CPAP Module 21, Section 4: Continuous Improvement Framework (PDSA, Lean)
MODULE 21: METRICS, QUALITY & PERFORMANCE IMPROVEMENT

Section 4: Continuous Improvement Framework (PDSA, Lean)

From Data to Action: The Science of Getting Better.

SECTION 21.4

Continuous Improvement Framework (PDSA, Lean)

Applying Scientific Method to the Art of Access.

21.4.1 The “Why”: The Engine of Sustainable Progress

In the previous sections of this module, we have constructed a powerful system for understanding our performance. We have established metrics to measure our work, implemented QA processes to ensure its quality, and built dashboards to visualize our progress. We now know, with data-driven certainty, where our strengths and weaknesses lie. This is a monumental achievement, but it is incomplete. Data and dashboards are like a car’s diagnostic system; they can tell you precisely what is wrong, but they cannot fix the engine. To make the car run better, you need a set of tools and a systematic method for using them. This is the role of a continuous improvement framework.

Continuous Improvement (CI) is the philosophy and practice of making incremental, evidence-based changes to a process to improve its efficiency, quality, and effectiveness. It is the deliberate rejection of the “this is how we’ve always done it” mindset. It provides a structured, scientific alternative to guesswork, intuition-based management, and random, large-scale changes that often fail. Instead of relying on a single manager’s “bright idea,” CI empowers the front-line staff—the people who actually do the work—to identify problems and test solutions in a controlled, low-risk manner.

As a pharmacist, you are a scientist by training. You understand the principles of forming a hypothesis, conducting an experiment, analyzing the results, and drawing a conclusion. The two frameworks we will master in this section—Plan-Do-Study-Act (PDSA) and Lean methodology—are simply the application of this scientific method to operational workflows. PDSA provides the framework for conducting small, rapid experiments, while Lean provides a powerful lens for identifying what to experiment on by systematically exposing “waste.” By mastering these tools, you will transition from a PA specialist who simply executes a process to a process engineer who owns, analyzes, and continuously refines it. This is the ultimate expression of professional autonomy and a critical skill for leading a high-performance PA team.

Retail Pharmacist Analogy: Solving the “Weekly Pill Planner Problem”

Imagine your pharmacy has a recurring, frustrating problem. Every Tuesday, Mrs. Jones’s daughter comes in to pick up her mother’s complex weekly pill planner. And every Tuesday, it’s not ready. The daughter is upset, the pharmacy gets backed up, and your team’s morale suffers. Your data shows that prescriptions for this patient have a terrible “Turnaround Time” metric on Tuesdays.

How do you solve this? You don’t just tell your technicians to “work faster.” You apply a continuous improvement mindset.

1. Lean Analysis (Identifying Waste): First, you observe the current process. You notice that the technician has to walk back and forth across the pharmacy multiple times to gather the 15 different medications (Waste of Motion). They then have to wait for you to perform a DUR check mid-process (Waste of Waiting). Finally, they sometimes grab the wrong bottle because two of Mrs. Jones’s medications look similar (Waste of Defects/Rework).

2. The PDSA Cycle (Testing a Change): Based on your Lean analysis, you develop a hypothesis: “If we create a dedicated ‘Mrs. Jones Bin’ with all 15 of her medications pre-staged on Monday afternoon, we can reduce the fill time on Tuesday morning.” You decide to test this change.

  • PLAN: You and your lead technician decide to try this new “pre-staging” process for next week only. You will measure the time it takes to fill the planner using the new method.
  • DO: On Monday, the technician gathers all 15 medications into a single bin. On Tuesday morning, they fill the planner from the dedicated bin.
  • STUDY: You review the results. The fill time was reduced from an average of 25 minutes to just 8 minutes. The daughter was in and out of the pharmacy in less than 5 minutes. No errors were made. Your hypothesis was correct.
  • ACT: The change was a success. You decide to make this the new Standard Operating Procedure (SOP). You create a recurring calendar reminder for every Monday to “Pre-stage Mrs. Jones’s medications.” You have successfully used CI principles to solve a real-world problem.

This methodical, small-scale, data-driven approach is the essence of PDSA and Lean. You didn’t overhaul your entire pharmacy workflow; you identified a specific problem, analyzed it for waste, and tested a small, targeted solution. This is precisely how you will tackle process problems in your PA department.

21.4.2 Deep Dive into Lean: The Philosophy of Waste Elimination

Lean is a management philosophy that originated in manufacturing but has been successfully adapted to healthcare. Its core principle is simple but profound: maximize value for the customer (the patient) by relentlessly identifying and eliminating waste. In the context of prior authorization, “value” is defined as any activity that directly contributes to getting a clinically appropriate medication approved and accessible to the patient. “Waste” is everything else.

Lean methodology provides a powerful vocabulary for categorizing waste into eight distinct types. By learning to see your workflow through this lens, you will begin to notice inefficiencies that were previously invisible. You will be able to pinpoint exactly where your process is breaking down and why.

Masterclass Table: The 8 Wastes of Lean Translated for Prior Authorization
Waste Type (Acronym: DOWNTIME) Description Concrete PA Department Examples
Defects Work that contains errors, or work that needs to be re-done.
  • Submitting a PA with the wrong Member ID, resulting in an administrative denial.
  • Failing to include required step-therapy documentation, causing a clinical denial.
  • Faxing a PA to the wrong payer’s fax number.
  • This is the most common and costly waste in PA. Every denial is a defect.
Over-production Doing more work than is necessary, or doing it sooner than needed.
  • Working on a PA for a non-formulary drug that you know will be denied, before discussing therapeutic alternatives with the provider.
  • Printing out every single page of a 200-page medical record when only 5 pages are relevant to the PA criteria.
Waiting Idle time created when a process has to stop, pending an input from another step.
  • A case is “pended” and sits idle, waiting for the clinic to fax over missing lab results.
  • A specialist is ready to work but is waiting for a manager to assign them their next case.
  • Holding on the phone for 45 minutes to speak to a payer representative.
  • This is the primary driver of high Turnaround Time.
Non-Utilized Talent Failing to use the skills, knowledge, and creativity of your team members.
  • Having highly skilled PharmDs or nurses spend most of their day doing basic data entry that could be handled by a technician.
  • A manager dictating all process changes without seeking input from the front-line staff who know the workflow best.
Transportation Unnecessary movement of information or materials.
  • Requiring a paper PA request form to be physically carried from a clinic to the PA department.
  • Excessive handoffs: An intake coordinator sends the case to a technician, who sends it to a pharmacist, who sends it to a lead for review.
Inventory An excess of work-in-progress (WIP).
  • A large backlog of un-triaged PA requests sitting in a fax queue or email inbox.
  • Having 50 “pended” cases that are all waiting for external information. A large WIP inventory hides bottlenecks and makes it difficult to manage priorities.
Motion Unnecessary movement of people.
  • In a digital environment, this translates to excessive clicks or navigation. For example, having to open 4 different software applications to work on a single case.
  • Physically walking to a fax machine multiple times a day instead of using a desktop faxing solution.
Extra-Processing Doing work that adds no value from the customer’s perspective.
  • Requiring multiple levels of internal approval for a routine, straightforward PA submission.
  • Writing a 3-page clinical narrative for a PA when the payer’s form only has space for 500 characters and the reviewer will only look at the attached notes.

21.4.3 Deep Dive into PDSA: The Engine of Experimentation

If Lean helps you find the problems, the Plan-Do-Study-Act (PDSA) cycle provides the scientific method for solving them. It is an iterative, four-stage model for testing a change in a real-world setting on a small scale, observing the results, and then refining the change before implementing it more broadly. It is the antidote to large, risky, “big bang” projects. PDSA cycles are meant to be rapid and small. The goal is to learn and adapt quickly.

Visualizing the PDSA Cycle

The PDSA cycle is a continuous loop, not a linear process. The learning from one cycle directly informs the “Plan” for the next.

PLAN
1. Plan the Change

State the objective, make a prediction, and plan to carry out the test (who, what, where, when).

DO
2. Carry Out the Test

Execute the plan. Document problems and unexpected observations. Collect the data.

STUDY
3. Analyze the Results

Compare the results to your predictions. Summarize what was learned.

ACT
4. Decide on Next Steps

Adopt the change, adapt it, or abandon it. Plan the next cycle.

PLAN
DO
STUDY
ACT
The PDSA Worksheet: A Tool for Structured Thinking

To ensure your PDSA cycles are rigorous, use a simple worksheet to structure your plan. This forces you to think through each step before you begin.

Masterclass Table: PDSA Planning Worksheet
PLAN
1. Objective of this Cycle: To test if a dedicated checklist for Payer C’s oncology PAs reduces administrative denial rates.
2. Questions to be Answered: 1. Is the checklist easy for specialists to use? 2. Does using the checklist change the First-Touch Approval Rate? 3. Does it impact TAT?
3. Prediction (Hypothesis): We predict that using the checklist will increase the First-Touch Approval Rate for Payer C oncology cases from 60% to over 85% without significantly increasing TAT.
4. Plan for the Test: Who: Two senior specialists (Jane and Tom).
What: They will use the new checklist for all new Payer C oncology submissions.
When: For a two-week period (Oct 1 – Oct 14).
Data to Collect: Submission date, determination date, initial outcome (approved/denied), denial reason if applicable.
DO
Jane and Tom execute the test as planned. They keep a simple log of their cases and note that the checklist adds about 5 minutes to their initial work-up time but makes them feel more confident.
STUDY
The team manager analyzes the data.
  • Total Payer C oncology cases submitted: 12
  • Initial Approvals: 11 (91.7% First-Touch Approval Rate)
  • Initial Denials: 1 (Administrative denial – patient eligibility issue, unrelated to checklist)
  • Average TAT: 2.1 days (compared to historical average of 2.0 days)
  • Conclusion: The prediction was correct. The checklist dramatically improved the approval rate with a negligible impact on TAT.
ACT
Based on the successful test, the team decides to ADOPT the change. The checklist is rolled out as a mandatory tool for all specialists working on Payer C oncology cases, effective immediately. The manager plans a new PDSA cycle to test a similar checklist for Payer B.