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Molecular Biology

Staffing & Productivity

In laboratory administration, the management of personnel is an exercise in resource allocation. The goal is to align the number of staff (Supply) with the volume of testing (Demand) to ensure patient results are released within the Turnaround Time (TAT) targets, while minimizing financial waste. Unlike the automated Core Laboratory, Molecular Biology presents unique staffing challenges due to long incubation times, complex manual techniques, and the necessity of batch processing. Understanding how staffing levels are calculated and how productivity is measured is essential for the laboratory scientist to understand the operational constraints of the department

The Full-Time Equivalent (FTE)

Staffing levels are not measured in “people” but in “Full-Time Equivalents” (FTEs). This is a standardized unit of measure that accounts for full-time, part-time, and per-diem employees in a single calculation. It is the basis for the laboratory budget

  • Defining the FTE
    • One FTE represents 2,080 paid hours: per year (40 hours/week \(\times\) 52 weeks/year)
    • A part-time employee working 20 hours a week represents 0.5 FTE
    • To determine how many staff are needed, the manager divides the total hours of work required by 2,080
  • Paid vs. Worked Hours (Productive vs. Non-Productive)
    • Paid Hours (Gross FTE): The total hours the laboratory pays for. This includes vacation, sick leave, holidays, and training time
    • Worked Hours (Productive FTE): The actual hours the employee is physically present at the bench performing tests. Typically, only about 85% to 90% of paid hours are “productive.”
    • Administration Insight: When staffing a bench, the manager must account for this “Non-Productive” time. To cover one 24/7 bench position (168 hours/week), it takes approximately 4.2 to 4.5 FTEs, not just 3, to account for vacation and sick coverage

Workload Measurement

To justify hiring staff, the laboratory must quantify the “Workload.” Simply counting the number of patient samples is often insufficient in Molecular Biology because the complexity varies wildly between tests (e.g., a rapid Flu PCR takes 5 minutes of hands-on time; an NGS leukemia panel takes 8 hours)

  • Billable Tests vs. Total Workload
    • Billable Tests: The number of patient results reported to insurance. This is the revenue metric
    • Total Workload: The actual work performed. This includes patient samples plus Quality Control (QC), calibrations, repeats, and standards. In molecular batch testing, the ratio of QC to patients can be high. If a lab runs 10 patients and 3 controls, the “Billable” count is 10, but the “Workload” is 13
  • Unit Values (CAP Load Management)
    • Historically known as “CAP Units,” this system assigns a time value to every activity
    • Definition: 1 Unit = 1 Minute of technical or clerical time
    • Application: If a COVID extraction takes 15 minutes, it is assigned 15 units. The manager sums the total units for the month and divides by 60 to find the total “Man-Hours” required. This provides the data needed to ask Hospital Administration for more staff

Productivity Metrics

Productivity is the ratio of output (test results) to input (labor hours). Managers monitor these metrics to determine if the lab is overstaffed (inefficient) or understaffed (dangerous)

  • Tests Per FTE
    • A calculation of volume divided by staff: \(\frac{\text{Total Billable Tests}}{\text{Total FTEs}}\)
    • Benchmarking: Labs compare their numbers to national averages (e.g., CAP LMIP data). If the average molecular lab produces 5,000 tests/FTE and your lab produces 2,000 tests/FTE, you are likely overstaffed or utilizing inefficient manual methods
  • Labor Cost Per Test
    • The total salary expense divided by the testing volume. This is a critical financial metric. Automating a manual DNA extraction process usually increases supply costs but drastically lowers labor costs, improving overall productivity
  • Utilization Rates
    • Laboratories generally aim for 80-85% productivity
    • Under 80%: Staff have too much downtime (inefficient)
    • Over 90%: Staff are overworked. At this level, error rates increase, burnout occurs, and there is no “slack” to handle a sudden surge in volume (e.g., an outbreak)

Staffing Strategies in Molecular Biology

Molecular workflows dictate specific staffing patterns that differ from the random-access nature of Hematology or Chemistry

  • Fixed vs. Variable Staffing
    • Fixed Staffing: The minimum number of personnel required to open the doors and maintain regulatory compliance, regardless of volume. For example, you always need one person to monitor the alarms, even if zero tests are ordered
    • Variable Staffing: Staff added to handle increased volume. In molecular, this is often seasonal (e.g., hiring temporary staff during respiratory virus season)
  • Batch-Based Scheduling
    • Because many molecular assays (like 96-well plate PCR) have fixed run times of 3 to 5 hours, staffing schedules must overlap with these distinct blocks of time
    • Staggered Shifts: Instead of a traditional 7:00 AM – 3:30 PM shift for everyone, molecular labs often stagger start times (e.g., 7:00 AM, 9:00 AM, 11:00 AM) to ensure that someone is fresh and available to start the next run or perform post-amplification analysis late in the day
  • Skill Mix (The “Tech” vs. The “Assistant”)
    • To improve productivity/cost, labs utilize a mix of laboratory scientists (MLS) and Lab Assistants (MLA)
    • Scope: The MLA performs pre-analytical work (accessioning, loading automated extractors). The laboratory scientist performs high-complexity tasks (result interpretation, releasing data, troubleshooting). This ensures the highest-paid staff (MLS) focus only on the most complex tasks

Challenges to Productivity

Several factors in the molecular environment can artificially lower productivity numbers, requiring explanation to administration

  • Validation and QA
    • Molecular labs run a high number of Laboratory Developed Tests (LDTs). Validating these assays requires weeks of laboratory scientist time where they are “working” but producing zero “billable patient results.” This can make productivity look low on paper
  • Dead Time (Incubation)
    • Molecular assays often have long passive incubation periods (e.g., 2 hours for amplification). During this time, the staff member may appear “idle.” Efficient management requires “Task Stacking” - assigning administrative duties (QA reviews, inventory) during these instrument run times