NSG/468 Week 1: Quality Improvement Methods, sample paper

Choosing an Improvement Method for Late Pain Reassessments on a Surgical Unit: PDSA, Lean, and Six Sigma Compared

[Student Name]

University of Phoenix

NSG/468: Influencing Quality within Healthcare

Week 1 Assignment

[Instructor Name]

[Date]

The unit and its data are a composite written for a model paper.

On a composite 32-bed surgical unit, the hospital's pain management policy requires a nurse to reassess pain within 60 minutes after an intravenous or oral opioid dose and document the result. A four-week audit of 400 doses found that 58% of reassessments were documented on time, 27% were documented late and 15% were never documented. The gap matters for two reasons. A reassessment is how nurses learn whether a dose worked, and it is how they catch oversedation before it becomes respiratory depression. A reassessment that happens but is not recorded protects the patient in front of the nurse, while a reassessment that never happens protects no one; the audit could not tell those two apart, and that was the first thing an improvement method had to fix. This paper compares three quality improvement methods, the Plan-Do-Study-Act (PDSA) cycle, Lean and Six Sigma, against this one problem and recommends the method that best fits it.

The Problem Stated as a Measure

Quality improvement begins with a measurable aim. For this unit the aim is that 90% of post-opioid pain reassessments will be documented within 60 minutes within three months, without an increase in naloxone use or rapid response calls for oversedation. The aim names the measure (on-time documented reassessments), a target, a time frame and a balancing measure that would show harm if nurses began rushing reassessments to meet the target. Framing the problem this way also exposes what the unit does not yet know: why the reassessments are late. Each method below approaches that question differently.

PDSA: Small Tests of Change

The Model for Improvement pairs three questions (what are we trying to accomplish, how will we know a change is an improvement and what change can we make) with rapid PDSA cycles in which a team plans a small change, tries it, studies the result and acts on what it learned (Langley et al., 2009). Its strength is speed and learning: a unit can test an idea on one shift with two nurses in a day. Its weakness is that it is often applied loosely. Taylor et al. (2014), in a systematic review of published PDSA projects, found that few reports showed iterative cycles, planned predictions or regular data over time, which suggests that many teams label a single change as PDSA without using the method's learning structure.

Against this problem PDSA fits well. The likely causes, such as no prompt at the 60-minute mark, reassessments done but charted later and patients asleep at the time of reassessment, can each be tested in small cycles.

Lean: Removing Waste From the Workflow

Lean, derived from the Toyota Production System, focuses on removing steps that add no value for the patient and making the remaining work flow. Mazzocato et al. (2010) reviewed Lean in health care and found it was most often used to understand and redesign processes through tools such as value stream mapping, with reported improvements in time and efficiency, though the evidence was stronger for process measures than for patient outcomes. Lean would help this unit see its reassessment workflow, from the dose in the medication administration record to the documentation screen, and find where time and effort are wasted, such as charting in a separate flowsheet that nurses must search for. A one-hour mapping session with four nurses would likely show the handoffs and hunting that the audit data cannot, such as a reassessment that is done at the bedside, remembered for an hour and charted at the end of a medication pass. On its own, however, Lean does not provide a strong structure for testing whether a redesigned step actually improves the measure.

Six Sigma: Reducing Variation

Six Sigma uses a structured define, measure, analyze, improve and control sequence and statistical tools to reduce variation and defects. It is powerful for high-volume processes with good data and stable definitions, and it often requires trained staff such as green belts or black belts. For a single unit's documentation problem, the method's data demands and training requirements are larger than the problem. The unit has one clear measure, a few likely causes and staff who can test changes quickly; a full Six Sigma project would spend weeks in measurement before the first change reached the floor.

Recommendation: PDSA Cycles Informed by a Simple Process Map

The unit should use PDSA cycles as its main method and borrow one Lean tool, a simple process map of the reassessment workflow, to decide what to test first. This combination keeps the speed and learning structure of PDSA and adds Lean's clarity about where the process breaks, without the overhead of Six Sigma. The trade-off is that the unit will rely on run charts rather than formal statistical process control, which is acceptable for a documentation measure that can be audited weekly.

The first cycles would test changes such as these, one at a time: an electronic prompt that fires at 45 minutes after an opioid dose for two nurses on day shift; moving the reassessment field onto the medication administration screen so documentation happens where the dose was charted; and a unit agreement that a sleeping patient with normal respiratory rate and sedation score is documented as reassessed, with the sedation score recorded, rather than left blank. Each cycle includes a prediction, a small sample and a decision to adopt, adapt or abandon.

How the Team Will Read Its Data

Weekly audits of 25 randomly selected opioid doses give the team one data point a week, plotted on a run chart with the baseline median of 58% drawn across it. The team agreed in advance on how it would read the chart. A run of six or more consecutive points above the baseline median, or a clear upward trend of five points, would be treated as a signal that a change was working rather than ordinary week-to-week noise (Langley et al., 2009). Annotating the chart with the date each PDSA change began makes it possible to connect a shift in the data with the change that caused it. The balancing measures, naloxone administrations and rapid response calls for oversedation, are plotted on the same timeline so that any improvement in documentation can be read against patient safety at a glance.

The run chart also protects the team from two common errors. The first is declaring success after one good week, which a single point cannot support. The second is abandoning a promising change after one bad week, which is often ordinary variation. Deciding the rules before the data arrive keeps the team's judgment honest.

Why Frontline Nurses Belong on the Team

The QSEN competencies define quality improvement as a core competency for every nurse, not only for managers and quality departments, including the skill of using data to monitor outcomes and the attitude of valuing measurement as part of daily work (Cronenwett et al., 2007). This problem shows why. The causes of late reassessments live in the workflow of the nurses who give the doses; a quality analyst reviewing charts from an office would see the late times but not the reasons. Two staff nurses on the improvement team, one from days and one from nights, are more likely to spot the causes and to know whether a proposed change will survive a busy shift.

Conclusion

A 58% on-time reassessment rate is a measurable, nursing-controlled gap with real safety consequences. Compared against that problem, PDSA offers speed and learning, Lean offers a clear view of the workflow and Six Sigma offers rigor that the problem does not need. PDSA cycles guided by a simple process map give the unit the best chance of reaching its 90% aim within three months, with a balancing measure to make sure faster documentation does not come at the cost of careful assessment.

References

Cronenwett, L., Sherwood, G., Barnsteiner, J., Disch, J., Johnson, J., Mitchell, P., Sullivan, D. T., & Warren, J. (2007). Quality and safety education for nurses. Nursing Outlook, 55(3), 122-131. https://doi.org/10.1016/j.outlook.2007.02.006

Langley, G. J., Moen, R. D., Nolan, K. M., Nolan, T. W., Norman, C. L., & Provost, L. P. (2009). The improvement guide: A practical approach to enhancing organizational performance (2nd ed.). Jossey-Bass.

Mazzocato, P., Savage, C., Brommels, M., Aronsson, H., & Thor, J. (2010). Lean thinking in healthcare: A realist review of the literature. Quality and Safety in Health Care, 19(5), 376-382. https://doi.org/10.1136/qshc.2009.037986

Taylor, M. J., McNicholas, C., Nicolay, C., Darzi, A., Bell, D., & Reed, J. E. (2014). Systematic review of the application of the plan-do-study-act method to improve quality in healthcare. BMJ Quality & Safety, 23(4), 290-298. https://doi.org/10.1136/bmjqs-2013-001862