NURS 626 Week 5 Capstone Project Part 3: Outline Example

Capstone Outline: From Ratios to Acuity, Implementing a Validated Patient Acuity Tool for Nurse Assignments on Two Medical-Surgical Units

Overview of the Project

This outline sets out the components of a capstone project that swaps assignments based only on patient counts for assignments guided by a tested acuity measure. It follows the order the Week 7 presentation will take, from the problem and the evidence to the intervention, implementation, evaluation, budget, ethics and Christian worldview. The project's central claim is simple: five patients is a count, not a workload, and fair assignments require measuring the second. Sources are the studies annotated in Part 2, cited where they support a point.

I. Problem Statement

A. Current practice on 4 North and 5 North

• 1. Each unit has 30 beds, and charge nurses give every nurse five patients by bed location and continuity
• 2. No structured measure of patient care needs is used for assignments or for shift-to-shift staffing requests

B. Evidence of the problem on the units

• 1. In a three-month staff survey, 71% of nurses rated assignments as unfair at least once a week
• 2. Falls with injury on the two units ran above the hospital's medical-surgical benchmark in four of the last six quarters
• 3. Exit interviews from eleven departures last year cited heavy, uneven assignments in seven cases

C. Why ratios alone fall short

• 1. How hard nurses work, more than any fixed ratio, may be what predicts patient outcomes (Greaves et al., 2026)
• 2. On medical-surgical units, nurses' perceived staffing adequacy tracked fall rates when hours per patient day did not (Lake et al., 2026)

II. Purpose and Project Question

A. Purpose

• 1. Implement a validated patient acuity tool for nurse assignments and staffing requests on 4 North and 5 North

B. Project question

• 1. Among nurses on two medical-surgical units, does using a validated acuity tool for assignments, compared with ratio-only assignments, improve perceived equity of assignments and staffing adequacy over six months?

C. Objectives

• 1. Select and locally validate one acuity tool by month 2
• 2. Reach 85% weekly use of the tool for assignments by month 4
• 3. Improve perceived assignment equity by 20% from baseline by month 6

III. Review of the Evidence

A. Acuity, staffing and outcomes

• 1. Staffing measured against acuity-based required hours was protective against nursing-sensitive adverse events in 6,873 cardiac inpatients (Asensio-Flores et al., 2026)
• 2. A Turkish time-motion study found care intensity drove one ward's workload and patient volume the other's (Biyik et al., 2026)

B. Validity of acuity tools

• 1. Each one-point rise in a classification score was associated with 7.45 more minutes of measured care after accounting for ward clustering in 472 patients (Zaboli et al., 2026)
• 2. A gastroenterology tool built on Orem and Henderson was checked against timed care in 357 patients (Ren et al., 2026)

C. Implementation and staff outcomes

• 1. A locally adapted tool reached 88% median weekly compliance over 24 weeks and improved perceived workload and equity (Lim et al., 2026)

D. Cost

• 1. Daily nursing cost averaged $586.23 per patient and rose with acuity and patient load (Lee et al., 2026)

IV. Intervention: Selecting the Tool

A. Selection criteria

• 1. Published validation against measured nursing time
• 2. Five to eight criteria that a charge nurse can score in under two minutes per patient
• 3. Ability to export scores to the staffing office

B. Local validation

• 1. Two-day time study on each unit, following the method of Zaboli et al. (2026)
• 2. Adjust weighting only with the vendor or authors' guidance

C. Charge nurse involvement

• 1. Six charge nurses from both shifts serve on the selection team
• 2. Charge nurses keep authority to override a tool-based assignment with a documented reason

V. Implementation Plan

A. Preparation, months 1 and 2

• 1. Education for all 64 nurses through two 30-minute sessions and a pocket guide
• 2. Inter-rater check: two charge nurses score the same ten patients each week until agreement reaches 90%
• 3. Baseline survey of perceived workload, equity and staffing adequacy
• 4. Super-user charge nurses named on each shift to answer questions during the first month

B. Plan-Do-Study-Act cycles, months 3 to 6

• 1. Cycle 1: day shift on 4 North only
• 2. Cycle 2: both shifts on 4 North
• 3. Cycle 3: both units, with scores sent to the staffing office every shift

C. Leadership practices during rollout

• 1. Model the way: managers score patients themselves on the first shifts
• 2. Encourage the heart: recognize the units' compliance milestones publicly (Kouzes & Posner, 2017)

VI. Evaluation

A. Process measure

• 1. Weekly percentage of assignments made with the tool

B. Staff outcomes

• 1. Perceived workload, assignment equity and staffing adequacy at baseline, 3 months and 6 months

C. Patient outcomes

• 1. Injurious falls and unit-acquired pressure injuries, each expressed as a rate per thousand days of patient care, set against the six months before the change
• 2. Missed care items reported at the end of shift, sampled one week each month

D. Financial measure

• 1. Agency and overtime hours per patient day, and variance between required and staffed hours

VII. Budget and Sustainability

A. Costs

• 1. Tool license and electronic record build, estimated at $28,000 in year one
• 2. Education time, about 130 paid hours
• 3. Charge nurse time for the time study and inter-rater checks, about 60 paid hours

B. Expected return

• 1. Each 0.1 reduction in agency hours per patient day across both units would offset the license cost within the first year
• 2. Retaining two nurses who would otherwise leave avoids replacement costs well above the project budget

C. Sustainability

• 1. Monthly compliance reports to the director and quarterly review by the unit councils
• 2. Acuity data incorporated into the next variable staffing budget (Roussel et al., 2020)

VIII. Ethical Considerations

A. Use of workload data

• 1. Acuity scores describe patients, not nurses, and will not be used to rate individual performance
• 2. Future use of electronic record audit logs to measure workload would require staff consultation first (Tiase et al., 2026)

B. Professional judgment

• 1. The tool informs assignments; the charge nurse remains accountable for them

IX. Christian Worldview

A. Fairness in bearing burdens

• 1. Paul asked the Corinthian church to give out of its plenty to believers in want, calling it fairness (English Standard Version Bible, 2001/2016, 2 Corinthians 8:13-14)
• 2. Assignments that load one nurse with the heaviest patients fail that standard even when the ratio is equal

B. Stewardship of nurses and patients

• 1. Matching staff to need protects nurses from exhaustion and patients from missed care
• 2. The administrator's role is to make the burden visible so it can be shared

References

Asensio-Flores, S., Adamuz, J., Soldevila-Cases, R., Castellà-Creus, M., Zuriguel-Perez, E., Polushkina-Merchanskaya, O., Delgado-Hito, P., & Juvé-Udina, M. E. (2026). Associations of safe nurse staffing coverage and care complexity factors with nursing-sensitive adverse events in cardiac inpatients: A cross-sectional multicenter study. Frontiers in Cardiovascular Medicine, 13, Article 1810207. https://doi.org/10.3389/fcvm.2026.1810207

Biyik, M., Durmuş, E., Ersoy, P., & Aslan, M. (2026). Nursing workload and optimal staffing in medical and surgical wards: A time-motion study using a patient classification system. Journal of Nursing Management, 2026(1), Article e3918250. https://doi.org/10.1155/jonm/3918250

English Standard Version Bible. (2016). Crossway. (Original work published 2001)

Greaves, P. J., Erfani, G., Simpson, D., Hill, B., Conner, T., Nemeckova, M., McCerery, A., Rolf, F., Monk, D., & Steven, A. (2026). Nursing in adult critical care services: Safe staffing evidence: A rapid review. Intensive and Critical Care Nursing, 98, Article 104585. https://doi.org/10.1016/j.iccn.2026.104585

Kouzes, J. M., & Posner, B. Z. (2017). The leadership challenge: How to make extraordinary things happen in organizations (6th ed.). Wiley.

Lake, E. T., Pascale, A., Warshawsky, N. E., Henderson, J. G., Smith, J. G., Staiger, D., Perez, Y., Venkataswamy, E., & Rogowski, J. A. (2026). Association of objective and subjective nurse staffing metrics with patient fall rate by unit type. Nursing Outlook, 74(3), Article 102750. https://doi.org/10.1016/j.outlook.2026.102750

Lee, S. Y., Park, C. G., Boyd, A. D., Quinn, L. T., Stogis, S. L., Davila, A., & Collins, E. G. (2026). Patient-level nursing cost analysis and cost drivers in acute care: A retrospective longitudinal study. Nursing Outlook, 74(2), Article 102684. https://doi.org/10.1016/j.outlook.2026.102684

Lim, Y. Y., Docherty, S. L., Huey Cheng, J. J. S., & Turner, B. (2026). Implementation and evaluation of a patient acuity tool in pediatric oncology. Journal of Pediatric Hematology/Oncology Nursing, 43(3), 178-188. https://doi.org/10.1177/27527530251408820

Ren, H. F., Wei, M. F., Shen, M., Lv, L., Hu, Y., Li, Y. P., Liu, C. Q., & Jiang, Y. (2026). Development of a machine learning-based patient classification system for a gastroenterology ward. Journal of Nursing Management, 2026(1), Article e2039402. https://doi.org/10.1155/jonm/2039402

Roussel, L. A., Thomas, P. L., & Harris, J. L. (2020). Management and leadership for nurse administrators (8th ed.). Jones & Bartlett Learning.

Tiase, V. L., Sward, K. A., Li, J., & Facelli, J. C. (2026). Quantitative insights from nursing workload measurement: An artificial intelligence-driven approach. Military Medicine, 191(Supplement 1), 543-548. https://doi.org/10.1093/milmed/usag168

Zaboli, A., Solazzo, P., Rigger, M., Vidi, M., Ruzzante, D., Macciocu, C., Piva, M., Innerhofer, H., Ziller, M., Lioni, R., Turcato, G., & Siller, M. (2026). Association between the PERROCA patient classification system and nursing workload: A multicentre cross-sectional study. Applied Nursing Research, 90, Article 152114. https://doi.org/10.1016/j.apnr.2026.152114