Whenever I explain to my non-clinical colleagues how hospitals calculate nursing workload and productivity, I often use an analogy to simplify the concept. For those in clinical settings, we know the most common formula used to determine if there are enough nursing resources is this:
Total number of nursing hours worked over a 24-hour period ÷ Total number of patient bed charges dropped at midnight = Worked Hours Per Patient Day
Now, let’s apply this methodology to a different industry to illustrate how this calculation misrepresents and underestimates the actual nursing workload needed in healthcare.
Productivity Analogy: Retail
Imagine you’re opening a clothing boutique that sells pants, shirts, dresses, hats, accessories, and jewelry. To calculate how many sales associates you need to hire, let’s use the same healthcare productivity equation:
Total number of sales associate hours worked over a 24-hour period ÷ Total number of shirts sold at noon = Worked Hours Per Shirt Sold
Clearly, this would be an absurd way to determine how many sales associates your boutique needs. First, you’re missing all the shirt sales before and after noon. Second, you’re ignoring all other types of sales, like dresses and hats. Using this calculation, the boutique would be grossly understaffed.
Yet, this is exactly how many healthcare organizations approach nurse staffing—by using narrow metrics that fail to capture the full complexity of patient care. If evaluating retail productivity by one category of sales is unreasonable, why apply similarly simplistic measures in healthcare, where the stakes are infinitely higher?
The Problem with Simplistic Metrics
In retail, staff do more than sell shirts—they stock shelves, assist customers, manage returns, and sell other products. Similarly, nurses provide emotional support, coordinate care, respond to emergencies, and care for different acuity levels of patients (regardless of the type of bed charge they may have). Reducing nursing productivity to a single metric, like patient bed charges at midnight, overlooks the broader scope of their work.
These limited metrics often lead to:
- Inaccurate Staffing Models: Decisions based on incomplete data fail to address the diverse and dynamic needs of patients.
- Burnout Among Nurses: Unrealistic productivity expectations increase stress and dissatisfaction.
- Compromised Patient Care: When staffing models fail to reflect the complexity of care, patient outcomes suffer.
We Need a New Nursing Productivity Methodology
Retailers analyze trends, peak hours, and sales holistically. Healthcare should do the same. At Parity, we recognize that the current methodology for calculating nursing needs is antiquated and underestimates the resources required. We are challenging the status quo and forging a new path forward for nurses and nurse leaders.
Our nurse-developed software solution provides OB and NICU teams with real-time, acuity-based decision support to determine staffing needs based on evidence and best practices. Parity’s analytics also empower leaders with aggregated data to identify staffing barriers, enabling targeted solutions that can be implemented and monitored. For the first time, we can capture and highlight the full scope of nursing activities and their impact on care.
Why It Matters
- Better Patient Outcomes: Proper staffing ensures quality care.
- Increased Job Satisfaction: Nurses feel valued when workloads are realistic.
- Reduction in Turnover: Safe staffing ratios improve retention.
- Efficiency: Improved staffing reduces overtime and turnover costs.
Let’s Do Better
If we wouldn’t measure retail productivity by shirts sold at noon, we shouldn’t use similarly narrow metrics for nurse staffing. Parity Healthcare Analytics helps healthcare organizations adopt smarter, more realistic staffing models—because in patient care, the stakes are far higher than selling clothes.