BUSI 419 Week 6 Discussion Board Forum 6 Example

Discussion Board Forum 6: Rapid-Cycle Improvement With Plan, Do, Study, Act

BUSI 419 Management of Quality Improvement and Outcomes, Discussion Board Forum 6

Thread by [Student Name]

The clinic, its project and the classmates are composites; the textbook, Scripture and the peer-reviewed sources cited are real.

Last year our primary care clinic redesigned patient check-in to shorten waits. Leaders called it a PDSA project, but on a single Monday they introduced a new kiosk, a revised intake form, a second front desk position and text reminders asking patients to arrive early. No one wrote down what they expected to happen, and the only measure was a patient survey three months later. When wait times barely changed, no one could say which of the four changes had helped, hurt or done nothing. Lighter (2011) presents rapid-cycle improvement as a way to learn from small, deliberate tests, which is the opposite of changing everything at once and hoping.

Our experience is common. Knudsen et al. (2019) examined 120 PDSA-based improvement projects published in 2015 and 2016 and found that 98% reported improvement, yet only 27% described a specific, numerical aim and reached it. Only 60% documented their cycles well enough to analyze, and just 4% followed all four key features: repeated cycles, continuous data collection, small-scale testing and a stated rationale for each change. When nearly every project succeeds on paper but few follow the method, the reported successes deserve less trust.

By contrast, Bothra et al. (2026) used a fishbone analysis to find why blood cultures at their hospital were being contaminated and then applied PDSA cycles: training on aseptic technique, supervised collection and direct feedback to staff whose samples grew contaminants. Across 7,329 specimens, contamination fell from 10.7% to 3.4%. The method worked because the problem was analyzed first and each change was tied to a cause.

If we redid our check-in project, I would run three sequenced tests. First, text reminders for one physician's patients for two weeks, predicting a 20% drop in late arrivals. Second, if that worked, the revised intake form at one desk, predicting a two-minute reduction in check-in time. Third, the kiosk for returning patients only. Each test would be measured weekly on a run chart, and each would be adopted, adapted or abandoned based on what the data showed, before the next began. A PDSA cycle without a prediction is not a test; it is a guess with paperwork.

Zechariah asks who has despised the day of small things (English Standard Version Bible, 2001/2016, Zechariah 4:10). Small tests can seem too modest to matter, but they are how lasting improvement is built.

Reply to Kendra

Kendra, you wrote that PDSA cycles feel too slow for your hospital's leadership, which wants to see results within a quarter. I understand the pressure, but I would argue that small tests are usually faster than large rollouts in the end. A large change that fails, as our clinic's check-in redesign did, costs months and leaves no clear lesson, while a two-week test that fails costs two weeks and teaches something specific. Knudsen et al. (2019) found that most published projects reported improvement but very few could show they had met a specific aim, which suggests that rushing to a large change often produces claims rather than results. Lighter (2011) describes rapid-cycle improvement as a way to speed learning, and cycles can be very short, sometimes a single shift or a single day for a simple change. Bothra et al. (2026) achieved a large drop in contamination over a period of months by layering one change on another, each built on what the last had shown. To satisfy leaders who want quick results, you might present a 90-day plan with three or four cycles, each with its own prediction and a weekly measure displayed on a run chart. Leaders would then see progress every week instead of waiting for a final report. Would your leadership accept a plan that promises learning every two weeks and a measurable result by the end of the quarter? Framing PDSA as a schedule of quick wins may turn the perceived slowness into an advantage. It also protects leaders from the embarrassment of announcing a large change that later has to be quietly reversed, which tends to cost far more credibility than a small test that did not pan out.

Reply to Andrew

Andrew, you mentioned that your team struggled with the first question of the Model for Improvement, what are we trying to accomplish, and ended up with an aim to improve discharge efficiency. That is a common place to get stuck, and it matters, because a vague aim makes every later step harder. Knudsen et al. (2019) found that only about a quarter of published PDSA projects stated a specific, numerical aim and reached it, which suggests that weak aims are one of the method's most common failures. A strong aim usually names the measure, the size of the change, the population and the deadline. For your project, that might read: increase the share of medical unit patients discharged before noon from 25% to 40% by the end of June. Lighter (2011) emphasizes that a measure is only useful when its definition leaves no room for different people to count differently, so your team would also need to agree on what counts as a discharge time, such as the moment the patient leaves the unit. Bothra et al. (2026) defined contamination clearly as the growth of skin organisms in a culture, which let them compare periods with confidence. Once the aim is set, the team can choose a small first test, such as having one unit's case manager begin discharge planning at morning rounds for a week. What number would your team consider a meaningful improvement in discharge timing? Agreeing on that figure early will make every later conversation about success much easier. It also helps to add a balancing measure, such as readmissions within a week, so that faster discharges do not quietly create a new problem elsewhere.

References

Bothra, M., Ghuliani, R., Swarup, P., Majumder, S., Jain, A., & Verma, S. (2026). Decreasing contamination rates in blood cultures: A plan-do-study-act approach. The National Medical Journal of India, 39, 303-305. https://doi.org/10.25259/NMJI_801_2024

English Standard Version Bible. (2016). Crossway. (Original work published 2001)

Knudsen, S. V., Laursen, H. V. B., Johnsen, S. P., Bartels, P. D., Ehlers, L. H., & Mainz, J. (2019). Can quality improvement improve the quality of care? A systematic review of reported effects and methodological rigor in plan-do-study-act projects. BMC Health Services Research, 19(1), 683. https://doi.org/10.1186/s12913-019-4482-6

Lighter, D. E. (2011). Advanced performance improvement in health care: Principles and methods. Jones and Bartlett Publishers.