Chapter 1 – Informing Public Policy: An Important Role for Registered
Nurses
Chapter 2 – News Literacy
Chapter 3 – Problem Identification and Agenda Setting: What Rises to
a Policymaker’s Attention?
Chapter 4 – Policy Analysis and Design Chapter 5 – Policy Enactment:
Legislation and Politics
Chapter 6 – Policy Implementation: Avoiding Policy Failure
Chapter 7 – Government Response: Regulation
Chapter 8 – Health Policy and Social Program Evaluation
Chapter 9 – The Influence of Patient Health Data on Health Policy
Chapter 10 – Financing Health Care
Chapter 11 – The Impact of Nurse Influence on Global Health Policy
Chapter 12 – An Insider’s Guide to Engaging in Policy Activities
,Chapter 1 — Informing Public Policy
1. A hospital nurse wants to inform a proposed institutional policy on early
mobility for ICU patients. Which contribution best leverages nursing clinical
expertise in the policy drafting stage?
A. Submit a petition signed by bedside nurses asking leaders to adopt the
intervention.
B. Provide an evidence summary combining unit-level mobility outcomes,
workflow mapping, and implementation barriers with staff
recommendations.
C. Encourage nurses to post their experiences on social media to raise public
awareness.
D. Request that the hospital purchase mobility equipment without proposing
changes to staffing or workflow.
Answer: B
Rationale: Option B translates bedside observations into actionable policy
input by combining outcomes data, workflow analysis, and identified
barriers—precisely what policymakers need to design feasible policy. A
petition (A) shows support but lacks analytic detail; social media (C) may
raise awareness but is poor for policy design; buying equipment (D)
addresses a resource but ignores workflow and staffing needs that affect
implementation. Nurses’ clinical expertise is most persuasive when
presented as structured evidence and actionable recommendations.
Key words: evidence translation, workflow mapping, implementation
barriers, policy brief
2. Which method is most appropriate for a nurse researcher to use when
converting routine clinical data into a policy brief recommending changes to
sepsis protocol?
A. Use unadjusted counts of sepsis cases and anecdotal vignettes.
B. Conduct risk-adjusted outcome analyses, cost implications, and pilot
implementation results, then summarize in a concise brief.
C. Rely solely on published randomized clinical trials from other health
systems.
D. Submit raw EHR extracts to the policymaker and ask them to interpret.
, Answer: B
Rationale: Policy briefs require contextualized, policy-relevant evidence—
risk adjustment addresses case-mix bias, cost implications appeal to
budgetary concerns, and pilot data show feasibility. RCTs (C) are valuable
but may not reflect local context; raw data (D) are unusable without
interpretation; unadjusted counts and anecdotes (A) risk misleading
conclusions. Converting clinical data into policy requires analysis,
interpretation, and actionable recommendations.
Key words: risk adjustment, pilot data, cost analysis, policy brief
3. A state nursing association seeks to influence legislation on minimum nurse-
to-patient ratios. Which stakeholder should be prioritized for early
engagement to maximize chances of legislative success?
A. Medical device manufacturers.
B. State legislative appropriations and budget staff.
C. Local news reporters.
D. National nursing schools.
Answer: B
Rationale: Budget and appropriations staff control fiscal feasibility—early
engagement helps shape realistic cost estimates and financing pathways.
Manufacturers (A) and schools (D) have peripheral influence; media (C) can
shape public opinion later but will not resolve financial concerns that
determine legislative viability. Because staffing ratio laws have strong
budget implications, work with budget stakeholders early is critical.
Key words: stakeholder mapping, appropriations, fiscal feasibility,
legislative strategy
4. During testimony to a legislative committee, a bedside nurse wants to
illustrate harm caused by inadequate staffing. Ethically and persuasively, the
nurse should:
A. Rely exclusively on vivid patient stories to elicit emotion.
B. Combine de-identified patient stories with aggregated safety metrics and
process evidence.
C. Use named patient details to underscore urgency.
D. Refrain from using any narratives—only present numbers.
Answer: B
, Rationale: Combining de-identified narratives with aggregated metrics
marries empathic storytelling to rigorous evidence, increasing
persuasiveness while protecting privacy. Using identifiable patient details
(C) breaches confidentiality; numbers alone (D) may fail to convey human
impact; stories alone (A) may be dismissed as anecdotal. Ethical policy
engagement uses both narrative and data responsibly.
Key words: testimony, confidentiality, narrative + data, ethical advocacy
5. A nurse epidemiologist is preparing EHR-based evidence to support a new
infection-control policy. Which analytic practice best addresses common
EHR biases?
A. Report crude infection counts for each month.
B. Use standardized case definitions, risk adjustment, validation sampling,
and time-trend analyses.
C. Compare only the most recent month to a single prior month.
D. Exclude complex patients to simplify the dataset.
Answer: B
Rationale: Standardized definitions and risk adjustment reduce
misclassification and confounding; validation sampling checks data
accuracy; time-trend analyses account for secular changes. Crude counts (A)
and one-month comparisons (C) are susceptible to noise; excluding complex
patients (D) introduces selection bias. Robust EHR analyses are essential for
credible policy influence.
Key words: EHR data quality, standardization, risk adjustment, validation
6. Which collaborative strategy most effectively embeds nursing clinical
expertise into a health-system policy on pressure-injury prevention?
A. Lead a nurse-only taskforce to design the policy and then present it to
administration.
B. Convene an interprofessional policy working group including nurses,
physicians, therapists, finance, and IT to co-design the intervention.
C. Circulate a survey asking nurses for opinions and implement the plurality
response.
D. Ask a national association to draft a one-size-fits-all policy for local
adoption.
Answer: B
, Rationale: Interprofessional co-design ensures clinical relevance and
operational feasibility while securing stakeholder buy-in necessary for
implementation. A nurse-only taskforce (A) risks missing system
constraints; surveys (C) may not produce implementable plans; national
templates (D) may lack local fit. Policy that combines frontline expertise
with system stakeholders has higher success probability.
Key words: interprofessional collaboration, co-design, buy-in,
implementation readiness
7. A nurse preparing evidence to show nursing’s impact on patient outcomes
chooses which measure as the strongest indicator for a proposal to reduce
hospital readmissions?
A. 30-day all-cause readmission rate adjusted for case mix.
B. Number of nursing staff education hours completed.
C. Average daily census.
D. Number of discharge summaries written.
Answer: A
Rationale: Risk-adjusted 30-day readmission is a validated outcome measure
that reflects care transitions and nursing interventions; it is directly relevant
to patients and payers. Education hours (B) are process measures; census (C)
and document counts (D) are indirect and less informative about patient
outcomes. Outcome measures that are standardized and adjusted are most
persuasive for policy.
Key words: outcome measures, readmission, risk adjustment, policy metrics
8. When nurses report limited integration of clinical expertise into state
regulatory rule-making, which systemic barrier is most likely responsible?
A. Lack of clinical evidence about nursing interventions.
B. Limited nurse representation in policymaking bodies and advisory
committees.
C. Excessive clinical data availability.
D. High levels of public support for nursing proposals.
Answer: B
Rationale: Underrepresentation on advisory committees and policy forums
limits the infusion of clinical insights into rules. Lack of evidence (A) can be
addressed but is less commonly the primary barrier; excess data (C) or