NUR 307 Module 1 Short Paper Example

Sixty-Eight and Falling: The Data-Information-Knowledge-Wisdom Framework at a School Nurse's Desk

[Student Name]

Southern New Hampshire University

NUR 307: Exploring Information Technology for Professional Practice

Module One Short Paper

[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.

Sixty-Eight and Falling: The Data-Information-Knowledge-Wisdom Framework at a School Nurse's Desk

Nursing informatics often begins with the data-information-knowledge-wisdom framework, a model of the path from an isolated fact to a sound clinical action, and one that the field has revised and debated since it was first adopted (Ronquillo et al., 2016). Matney et al. (2011) trace the framework's philosophical roots and treat wisdom, its highest level, as the skill of applying knowledge well to the real problems of real people. The framework can sound abstract until it is applied to a single moment. This paper follows one continuous glucose monitor alert received by a school nurse at a composite elementary school and shows what happens at each level. It argues that the technology delivers data faster than ever, but that the steps from information to wisdom still depend on context the device cannot see: the child, the classroom and the plan her family and clinicians wrote.

The Scenario

Maya, a composite nine-year-old with type 1 diabetes, wears a continuous glucose monitor that sends readings every five minutes to an app on her mother's phone and, with the family's written permission, to a follow app on the school nurse's phone. The school nurse covers three buildings and is at a neighboring school. At 10:40 a.m., her phone shows an alert: glucose 68 mg/dL with a single arrow pointing down. Maya's class had physical education from 9:45 to 10:15 and is now taking a math test. Lunch is at 11:30. Maya's diabetes medical management plan, written by her endocrinology team, directs school staff to treat readings below 70 with fast-acting carbohydrate and to recheck in 15 minutes.

Data

At the first level, the alert is only data: the number 68, the unit mg/dL, a timestamp and a symbol for the direction of change. On its own, 68 means nothing. It could be a reading from any person, at any time, from any device. Even the arrow is only a coded symbol until someone knows what it represents. The monitor measures glucose in the fluid between cells, not in blood, and interstitial readings can lag behind blood glucose when levels are changing quickly. A nurse who treats the number as a finished fact, rather than as data with known limits, has skipped a level before starting.

Information

Data become information when they are organized and interpreted in context. Placed on Maya's trend graph, the 68 is the latest of six readings that have fallen from 142 at 10:15, a drop of roughly 74 points in 25 minutes. The single down arrow indicates a steady fall. The timestamp places it about 25 minutes after physical education and 50 minutes before lunch. Now the number says something: Maya's glucose is below her plan's threshold and still dropping, probably because exercise increased her glucose use. The school nurse's app also shows that her mother has seen the alert, which is information about who else is aware.

Knowledge

Knowledge comes from connecting that information to what the nurse knows about diabetes, children and school care. The nurse knows that exercise can lower glucose for hours afterward, that children may not notice or report early symptoms of hypoglycemia, especially while concentrating, and that a falling reading below 70 needs treatment now rather than at lunch. The American Diabetes Association position statement on school care emphasizes that each student should have an individualized diabetes medical management plan, that school nurses coordinate care and train other staff, and that students should be able to treat low glucose promptly wherever they are in the building (Jackson et al., 2015). The nurse also knows Maya: she is shy about her diabetes, and last month she was upset when a substitute sent her walking alone to the office during a low.

Wisdom

Wisdom is the decision. The nurse calls Maya's teacher, who has been trained under the plan, and asks her to give Maya the juice box and glucose tablets kept in the classroom diabetes kit, at her desk, without sending her anywhere. The teacher does so quietly while the class continues the test. The nurse texts Maya's mother that treatment was given, and asks the teacher to note whether Maya feels shaky or confused. At 10:55 the monitor reads 81 with a flat arrow; the teacher reports that Maya finished her test. Before lunch, the nurse confirms that Maya will eat as planned.

The wise decision was not simply to treat a low reading, which the plan already required. It was to treat it in a way that kept Maya safe without isolating her, used the trained adult closest to her, and informed the family in real time. Later that week, the nurse suggested to Maya's mother that the endocrinology team review whether a snack before physical education should be added to the plan, which moves from managing one event to preventing the next.

What the Technology Adds and What It Cannot Do

The monitor changed the timing of this event. Without it, Maya's low might have been noticed only when she felt unwell or when a fingerstick was due before lunch. With it, the nurse learned of the fall within minutes, from another building. But the device supplied only the first level of the framework. It could not see the math test, Maya's shyness or the classroom kit, and it could not decide how to act. It also created new questions: how many alerts a nurse covering three schools can safely monitor, what happens when the app loses connection, and who responds when the nurse is busy with another child. Those questions belong in any school's plan for using remote monitoring.

Conclusion

Following one alert through the data-information-knowledge-wisdom framework shows why informatics is a nursing skill rather than a technical one. The glucose monitor delivered data quickly and accurately. Turning those data into a safe, respectful decision required context, clinical knowledge, a written plan and knowledge of a particular child. Technology moved the first step closer to real time; the last step remained a nurse's judgment.

References

Jackson, C. C., Albanese-O'Neill, A., Butler, K. L., Chiang, J. L., Deeb, L. C., Hathaway, K., Kraus, E., Weissberg-Benchell, J., Yatvin, A. L., & Siminerio, L. M. (2015). Diabetes care in the school setting: A position statement of the American Diabetes Association. Diabetes Care, 38(10), 1958-1963. https://doi.org/10.2337/dc15-1418

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

Ronquillo, C., Currie, L. M., & Rodney, P. (2016). The evolution of data-information-knowledge-wisdom in nursing informatics. Advances in Nursing Science, 39(1), E1-E18. https://doi.org/10.1097/ANS.0000000000000107