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4. QI Tools and Frameworks: Practical Methods for Internal Medicine

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 QI Tools and Frameworks: Practical Methods for Internal Medicine 
==================================================================

  Map the workflow, test a change, and distinguish improvement from noise.

  [     MDster Editorial Team ](https://mdster.com/about) ·      Sep 11, 2026  ·      6 min read  ·       49  

  [     Reviewed by Dr. Ali Ragab, MBBCH, MSc, MCAI ](https://mdster.com/medical-reviewers/dr-ali-ragab) [Editorial Policy](https://mdster.com/editorial-policy) | [Corrections Policy](https://mdster.com/corrections) 

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    On this page

 1. [ Start With an Aim, Not a Favorite Tool ](#start-with-an-aim-not-a-favorite-tool)
2. [ Map What Actually Happens ](#map-what-actually-happens)
3. [ Find the Failure Point Before Designing the Fix ](#find-the-failure-point-before-designing-the-fix)
4. [ Use PDSA to Learn Before Scaling ](#use-pdsa-to-learn-before-scaling)
5. [ Make a Prediction You Can Actually Test ](#make-a-prediction-you-can-actually-test)
6. [ Read Change Over Time, Not Just Before and After ](#read-change-over-time-not-just-before-and-after)
7. [ Start With a Run Chart ](#start-with-a-run-chart)
8. [ Use Control Charts to Assess Process Stability ](#use-control-charts-to-assess-process-stability)
9. [ Key Takeaways ](#key-takeaways)
10. [ Frequently Asked Questions ](#blog-faqs)
11. [ References ](#references-heading)

     On this page

 1. [ Start With an Aim, Not a Favorite Tool ](#start-with-an-aim-not-a-favorite-tool)
2. [ Map What Actually Happens ](#map-what-actually-happens)
3. [ Find the Failure Point Before Designing the Fix ](#find-the-failure-point-before-designing-the-fix)
4. [ Use PDSA to Learn Before Scaling ](#use-pdsa-to-learn-before-scaling)
5. [ Make a Prediction You Can Actually Test ](#make-a-prediction-you-can-actually-test)
6. [ Read Change Over Time, Not Just Before and After ](#read-change-over-time-not-just-before-and-after)
7. [ Start With a Run Chart ](#start-with-a-run-chart)
8. [ Use Control Charts to Assess Process Stability ](#use-control-charts-to-assess-process-stability)
9. [ Key Takeaways ](#key-takeaways)
10. [ Frequently Asked Questions ](#blog-faqs)
11. [ References ](#references-heading)

  A patient leaves your ward with conflicting medication lists. At the safety meeting, someone proposes another educational email—but nobody can explain where reconciliation failed. Before prescribing a solution, understand the workflow: process mapping identifies vulnerabilities, PDSA tests changes, and time-series charts assess whether performance changes. [\[1\]](#cite-1 "Reference [1]")

Start With an Aim, Not a Favorite Tool
--------------------------------------

The Model for Improvement links three questions: What are we trying to achieve? How will we recognize improvement? Which changes might produce it? PDSA cycles then test those changes locally. Treat the framework as your reasoning structure, not paperwork. [\[2\]](#cite-2 "Reference [2]")

For this hypothetical project, set an aim: reduce discharges with at least one unintended medication discrepancy from 20% to 10% within 12 weeks on one medical ward. These are illustrative targets, not clinical benchmarks.

Build a small measurement family rather than collecting everything. Outcome, process, and balancing measures answer different questions about effectiveness and unintended consequences. [\[3\]](#cite-3 "Reference [3]")

- Track the percentage of audited discharges with a discrepancy as the outcome.
- Track completion of the proposed reconciliation check as the process measure.
- Track discharge delays and staff time as balancing measures.

For this project, define eligible discharges, discrepancy criteria, sampling, and adjudication before collecting data. Keep measurement consistent; otherwise, changing ascertainment may masquerade as improvement. [\[3\]](#cite-3 "Reference [3]")

Map What Actually Happens
-------------------------

### Find the Failure Point Before Designing the Fix

Construct the current-state process map with the people doing the work: residents, nurses, pharmacists, and discharge staff. Walk through actual cases rather than copying the written policy; flowcharts expose handoffs, duplication, delays, and rework. [\[1\]](#cite-1 "Reference [1]")

For our hypothetical ward, the map might reveal this sequence:

1. The resident edits discharge prescriptions.
2. Pharmacy reviews the list.
3. A consultant subsequently changes a medication.
4. Nursing prints an earlier version for the patient.

Now the proposed email looks poorly matched to the problem. The example suggests a version-control failure after review, so test a final reconciliation checkpoint rather than assuming a knowledge deficit.

Use rectangles for tasks, diamonds for decisions, and arrows for sequence. Add role-based lanes when ownership is unclear, and mark waiting or feedback loops explicitly. A map identifies where to investigate; it does not establish causation by itself. [\[1\]](#cite-1 "Reference [1]")

Use PDSA to Learn Before Scaling
--------------------------------

### Make a Prediction You Can Actually Test

Start with one willing team and a few discharges, not a hospital-wide mandate. Early PDSA cycles primarily test feasibility and mechanisms; they do not establish an effect on rare patient harms. [\[4\]](#cite-4 "Reference [4]")

For the proposed final reconciliation checkpoint, document:

1. **Plan:** Predict that checking after the last prescribing change will detect mismatches without materially delaying discharge. Specify who checks, when, and what data are collected.
2. **Do:** Test on three discharges. Record missed checks, interruptions, discrepancies, and time required.
3. **Study:** Compare observations with the prediction. If the check failed, determine whether the idea or its execution failed.
4. **Act:** Adapt, adopt for further testing, or abandon the change. Write the next test before ending the cycle. [\[4\]](#cite-4 "Reference [4]")

Expand sequentially across clinicians, busy periods, and weekends. Implement routinely only after repeated testing supports reliability under relevant conditions; document each cycle so learning survives staff rotation. [\[4\]](#cite-4 "Reference [4]")

> **Clinical Pearl:** “Study” means comparing results with a prediction—not simply announcing that staff liked the intervention. A failed test that changes your next decision is useful learning. [\[4\]](#cite-4 "Reference [4]")

Read Change Over Time, Not Just Before and After
------------------------------------------------

### Start With a Run Chart

Plot the weekly discrepancy percentage chronologically, add a baseline median, and annotate intervention dates. Aim for at least 10 baseline observations when feasible; two aggregated before-and-after percentages conceal the sequence and variation that help interpretation. [\[5\]](#cite-5 "Reference [5]")

Using IHI run-chart conventions, look for:

- A shift: six or more consecutive points on one side of the median; ignore points on the median.
- A trend: five or more consecutively increasing or decreasing points.
- An unusual number of runs or an obviously extreme, “astronomical” point. [\[6\]](#cite-6 "Reference [6]")

For example, six weekly discrepancy percentages below the baseline median suggest nonrandom change. That supports investigation of improvement, but temporal association alone does not prove your intervention caused it. [\[6\]](#cite-6 "Reference [6]")

### Use Control Charts to Assess Process Stability

Control charts add statistically calculated limits, usually three-sigma limits, around a centerline. Select the chart for the data type: a p-chart suits proportions, such as discharges with discrepancies, and accommodates varying denominators through varying limits. [\[7\]](#cite-7 "Reference [7]")

FeatureRun chartControl chartCenterlineUsually medianUsually meanStatistical limitsNoneCalculated from process variationInterpretationNonrandom patternsCommon- versus special-cause variation

These are complementary tools; control-chart interpretation requires chart-specific rules rather than simply importing run-chart thresholds. [\[5\]](#cite-5 "Reference [5]")

Common-cause variation belongs to the existing system: improve the underlying process. Special-cause signals—such as a point beyond a control limit or a qualifying nonrandom pattern—prompt investigation of what changed. Special causes can represent improvement, deterioration, or measurement problems. [\[7\]](#cite-7 "Reference [7]")

For examinations, remember that **control limits are not clinical targets**. A stable process can remain consistently unsafe; conversely, reacting to every ordinary fluctuation can produce unnecessary changes and wasted effort. [\[8\]](#cite-8 "Reference [8]")

Key Takeaways
-------------

- Map the actual workflow before selecting an intervention. [\[1\]](#cite-1 "Reference [1]")
- Use linked PDSA cycles with explicit predictions and documented learning. [\[4\]](#cite-4 "Reference [4]")
- Pair outcome measures with process and balancing measures. [\[3\]](#cite-3 "Reference [3]")
- Distinguish statistical stability from acceptable performance. [\[8\]](#cite-8 "Reference [8]")

The practical sequence is straightforward: understand the work, test deliberately, and examine performance over time. The goal is not a completed QI presentation—it is a change that works reliably in clinical practice. [\[2\]](#cite-2 "Reference [2]")

    Frequently Asked Questions 
----------------------------

 ###     Is one successful PDSA cycle enough to implement a change?             

Usually not. Repeat tests under different conditions before implementation; early success may depend on unusually favorable staffing or workload. [\[4\]](#cite-4 "Reference [4]")

###     Can a control chart be stable but still show poor care?             

Yes. Stability means predictable variation, not acceptable quality. A consistently poor process requires redesign even without special-cause signals. [\[8\]](#cite-8 "Reference [8]")

###     Why measure discharge delays in a medication-safety project?             

They are a balancing measure: improved medication accuracy could create delays or additional workload elsewhere in the discharge process. [\[3\]](#cite-3 "Reference [3]")

        References  (8)  
------------------

 1. 1.  [ Institute for Healthcare Improvement. Flowchart.     ](https://www.ihi.org/library/tools/flowchart)   [↩](#cite-ref-1-1 "Back to text")
2. 2.  [ Institute for Healthcare Improvement. Model for Improvement.     ](https://www.ihi.org/library/model-for-improvement)   [↩](#cite-ref-2-1 "Back to text")
3. 3.  [ www.ihi.org/library/model-for-improvement/establishing-measures     ](https://www.ihi.org/library/model-for-improvement/establishing-measures)   [↩](#cite-ref-3-1 "Back to text")
4. 4.  [ Institute for Healthcare Improvement. Testing Changes.     ](https://www.ihi.org/library/model-for-improvement/testing-changes)   [↩](#cite-ref-4-1 "Back to text")
5. 5.  [ www.ihi.org/learn/courses/open-school/catalog/qi-104     ](https://www.ihi.org/learn/courses/open-school/catalog/qi-104)   [↩](#cite-ref-5-1 "Back to text")
6. 6.  [ www.ihi.org/education/ihiopenschool/Courses/Documents/Course%20Summaries.pdf     ](https://www.ihi.org/education/ihiopenschool/Courses/Documents/Course%20Summaries.pdf)   [↩](#cite-ref-6-1 "Back to text")
7. 7.  [ NHS. A Guide to Creating and Interpreting Run and Control Charts.     ](https://www.england.nhs.uk/improvement-hub/wp-content/uploads/sites/44/2017/11/A-guide-to-creating-and-interpreting-run-and-control-charts.pdf)   [↩](#cite-ref-7-1 "Back to text")
8. 8.  [ www.england.nhs.uk/commissioning/wp-content/uploads/sites/44/2017/11/the\_handbook\_of\_quality\_and\_service\_improvement\_tools\_2010-2.pdf?trk=public\_post\_comment-text     ](https://www.england.nhs.uk/commissioning/wp-content/uploads/sites/44/2017/11/the_handbook_of_quality_and_service_improvement_tools_2010-2.pdf?trk=public_post_comment-text)   [↩](#cite-ref-8-1 "Back to text")

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