NR 512 Week 4 Concept Map of One Reading's Path Example

Concept Map With Key: Seven States of One Saturation Reading, From a Finger Probe to a Monthly Quality Report, and the Three Edges Where Its Meaning Narrows

Student Name

College of Nursing, Chamberlain University

NR 512: Fundamentals of Nursing Informatics

Instructor Name

Month Day, Year

Concept Map With Key: Seven States of One Saturation Reading, From a Finger Probe to a Monthly Quality Report, and the Three Edges Where Its Meaning Narrows

The Item Being Traced

The item is a single pulse oximetry reading: 91% at 0215 for a 66-year-old woman on a medical unit whose nasal cannula was delivering two liters a minute. The map follows that reading from the moment the probe produced it to the moment it became part of a number in the hospital's monthly deterioration report. Nobody edits the value along the way. It changes identity anyway, because at each hand-off a different system or person takes it up for a different purpose. Matney et al. (2011) describe the move from data to information to knowledge as a matter of context and interpretation, and the map is an attempt to show where that context is added and where it is lost.

The Map

The map is drawn as seven nodes in a single column, joined by six labeled arrows. For this submission it is reproduced as Table 1, one row per edge, reading top to bottom. In the drawn version, the three arrows marked narrows are the only red ones.

Table 1

Concept Map of One Saturation Reading, Written as Nodes and Labeled Edges

Note. Point values are from the NEWS2 chart for SpO2 scale 1 and the air or oxygen parameter (Royal College of Physicians, 2017). Codes are from the HL7 US Core pulse oximetry profile (HL7 International, n.d.).

Key: How to Read the Map

Each node is the same reading in a different state, not a concept from the course. Each arrow carries a verb, because a line without a verb makes no claim. The column runs from the most detailed state to the least detailed one, and the map ends at the report because that is where the reading last does work: after that, nobody asks what it was.

Only one distinction is shown in color. Red arrows mark edges where something the reading carried before the arrow cannot be recovered after it. The other three arrows change the form of the reading without losing anything a later reader would need.

Marked Edge 1: Candidate to Validated Entry

The monitor sends a value every 15 minutes, so the hour holds four candidates, perhaps 94, 93, 91 and 92. The nurse saves one. The flowsheet does not record which of the four she chose, why, or whether the others were artifact from a cold finger. Once saved, 91 is the reading for that hour and the others disappear from the chart. A reader later cannot tell whether 91 was the lowest of a steady set or a dip in a falling trend.

Something else narrows here too. The value on the monitor is only as good as the device. Sjoding et al. (2020) matched oximeter readings against arterial blood gases taken close in time; hidden low oxygen, meaning a blood gas saturation under 88% while the probe showed 92% to 96%, turned up in 11.7% of Black patients against 3.6% of White patients. Nothing in the validated entry records skin pigmentation, probe site or perfusion, so a later reader cannot weigh the value against that known error.

Marked Edge 2: Coded Observation to Score Points

At this edge the number becomes a band. On the NEWS2 chart for SpO2 scale 1, any value of 91% or below scores 3 points (Royal College of Physicians, 2017). A reading of 91% and a reading of 84% become the same 3. The flow rate narrows even further: the air or oxygen parameter asks only whether the patient is on oxygen, so 2 L/min and 6 L/min both score 2. The score was designed to be simple enough to calculate at the bedside, and that simplicity is its value. The map only records the cost: after this edge, nobody can tell from the score how low the saturation went or how much oxygen was needed to hold it there.

Marked Edge 3: Score to Monthly Count

The last edge turns a patient's night into a yes or no. The report counts patients whose total NEWS2 reached 5 or more and, among them, how many were reviewed within an hour. This patient's 91% on oxygen contributed 5 points and made her one of the counted. A patient whose score stayed at 4 all night, falling slowly, is invisible to the report, even though her trend may have been the more worrying one. The count also cannot show which scores were driven by oxygen and which by saturation, so a unit that places more patients on low-flow oxygen will see its count rise without any change in how sick its patients are.

What the Map Leaves Out

The map follows one path and ignores branches. The same validated entry also flows to the physician's results review, to a respiratory therapist's worklist and to the discharge summary, and each of those paths has its own edges. They were left off because a map with every branch would need thirty nodes and would be unreadable at the size a course upload allows. The path chosen is the one that ends in a number the hospital reports about itself, since that is where a narrowing at the bedside has its widest effect. A second map of the same reading, following it into the physician's review, would probably show fewer narrowing edges, because a physician reads the trend rather than a band.

What the Map Shows Overall

Three of six edges narrow the reading, and all three do it for good reasons: charting has to pick one value, bedside scores have to be simple, and reports have to count. The map's use is in showing where a nurse's entry still controls what happens downstream. Only the first narrowing edge is in the nurse's hands. Choosing and recording a representative value, with its oxygen flow, is the last point at which the reading carries its full context. Every later state depends on that entry being complete.

References

HL7 International. (n.d.). US Core pulse oximetry profile (US Core Implementation Guide, Version 9.0.0, STU 9). Retrieved September 30, 2026, from https://hl7.org/fhir/us/core/StructureDefinition-us-core-pulse-oximetry.html

Matney, S., Brewster, P. J., Sward, K. A., Cloyes, K. G., & Staggers, N. (2011). Philosophical approaches to the nursing informatics data-information-knowledge-wisdom framework. Advances in Nursing Science, 34(1), 6-18. https://doi.org/10.1097/ANS.0b013e3182071813

Royal College of Physicians. (2017). National Early Warning Score (NEWS) 2: Standardising the assessment of acute-illness severity in the NHS. Updated report of a working party. https://www.rcp.ac.uk/improving-care/resources/national-early-warning-score-news-2/

Sjoding, M. W., Dickson, R. P., Iwashyna, T. J., Gay, S. E., & Valley, T. S. (2020). Racial bias in pulse oximetry measurement. New England Journal of Medicine, 383(25), 2477-2478. https://doi.org/10.1056/NEJMc2029240