Performance of Nursing Activities Score in intensive care units of a teaching hospital in a low-middle-income country: An observational study

This observational study of 501 ICU patients in a teaching hospital within a low-middle-income country demonstrates that the Nursing Activities Score (NAS) is a reliable tool for assessing nursing workload and effectively predicting patient mortality, with non-survivors exhibiting significantly higher scores than survivors.

The Gist

Imagine the Intensive Care Unit (ICU) as the engine room of a hospital. It's where the sickest patients are kept, surrounded by beeping machines, IV drips, and life-support systems. In this high-stakes environment, the nurses are the engineers keeping the ship running.

But here's the problem: Sometimes, there are too many broken engines (sick patients) and not enough engineers (nurses). If an engineer is trying to fix three broken engines at once, things start to go wrong. The ship might sink, or the patients might not survive.

This study, conducted in a teaching hospital in Nepal (a country with fewer resources than places like the US or UK), asked a simple but vital question: "How do we know exactly how much work our nurses are doing, and does that workload tell us if a patient will live or die?"

To answer this, they used a tool called the Nursing Activities Score (NAS). Think of NAS as a "Workload Thermometer."

The "Workload Thermometer" (NAS)

Instead of just guessing, "Oh, Nurse Sarah looks busy," the NAS gives every patient a score based on exactly what the nurse has to do for them in a day.

• Low Score: The patient is stable. The nurse just checks their pulse and changes their sheets. (Like a car needing a quick oil change).
• High Score: The patient is critical. The nurse has to adjust ventilators, give complex medications, and monitor them every minute. (Like a race car engine that needs constant, expert tuning).

The study looked at 501 patients and measured this "thermometer" for each one.

What They Found

1. The Engine Room is Overheated: The average score was very high. This means the nurses were working incredibly hard, often managing patients who needed constant, intense care. It's like the engine room is running at 100% capacity all the time.
2. The Thermometer Predicts the Future: The researchers discovered that this "Workload Thermometer" is actually a crystal ball.
   • Patients who survived had lower scores (less work needed).
   • Patients who did not survive had much, much higher scores (they needed a massive amount of nursing care).
   • The Analogy: If you see a car engine smoking heavily and needing a mechanic to run around it frantically, you know that car is in deep trouble. The NAS score is that smoke. A high score didn't just mean "the nurse is busy"; it meant "the patient is very sick."

The "Magic Number"

The study found a specific "danger zone" on the thermometer: 90.4.

• If a patient's score goes above 90.4, they are in the danger zone. The study found that nurses could use this number to predict, with about 73% accuracy, that a patient might not make it.

Why This Matters (The "So What?")

In many countries, hospitals don't have enough nurses. They often just guess how many nurses to schedule for a shift. This study suggests they should stop guessing and start using the NAS Thermometer.

• Before: "We have 10 patients, so we need 3 nurses." (Guessing).
• After: "We have 10 patients, but their total NAS score is huge. We actually need 5 nurses to keep everyone safe." (Data-driven).

The Big Takeaway

This research is like installing a dashboard warning light in a hospital.

• If the light turns red (high NAS score), it tells the hospital managers: "Hey, this patient is critical, and our nurses are stretched too thin. We need more help right now, or the patient might not survive."

By using this tool, hospitals in places like Nepal (and anywhere else) can:

1. Save Lives: By spotting the sickest patients early.
2. Protect Nurses: By ensuring they aren't overwhelmed, which prevents burnout and mistakes.
3. Use Resources Wisely: By putting the right number of nurses in the right places at the right time.

In short, the study proves that measuring the work nurses do isn't just about paperwork; it's a life-or-death tool that helps hospitals run smoother and keeps patients safer.

Technical Summary

1. Problem Statement

Intensive Care Units (ICUs) in Low- and Middle-Income Countries (LMICs), particularly in Nepal, face significant challenges regarding nurse staffing shortages and excessive workloads. These conditions often lead to compromised patient safety, increased mortality rates, and nurse burnout. While the Nursing Activities Score (NAS) is a validated international tool for quantifying nursing workload and estimating time requirements, its application and predictive validity in resource-limited LMIC settings remain under-researched. There is a critical lack of objective data to guide staffing optimization and resource allocation in Nepalese ICUs, necessitating a study to validate NAS as a tool for workload assessment and mortality prediction in this specific context.

2. Methodology

• Study Design: Prospective observational study.
• Setting: ICU of a tertiary care teaching hospital in Chitwan, Nepal.
• Participants: 501 critically ill patients (aged ≥18 years) admitted between March 7, 2022, and February 27, 2023.
  • Inclusion: Patients requiring continuous monitoring/interventions with a stay of ≥24 hours.
  • Exclusion: Discharge/death within 24 hours, transfers, or missing data.
• Instrument: The Nursing Activities Score (NAS), which quantifies workload based on 23 specific nursing interventions weighted by time. Scores range from 0% to 177%, representing the percentage of a nurse's time dedicated to a single patient over 24 hours.
• Data Collection: Demographics, clinical condition, length of stay (LOS), NAS scores, and discharge status (Survivor vs. Non-survivor).
• Statistical Analysis:
  • Descriptive statistics (Median, IQR) for continuous variables.
  • ROC Curve Analysis: To evaluate predictive accuracy (AUROC), sensitivity, and specificity.
  • Hosmer–Lemeshow Test: To assess model calibration (goodness-of-fit).
  • Logistic Regression: To determine the association between NAS scores and mortality risk (Odds Ratio).
  • Mann–Whitney U Test: To compare NAS scores between survivors and non-survivors.
• Ethics: Approved by the Lincoln University College and Nepal Health Research Council; written consent obtained.

3. Key Contributions

• First Regional Validation: This is the first study to systematically assess ICU nursing workload using NAS in Nepal, filling a significant knowledge gap in LMIC literature.
• Predictive Modeling: It establishes NAS not just as a workload metric, but as a robust predictor of patient mortality in a resource-constrained setting.
• Evidence for Staffing: Provides data-driven evidence linking high NAS scores to increased mortality, supporting the need for optimized nurse-to-patient ratios in LMICs.

4. Key Results

• Workload Intensity: The median NAS score was 83.40 (IQR: 68.30–101.10; Range: 39.2–134.4), indicating a high level of nursing workload.
• Predictive Accuracy:
  • AUROC: 0.838 ($p < 0.001$), indicating good discriminatory power.
  • Optimal Cut-off: A NAS score of 90.40 yielded 73.5% sensitivity and 73.1% specificity for predicting mortality.
• Model Fit: The Hosmer–Lemeshow test showed a non-significant difference between observed and predicted outcomes ($p = 0.422$), confirming a good model fit.
• Mortality Association:
  • Logistic Regression: Higher NAS scores were significantly associated with increased mortality risk (Exp(B) = 0.937, $p < 0.001$).
  • Group Comparison: Non-survivors had a significantly higher median NAS (110.70) compared to survivors (76.20) ($p < 0.001$).
• Demographics: The cohort included 501 patients (61.1% male); 36.9% died, and 63.1% survived. The median Length of Stay was 6 days.

5. Significance and Implications

• Clinical Utility: The study confirms that NAS is a reliable tool for identifying critically ill patients at high risk of mortality. A score above 90.40 serves as a critical threshold for heightened monitoring and resource allocation.
• Workforce Management: The findings highlight that high NAS scores reflect greater patient severity and dependency rather than improved care efficiency. In LMICs where nurse-to-patient ratios often exceed recommended standards (e.g., 1:3), these results argue for dynamic staffing models based on real-time workload scores rather than static ratios.
• Policy Impact: Integrating NAS into routine ICU management can help hospital administrators justify staffing needs, reduce nurse burnout, and potentially lower mortality rates by ensuring adequate resources for high-acuity patients.
• Future Directions: The authors recommend multi-center validation and longitudinal studies to refine staffing models and incorporate NAS into broader critical care quality improvement initiatives in resource-limited environments.

Conclusion: The Nursing Activities Score is a valid, reliable, and predictive tool for assessing nursing workload and patient outcomes in Nepalese ICUs. Its implementation can facilitate evidence-based staffing decisions, ultimately enhancing patient safety and survival rates in low-resource settings.