# Situation: A nurse works in the delivery room of a provincial hospital that is a comprehensive emergency obstetric and newborn care (CEmONC) referral facility. The delivery room team ran a quality improvement project aimed at reducing postpartum hemorrhage among women giving birth in the hospital. Comparing the quarter before with the quarter after the change, which result gives the BEST evidence that the aim was achieved?

> source: MyMerci (mymerci.kr)  
> url: https://mymerci.kr/pages/nclex_q.php?qn_id=629614  
> language: ko  
> subject: Nursing Practice II — Maternal and Child Health Nursing

## 문제

Situation: A nurse works in the delivery room of a provincial hospital that is a comprehensive emergency obstetric and newborn care (CEmONC) referral facility.

The delivery room team ran a quality improvement project aimed at reducing postpartum hemorrhage among women giving birth in the hospital. Comparing the quarter before with the quarter after the change, which result gives the BEST evidence that the aim was achieved?

## 보기

1. Hemorrhage rate fell from 3.0 to 1.8 per 100 births; births were similar **✔ 정답**
2. Hemorrhage cases fell from 30 to 24, while births fell from 1,000 to 600
3. Timely oxytocin rose from 70% to 98% of births between the two quarters
4. All delivery room staff completed a refresher course on the third stage

**정답: 1**

## 해설

The aim is an outcome, so the best evidence is an outcome measure expressed as a rate. A fall from 3.0 to 1.8 hemorrhages per 100 births with similar numbers of births shows real improvement. Raw counts can mislead: 30 of 1,000 births is 3.0 per 100, but 24 of 600 is 4.0 per 100, a rise. Better oxytocin timing (process) and staff training (structure) support improvement but do not show that the aim was met.

## 심화 해설

Why the rate—not the raw count—is the best evidence

The project’s stated aim is to reduce postpartum hemorrhage (PPH) among women giving birth in the hospital. That is an outcome aim, so the strongest evidence must be an outcome measure expressed as a rate per 100 births. A rate adjusts for how many women actually delivered during each period, which lets the team compare performance fairly even if delivery volume changed.

Option 1 shows a fall from 3.0 to 1.8 hemorrhages per 100 births while the number of births remained similar, which is a true reduction in the frequency of PPH. The denominator is stable, so the change in the numerator reflects a genuine improvement in outcomes rather than a change in patient volume.

Why raw counts can mislead

Option 2 appears to show fewer hemorrhage cases—30 down to 24—but the number of births also fell sharply, from 1,000 to 600. Converting to rates reveals the problem:

| Quarter | Hemorrhage cases | Births | Rate per 100 births |
| --- | --- | --- | --- |
| Before | 30 | 1,000 | 3.0 |
| After | 24 | 600 | 4.0 |

The hemorrhage rate actually rose from 3.0 to 4.0 per 100 births, so the outcome worsened despite the smaller raw count. Watch out! In quality-improvement data, a falling numerator can hide a rising rate when the denominator shrinks. Always calculate the rate before declaring success.

Process and structure measures support—but do not prove—the outcome

Option 3 reports that timely oxytocin administration rose from 70% to 98% of births. This is a process measure: it shows the team is delivering a recommended intervention more consistently. Option 4 reports that all delivery room staff completed a refresher course on the third stage of labor. This is a structure measure: it shows the environment or workforce capacity changed.

Both are valuable in a quality-improvement project. Improved uterotonic availability and staff education can plausibly contribute to fewer hemorrhages, as quality-improvement evaluations of evidence-based PPH protocols and uterotonic access strategies suggest . However, a process or structure measure alone does not confirm that the clinical outcome—the actual PPH rate—improved. The team could administer oxytocin perfectly and still see no change in hemorrhage rates if other factors are at play.

Linking measures to the aim

A well-designed improvement project tracks all three types of measures, but the outcome measure is the one that directly answers whether the aim was achieved. In this scenario, the aim is explicitly about reducing PPH, so the rate of hemorrhage per 100 births is the most direct evidence. A clinical pathway implementation study similarly evaluated PPH outcomes before and after the intervention by comparing actual hemorrhage-related results, not just whether staff followed the pathway .

Key point! When a project aims to reduce a clinical event, the best evidence of success is a change in the outcome rate, not a change in raw counts, process compliance, or training completion.

## 임상 시나리오

PPH Quality Improvement: Choosing the Right MeasureRate vs. count for outcome evaluation
The aim is an outcome, so use an outcome measure expressed as a rate per 100 births. A fall from 3.0 to 1.8 with stable births shows true improvement.

Raw counts mislead when the denominator changes. 30 of 1,000 is 3.0 per 100, but 24 of 600 is 4.0 per 100—a rise, not a fall.

CautionAlways calculate the rate before declaring success. Process measures (timely oxytocin) and structure measures (staff training) support but do not prove the outcome aim was met.

## 핵심 개념

- **Outcome measure** — A measure of the end result of care, such as hemorrhage rate per 100 births
- **Process measure** — A measure of whether a step in care was performed, such as timely oxytocin administration
- **Structure measure** — A measure of resources or capacity, such as staff training completion
- **Rate per 100 births** — Number of events divided by total births, multiplied by 100, to allow fair comparison
- **Denominator** — The total population at risk, such as total births in a quarter

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