NUR 5053 Module 3 Failure Mode and Effects Analysis Example

Nine Steps Between the Order and the First Feeding: A Healthcare Failure Mode and Effect Analysis of Bedside Small-Bore Feeding Tube Placement

Student Name

American College of Education

NUR5053: Quality Improvement and Safety

Module 3 Assignment

Instructor Name

October 27, 2026

Why This Process, and Why Look Forward

The root cause analysis completed in the previous module examined one event: a patient fed for four hours through a tube lying in her right lower lobe bronchus. That analysis explained how one failure happened. It could not say how else the same process might fail, and a unit that fixes only the path its last accident took leaves the other paths open. A prospective method starts from the process instead of the event and asks, step by step, what could go wrong, how badly and how often.

Bedside placement of small-bore feeding tubes meets every criterion for choosing a process to study this way. It is done often on this composite 30-bed neuroscience step-down unit, roughly 25 insertions a month. Its worst outcome is death or serious injury. It depends on several departments, since nursing inserts the tube, radiology confirms it, informatics builds the order and pharmacy and nutrition services supply the formula. It also relies on tacit knowledge, such as how far to advance a tube or what a completed imaging order means, that newer nurses learn from whoever happens to be on shift.

Method and Team

The analysis used Healthcare Failure Mode and Effect Analysis (HFMEA), the version built by the patient safety center of the Department of Veterans Affairs (DeRosier et al., 2002). HFMEA follows the familiar sequence of defining the topic, assembling a team, mapping the process and listing failure modes, but it replaces the three-factor risk priority number of engineering FMEA with a hazard score, the product of severity and probability each rated from 1 to 4, and then passes every failure mode scoring 8 or higher through a decision tree. The tree asks whether the failure is a single point of weakness, whether an effective control already exists and whether the hazard is so obvious that no control is needed.

This choice was deliberate. Franklin et al. (2012) reviewed the evidence behind classic FMEA and concluded that its numerical ranking lacks both reliability and validity, while the multidisciplinary mapping stage appears to be where the value lies. In a direct test, two hospital teams analyzing the same medication process each listed 50 failures, only 17 of which appeared on both lists, and scored them so differently that their priorities diverged (Shebl et al., 2009). The team therefore treated the scores as a structured way to argue about priorities, not as measurements, and recorded the reasoning behind each one.

The team met four times for 90 minutes. It included two staff nurses from the unit, one of them in her first year, the clinical nurse specialist, a radiology technologist, a night-shift radiologist who joined by video, an informatics nurse from the clinical systems team, a registered dietitian and, as sponsor, the unit manager. A patient safety specialist facilitated. Every member walked the process on the unit before the second meeting, and the new graduate nurse described each step as she had been taught it, which turned out to differ from the policy at two points.

The Process Map

The team mapped nine steps. First, the provider writes an order for tube placement and enteral nutrition. Second, the nurse assesses the patient's risk, including alertness, cough, swallow and any airway device. Third, the nurse measures and inserts the tube using the blind technique. Fourth, the nurse checks the bedside signs available, such as the patient's breathing and the appearance and pH of any aspirate. Fifth, the nurse orders a confirming radiograph. Sixth, the technologist acquires the image. Seventh, the radiologist reads it and files a result. Eighth, the nurse receives the result, marks the tube at the nostril and secures it. Ninth, the nurse starts the feeding and continues to check tube position at set intervals.

Two of these steps existed only in practice. The written policy said nothing about risk assessment at step two, and at step eight it did not say how a result reaches the nurse, which is precisely the gap the Module 2 event fell through. A process map drawn from policy alone would have missed both of the places where this unit's process is weakest.

Failure Modes and Hazard Scores

The team listed 23 failure modes across the nine steps. Eleven scored below 8 and were set aside, among them an order written without a formula and a tube taped too loosely. Twelve scored 8 or higher. The five highest are described here with their scores.

At step two, a high-risk patient is not recognized as high risk, so a blind insertion goes ahead in a patient whose weak cough will not signal an airway placement. Severity was rated catastrophic (4) and probability occasional (3), for a hazard score of 12. At step four, the nurse treats a bedside sign such as auscultation or the absence of coughing as confirmation. Metheny et al. (2019) found that all 14 national guidelines they reviewed ranked radiography as the most accurate confirmation method and auscultation as the least favored of the bedside checks, yet the new nurse on the team had been taught to listen. Severity 4, probability 3, score 12.

At step seven, the radiograph is read hours after it is taken because it has no priority, which tempts staff to start feeding on the strength of the bedside signs. Severity 3, probability 4, score 12. At step eight, the nurse reads an imaging status of Completed as a filed result, which is how the Module 2 event began. Severity 4, probability 3, score 12. At step nine, a tube that was correctly placed migrates upward after vomiting or a coughing spell and is not rechecked before the next bolus or after the pump restarts. Severity 4, probability 2, score 8.

The team debated the step seven score longest. The radiologist argued that a delayed read harms no one by itself. The nurses argued that the delay is the pressure that produces the step four and step eight failures, and the group recorded both views and kept the score. That discussion was worth more than the number.

The Decision Tree and the Actions

All five failure modes passed the decision tree as needing action. Four were single points of weakness, meaning one failure alone would cause harm, and none had an effective existing control: the policy's instruction to confirm placement was a rule, not a barrier. Only the migration failure at step nine had a partial control, since nurses already measured the external tube length each shift, but the measurement was not required after vomiting or before restarting a paused feed.

The actions follow the logic HFMEA asks for: eliminate the hazard where possible, control it where not and accept it only with a stated reason. For the recognition failure, a required risk screen will be added to the placement order, and a positive screen will route the insertion to nurses trained in electromagnetically guided placement. For the bedside-sign failure, the policy will state that no bedside method confirms position, and the placement competency will be rebuilt on the model Powers et al. (2021) developed with the backing of ASPEN, the national enteral nutrition society, which documents training and competency for every clinician who places these tubes. For the delayed read, radiology will create a feeding tube priority with a 60-minute target. For the status failure, the feeding order will stay locked until a radiologist's result is filed, the forcing function already proposed in Module 2. For migration, an external length check will be required before any feed resumes after vomiting, retching or a pause longer than an hour.

Each action has an owner and an outcome measure, and the first two will be tested before the others because they block the most severe failures. An FMEA earns its time only if its last page reads like a work plan. The next module turns the forcing function and the risk screen into a formal improvement project with an aim and a first test of change.

Limits of This Analysis

The scores came from one team on one unit and would probably differ if another team repeated the exercise, which is the central weakness Shebl et al. (2009) documented. The analysis also covered only nasal small-bore tubes placed at the bedside and left out tubes placed in radiology or endoscopy, where different failures occur. Finally, prospective analysis can name what might fail but cannot show how often it does; that requires the reporting culture the Module 1 appraisal found to be weak. The team's list of failure modes should be revisited after six months of reported events to check which of its predictions came true.

References

DeRosier, J., Stalhandske, E., Bagian, J. P., & Nudell, T. (2002). Using health care failure mode and effect analysis: The VA National Center for Patient Safety's prospective risk analysis system. The Joint Commission Journal on Quality Improvement, 28(5), 248-267. https://doi.org/10.1016/S1070-3241(02)28025-6

Franklin, B. D., Shebl, N. A., & Barber, N. (2012). Failure mode and effects analysis: Too little for too much? BMJ Quality & Safety, 21(7), 607-611. https://doi.org/10.1136/bmjqs-2011-000723

Metheny, N. A., Krieger, M. M., Healey, F., & Meert, K. L. (2019). A review of guidelines to distinguish between gastric and pulmonary placement of nasogastric tubes. Heart & Lung, 48(3), 226-235. https://doi.org/10.1016/j.hrtlng.2019.01.003

Powers, J., Brown, B., Lyman, B., Escuro, A. A., Linford, L., Gorsuch, K., Mogensen, K. M., Engelbrecht, J., Chaney, A., McGinnis, C., Quatrara, B. A., Leonard, J., & Guenter, P. (2021). Development of a competency model for placement and verification of nasogastric and nasoenteric feeding tubes for adult hospitalized patients. Nutrition in Clinical Practice, 36(3), 517-533. https://doi.org/10.1002/ncp.10671

Shebl, N. A., Franklin, B. D., & Barber, N. (2009). Is failure mode and effect analysis reliable? Journal of Patient Safety, 5(2), 86-94. https://doi.org/10.1097/PTS.0b013e3181a6f040