NUR 400 Module 5 Short Paper example

Signal or Noise? Reading a Year of Unplanned Extubations on a Control Chart

[Student Name]

Southern New Hampshire University

NUR 400: Systems Leadership for Continuous Quality

Module Five Short Paper

[Instructor Name]

[Date]

The organization, setting and figures below are a composite written as a model document. No real employer, client, colleague or patient is described.

Signal or Noise? Reading a Year of Unplanned Extubations on a Control Chart

In July, the medical intensive care unit described here, an 18-bed composite, recorded eight unplanned extubations, episodes in which a patient's breathing tube came out before it was meant to, either removed by the patient or dislodged during care. The previous months had averaged about two. The nurse manager faced pressure to respond immediately with a new restraint protocol, additional sedation and a mandatory education program. Before choosing, she asked a different question: was July a sign that something had changed, or was it within the normal variation of the unit's process? Answering that question is the purpose of statistical process control, and the answer determines whether a leader should investigate a specific event or redesign the whole system.

Unplanned extubation matters because reintubation carries risks of airway injury, aspiration, low oxygen and cardiac arrest, and it is associated with longer ventilation and intensive care stays. A systematic review of unplanned extubations reported that the rates in published studies varied widely and identified agitation, inadequate sedation, physical restraint practices and insufficient staffing among factors associated with them (da Silva & Fonseca, 2012).

Defining the Measure

Because the number of ventilated patients varies from month to month, raw counts can mislead. The measure used was unplanned extubations per 100 ventilator days: the monthly count divided by the total ventilator days in that month, multiplied by 100. Ventilator days were taken from the daily census of ventilated patients, and extubation events from the unit's safety event reports, cross-checked against respiratory therapy records. Because events are counts that can occur more than once within a varying amount of exposure, a u-chart was chosen (Benneyan et al., 2003).

The Data and Calculations

Table 1 shows twelve months of data, with the rate and the upper control limit for each month.

Table 1

Unplanned Extubations per 100 Ventilator Days, Medical Intensive Care Unit, One Year

Note. Composite data. Lower control limits were zero in every month and are not shown.

Across the year there were 27 unplanned extubations in 4,960 ventilator days, giving a center line of 27 divided by 49.6, or 0.54 per 100 ventilator days. For each month, the control limits depend on that month's exposure. The upper limit is the center line plus three times the square root of the center line divided by the month's ventilator days in hundreds. For July, with 450 ventilator days, the calculation is 0.54 plus three times the square root of 0.54 divided by 4.5, which gives 1.59. The lower limit fell below zero in every month and was set at zero.

Interpreting the Chart

July's rate of 1.78 per 100 ventilator days falls above its upper control limit of 1.59, which signals special cause variation: something unusual likely affected the process that month. The other eleven months, ranging from 0.24 to 0.68, fall within their limits and show no run of consecutive points above or below the center line long enough to suggest a trend. They represent common cause variation, the normal fluctuation of the unit's current system, and the usual rules for detecting shifts and trends on control charts are not met (Provost & Murray, 2011).

The distinction changed the manager's response. A special cause calls for investigating what was different in July, not for redesigning the entire process on the basis of one month. Investigation found that during the first three weeks of July, the unit had six newly hired nurses on orientation, a temporary shortage of the usual sedation infusion due to a supply problem, and a new brand of endotracheal tube holder introduced by the supply department. Five of the eight events occurred on night shifts in patients receiving the substitute sedative, and four involved the new tube holder, which staff reported slipped when patients turned their heads.

Why Not Compare Months Directly?

It is tempting to compare July with June, or this year with last year, and call any difference a trend. Two-point comparisons ignore the fact that every stable process produces some months above and some below its average. A monthly count of two events can become three or one with no change in care at all. On a small unit, a single agitated patient can generate two events in a week. The control chart handles this by setting limits based on the data themselves and the exposure each month, so that only variation larger than the system normally produces is flagged. That discipline protects staff from being blamed for random bad months and protects managers from celebrating random good ones, which is especially important when results are posted publicly on the unit or reported to hospital leadership.

Implications for Improvement

The chart and investigation led to targeted actions rather than a unit-wide overhaul: the supply department returned to the previous tube holder, pharmacy restored the usual sedation infusion and developed a plan for future shortages, and orientation added a session on securing tubes and assessing agitation at night. A broad restraint protocol was not adopted, because restraints have not been shown to prevent unplanned extubation reliably and carry their own risks.

The chart also tells the manager something about the stable months. A rate of about 0.54 per 100 ventilator days is what the current system produces. If the unit wants a lower rate, it will need a system change, such as structured sedation and delirium assessment or consistent tube-securement practice, and the chart will then be used to see whether the new process shifts the center line downward. Continuing to plot the data monthly, and marking the dates of each change on the chart, will allow the team to separate real improvement from chance (Benneyan et al., 2003).

Conclusion

Statistical process control helped a nurse leader avoid two common errors: overreacting to ordinary variation and underreacting to a true signal. Plotting unplanned extubations per 100 ventilator days on a u-chart showed that July was a special cause, traced to a new tube holder and a sedation shortage, while the other months reflected a stable system. Targeted fixes addressed July, and the chart now provides a baseline for testing system changes that could lower the rate over time.

References

Benneyan, J. C., Lloyd, R. C., & Plsek, P. E. (2003). Statistical process control as a tool for research and healthcare improvement. Quality and Safety in Health Care, 12(6), 458-464. https://doi.org/10.1136/qhc.12.6.458

da Silva, P. S. L., & Fonseca, M. C. M. (2012). Unplanned endotracheal extubations in the intensive care unit: Systematic review, critical appraisal, and evidence-based recommendations. Anesthesia & Analgesia, 114(5), 1003-1014. https://doi.org/10.1213/ANE.0b013e31824b0296

Provost, L. P., & Murray, S. K. (2011). The health care data guide: Learning from data for improvement. Jossey-Bass.