NURS 8542 Week 2 Program Data Analysis Example

From Anecdote to Pattern, or Not: Six Terms of Program Data on the Complaint That Graduates Cannot Prioritize, Disaggregated by Entry Route

Student Name

College of Nursing, Walden University

NURS 8542: Curriculum Change: Applying Research Strategies to Prepare Tomorrow's Nursing Education Programs

Instructor Name

Month Day, Year

From Anecdote to Pattern, or Not: Six Terms of Program Data on the Complaint That Graduates Cannot Prioritize, Disaggregated by Entry Route

The Complaint

Complaints about a cohort usually arrive as anecdote. At a composite regional university's prelicensure baccalaureate nursing program, faculty teaching the final practicum and clinical partners at two hospitals have reported that recent graduates "cannot prioritize": they manage one patient well but struggle when assigned four. This analysis asks whether anything in the program's own record supports the claim, using six graduating terms of aggregate results. Every number below is illustrative, invented to demonstrate the method, and the program is a composite.

Prioritization is a core element of clinical judgment. The clinical judgment model now built into the licensure exam breaks nursing judgment into a chain that runs from spotting relevant cues through deciding which problems come first to acting and then checking the result, and educators have been urged to align their frameworks with it (Dickison et al., 2019). If graduates struggle with prioritization, the gap matters for both practice and licensure.

Data Sources

Three sources were used, all already collected by the program. The first is the management-of-care subscale of the standardized exit exam taken in the final term, reported as the percentage of students meeting the vendor's benchmark. The second is first-time licensure pass rates by graduating term. The third is the final-practicum preceptor evaluation item "prioritizes care for an assignment of multiple patients," rated from 1 to 4. The analysis covers six terms, 244 graduates in all. Each source was examined first in aggregate and then by entry route: students admitted as first-year students, called traditional here, and students admitted in the junior year after completing prerequisites and, in many cases, a fundamentals course elsewhere, called transfer here.

Aggregate Results

Table 1 shows the aggregate results.

Table 1

Aggregate Results by Graduating Term (Illustrative)

Licensure results are stable; the management-of-care subscale and preceptor rating decline gradually.

Reading the Aggregate

Read in aggregate, the record gives modest support to the complaint. The share of students meeting the management-of-care benchmark fell from 71% to 62% over six terms, and the mean preceptor rating on prioritization drifted down from 3.1 to 2.9. Licensure pass rates stayed in the mid to high 80s. A faculty member reading only the pass rates would see no problem; one reading only the practicum anecdotes would see a crisis. The aggregate suggests something in between: a gradual decline in the specific skill, not yet reflected in overall licensure results.

Disaggregated Results

Table 2 separates the subscale results by entry route. About 30% of each cohort entered by the transfer route.

Table 2

Management-of-Care Benchmark Met, by Entry Route (Illustrative)

The traditional route is nearly flat; the transfer route accounts for most of the decline.

What the Disaggregation Shows

Disaggregated, the pattern changes. Traditional students met the benchmark at 72% to 76% across all six terms, a nearly flat line. Transfer students fell from 60% to 38%. Because transfer students are about 30% of each cohort, their decline accounts for most of the aggregate drop. Preceptor ratings showed the same shape: traditional students held near 3.2, while transfer students fell from 2.9 to 2.5.

The complaint, then, is partly supported and partly misdirected. There is a pattern, but it is concentrated in one subgroup. Faculty perceiving that graduates in general cannot prioritize were generalizing from a subgroup that makes up a third of each cohort.

Possible Explanations

The data do not explain the pattern, but they narrow the possibilities. Transfer students enter after completing fundamentals and sometimes health assessment elsewhere, so they have fewer semesters of clinical experience in the program's own sequence, where early multi-patient practice is introduced in the sophomore year. The transfer route has also grown in popularity, which may have changed who uses it. And subgroups of twelve or thirteen students per term are small, so some variation is expected. The next step is not to revise the curriculum for everyone but to examine what the transfer route's sequence omits, which the gap analysis later in the term will do.

Why Aggregate Program Data Mislead

Programs typically review outcome data in aggregate because accreditors and boards ask for aggregate results. That practice is sensible for accountability but poor for diagnosis. Curriculum texts recommend that program evaluation examine results for subgroups and over time, so that problems concentrated in one group are not averaged away (Iwasiw et al., 2020). In this case, a faculty committee reviewing only the overall subscale might have redesigned senior-year teaching for everyone, spending effort on the 70% of students who were already meeting the benchmark at a steady rate.

The faculty's anecdote was not wrong, only too broad. Concern that new graduates are less ready for the complexity of practice has been widely voiced by nursing leaders (Kavanagh & Sharpnack, 2021), and it is easy for a program to absorb that general concern and apply it to its own graduates without checking. The disaggregated data give the program something better: a specific group, a specific skill and a question about what that group's path through the curriculum omits.

Limits

The subscale is a proxy for prioritization, not a direct observation. Preceptor ratings vary with the preceptor. Subgroup numbers are small, and a single term's result should not be over-read. Licensure data are reported by the state board in aggregate, so they could not be disaggregated by entry route here. With those limits, the analysis still does what the complaint could not: it locates the problem, which is the precondition for any change the program might later propose.

References

Dickison, P., Haerling, K. A., & Lasater, K. (2019). Integrating the National Council of State Boards of Nursing Clinical Judgment Model into nursing educational frameworks. Journal of Nursing Education, 58(2), 72-78. https://doi.org/10.3928/01484834-20190122-03

Iwasiw, C. L., Andrusyszyn, M.-A., & Goldenberg, D. (2020). Curriculum development in nursing education (4th ed.). Jones & Bartlett Learning.

Kavanagh, J. M., & Sharpnack, P. A. (2021). Crisis in competency: A defining moment in nursing education. OJIN: The Online Journal of Issues in Nursing, 26(1), Manuscript 2. https://doi.org/10.3912/OJIN.Vol26No01Man02