| Course | N437 Healthcare Informatics |
|---|---|
| Module | Module 7 |
| Paper type | Emerging technology paper |
| Length | About 1,025 words, 6 pages |
| Format | APA 7 student paper |
| School | Aspen University |
| Program | Pre-licensure BSN |
| Updated | September 2026 |
Free sample paper for N437 Module 7
Between the Four-Hour Checks: Wearable Continuous Vital Sign Monitoring on General Wards and What the Evidence Shows So Far
Student Name
Pre-licensure BSN Program, Aspen University
N437: Healthcare Informatics
Instructor Name
Month Day, Year
Between the Four-Hour Checks: Wearable Continuous Vital Sign Monitoring on General Wards and What the Evidence Shows So Far
On most general wards, vital signs are measured every four to eight hours, and a patient can deteriorate between checks. Wearable wireless sensors, patches or small devices worn on the chest or wrist that send heart rate, breathing rate, temperature and sometimes oxygen saturation to a central screen or a nurse's phone, promise to fill those gaps. This paper describes the technology, follows a composite night on a medical-surgical unit, reviews what the evidence shows so far and sets out the questions a unit should answer before adopting it.
How the Technology Works
A typical system uses a disposable patch that measures heart rate and breathing rate every minute or so and a separate probe for oxygen saturation. Readings travel wirelessly to a server, which displays trends and sends alerts when values cross set thresholds or combine into a worrying pattern. Unlike bedside monitors in intensive care, the patient can walk, shower in some cases and go home with the patch removed. The system does not replace nurse assessment; it adds data between checks.
A Night on the Unit
Mr. N., a composite 67-year-old man, was two days after bowel surgery on a unit piloting wearable sensors. His 10 p.m. vital signs were normal. At 1:30 a.m., the system alerted the nurse's phone that his heart rate had risen from the 80s to 118 over 90 minutes and his breathing rate to 26. The nurse found him sweaty and uncomfortable, with a temperature of 38.4 degrees Celsius and a firm abdomen. She called the rapid response team. A leak where his bowel had been joined was found, and he was in the operating room by 4 a.m. Without the sensor, the next scheduled vital signs would have been at 2 a.m. at the earliest, and the rising trend would not have been visible.
What the Evidence Shows
A systematic review of wearable wireless continuous monitoring in hospitalized adults found that most studies were still testing validation and feasibility, that the few reporting clinical outcomes did not show significantly better results than standard vital sign measurement, that none reported costs, and that study quality was mostly low or moderate (Leenen et al., 2020). A pilot study on a general ward found that wearable devices could be used by patients and staff but also identified problems with connectivity and data gaps (Weenk et al., 2017). More encouraging, a before-and-after study of 2,466 baseline and 2,303 intervention admissions found fewer unplanned intensive care admissions after wireless monitoring was introduced (3.1% in the monitored period), and rapid response calls that did not lead to intensive care fell from 2.8% to 2.0%, although length of stay and deaths did not change (Eddahchouri et al., 2022).
How Strong Is That Evidence?
The review's conclusion is the fairest summary: there are no large, high-quality controlled trials yet showing clinical benefit or cost-effectiveness (Leenen et al., 2020). A before-and-after comparison leaves open the possibility that something else, a new protocol or a staffing change, drove the improvement. Mr. N.'s story is persuasive, but single cases cannot show how often alerts help and how often they distract. For now, wearable monitoring is a promising emerging technology rather than an established standard.
Alarm Burden and Workflow
The biggest nursing question is alerts. Continuous data can produce many alerts that do not reflect real deterioration, for example a heart rate rise when a patient walks to the bathroom. If thresholds are too sensitive, nurses receive constant notifications and may begin to ignore them, which defeats the purpose. Units adopting the technology need agreed thresholds, delays that filter brief spikes, clear rules on who responds to which alert and how quickly, and a way for nurses to acknowledge and document their response. The technology should be tested with nurses before thresholds are fixed.
The Nurse's Part in Adoption
Nurses are the main users of continuous monitoring on the ward, so their involvement in adoption is essential. During a pilot, bedside nurses should help set and adjust thresholds, record whether each alert led to action, and describe what the alerts did to their workload. Charge nurses can track alerts per shift and identify patients whose alerts are persistently false, such as a patient with a known fast heart rate from atrial fibrillation, so that individual thresholds can be changed by an agreed process. Nurses also teach patients why they are wearing the patch and what to do if it comes off. Units that treat nurses as partners in setting up the system are more likely to find a balance between catching deterioration and avoiding constant noise.
Equity, Privacy and Cost
Sensors must work reliably on all skin tones, since some optical sensors are less accurate on darker skin, and devices must be validated in the populations where they are used. Continuous data streams must be protected like other health information. Finally, the patches are disposable and add cost per patient, which, given the lack of cost-effectiveness studies, must be weighed against uncertain savings from fewer transfers to intensive care.
Questions a Unit Should Ask
Before adopting wearable monitoring, a unit should ask: Which patients will wear the sensors, all patients or those at higher risk? What thresholds will trigger alerts, and who set them? Who receives alerts, on which device, and what response time is expected? How will the unit measure alerts per patient per day, false alarms, rapid response calls, unplanned intensive care transfers and nurse satisfaction? What happens when the connection drops? And how will the unit decide, after a defined pilot, whether to continue? Answering these questions in writing before the pilot starts gives the unit a fair basis for its final decision.
Conclusion
Wearable continuous monitoring addresses a real gap between scheduled vital signs, and early studies suggest it may reduce unplanned intensive care admissions. The evidence so far is limited, costs are unknown and alarm burden is a serious risk. Nurses should approach it as they would any emerging technology: interested, involved in setting it up and insistent on measuring whether it helps patients.
References
Eddahchouri, Y., Peelen, R. V., Koeneman, M., Touw, H. R. W., van Goor, H., & Bredie, S. J. H. (2022). Effect of continuous wireless vital sign monitoring on unplanned ICU admissions and rapid response team calls: A before-and-after study. British Journal of Anaesthesia, 128(5), 857-863. https://doi.org/10.1016/j.bja.2022.01.036
Leenen, J. P. L., Leerentveld, C., van Dijk, J. D., van Westreenen, H. L., Schoonhoven, L., & Patijn, G. A. (2020). Current evidence for continuous vital signs monitoring by wearable wireless devices in hospitalized adults: Systematic review. Journal of Medical Internet Research, 22(6), Article e18636. https://doi.org/10.2196/18636
Weenk, M., van Goor, H., Frietman, B., Engelen, L. J., van Laarhoven, C. J., Smit, J., Bredie, S. J., & van de Belt, T. H. (2017). Continuous monitoring of vital signs using wearable devices on the general ward: Pilot study. JMIR mHealth and uHealth, 5(7), Article e91. https://doi.org/10.2196/mhealth.7208
N437 Module 7 instructions, in plain terms
Emerging technologies close out the N437 content in Aspen's catalog before the presentation, and this example follows that content because the module prompt is not published outside the classroom. An emerging technology assignment usually asks you to describe a new tool, explain its intended benefit for nursing or patients, summarize the evidence so far and discuss barriers, risks and ethical questions. Instructors vary in how new the technology must be and whether it must already be in use. Check whether you should rate the strength of the evidence, whether a case example is welcome, and whether your paper should end with a recommendation or with questions for adoption. Ask whether a vendor's own materials count as a source. Keep the focus on nursing work throughout.
How the N437 Module 7 example is put together
This sample holds about 1,020 words in ten sections. It opens with the gap between scheduled vital signs. A section explains how the sensors and alerts work. A composite night illustrates the benefit. The evidence section summarizes three studies, and the next rates how strong they are. Alarm burden and workflow get their own section, followed by the nurse's part in adoption. Equity, privacy and cost raise sensor accuracy and uncertain savings. A list of questions a unit should answer before adopting leads to a conclusion that treats the technology as promising but unproven. Study designs are named each time a finding is reported, so readers can judge its weight.
Where the marks sit in the N437 Module 7 rubric
Emerging technology papers are generally graded on clear description, balanced use of evidence, nursing relevance and critical thinking. Description is concise and accurate. Evidence is balanced across three designs, a systematic review, a ward pilot and an uncontrolled comparison of two periods, and a margin note explains why rating each design matters for a new technology. Nursing relevance is strong, since alarm burden and threshold setting fall to nurses, which a second note highlights. Critical thinking shows in the section on evidence strength and in the adoption questions. Equity and cost are not ignored. The final marks cover writing quality and correct APA entries for the three studies. The case and the studies are kept clearly separate, which instructors look for.
N437 Module 7 help: mistakes that cost marks
The most common weakness is writing a product description instead of an evidence review. Summarize what studies found and how strong they are. Students also rely on a single dramatic case, which cannot show how often a technology helps. Pair stories with data. Another frequent gap is ignoring alarm burden, the main reason continuous monitoring can fail on busy wards. Some papers overlook equity, although sensor accuracy can vary with skin tone. Others end with an unconditional recommendation to adopt. For a technology without strong trials, end with questions a unit should answer and a plan to measure results during a pilot. Name the measures you would track.
Write yours, or have the desk draft it
This paper is an original model document written by our desk, not a submitted student paper and not an official Aspen University document. Read it for the moves, then write your own to the instructions in your classroom. If you want one built to your exact prompt and rubric, the first custom sample is free and arrives in 24 to 48 hours.
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N437 Module 7 questions, answered
What does N437 Module 7 usually ask for?
Aspen's N437 description includes emerging technologies, so a paper on one new technology in nursing and what the evidence shows so far is a typical assignment. Check your classroom for the prompt.
How do I choose an emerging technology to write about?
Pick one with published studies, even if early, and a clear link to nursing work, such as wearable monitoring, virtual nursing or documentation tools, and judge the evidence honestly.
What is alarm fatigue?
Desensitization that develops when clinicians receive many alarms, most of which do not need action, so that important alarms may be missed or delayed.
Where can I find a free N437 Module 7 sample paper?
This page contains the complete emerging technology paper on wearable monitoring, margin notes included, open to anyone without payment. It is the seventh N437 sample, before the presentation.
How new does the technology have to be in N437 Module 7?
New enough that its evidence is still developing but established enough to have published studies. Wearable monitoring, virtual nursing and AI documentation tools are common examples.