| Course | NR 555 Health Policy: Advancing Health Equity & Outcomes |
|---|---|
| Week | 5 |
| Paper type | Equity-focused literature matrix |
| Length | About 1,120 words, 2 pages |
| Format | APA 7 student paper |
| School | Chamberlain University |
| Program | MSN, Healthcare Policy |
| Updated | September 2026 |
Free sample paper for NR 555 Week 5
Equity-Focused Literature Matrix: Six Studies on Postpartum Coverage and Follow-Up, Each Read for Who Actually Enrolled, Whether Results Were Split by Group and What Happened to the Gap
Student Name
College of Nursing, Chamberlain University
NR 555: Health Policy: Advancing Health Equity & Outcomes
Instructor Name
Month Day, Year
Equity-Focused Literature Matrix: Six Studies on Postpartum Coverage and Follow-Up, Each Read for Who Actually Enrolled, Whether Results Were Split by Group and What Happened to the Gap
Purpose
A standard literature matrix records each study's design, sample, intervention and findings. That is not enough for an equity question. A study can show that an intervention improved postpartum visit rates on average while the gap between groups widened, or it can enroll mostly people who were already likely to attend. This matrix adds three columns suggested by equity reporting guidance: who actually enrolled compared with the population the study claims to represent, whether outcomes were reported separately by group, and what happened to the distance between groups (Welch et al., 2012). The PROGRESS-Plus framework, which lists socially stratifying factors such as place of residence, race and ethnicity, occupation, gender, religion, education, socioeconomic status and social capital, guided which groups to look for (O'Neill et al., 2014).
The Matrix
Table 1 summarizes six sources relevant to the postpartum visit gap in Medicaid.
Equity-focused matrix of sources on postpartum coverage and follow-up
Table 1
| Source | Design and question | Enrolled versus intended population | Split by group? | What happened to the gap |
|---|---|---|---|---|
| Daw et al., 2017 | National survey analysis of insurance changes around childbirth | Nationally representative women giving birth; relies on survey response | Yes, by several characteristics | Describes churn; no intervention |
| Gordon et al., 2020 | Comparison of a Medicaid expansion state with a non-expansion state on postpartum coverage and visits | All Medicaid births in two states' data; no consent selection | Limited in the published summary | Coverage and visits rose; gap by race not the main focus |
| Petersen et al., 2019 | Surveillance of pregnancy-related deaths | National surveillance data | Yes, by race and ethnicity | Documents a large Black-white gap in deaths |
| ACOG Committee Opinion 736, 2018 | Professional guidance on postpartum care | Not a study | Not applicable | Recommends early, ongoing postpartum contact |
| Bailey et al., 2017 | Review of evidence on structural racism and health | Not a single sample | Not applicable | Frames mechanisms; proposes interventions |
| Local hospital pilot, 2023 | Booking postpartum visits before discharge at one hospital | Patients delivering on weekdays only; weekend discharges excluded | No | Average attendance rose; gap unknown |
Enrolled, Not Intended
The column comparing who enrolled with who the study claims to represent is where equity problems hide. Studies based on administrative data, such as the comparison of Medicaid expansion effects on postpartum coverage and outpatient use (Gordon et al., 2020), include everyone in the data and avoid consent selection. Survey studies, such as the national analysis of coverage churn (Daw et al., 2017), are representative by design but depend on response, which is often lower among people with unstable housing or work.
The local pilot is the clearest warning. It booked postpartum visits before discharge, but only for patients discharged on weekdays, when the scheduler worked. Weekend discharges, which at that hospital include more patients who arrive through the emergency department and more Medicaid enrollees, were excluded. An intervention tested only on the easier-to-reach group can look effective while missing the group holding the gap.
Split Results or Silence
Only two of the six sources report outcomes split by race: the survey analysis of churn and the surveillance of pregnancy-related deaths (Petersen et al., 2019). The expansion study's published summary focuses on overall effects. The local pilot reported average attendance only. A study silent on group results cannot support any claim that an intervention narrows a gap, however large its average effect. This is the most common finding of equity-focused reviews: most intervention studies do not report the information needed to judge their effect on inequality.
What Happened to the Distance
No source in the matrix directly measures the effect of an intervention on the Black-white gap in postpartum visits. The expansion study shows that broader coverage raises postpartum visits overall, and because Black enrollees are more affected by coverage loss, it is plausible that coverage extension narrows the gap, but the published results do not show it. The local pilot raised average attendance, but because weekend patients were excluded, it may have widened the gap by improving care mainly for those already more likely to attend. Guidance and reviews describe what should work but do not measure it.
Sources Considered and Left Out
Several types of source were reviewed and left out of the matrix. Studies of postpartum care in commercially insured populations were excluded because their enrollees face different coverage rules and barriers, so their findings would not transfer to Medicaid. Studies from other countries with universal coverage were excluded for the same reason, though they may be useful later for ideas about how postpartum care can be organized. Opinion pieces and news reports on the postpartum extension were read for context but not included, because they do not report data. Leaving these out keeps the matrix focused on evidence that could speak to the gap in our program.
The matrix is also short. A systematic search would find more studies, and a full review would be the right next step before a large investment. For a course project, six sources chosen to cover coverage, outcomes, guidance, mechanisms and a local pilot are enough to show what the evidence can and cannot support.
How the Matrix Will Be Used
The matrix shapes the intervention proposal in three ways. It shows that coverage policy has evidence behind it, so the proposal can treat the 12-month extension as a given and focus elsewhere. It shows that interventions are rarely evaluated by their effect on the gap, so the proposal must build that evaluation in. And it shows, through the local pilot, how an intervention can miss the group holding the gap by operating only when it is convenient, so the proposal must run seven days a week. Each of these lessons comes from the equity columns, not from the standard ones.
What the Matrix Shows
The matrix shows three things. First, there is good evidence that coverage churn is common and that coverage rules affect postpartum care. Second, there is almost no direct evidence on which interventions narrow the racial gap in postpartum visits, because studies rarely split their results. Third, local pilots can widen gaps by enrolling the easiest patients. The implication for this course's intervention proposal is that it must fix its group split in advance and measure the gap, not the average, as its primary outcome.
References
Daw, J. R., Hatfield, L. A., Swartz, K., & Sommers, B. D. (2017). Women in the United States experience high rates of coverage "churn" in months before and after childbirth. Health Affairs, 36(4), 598-606. https://doi.org/10.1377/hlthaff.2016.1241
Gordon, S. H., Sommers, B. D., Wilson, I. B., & Trivedi, A. N. (2020). Effects of Medicaid expansion on postpartum coverage and outpatient utilization. Health Affairs, 39(1), 77-84. https://doi.org/10.1377/hlthaff.2019.00547
O'Neill, J., Tabish, H., Welch, V., Petticrew, M., Pottie, K., Clarke, M., Evans, T., Pardo Pardo, J., Waters, E., White, H., & Tugwell, P. (2014). Applying an equity lens to interventions: Using PROGRESS ensures consideration of socially stratifying factors to illuminate inequities in health. Journal of Clinical Epidemiology, 67(1), 56-64. https://doi.org/10.1016/j.jclinepi.2013.08.005
Petersen, E. E., Davis, N. L., Goodman, D., Cox, S., Syverson, C., Seed, K., Shapiro-Mendoza, C., Callaghan, W. M., & Barfield, W. (2019). Racial/ethnic disparities in pregnancy-related deaths: United States, 2007-2016. MMWR. Morbidity and Mortality Weekly Report, 68(35), 762-765. https://doi.org/10.15585/mmwr.mm6835a3
Welch, V., Petticrew, M., Tugwell, P., Moher, D., O'Neill, J., Waters, E., & White, H. (2012). PRISMA-Equity 2012 extension: Reporting guidelines for systematic reviews with a focus on health equity. PLoS Medicine, 9(10), Article e1001333. https://doi.org/10.1371/journal.pmed.1001333
What the NR 555 Week 5 assignment asks for
The fifth week asks you to review literature relevant to a health equity question. The prompt usually requests a matrix of sources with design, sample, findings and relevance, plus a synthesis. Add columns that a standard matrix lacks. Compare who actually enrolled with the population the study claims to represent, since consent, attendance and scheduling can select against the group holding the gap. Mark whether outcomes were reported separately by group; a study silent on that cannot support a claim about a gap narrowing. Record what happened to the distance between groups. Explain which sources you left out and why. Synthesize what the evidence can and cannot support, and say how the matrix will shape your intervention. Use equity reporting frameworks and cite all sources in APA 7.
Inside the NR 555 Week 5 example
The matrix opens by explaining why standard columns are not enough and cites equity reporting guidance and a stratifying-factors framework. Table 1 lists six sources with design, enrolled versus intended population, whether results were split and the effect on the gap. A section on enrollment contrasts administrative data with surveys and highlights a local pilot that excluded weekend discharges. A section notes that only two sources split results by race. A section finds no source that directly measures an intervention's effect on the gap. Sections explain sources left out and how the matrix will be used. The conclusion identifies strong evidence on coverage and almost none on gap-narrowing interventions.
Where the points sit in the NR 555 Week 5 rubric
Equity-focused matrices are typically weighed on relevant source selection, accurate extraction, meaningful equity columns and a synthesis that answers the equity question. Comparing enrolled with intended populations reveals selection that ordinary matrices miss, and instructors read for it. Marking whether results were split by group shows understanding of what evidence can support. Recording the direction of the gap, where reported, connects the literature to the course's question. Explaining exclusions shows transparency. A synthesis that states plainly where evidence is missing reads as honest. Showing how the findings shape the intervention demonstrates application. Equity frameworks and sources cited in APA 7 complete the matrix.
Common NR 555 Week 5 mistakes, and how to avoid them
Matrices often summarize each study's overall findings without asking whether results were reported by group. Add that column. Another weakness is ignoring who actually took part, which can hide selection against the group of interest. Some students include sources from very different populations without noting that findings may not transfer. Avoid claiming evidence shows a gap narrowing when studies report only averages. Keep the matrix focused rather than exhaustive, and say what you left out. End with a synthesis that tells the reader what the evidence can support and what your proposal must therefore measure itself. Where two sources disagree, say so in the synthesis rather than averaging them.
Get a NR 555 Week 5 example written to your instructions
Send the Week 5 instructions with the table your section supplies and the gap you are chasing, and a custom example is written to that prompt and returned inside 24 to 48 hours. The first one is free. Tell us the required number of studies and the date window and the matrix is built inside them.
More NR 555 papers and MSN samples
- NR 555 Week 1: Health Equity Tests Discussion
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- NR 555 Week 6: Policy Analysis
- NR 555 Week 7: Intervention Proposal
- NR 555 Week 8: Equity Brief
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- NR 517 Week 5: Access and Coverage Brief
NR 555 Week 5 questions, answered
What if none of my studies report results by group?
Record that as the finding and say it plainly in the synthesis. A body of evidence that never splits its results is itself an equity problem, and naming it is worth more than pretending the overall effects answer your question. It also gives Week 7 a defensible starting point, since an untested population is a reasonable thing to propose testing.
How many studies does the matrix need?
Whatever your instructions set, and the count is usually stated there. Going beyond it rarely helps. A matrix with fifteen thin rows takes longer to read and says less than one with eight rows where the equity columns are filled in from the papers themselves rather than from their abstracts, which is where the real work of this week sits.
Can I include a study that failed?
Include it and give it a full row. An intervention that worked in one setting and did nothing in another is the most informative pair in the table, because the difference between them is usually a feature of the population or the delivery rather than of the idea. Tables containing only successes read as advocacy and are marked accordingly.
Where can I find a free NR 555 Week 5 sample paper?
The equity-focused postpartum matrix is the NR 555 Week 5 sample above, shown complete. If your topic needs a different set of sources, send us the question and a matrix with equity columns can be prepared.
What equity columns does the NR 555 Week 5 matrix add?
Who actually enrolled compared with the intended population, whether outcomes were split by group, and what happened to the distance between groups.