HLTH 4393 Module 2 Process Map and Root Cause Analysis Example

A Basket by the Printer and a Second Draw Nobody Owns: Mapping and Analyzing Delays in Emergency Department Troponin Results

Student Name

American College of Education

HLTH4393: Quality Management for Healthcare Administrators

Module 2 Assignment

Instructor Name

October 12, 2026

Why Map Before Fixing

The first module defined the measure for emergency department troponin testing at our composite community hospital: the share of results posted within an hour of the order, which stood at 58%. That definition deliberately covers the whole interval the physician experiences, which is why it could expose a delay the laboratory's own reports never showed. The obvious next step would be to ask the laboratory to work faster, and that is what the emergency physicians have been asking for two years. But the laboratory's own interval, from receipt to result, has averaged well under half an hour. The delay lives somewhere else, and nobody could say exactly where.

Process mapping was chosen as the first tool because it shows the process as it is actually performed rather than as policy describes it. In a study of eight improvement projects, Antonacci et al. (2018) found that participants valued process mapping for building a shared understanding of reality, identifying improvement opportunities and engaging stakeholders, and that maps worked best when the information came from several groups of staff and the visual form was kept simple. Both findings shaped how this map was built.

How the Map Was Built

A team of seven met twice: an emergency nurse, an emergency technician, an emergency physician, a unit secretary, the night phlebotomist, a laboratory technologist and the laboratory supervisor. Rather than drawing the process from memory in a conference room, two members followed 30 troponin specimens in person, 10 on each shift, recording each step and its time from order to posted result. The laboratory information system supplied the order, collection, receipt and result timestamps for the same specimens, so the observations could be checked against the record.

The map was drawn as a swim-lane diagram with four lanes, physician, nurse or technician, transport and laboratory, because the delays that interested the team occurred when a specimen passed from one lane to another. Each handoff was marked with the median wait observed there, and every step that existed only to make up for another step, such as walking back to the station for labels, was drawn in a different color.

The Process as It Actually Runs

The mapped process has 14 steps, and the time divides into three segments. From order to collection, the median was 26 minutes. From collection to laboratory receipt, it was 15 minutes. From receipt to result, it was 23 minutes. Only the last belongs to the laboratory, and it was the shortest.

Four findings explain most of the first two segments. First, specimen labels print on a single printer at the central nursing station, so a nurse drawing blood in a room or hallway bed must walk to the station, find the labels among others and return, and on busy shifts that trip is postponed until several tasks are done. Second, the second troponin has no owner. The pathway calls for a draw two hours after the first, but the order fires at the time it is placed, and whether the draw happens at two hours depends on a nurse remembering; in 11 of the 30 cases it was drawn more than 20 minutes late. Third, after collection, specimens are often placed in a basket beside the label printer to be sent together through the pneumatic tube, and they sat there a median of nine minutes. Fourth, at night the emergency department's tube station is shared with two inpatient units, and the observers saw specimens wait behind other deliveries.

In the laboratory, the main delay came at shift change between 6:45 and 7:15, when specimens waited to be accessioned, and when hemolyzed specimens required a redraw, which added a median of 47 minutes to those results.

Cause-and-Effect Analysis

The team organized contributing factors on a cause-and-effect diagram under six headings. Under methods: the untimed second draw, batching specimens before sending and the shift-change handoff in the laboratory. Under equipment: the single label printer and the shared tube station. Under people: nurses' competing tasks, especially with several hallway patients, and one phlebotomist for the whole hospital at night. Under environment: hallway beds far from the station. Under materials: blood drawn through newly placed intravenous catheters, which the team suspected of causing hemolysis. Under measurement: the laboratory's receipt-to-result report, which had hidden the delays for years.

The hemolysis suspicion has published support. In a crossover study in a community emergency department, Lowe et al. (2008) found that 5.6% of samples drawn through intravenous catheters were hemolyzed compared with 0.3% drawn by venipuncture. At this hospital most troponin draws are taken from the catheter placed at arrival, which may explain a hemolysis rate of 2.8%.

Asking Why Five Times

For the most important finding, the late second draw, the team asked why repeatedly. The second troponin is drawn late because the nurse does not know when it is due. The nurse does not know because nothing signals the due time. Nothing signals it because the order is placed as a routine order rather than a timed one. It was built as a routine order because the pathway was added to the electronic record by the emergency department and the laboratory configured the test separately, and neither built the timing. And no one caught it because no measure covered the interval from the first result to the second draw. The problem was not that a nurse forgot; it was that the system asked her to remember.

What Root Cause Analysis Can and Cannot Do

The phrase root cause suggests a single cause waiting to be found. Peerally et al. (2017) argue that root cause analysis in health care often falls short for exactly that reason: investigations tend to settle on one cause, produce weak remedies such as reminders, retraining and new policies rather than changes to the system, and focus on single incidents instead of recurring patterns. This analysis tried to avoid those traps. It examined a recurring process, not one bad case; it identified several contributing causes rather than one; and it points toward changes in equipment, timing and workflow rather than instructions to try harder. A memo telling nurses to draw the second troponin on time would have been the easiest recommendation and the least likely to work.

Findings to Test With Data

The map and analysis produce hypotheses rather than conclusions, and the next module will test them against a larger sample. The team expects the largest share of late results to come from late second draws, followed by specimens held before sending, then hemolysis redraws, then the laboratory shift-change queue. If the data confirm that order, the improvement work will begin with the timing of the second draw and the location of the label printer, both of which can be changed without new staff. The map will be kept and updated, because each change will create a new version of the process that must be walked again.

References

Antonacci, G., Reed, J. E., Lennox, L., & Barlow, J. (2018). The use of process mapping in healthcare quality improvement projects. Health Services Management Research, 31(2), 74-84. https://doi.org/10.1177/0951484818770411

Lowe, G., Stike, R., Pollack, M., Bosley, J., O'Brien, P., Hake, A., Landis, G., Billings, N., Gordon, P., Manzella, S., & Stover, T. (2008). Nursing blood specimen collection techniques and hemolysis rates in an emergency department: Analysis of venipuncture versus intravenous catheter collection techniques. Journal of Emergency Nursing, 34(1), 26-32. https://doi.org/10.1016/j.jen.2007.02.006

Peerally, M. F., Carr, S., Waring, J., & Dixon-Woods, M. (2017). The problem with root cause analysis. BMJ Quality & Safety, 26(5), 417-422. https://doi.org/10.1136/bmjqs-2016-005511