NR 439 Week 8 Evidence-Based Practice Reflection Example

The Thermometer I Trusted: A Course Reflection on One Evidence-Based Practice Question

Student Name

College of Nursing, Chamberlain University

NR 439: RN Evidence-Based Practice

Instructor Name

Month Day, Year

The Thermometer I Trusted: A Course Reflection on One Evidence-Based Practice Question

The Question That Carried the Course

I started this course with a practice problem I did not think was a problem. On the postoperative unit where I work, we take every temperature with a temporal artery thermometer: a quick sweep across the forehead, a number on the screen, and on to the next room. Early in the term, a patient two days after abdominal surgery had a forehead reading of 37.4 degrees Celsius at 0400. He was shivering and his heart rate had climbed. The charge nurse asked me to recheck with an oral thermometer, which read 38.6. That gap of more than a degree bothered me enough to build my PICOT question around it: in adult postoperative inpatients, how accurately does a temporal artery thermometer, compared with an oral electronic thermometer, detect fever during the hospital stay?

The reason the gap mattered is that fever is often the first measurable sign of a postoperative complication. An anastomotic leak, a wound infection or an early pneumonia can all announce themselves with a temperature before the white cell count rises or the wound looks different. If the thermometer reads low in exactly the patients who are starting to become septic, the delay is not a matter of documentation; it is a matter of hours before anyone calls the surgeon. That was the stake I wrote into the problem statement, and it kept the question from feeling like a debate about equipment.

Everything I did in the course followed that one question. I wrote the PICOT worksheet around it, built a search in CINAHL and PubMed, appraised a meta-analysis and two comparison studies in the evidence matrix, wrote a synthesis, and proposed a change for my unit. This reflection follows that thread rather than walking through each week, because the thread is where my thinking actually changed.

What Changed in My Thinking

At the start, I believed the forehead reading on that night was a fluke caused by sweat or a poor sweep. I believed the device was accurate and that I had used it badly. What changed my mind was the meta-analysis by Niven et al. (2015), which pooled studies comparing peripheral thermometers, including temporal artery devices, with central measurements. Peripheral thermometers were good at confirming that a patient without fever did not have one, but they missed a substantial share of fevers that central methods detected. The finding was not that my sweep was poor. It was that the device, used correctly, is built to be less sensitive exactly when sensitivity matters most.

The moment this became real was the synthesis week, when I tried to write one sentence answering my question and kept writing sentences that defended the device. I realized I had been appraising the evidence as if my job was to rescue a tool my unit already owned. Melnyk and Fineout-Overholt (2023) describe the tendency to look for evidence that supports current practice, and I recognized myself in that description. The belief I hold now is narrower and more useful: a normal forehead reading in a patient who looks septic is not reassuring, and a second method should be used before that number is trusted.

The Course Tools That Did the Work

Two methods from the course did most of the work. The first was the comparison box of the PICOT worksheet. Writing oral electronic thermometer as the comparison forced me to ask what the gold standard actually was, and the answer, a central measurement such as a pulmonary artery catheter or bladder probe, showed me that both of the thermometers on my unit are estimates. The second was the level of evidence column in the matrix. I had assumed that the manufacturer's accuracy data were the strongest source I could find, but assigning a level to them made me see that validation studies run by the maker of a device sit well below an independent meta-analysis. That single column changed which source I led with.

The search itself taught me something I did not expect. My first run in PubMed, using temporal artery thermometer and accuracy, returned more than a hundred studies, and I assumed the question had been settled long ago. When I added postoperative and adult and removed pediatric and emergency department settings, the set shrank to a handful, and most of those compared devices in patients who had no fever at all. Studies of accuracy in afebrile patients cannot tell me much about detecting fever, because a thermometer that always reads 37 degrees would look accurate in a room full of healthy people. Learning to read a study for who was measured, and not only for how many, was the most transferable skill I took from the search week.

I also learned that appraisal includes the population. Many of the studies in the meta-analysis enrolled intensive care patients, febrile children or emergency department patients rather than postoperative adults on a general unit. Tanner (2006) describes clinical judgment as interpreting findings in the context of the particular patient, and the same applies to evidence: a study is only as useful as its similarity to the patients I care for.

One Thing I Will Do Differently

My next step is small. When a postoperative patient has a normal forehead temperature and any sign that worries me, such as rigors, a rising heart rate, new confusion or falling blood pressure, I will recheck with an oral thermometer before I document the reading or decide whether to call the surgical team. I have already shared the meta-analysis with our unit educator, who has agreed to raise the question at the next practice council meeting, but that is a unit decision and not one I can make. What I can decide is how I use the number on my own shifts. I will also document both readings and the method used for each, so that the next nurse can see the difference rather than a single reassuring number.

Looking back at Gibbs (1988), the reflective cycle ends with an action plan because reflection that does not change what happens next is only a description. The course did not make me an evidence-based nurse in some general sense. It showed me that one number I trusted every night was less trustworthy than I believed, and it gave me a method for finding that out about the next number too.

References

Gibbs, G. (1988). Learning by doing: A guide to teaching and learning methods. Further Education Unit, Oxford Polytechnic.

Melnyk, B. M., & Fineout-Overholt, E. (2023). Evidence-based practice in nursing and healthcare: A guide to best practice (5th ed.). Wolters Kluwer.

Niven, D. J., Gaudet, J. E., Laupland, K. B., Mrklas, K. J., Roberts, D. J., & Stelfox, H. T. (2015). Accuracy of peripheral thermometers for estimating temperature: A systematic review and meta-analysis. Annals of Internal Medicine, 163(10), 768-777. https://doi.org/10.7326/M15-1150

Tanner, C. A. (2006). Thinking like a nurse: A research-based model of clinical judgment in nursing. Journal of Nursing Education, 45(6), 204-211. https://doi.org/10.3928/01484834-20060601-04