Yuan et al., 2015). Super users will be chosen for those qualities, not only for technical skill, and their managers will protect time for the role. Training for all staff will be a 20-minute hands-on session scheduled at the start of each shift type, including nights and weekends, with a one-page guide attached to every badge charger. Content will focus on what changes for the nurse: what a badge alert means, how to acknowledge it and how to set bed sensitivity.

Go-Live Support and Downtime

During each phase's first week, an informatics nurse will be on the unit for part of every night shift, and a daily huddle will collect problems. A downtime procedure will cover interface failure: if flags stop reaching the nurse call system, the charge nurse will print the list of high-risk patients each shift and post it at the station, and the old station alarms will continue to sound. This protects patients if the integration fails and reassures staff that the change does not remove existing safeguards.

Evaluation

Evaluation will use data the systems already record. The primary outcome is the unit's fall rate per thousand patient days over the year before and the year after implementation, with injurious falls as a key secondary outcome. Process measures come straight from the logs: how often a flagged patient's bed alert is acknowledged within a minute at night, how many bed alerts sound in a typical week and what share of those are canceled almost immediately as nonactionable. A balancing measure will follow response times to calls from patients who carry no flag, so that faster help for high-risk patients does not mean slower help for everyone else. A brief staff survey at baseline and six months will capture perceived alarm burden. Results will appear monthly as run charts and be discussed at unit meetings, because staff who see progress are more likely to sustain the change.

The evaluation also has limits that the unit's leaders should understand before they read the results. A before-and-after comparison cannot rule out other changes that happen during the year, such as new staff or a change in patient mix, so the half-unit comparison in weeks nine and ten, though brief, will be reported alongside the annual figures. Falls are relatively uncommon events on a single unit, so a real improvement may take many months to become visible in the run chart, and the process measures will show earlier whether the system is working as designed. The project team will agree in advance on the decision it will make at week sixteen: continue, adjust or stop, based on whether flagged alerts are being acknowledged promptly and whether nurses report less alarm burden.

Conclusion

The integrated fall alert system will succeed or fail on 6 West depending less on its code than on its rollout. Anticipating barriers with the CFIR, testing with night staff, choosing super users for how they support colleagues, training around shifts, planning for downtime and measuring with the systems' own logs give the design a fair test. The final project will assemble the full proposal.

References

Damschroder, L. J., Aron, D. C., Keith, R. E., Kirsh, S. R., Alexander, J. A., & Lowery, J. C. (2009). Fostering implementation of health services research findings into practice: A consolidated framework for advancing implementation science. Implementation Science, 4, Article 50. https://doi.org/10.1186/1748-5908-4-50

Dykes, P. C., Carroll, D. L., Hurley, A., Lipsitz, S., Benoit, A., Chang, F., Meltzer, S., Tsurikova, R., Zuyov, L., & Middleton, B. (2010). Fall prevention in acute care hospitals: A randomized trial. JAMA, 304(17), 1912-1918. https://doi.org/10.1001/jama.2010.1567

Yuan, C. T., Bradley, E. H., & Nembhard, I. M. (2015). A mixed methods study of how clinician 'super users' influence others during the implementation of electronic health records. BMC Medical Informatics and Decision Making, 15, Article 26. https://doi.org/10.1186/s12911-015-0154-6