| Course | HA 640 Healthcare Operations Assessment and Decision-Making |
|---|---|
| Unit | Unit 2 |
| Paper type | Bottleneck assessment |
| Length | About 920 words, 6 pages |
| Format | APA 7 student paper |
| School | Herzing University |
| Program | MS in Healthcare Administration |
| Updated | October 2026 |
Free sample paper for HA 640 Unit 2
Not the Analyzers: A Bottleneck Assessment That Finds the Core Laboratory's Morning Constraint at the Specimen Processing Bench
Student Name
Health Care Administration, Herzing University
HA 640: Healthcare Operations Assessment and Decision-Making
Instructor Name
January 22, 2026
Not the Analyzers: A Bottleneck Assessment That Finds the Core Laboratory's Morning Constraint at the Specimen Processing Bench
The Question
The baseline found that routine chemistry tubes received during the two-hour morning peak take a median of 88 minutes from receipt to verified result, against 41 minutes at other hours, and that a backlog builds through the morning peak. Laboratory staff and several physicians attribute the delay to the chemistry analyzers, and a request for a third analyzer is circulating. This assessment identifies the stage that actually limits output, using the processing times and resources recorded in the baseline.
The Process Map
The process runs in this sequence, with decision points and rework loops where they occur.
1. Receipt at the tube station or courier bench. 2. Label check, a decision point: if the label is missing, mismatched or the tube is clotted or underfilled (1.7% of tubes), the tube goes to the exception bench, where a processor calls the unit; the tube is either relabeled under policy after identity is confirmed, or rejected and recollected, a rework loop that sends about 0.6% of tubes back to the patient's bedside. 3. Accession in the laboratory information system. 4. Batch wait until a centrifuge rack is filled or 10 minutes pass. 5. Centrifugation. 6. Sorting into analyzer racks and loading. 7. Analysis, followed by a decision point: results flagged by the analyzer's quality checks or above the measuring range are rerun or diluted, a loop affecting about 3% of tubes and adding about 19 minutes. 8. Verification, a decision point: 80% of results pass automatic verification rules; 20% go to a scientist for review; critical values also require a phone call to the unit. 9. Release to the electronic record.
Two kinds of hidden work appear on the map. The exception loop consumes processor time on every morning, and the phone calls from units asking where morning results are, about five an hour during the peak, are answered by the same processors. Neither is counted in staffing models, but both consume capacity at the stage that has the least of it.
Capacity by Stage
Each stage is converted to tubes per hour, using processing time and the number of parallel resources at the morning peak, so the stages can be compared directly.
| Stage | Processing time or cycle | Resources, 4:00 to 8:00 a.m. | Capacity, tubes per hour | Utilization at 152 tubes an hour |
|---|---|---|---|---|
| Specimen processing (accession, centrifuge handling, sorting, exceptions) | 0.90 minutes per tube | 2 processors | 133, or about 130 after phone calls | 114% to 117% |
| Centrifugation | 12-minute cycle, 40 tubes per run | 2 centrifuges | 400 | 38% |
| Chemistry analysis | 170 tubes per hour each, less 3% reruns | 2 analyzers | 330 | 46% |
| Verification | Auto for 80%; 1.2 minutes for the 20% reviewed | 1 scientist, about 70% available for chemistry | 175 | 87% |
The Constraint
The lowest capacity is specimen processing, at about 130 tubes an hour with two processors, against 152 tubes an hour arriving in the 5-to-7 window It is the only stage whose capacity is below the peak arrival rate, and therefore the constraint. The analyzers, at 330 tubes an hour, have more than twice the capacity the morning demands. A third analyzer would add capacity to a stage that is already idle more than half of the peak.
The queue evidence agrees. Work accumulates in front of a real bottleneck and starves the stages behind it (Goldratt & Cox, 2004). At 6:30 a.m. on the observed mornings, an average of 38 tubes sat in racks at the tube station waiting to be accessioned, while the centrifuges ran partly empty and the analyzers waited for loaded racks: the median wait before accessioning was 31 minutes at the peak, compared with 4 minutes between centrifuge and analyzer. Verification is the second-tightest stage, at 87% utilization; it is not the constraint today, but it would become one if processing capacity rose above about 175 tubes an hour.
What the Constraint Permits
While specimen processing holds at about 130 tubes an hour, the laboratory cannot process more than about 260 tubes in the two peak hours, against about 305 arriving. The backlog at 7:00 a.m. is therefore about 45 tubes, which takes until roughly 8:10 a.m. to clear, because 7:00 to 8:00 a.m. arrivals of 94 tubes still consume most of the capacity. That is the arithmetic behind the physicians' complaint. Waiting grows faster than linearly as utilization approaches and passes 100% (Hopp & Spearman, 2008), which explains why the wait before accessioning is about fifteen times the off-peak wait while arrivals are only about six times higher.
The exception loop matters here. At 0.10 minutes per tube averaged across all tubes, exception handling consumes about 11% of processor time. If labeling errors fell from 1.7% to 0.8%, processing capacity would rise by about 6%, to roughly 138 tubes an hour, without adding staff. Since most laboratory errors arise before analysis (Plebani, 2006), the loop is a quality problem as well as a capacity problem.
Why the Analyzer Explanation Persisted
The belief that the analyzers are the problem is understandable. The analyzers are the most visible and expensive equipment in the laboratory, they display a run queue that looks long in the morning, and they occasionally stop for quality control or maintenance, which staff remember. The processing bench, by contrast, looks like ordinary handling work. But the analyzer's run queue in the morning is short relative to its capacity, and on the observed mornings neither analyzer stopped for more than 6 minutes during the peak. Nominating the most visible stage as the bottleneck, without converting every stage to the same unit, is the error this assessment was designed to avoid. The table makes the comparison that intuition skips.
Conclusion
The constraint on morning chemistry results is the specimen processing bench, not the analyzers. The request for a third analyzer should be paused. The next units forecast morning volume, test how the queue behaves under different staffing and arrival patterns, and compare options that raise processing capacity or spread the arrival peak.
References
Goldratt, E. M., & Cox, J. (2004). The goal: A process of ongoing improvement (3rd rev. ed.). North River Press.
Hopp, W. J., & Spearman, M. L. (2008). Factory physics (3rd ed.). McGraw-Hill/Irwin.
Plebani, M. (2006). Errors in clinical laboratories or errors in laboratory medicine? Clinical Chemistry and Laboratory Medicine, 44(6), 750-759. https://doi.org/10.1515/CCLM.2006.123
HA 640 Unit 2 instructions, in plain terms
Unit 2 asks you to identify the bottleneck in a health care process. Expect to state the question, map the process with decisions and rework, convert each stage to the same capacity unit, identify the constraint, show what it allows and explain any competing belief. Students often ask how to compare stages with different resources. Convert each to units per hour using processing time and the number of parallel staff or machines at the peak. The stage with the lowest capacity below arrival rate is the constraint. Show the backlog it creates in numbers. Address the common explanation directly, since staff beliefs often point at the most visible equipment. End with what should and should not be bought.
How this HA 640 Unit 2 example is built
The assessment opens with the baseline gap between peak and off-peak turnaround. The process map lists ten steps in order, with the label check and exception bench as decision points. A capacity table gives each stage's processing time, parallel resources and tubes per hour. The constraint section shows that processing alone falls below peak arrivals, while the analyzers have more than twice the needed capacity. The permits section calculates the two-hour backlog and the time needed to clear it. The persistence section explains why visible analyzer queues and occasional maintenance stops made the analyzers look guilty. The conclusion recommends pausing the analyzer purchase and previews the forecast and queue analysis in later units.
Reading the HA 640 Unit 2 rubric
Herzing's rubric for a bottleneck assessment typically covers the question, process map, capacity by stage, the constraint, its effects and the competing explanation. Converting every stage to a common capacity measure earns the largest share, since only then can stages be compared and the true constraint identified. Question points reward a link to baseline figures. Map criteria look for decision points and rework loops. Constraint credit goes to the stage below arrival rate, shown with numbers. Effect points reward a backlog calculation. Addressing the popular explanation is often credited. The conclusion should change a decision, such as a purchase. The assessment rests on Goldratt and Cox's The Goal, Factory Physics by Hopp and Spearman and Plebani's review of laboratory errors.
Common HA 640 Unit 2 mistakes, and how to avoid them
Bottleneck assessments in HA 640 Unit 2 tend to stumble when the writer accepts the explanation staff already believe. Another frequent problem is comparing stages in different units, such as minutes for one and tubes for another. Students often ignore parallel resources. Rework loops are left off the map. The constraint is named without showing its capacity against arrivals. Backlog is not calculated. The conclusion does not change any decision. Off-peak hours are mixed with peak hours. Finally, put every stage on the same per-hour scale, because graders reward an assessment that overturns a costly assumption with arithmetic anyone can check.
Get a HA 640 Unit 2 example written to your instructions
Send the Unit 2 instructions and the rubric from your HA 640 classroom, plus the process and any timing figures your section provides. We write a custom example with the map drawn, every stage converted to a common rate, the constraint identified by calculation and the next limit named, returned in 24 to 48 hours. The first custom sample is free.
More HA 640 papers and healthcare administration samples
- HA 640 Unit 1: Operations baseline report
- HA 640 Unit 3: Demand forecast
- HA 640 Unit 4: Capacity and queue analysis
- HA 640 Unit 5: Make or buy analysis
- HA 640 Unit 6: Decision matrix
- HA 640 Unit 7: Project sequencing and risk register
- HA 640 Unit 8: Operations improvement recommendation
- HA 645 Unit 2: Measure specification
- HA 695 Unit 2: Evidence and oversight plan
- HA 610 Unit 2: Legislative analysis
- HA 620 Unit 2: Payer mix analysis
HA 640 Unit 2 questions, answered
Do I need software to draw the process map?
No. A clean diagram built in a word processor or drawing tool is enough, provided each box carries a name, a time and the resources assigned. What matters is that the map and the capacity table describe the same process, since graders check them against each other. An elaborate diagram with no numbers attached scores below a plain one that supports the arithmetic.
What is the difference between utilization and capacity?
Capacity is how much a stage could produce per period; utilization is how much of that it is currently using. A stage can run at full utilization and still not be the constraint if its capacity exceeds the stage in front of it. Report both, and identify the bottleneck from capacity, because utilization tells you how busy people are rather than what limits output.
Can a person be the bottleneck?
A role can be, and often is, but write it as a resource constraint rather than as a performance problem. One credentialed reader, one interpreter or one authorizing signature limits the whole process regardless of how fast that person works. Framing it that way keeps the assessment operational and points at the real remedies, which are additional capacity, changed sequencing or a redistributed approval rule.
Where can I find a free HA 640 Unit 2 sample paper?
Read the complete HA 640 Unit 2 bottleneck assessment here at no charge, a core laboratory constraint found at the processing bench with stage capacities and backlog math. Ask for a custom assessment of another process.
How do you find the bottleneck in a hospital process?
Convert each stage's capacity to the same unit, such as items per hour, using processing time and parallel resources, then compare with the peak arrival rate. The lowest stage below arrivals is the constraint.