# Quality Improvement Report: [Project title]

> Report template for a healthcare quality improvement (QI) project,
> written for an internal governance committee, a learning event or a
> journal submission. The numbered body sections follow the 18 items of
> SQUIRE 2.0 (Standards for QUality Improvement Reporting Excellence,
> Ogrinc et al., BMJ Quality and Safety 2016), grouped as the guideline
> groups them, with original wording written for this collection. Use it
> together with the official SQUIRE 2.0 checklist and its Explanation and
> Elaboration paper. The worked example (a fictional ward at a fictional
> hospital) shows how the sections connect. Replace every `[bracketed]`
> value and every row marked *Example*. This is a reporting format, not
> clinical advice; check the current official guideline text and your
> organisation's governance, ethics and privacy rules.

<!--
Guidance: How to use this template
- Write sections 3 to 12 (the methods) while the project runs, not at the
  end. Keep the PDSA log (appendix A) and the measure definitions up to
  date each week; the results then write themselves.
- Use the same measure IDs (M1, M2, M3) and change IDs (CH-01 to CH-04) in the
  driver diagram, PDSA log, run charts and results tables.
- Report what happened, including the changes that failed. SQUIRE asks
  for the reasoning behind the work (theory), the context and how you
  studied the intervention, not only whether the numbers went up.
- No patient-identifiable data anywhere in this report. Use aggregate
  counts, weeks and ward names that your organisation allows you to
  publish.
- Journals that require SQUIRE ask for the completed checklist with page
  numbers. Section 19 maps each item to this report.
-->

## Document control

<!-- Guidance: Treat the report as a controlled document. Record the governance route, because QI and research approval paths differ by organisation and country. -->

| Field | Value |
|---|---|
| Document ID | [QIR-2026-007] |
| Project title | [Short title, same as section 1] |
| Version | [0.3] |
| Status | [Draft / In review / Approved / Submitted] |
| Owner | [@project-lead] |
| Executive sponsor | [@sponsor] |
| Approvers and reviewers | [@clinical-director], [@qi-lead], [@information-governance] |
| Governance route | [QI registration number / audit and QI committee / ethics decision reference] |
| Reporting period | [YYYY-MM-DD to YYYY-MM-DD] |
| Intended audience | [Committee / learning event / journal name] |
| Last updated | YYYY-MM-DD |
| Classification | [Internal / Public after approval] |

### Approvals

| Role | Name | Decision | Date |
|---|---|---|---|
| Project lead | [@name] | [Approved] | YYYY-MM-DD |
| Executive sponsor | [@name] | [Approved] | YYYY-MM-DD |
| QI or clinical governance lead | [@name] | [Approved for release] | YYYY-MM-DD |
| Information governance reviewer (if publishing data) | [@name] | [Approved] | YYYY-MM-DD |

## Revision history

<!-- Guidance: One row per circulated draft. Note when the data cut-off changes, because results tables depend on it. -->

| Version | Date | Author | Change summary |
|---|---|---|---|
| 0.1 | YYYY-MM-DD | [@name] | First draft: background, aim and measure definitions |
| 0.2 | YYYY-MM-DD | [@name] | *Example:* Added weeks 13 to 24 data and PDSA cycles 1 to 4 |
| 0.3 | YYYY-MM-DD | [@name] | *Example:* Added limitations and sustainability plan after committee comments |

## Contents

<!-- Guidance: Keep the list in sync with the headings. Numbers 1 to 18 match the SQUIRE 2.0 item numbers. -->

- Title and abstract: [1. Title](#1-title), [2. Abstract](#2-abstract)
- Introduction: [3. Problem description](#3-problem-description), [4. Available knowledge](#4-available-knowledge), [5. Rationale](#5-rationale), [6. Specific aims](#6-specific-aims)
- Methods: [7. Context](#7-context), [8. Interventions](#8-interventions), [9. Study of the interventions](#9-study-of-the-interventions), [10. Measures](#10-measures), [11. Analysis](#11-analysis), [12. Ethical considerations](#12-ethical-considerations)
- Results: [13. Results](#13-results)
- Discussion: [14. Summary](#14-summary), [15. Interpretation](#15-interpretation), [16. Limitations](#16-limitations), [17. Conclusions](#17-conclusions)
- Other information: [18. Funding](#18-funding)
- [19. SQUIRE 2.0 cross-reference](#19-squire-20-cross-reference), [20. Sustainability and spread plan](#20-sustainability-and-spread-plan), [21. Glossary and references](#21-glossary-and-references), [Appendix A. PDSA log](#appendix-a-pdsa-log), [Appendix B. Data collection sheet](#appendix-b-data-collection-sheet)

## 1. Title

<!-- Guidance: Say that this is a quality improvement initiative and name the problem, the setting and the change. Readers search for "quality improvement" in titles. -->

**[Improving outcome or process] in [setting] through [main change]: a
quality improvement project**

*Example:* Getting discharge medicines ready before 11:00 on an adult
medical ward: a quality improvement project at Halvermoor District
Hospital (fictional).

## 2. Abstract

<!-- Guidance: Write it last. Use the headings your target journal or committee requires; the table below covers what SQUIRE expects an abstract to carry. Keep to 250 to 300 words unless told otherwise. -->

| Part | Content |
|---|---|
| Background | [The problem, its size locally and why it matters] |
| Local problem | [Baseline performance with the measure and period] |
| Methods | [Model for improvement, design (for example time series with run charts), measures, period] |
| Interventions | [Main changes and how many PDSA cycles] |
| Results | [Outcome measure before and after, signal on the run chart, balancing measure] |
| Conclusions | [What was learned and what happens next] |

*Example:* On Ward 6, a 28-bed adult medical ward, 41.6% (197 of 474)
of planned discharges had their discharge medicines ready on the ward
by 11:00 over a 12-week baseline. Using the Model for Improvement, a
multidisciplinary team tested four changes in sequential PDSA cycles
over 12 weeks: a ward pharmacist at the morning board round, a
"tomorrow's discharges" list, prescribing on the day before discharge,
and a ward medicines cupboard for common discharge items. The weekly
proportion rose above the baseline median from week 13 and stayed above
it for 12 consecutive weeks, a shift on the run chart. Over weeks 17 to
24 the proportion was 70.1% (225 of 321). The balancing measure,
discharge prescriptions needing a pharmacist correction, was 17.7% at
baseline and 18.4% in weeks 17 to 24. The changes are now standard work
on Ward 6 and are being tested on two further wards.

## Introduction

<!-- Guidance: This group answers "why did you start?" Keep it focused on the local problem and the knowledge that shaped your change ideas. -->

The four items below explain the problem, what was already known, why
the team expected the changes to work, and what the project set out to
achieve. Write them so that a reader from another organisation can judge
whether the problem looks like theirs.

### 3. Problem description

<!-- Guidance: Describe the gap between current and desired performance in your setting, with numbers. Say who noticed it and how. Avoid general statements about national problems unless they explain the local one. -->

[Describe the nature and significance of the local problem: what happens
now, what should happen, how often the gap occurs, and the effect on
patients, staff and flow.]

*Example:* Patients on Ward 6 who were medically fit to leave often
waited on the ward for discharge medicines. Baseline data from 12 weeks
(474 planned discharges) showed that 41.6% had medicines ready by 11:00.
Late medicines delayed bed availability for patients waiting in the
emergency department and the acute medical unit, and patients and
families reported uncertainty about when they could leave.

### 4. Available knowledge

<!-- Guidance: Summarise what is known about the problem and about interventions that address it: published studies, guidance, other organisations' projects. Cite sources. Say what is uncertain. -->

[Summarise relevant evidence and experience: published studies, national
or professional guidance, previous local projects and benchmarking.
State where the evidence is thin or comes from different settings.]

| Source *(Example)* | What it showed | Relevance to this project |
|---|---|---|
| [Published study or review on discharge medicines turnaround] | [Finding in original words] | [Similar ward type / different setting] |
| [Previous local project on another ward] | [Finding] | [Same pharmacy service, different staffing] |
| [Professional or national guidance] | [What it recommends] | [How it shaped measures or changes] |

### 5. Rationale

<!-- Guidance: State the theory of change: why you expected these changes to work in this context. A driver diagram is a compact way to show it. SQUIRE gives weight to making the reasoning explicit. -->

[Explain the informal or formal theory, framework or logic model that
links the changes to the expected improvement, and the assumptions it
rests on.]

*Example:* The team's theory was that medicines are late because the
prescription is written on the morning of discharge, then queues in
pharmacy with that day's other work. Moving prescribing to the day
before, and giving the pharmacist early sight of likely discharges,
should move the work out of the morning peak. The driver diagram below
shows the aim, primary drivers, secondary drivers and change ideas
(CH-01 to CH-04) that the PDSA log in appendix A tests.

```mermaid
flowchart LR
  AIM["Aim: 70% of planned discharges with medicines ready by 11:00"]
  P1["P1 Early identification of discharges"]
  P2["P2 Prescribing timing"]
  P3["P3 Pharmacy workflow"]
  S1["S1 Shared list of likely discharges"]
  S2["S2 Pharmacist present at decision point"]
  S3["S3 Prescription written the day before"]
  S4["S4 Common items available on ward"]
  C1["CH-01 Pharmacist at board round"]
  C2["CH-02 Tomorrow's discharges list"]
  C3["CH-03 Day-before prescribing"]
  C4["CH-04 Ward discharge cupboard"]
  AIM --> P1
  AIM --> P2
  AIM --> P3
  P1 --> S1
  P1 --> S2
  P2 --> S3
  P3 --> S2
  P3 --> S4
  S2 --> C1
  S1 --> C2
  S3 --> C3
  S4 --> C4
```

### 6. Specific aims

<!-- Guidance: One SMART aim statement: what, how much, by when, for whom. Name the outcome measure that tests it. Add secondary aims only if you measure them. -->

[State the purpose of the project and of this report.]

*Example:* To increase the proportion of planned discharges from Ward 6
with discharge medicines ready on the ward by 11:00 from a baseline of
41.6% to 70% within 12 weeks of the first test of change, without an
increase in discharge prescriptions needing pharmacist correction. This
report describes the first 24 weeks (12 baseline, 12 improvement).

## Methods

<!-- Guidance: This group answers "what did you do and how did you study it?" Separate the interventions (what changed) from the study of the interventions (how you learned whether and why it worked). -->

The six items below describe the setting, the changes, the approach to
studying them, the measures, the analysis and the ethical review. Give
enough detail that another team could repeat the work and judge how
much of the result depends on local conditions.

### 7. Context

<!-- Guidance: Describe the elements of context that mattered: setting, staffing, leadership, culture, information systems, other projects running at the same time. Say how context could have helped or hindered the work. -->

| Context element | Description *(Example)* |
|---|---|
| Setting | Ward 6, 28-bed adult general medical ward in a 410-bed district hospital (fictional) |
| Patient population | Adults admitted as emergencies; median length of stay [n] days |
| Staffing | Two consultant teams, one ward pharmacist 09:00 to 13:00 on weekdays |
| Pharmacy service | Central dispensary, discharge prescriptions processed in order of arrival |
| Information systems | Electronic prescribing; discharge prescription status visible on the ward board |
| Leadership and culture | Ward manager and matron sponsored the project; daily board round already established |
| Concurrent initiatives | Hospital-wide flow programme started in week 10 (see section 16) |

### 8. Interventions

<!-- Guidance: Describe each change in enough detail to reproduce it: what, who, when, how often, with which tools. Name the team members by role and say how the team worked. -->

**Team.** [List roles: project lead, clinicians, pharmacist, nursing,
patient partner, data analyst, sponsor. Say how often the team met.]

| Change ID | Change | Who delivers it | When and how often | Start week |
|---|---|---|---|---|
| CH-01 *(Example)* | Ward pharmacist joins the 09:00 board round and flags likely discharges | Ward pharmacist | Weekdays | 13 |
| CH-02 *(Example)* | Nurse in charge updates a "tomorrow's discharges" list at 16:00 | Nurse in charge | Daily | 15 |
| CH-03 *(Example)* | Discharge prescription written the day before for patients on the list | Ward doctors | Daily by 18:00 | 16 |
| CH-04 *(Example)* | Ward cupboard stocked with pre-packed common discharge items | Pharmacy technician | Restocked twice weekly | 17 |

Describe also what did not change: the discharge criteria, the clinical
decision about fitness for discharge and the prescribing rules stayed
the same, so that any change in the measures can be attributed to the
workflow changes.

### 9. Study of the interventions

<!-- Guidance: Explain how you assessed the effect of the changes and whether they were delivered as planned: the design (for example time series with run charts), PDSA cycles, process evaluation, interviews. This is the "how do we know" part. -->

[Describe the approach chosen for assessing the impact of the
interventions and for judging whether the observed effects were due to
them. Include how you checked that each change was carried out as
intended.]

*Example:* The team used the Model for Improvement with sequential PDSA
cycles (appendix A). Impact was studied as a time series with weekly
data plotted on a run chart against the baseline median. Fidelity was
checked for each change: the pharmacist's attendance at board rounds
(CH-01) and the completion of the 16:00 list (CH-02) were recorded on
the ward board and counted weekly. Two short staff huddles after weeks
18 and 22 collected views on what helped and what got in the way.

### 10. Measures

<!-- Guidance: Give each measure an ID, a type (outcome, process, balancing), an operational definition (numerator, denominator, inclusions, exclusions), a data source and a collection frequency. Say how you checked data quality. -->

| ID | Type | Operational definition | Source | Frequency |
|---|---|---|---|---|
| M1 *(Example)* | Outcome | Numerator: planned discharges with all discharge medicines on the ward by 11:00 on the day of discharge. Denominator: planned discharges from Ward 6 that week. Excludes self-discharge and transfers to other hospitals | Electronic prescribing timestamps and ward board | Weekly |
| M2 *(Example)* | Process | Numerator: planned discharges with the prescription signed by 18:00 the day before. Denominator: as M1 | Electronic prescribing | Weekly |
| M3 *(Example)* | Balancing | Numerator: discharge prescriptions needing a pharmacist correction before dispensing. Denominator: as M1 | Pharmacy intervention log | Weekly |

**Data quality.** [Describe how the data were validated: for example,
the project lead checked 10 records a week against the paper ward board
for the first four weeks, and the definition was fixed before baseline
collection began.]

### 11. Analysis

<!-- Guidance: Describe qualitative and quantitative methods. For run charts, state the rules used to detect non-random variation and when the baseline median was frozen. For control charts, name the chart type. -->

[Describe the analytic methods used to draw inferences from the data,
and how variation over time was handled.]

*Example:* M1, M2 and M3 were plotted weekly on run charts. The baseline
median of M1 (42.3%) was calculated from weeks 1 to 12 and frozen, then
extended across the improvement period. Non-random variation was judged
with commonly used run chart rules (Perla, Provost and Murray, 2011): a
shift (six or more consecutive points above or below the median, with
points on the median neither breaking nor adding to the run), a trend
(five or more consecutive points all going up or all going down), too
few or too many runs, and an astronomical data point. Staff huddle notes
were grouped into themes by two team members independently.

### 12. Ethical considerations

<!-- Guidance: State how ethical aspects were reviewed and by whom, including whether formal ethics review was required. Rules for QI and research differ; follow your organisation's decision tool and record the outcome. Declare conflicts of interest. -->

[State the ethical review route and outcome, data protection measures and
any conflicts of interest.]

*Example:* The project was registered with the hospital's audit and QI
office (reference [QI-2026-041]). Using the organisation's research
decision tool, the office confirmed it was service improvement and did
not need research ethics committee review. Only aggregate counts left
the ward. The team declared no conflicts of interest.

## 13. Results

<!-- Guidance: Report the initial steps and how the interventions evolved, the details of the process measures, the outcome measures with the run chart, contextual elements that interacted with the changes, unexpected consequences, and missing data. Use the same IDs as section 10. -->

### 13.1 How the interventions evolved

[Describe the sequence of PDSA cycles and how each changed the next. The
full log is in appendix A.]

*Example:* CH-01 began in week 13 with one consultant team and spread to
both teams in week 14 after the first cycle showed that the pharmacist
could cover both board rounds in 30 minutes. CH-02 was adapted in its
second cycle: the list moved from a paper sheet to a column on the
electronic ward board because the paper sheet was lost twice. CH-04
started in week 17 with 12 pre-packed items chosen from a month of
dispensing data.

### 13.2 Outcome measure M1

| Period *(Example)* | Weeks | Discharges ready by 11:00 | Planned discharges | Proportion |
|---|---|---|---|---|
| Baseline | 1 to 12 | 197 | 474 | 41.6% |
| Testing changes | 13 to 16 | 86 | 161 | 53.4% |
| All changes in place | 17 to 24 | 225 | 321 | 70.1% |
| Total | 1 to 24 | 508 | 956 | 53.1% |

The run chart shows weekly M1 against the frozen baseline median. All 12
points from week 13 to week 24 sit above the median, which meets the
shift rule (six or more consecutive points on one side). Weeks 12 to 21
also form a trend: ten consecutive points, each higher than the one
before.

```vega-lite
{
  "$schema": "https://vega.github.io/schema/vega-lite/v5.json",
  "description": "Example run chart: weekly proportion of planned discharges with medicines ready by 11:00, Ward 6 (fictional), baseline median 42.3 percent",
  "width": 460,
  "height": 240,
  "data": {
    "values": [
      {"week": 1, "pct": 39.5}, {"week": 2, "pct": 43.9}, {"week": 3, "pct": 38.9}, {"week": 4, "pct": 42.5},
      {"week": 5, "pct": 38.5}, {"week": 6, "pct": 45.2}, {"week": 7, "pct": 43.2}, {"week": 8, "pct": 37.5},
      {"week": 9, "pct": 44.2}, {"week": 10, "pct": 42.1}, {"week": 11, "pct": 43.9}, {"week": 12, "pct": 38.5},
      {"week": 13, "pct": 47.5}, {"week": 14, "pct": 47.6}, {"week": 15, "pct": 57.9}, {"week": 16, "pct": 61.0},
      {"week": 17, "pct": 66.7}, {"week": 18, "pct": 67.4}, {"week": 19, "pct": 70.0}, {"week": 20, "pct": 70.3},
      {"week": 21, "pct": 71.4}, {"week": 22, "pct": 70.7}, {"week": 23, "pct": 71.8}, {"week": 24, "pct": 72.5}
    ]
  },
  "layer": [
    {
      "mark": {"type": "line", "point": true},
      "encoding": {
        "x": {"field": "week", "type": "quantitative", "title": "Week", "scale": {"domain": [1, 24]}},
        "y": {"field": "pct", "type": "quantitative", "title": "M1 medicines ready by 11:00 (%)", "scale": {"domain": [30, 80]}}
      }
    },
    {
      "data": {"values": [{"median": 42.3}]},
      "mark": {"type": "rule", "strokeDash": [4, 4]},
      "encoding": {"y": {"field": "median", "type": "quantitative"}}
    },
    {
      "data": {"values": [{"goal": 70}]},
      "mark": {"type": "rule", "color": "gray"},
      "encoding": {"y": {"field": "goal", "type": "quantitative"}}
    }
  ]
}
```

Dashed line: baseline median (42.3%). Solid grey line: aim (70%). The
weekly counts behind each point are in appendix B.

### 13.3 Process and balancing measures

| Measure *(Example)* | Baseline (weeks 1 to 12) | Weeks 17 to 24 | Comment |
|---|---|---|---|
| M2 prescriptions signed by 18:00 the day before | [n of 474, %] | [n of 321, %] | [Signal on run chart?] |
| M3 prescriptions needing pharmacist correction | 84 of 474 (17.7%) | 59 of 321 (18.4%) | No signal on the run chart; no evidence of harm from earlier prescribing |
| CH-01 fidelity: board rounds with pharmacist present | not applicable | [n of n weekdays] | [Gaps during annual leave] |

### 13.4 Context, unintended consequences and missing data

[Describe how context interacted with the changes, any unexpected
benefits or problems, and how much data was missing and why.]

*Example:* The hospital flow programme started in week 10, before the
first change, and introduced a daily site meeting that did not involve
Ward 6 pharmacy staff; M1 did not change in weeks 10 to 12. Staff
reported an unexpected benefit: earlier conversations with patients
about their medicines. Data for two days in week 20 were missing
because of an electronic prescribing outage; those discharges were
excluded from both numerator and denominator.

## Discussion

<!-- Guidance: This group answers "what does it mean?" Keep the interpretation proportionate to a single-site time series. -->

The four items below summarise the findings, interpret them against
other work and the costs, set out the limitations and state the
conclusions and next steps.

### 14. Summary

<!-- Guidance: Key findings in a few sentences, linked to the aim, plus what is particularly strong about the project. -->

[Summarise the key findings, their relevance to the rationale and aims,
and the particular strengths of the project.]

*Example:* Moving discharge prescribing to the day before, with early
pharmacist involvement, was followed by a sustained rise in the
proportion of discharges with medicines ready by 11:00 from 41.6% to
70.1%, meeting the aim in weeks 19 to 24 without a rise in prescription
corrections. The project's strength is that it measured fidelity for
each change and a balancing measure from the start.

### 15. Interpretation

<!-- Guidance: Discuss the association between changes and outcomes, compare with other publications, describe the impact on people and systems, explain differences between expected and observed results, and report costs and trade-offs. -->

[Discuss the nature of the association between the interventions and
the outcomes, comparison with other work, the effect on people and
systems, reasons for any differences from what was expected, and
costs, opportunity costs and trade-offs.]

| Question | Answer *(Example)* |
|---|---|
| Does the timing of the signal fit the changes? | The rise began in week 13 with CH-01 and steepened after CH-03 in week 16 |
| How does this compare with published work? | [Similar or different, with reasons] |
| What did it cost? | 4 hours of pharmacist time a week moved from the dispensary; [cost of pre-packed stock] |
| What trade-offs appeared? | Dispensary queue for other wards [rose / unchanged]; monitored by the pharmacy manager |

### 16. Limitations

<!-- Guidance: Name the threats to generalisability and to internal validity (concurrent changes, secular trend, measurement changes, regression to the mean) and what you did to reduce them. -->

[List the limits to generalisability, factors that might have limited
internal validity, and the efforts made to minimise them.]

*Example:* The design is a single-ward time series without a control
ward, so a concurrent hospital-wide effect cannot be excluded; the flow
programme that began in week 10 is the main alternative explanation.
The absence of change in weeks 10 to 12 and the step pattern that
follows the change dates make it less likely. The definition of a
planned discharge relied on the ward board, which was updated by many
staff.

### 17. Conclusions

<!-- Guidance: State usefulness, sustainability, potential for spread, implications for practice and further study, and next steps. -->

[State the usefulness of the work, how it will be sustained, the
potential for spread to other settings, implications for practice and
further study, and suggested next steps.]

*Example:* The four changes are now standard work on Ward 6. The team
will monitor M1 monthly for six months and is testing CH-01 and CH-03 on
two surgical wards with different pharmacy cover.

## Other information

<!-- Guidance: Funding is the only item in this SQUIRE group. Keep it factual. -->

Add here any information required by the target journal or committee
that does not fit the SQUIRE items, such as patient partner involvement
or data availability statements.

### 18. Funding

<!-- Guidance: Name every funding source and the role of the funder in design, implementation, interpretation and reporting. Say "none" when there was none. -->

[List sources of funding that supported this work and the role, if any,
of the funder in the design, implementation, interpretation and
reporting.]

*Example:* No external funding. Staff time was provided by the hospital
within normal duties. The pre-packed stock for CH-04 was funded from the
pharmacy budget.

## 19. SQUIRE 2.0 cross-reference

<!-- Guidance: Fill the last column before submission. Journals ask for page numbers; for an internal report, section numbers are enough. Use the official checklist for the full item wording. -->

| SQUIRE group | Item | Topic (short name) | Where in this report |
|---|---|---|---|
| Title and abstract | 1 | Title | Section 1 |
| Title and abstract | 2 | Abstract | Section 2 |
| Introduction | 3 | Problem description | Section 3 |
| Introduction | 4 | Available knowledge | Section 4 |
| Introduction | 5 | Rationale | Section 5 |
| Introduction | 6 | Specific aims | Section 6 |
| Methods | 7 | Context | Section 7 |
| Methods | 8 | Intervention(s) | Section 8 |
| Methods | 9 | Study of the intervention(s) | Section 9 |
| Methods | 10 | Measures | Section 10 |
| Methods | 11 | Analysis | Section 11 |
| Methods | 12 | Ethical considerations | Section 12 |
| Results | 13 | Results | Section 13 |
| Discussion | 14 | Summary | Section 14 |
| Discussion | 15 | Interpretation | Section 15 |
| Discussion | 16 | Limitations | Section 16 |
| Discussion | 17 | Conclusions | Section 17 |
| Other information | 18 | Funding | Section 18 |

## 20. Sustainability and spread plan

<!-- Guidance: Not a SQUIRE item, but committees ask for it. Name an owner for each measure after the project team disbands, and the trigger that restarts improvement work. -->

| Element | Plan *(Example)* |
|---|---|
| Standard work | CH-01 to CH-04 written into the ward operating procedure [document ID] |
| Measure owner after handover | Ward manager reviews M1 monthly; pharmacy manager reviews M3 monthly |
| Trigger for review | Six consecutive weekly points below 60%, or any month with M3 above 25% |
| Spread | Test on Wards 3 and 9 from [YYYY-MM-DD]; adapt CH-01 to afternoon pharmacist cover |
| Learning shared | Hospital QI event [YYYY-MM-DD]; summary in the pharmacy newsletter |

## 21. Glossary and references

<!-- Guidance: Define abbreviations a reader outside your organisation will not know, and list every source cited in sections 4 and 15. -->

### 21.1 Glossary

| Term | Meaning |
|---|---|
| Balancing measure | A measure that checks whether a change has caused a problem elsewhere in the system |
| Driver diagram | A diagram linking an aim to the factors (drivers) that influence it and the change ideas that act on them |
| Fidelity | The extent to which a change was delivered as intended |
| PDSA | Plan, Do, Study, Act: a cycle for testing a change on a small scale and learning from it |
| Run chart | A plot of a measure over time with its median, read with rules for non-random variation |
| Shift | A run of six or more consecutive points on one side of the median, a signal of non-random change |
| SQUIRE | Standards for QUality Improvement Reporting Excellence |

### 21.2 References

1. Ogrinc G, Davies L, Goodman D, Batalden P, Davidoff F, Stevens D.
   SQUIRE 2.0 (Standards for QUality Improvement Reporting Excellence):
   revised publication guidelines from a detailed consensus process.
   BMJ Qual Saf. 2016;25(12):986-992. doi:10.1136/bmjqs-2015-004411.
   Published simultaneously in several journals.
2. SQUIRE 2.0 Explanation and Elaboration. BMJ Qual Saf.
   2016;25(12):e7. Listed on the EQUATOR Network page:
   https://www.equator-network.org/reporting-guidelines/squire/
3. Langley GJ, Moen RD, Nolan KM, Nolan TW, Norman CL, Provost LP. The
   Improvement Guide: A Practical Approach to Enhancing Organizational
   Performance. 2nd edition. Jossey-Bass; 2009. Model for Improvement
   summary: https://www.ihi.org/library/model-for-improvement
4. Perla RJ, Provost LP, Murray SK. The run chart: a simple analytical
   tool for learning from variation in healthcare processes. BMJ Qual
   Saf. 2011;20(1):46-51. doi:10.1136/bmjqs.2009.037895.
5. [Local and published sources cited in sections 4 and 15]

Related templates in this collection: `healthcare/pdsa-cycle` for each
test of change, `healthcare/clinical-audit` for criterion-based audit
before and after a project, `healthcare/root-cause-analysis` when the
project starts from a serious incident, `business/kpi-scorecard` for
ongoing monitoring and `project/lessons-learned` for the close-out
review.

## Appendix A. PDSA log

<!-- Guidance: One row per cycle. The prediction is the most often skipped field and the most useful: write it before the test. Keep failed cycles. -->

| Cycle | Change | Plan and prediction | Do (what happened) | Study (result vs prediction) | Act |
|---|---|---|---|---|---|
| PDSA-01 *(Example)* | CH-01 | Pharmacist at one team's board round for 5 days; predict at least 5 likely discharges flagged | Attended 5 of 5 days; 9 discharges flagged | 9 flagged, more than predicted; 7 of the 9 had medicines by 11:00 | Adopt; extend to both teams |
| PDSA-02 *(Example)* | CH-02 | Paper list at 16:00 for 1 week; predict list complete 4 of 5 days | Complete 3 of 5 days; sheet lost twice | Worse than predicted; paper unreliable | Adapt: move list to electronic ward board |
| PDSA-03 *(Example)* | CH-02, CH-03 | Electronic list plus day-before prescribing for 1 week; predict 50% signed by 18:00 | Doctors prescribed for 14 of 22 listed patients | 64% signed by 18:00, above prediction | Adopt; add to doctors' handover |
| PDSA-04 *(Example)* | CH-04 | Ward cupboard with 12 pre-packed items for 2 weeks; predict 20% of discharges use it | Used for 19 of 81 discharges | 23%, close to prediction; one stock-out | Adopt; restock twice weekly |

## Appendix B. Data collection sheet

<!-- Guidance: Keep the raw weekly counts here so that anyone can recompute the run chart and the period totals. -->

| Week | M1 numerator | M1 denominator | M1 % | Notes |
|---|---|---|---|---|
| 1 | 15 | 38 | 39.5 | Baseline |
| 2 | 18 | 41 | 43.9 | |
| 3 | 14 | 36 | 38.9 | |
| 4 | 17 | 40 | 42.5 | |
| 5 | 15 | 39 | 38.5 | |
| 6 | 19 | 42 | 45.2 | |
| 7 | 16 | 37 | 43.2 | |
| 8 | 15 | 40 | 37.5 | |
| 9 | 19 | 43 | 44.2 | |
| 10 | 16 | 38 | 42.1 | Hospital flow programme starts |
| 11 | 18 | 41 | 43.9 | |
| 12 | 15 | 39 | 38.5 | Baseline median frozen: 42.3% |
| 13 | 19 | 40 | 47.5 | CH-01 starts (PDSA-01) |
| 14 | 20 | 42 | 47.6 | CH-01 both teams |
| 15 | 22 | 38 | 57.9 | CH-02 starts (PDSA-02) |
| 16 | 25 | 41 | 61.0 | CH-03 starts (PDSA-03) |
| 17 | 26 | 39 | 66.7 | CH-04 starts (PDSA-04) |
| 18 | 29 | 43 | 67.4 | Staff huddle 1 |
| 19 | 28 | 40 | 70.0 | |
| 20 | 26 | 37 | 70.3 | Two days excluded (system outage) |
| 21 | 30 | 42 | 71.4 | |
| 22 | 29 | 41 | 70.7 | Staff huddle 2 |
| 23 | 28 | 39 | 71.8 | |
| 24 | 29 | 40 | 72.5 | |

*Example data:* every row above is fictional. Totals: weeks 1 to 12,
197 of 474; weeks 13 to 16, 86 of 161; weeks 17 to 24, 225 of 321.

## Standard and licence note

Structure aligned with SQUIRE 2.0 (Standards for QUality Improvement
Reporting Excellence), Ogrinc G and colleagues, BMJ Quality and Safety
2016;25(12):986-992, published simultaneously in several journals and
listed by the EQUATOR Network. This template uses the SQUIRE item
numbers and short item names only; every heading explanation, guidance
note and example is original text, and no checklist wording is
reproduced. Use the official SQUIRE 2.0 checklist and the Explanation
and Elaboration paper when you submit, and check the EQUATOR Network
page for the current version. The Model for Improvement is cited from
Langley and colleagues (Associates in Process Improvement) and the run
chart rules from Perla, Provost and Murray (2011). The organisation,
ward and all figures in the examples are fictional. This is a reporting
format, not clinical advice; follow your organisation's governance,
ethics and privacy rules and consult qualified professionals. Template
licence: MIT.