Step 1 — Understand what the formula is actually doing
The staffing formula has three moving parts: the number of patients, the average nursing care hours each patient needs per day, and the length of one shift. The product of census and care hours gives the total nursing workload for the ward in one day. Dividing by the shift length converts that workload into the number of nurse-shifts required daily. The relief factor then inflates that number so the schedule can absorb days off, sick leave, holidays, and training without falling below safe coverage.
In this ward, the average daily census is
24 mothers, and each mother requires
4 nursing care hours per day. The total daily nursing care hours are therefore
24 × 4 = 96 hours. Because each nurse works an
8-hour shift, the ward needs
96 ÷ 8 = 12 nurse-shifts per day just to meet the direct care workload.
The relief factor is not optional padding; it represents the additional staff needed to keep the same number of nurses at the bedside every day when some are legitimately absent. A relief factor of
1.6 means that for every one nurse physically present on a given shift, the organization must employ 1.6 full-time equivalents to cover weekends, vacations, and leave. Multiplying
12 × 1.6 = 19.2 gives the total number of nursing staff positions to request.
Key point! Staffing is always rounded up, never down. A calculated value of
19.2 means 19 people would leave the ward short by 0.2 full-time equivalents on average, which translates into uncovered shifts. Rounding up to
20 ensures the schedule can be filled without chronic overtime or missed coverage.
Step 2 — Why the relief factor matters in clinical staffing
The relief factor addresses a fundamental scheduling problem: a ward that needs 12 nurses on duty every day cannot function with only 12 nurses on the payroll. If every nurse works five shifts per week, the ward must cover seven days, meaning weekend coverage alone requires more than the daily minimum. Add annual leave, sick days, maternity leave, and continuing education, and the gap between “nurses needed per shift” and “nurses needed on staff” grows substantially.
In the Saudi Arabian cross-sectional study of government hospitals, nursing directors consistently identified staffing shortages as a major operational challenge, and the ability to calculate shortages accurately varied with the methods used . The formula in this question is one of the standard calculation methods used to quantify that gap. The relief factor is the mathematical bridge between the clinical workload and the human reality of a workforce that cannot be present every single day.
Without a relief factor, a staffing plan based only on daily nurse-shifts systematically underestimates the number of people who must be employed to sustain that coverage. The result is either unfilled shifts or nurses working overtime, both of which are associated with adverse patient outcomes.
Step 3 — Connecting staffing calculations to patient safety
The rationale for precise staffing calculations is not administrative convenience; it is patient safety. Research on cardiac inpatient units found that achieving at least
90% of the required nursing hours per patient day was associated with fewer nursing-sensitive adverse events . When staffing falls below the calculated requirement, the risk of missed care, delayed response to deterioration, and medication errors rises.
The postpartum ward in this question has a relatively stable census, but the principle is the same: the calculated number of staff must reflect both the average workload and the variability introduced by human absence. A charge nurse who requests only 19 staff members when the calculation yields 19.2 is effectively planning for a deficit. The rounding rule exists because staffing is a threshold requirement, not a continuous variable.
Watch out! Do not round the intermediate steps. If a student rounds 96 ÷ 8 = 12 to a different number or rounds 19.2 down to 19, the final answer becomes unsafe. The correct sequence is: calculate the daily nurse-shifts first, apply the relief factor second, and round up only at the very end.
Step 4 — Comparing calculation approaches
Different staffing methods produce different numbers, and licensure exams often test whether a candidate can distinguish them. The table below contrasts the formula used in this question with two other common approaches.
| Method | What it calculates | Key feature | Example for this ward |
|---|
| Required staff formula | Total positions needed including relief coverage | Multiplies daily nurse-shifts by a relief factor | (24 × 4 ÷ 8) × 1.6 = 19.2 → 20 |
| Nurse-to-patient ratio | Number of nurses per shift based on a fixed ratio | Does not directly account for days off or leave | If ratio is 1:6, then 24 ÷ 6 = 4 nurses per shift, but total staff still needs relief coverage |
| Nursing hours per patient day (NHPPD) | Total nursing hours delivered per patient per day | Used to compare actual vs. required staffing, often with a 90% safety threshold | Required NHPPD = 4 hours; actual coverage below 3.6 hours would be considered unsafe |
The required staff formula is the only one of the three that directly produces a headcount for hiring or requesting positions. The NHPPD approach is useful for auditing whether existing staffing meets patient needs, while ratio-based methods set a minimum per shift but still require a separate relief calculation to determine total positions.
Step 5 — Why option 4 is correct and the others fail
Option
1 (8) likely results from dividing the total care hours by the shift length incorrectly or ignoring the relief factor entirely. Option
2 (12) is the daily nurse-shift requirement before relief coverage, which is a necessary intermediate step but not the final answer. Option
3 (19) is the result of rounding down from 19.2, which violates the principle that staffing must never be short.
The correct answer is 20 because the relief factor of 1.6 converts 12 daily nurse-shifts into 19.2 full-time equivalent positions, and any fractional staffing requirement must be rounded up to guarantee coverage.
The simulation and economic modelling study on flexible staffing reinforces this point: baseline staffing plans that underestimate the required number of nurses force reliance on temporary hires or floating staff, which is less cost-effective and less safe than building adequate relief into the baseline roster . The charge nurse who requests 20 staff members is planning for sustainability, not just for an average day.