Abstract
Background
Quality improvement reports (QIRs) are important for disseminating real-world interventions in healthcare. However, as a relatively new genre of scholarly writing, QIRs vary widely in clarity, methodological rigour and scholarly contribution. Despite the availability of reporting frameworks such as Standards for Quality Improvement Reporting Excellence (SQUIRE) V.2.0, key elements—such as methodological rigour, contextual detail and rationale for interventions—are often under-reported or poorly articulated. This study aimed to (1) identify best practices in publishing QIRs and (2) examine common methodological strengths and weaknesses in project design and execution.
Methods
We conducted a scoping review using the six-stage framework by Arksey and O’Malley. A purposeful sample of 71 QIRs published in 2019 across three leading quality improvement (QI) journals—BMJ Quality & Safety, BMJ Open Quality and Joint Commission Journal on Quality and Patient Safety—was analysed. Data extraction was guided by SQUIRE V.2.0 and supplemented by additional best practices. Return-of-findings sessions with QI scholars, journal editors, frontline practitioners and an international QI conference audience refined the findings and ensured practical relevance.
Results
Most QIRs described a local problem and intervention but only 22% articulated strong aim statements with measurable targets. Two-thirds referenced a QI methodology but many descriptions of common QI tools lacked rigour. Process and balancing measures were often missing or inadequately justified. While Plan-Do-Study-Act cycles were commonly reported, few met criteria for ‘authenticity’. Data analysis and display methods varied, with several common weaknesses. Discussion sections frequently lacked depth and contextual factors—critical for reproducibility—were inconsistently described. Eight core lessons emerged to support more rigorous, transparent and impactful reporting.
Conclusions
As an emerging genre of scholarly communication, many QIRs still fall short in conveying methodological rigour and transferable insights. This review provides practical recommendations, illustrated by strong examples, to help authors and educators improve the clarity and impact of QIRs across healthcare settings.
Keywords: Quality improvement, Quality improvement methodologies, PDSA
WHAT IS ALREADY KNOWN ON THIS TOPIC
Quality improvement reports (QIRs) aim to share real-world interventions that improve care, but the quality and clarity of published reports are highly variable.
Despite the existence of guidelines like Standards for Quality Improvement Reporting Excellence (SQUIRE) V.2.0, authors often struggle to convey methodological rigour, contextual detail, change theory and transferable lessons, limiting the scholarly and practical value of QIRs.
WHAT THIS STUDY ADDS
This scoping review analysed 71 QIRs and identified common gaps, inconsistencies and methodological pitfalls.
It synthesises eight practical lessons for improving QIRs, supported by examples of strong reporting.
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY
The results offer actionable guidance for quality improvement (QI) educators, authors and reviewers to improve the rigour, coherence and impact of QIRs.
Adoption of these lessons would enhance the impact and reproducibility of successful QI work and increase its influence across this emerging genre of scholarly work.
Background
Quality improvement (QI) is an evolving discipline, rooted in advancing patient care, safety and system performance. As the field matures, the publication of QI work has become increasingly important—to disseminate lessons learnt and to support scholarly advancement and professional recognition for QI practitioners. Unlike traditional clinical research, QI is primarily concerned with driving real-world change. Its publications, therefore, must serve a dual function: documenting methodological rigour and providing practical guidance to other scholars undertaking similar improvements in different contexts.
There are many ways authors can contribute to the scholarly conversation in QI; common archetypes include implementation studies and retrospective evaluations. A particularly valuable type is the full-scope quality improvement report (QIR)—a prospective, rigorous account of an improvement initiative that spans from problem definition to testing change ideas and demonstrating sustainability. When executed well, this format is uniquely suited to both build on prior knowledge and communicate experiential learning. However, because the format is still evolving, the quality and clarity of published QIRs remain highly variable.
In well-established fields, publication types are supported by clear guidelines with widely available examples. In contrast, QI remains a developing genre of scholarship where rhetorical strategy is still maturing. As a result, authors often rely on journal-specific instructions or broad guidelines like Standards for Quality Improvement Reporting Excellence (SQUIRE) V.2.0.1 While these resources provide an important starting point, their aim of inclusivity for various archetypes can inadvertently obscure which elements are essential for transparency, rigour and generalisability of QIRs.
Too often, QIRs fail to fully convey the complexity of QI work or highlight transferrable insights. Key elements—such as the rationale behind intervention choices, descriptions of local context and the evolution of change ideas—are inconsistently reported or missing altogether. Even robust improvement work can lose value when the report lacks logical flow, fails to situate the work within a broader quality landscape or does not reflect on why the intervention succeeded (or failed). Without consistency and narrative coherence, QIRs have become undervalued and undercited rather than serving as practical resources. This is particularly concerning as QIRs are often used as templates by novice QI practitioners and as teaching tools to guide new scholars through their first publications.
Recognising these challenges, we conducted a scoping review to examine how QIRs are currently written and where opportunities exist to strengthen their scholarly and practical value. We reviewed 71 QIRs from leading QI journals, analysed their structure, content and rhetorical features to identify common gaps, inconsistencies and methodological pitfalls. Our goal was to describe the current state of the field and to offer practical, field-informed guidance for both new and experienced authors seeking to improve the clarity, rigour and impact of their QI reporting.
Methods
The six-stage scoping review framework by Arksey and O’Malley2 was used to synthesise and share findings, identify key gaps and inconsistencies in the literature and inform future directions for QI research and reporting.
Stage 1: identifying the research question
The primary question guiding this review asked: What can be learnt from existing QI publications about best practices for writing and publishing QI work? A secondary objective emerged during analysis: to identify common methodological strengths and weaknesses in project design and execution.
Stage 2: identifying relevant literature
Unlike the exhaustive search strategies typical of systematic or scoping reviews,3 4 a purposeful approach to sampling was employed to balance feasibility and depth by selecting information-rich cases for analysis.5 This approach, commonly used in qualitative evidence synthesis,3 4 is not intended to be exhaustive; rather, it aims to capture sufficient variation to examine complexity4 and explore meaningful patterns within the data.6 To avoid over-representation of COVID-related publications, a 1-year period (2019) was selected across three leading quality improvement journals: BMJ Quality & Safety, BMJ Open Quality and Joint Commission Journal on Quality and Patient Safety (JC). These journals were chosen for their academic reach within this genre, geographic diversity (European and North American) and relatively high volume of QIRs (BMJ Open Quality). From BMJ Quality & Safety and BMJ Open Quality, original research and QI studies were selected; from JC, original articles, improvement briefs and innovation reports were included.
Stage 3: study selection
The full search strategy produced 318 results (figure 1). Two reviewers independently screened full-text articles for relevance, with an independent third reviewer resolving discrepancies. While 247 papers contributed to the QI scholarly conversation (eg, implementation studies, retrospective studies of QI interventions, etc), 71 met criteria for full-text inclusion as QIR.
Figure 1. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram.
Stages 4 and 5: analysis (charting, collating and summarising the data and reporting of results)
DistillerSR was used to extract, categorise and organise data. Extraction criteria focused on key elements of a QIRs based on SQUIRE V.2.01 reporting guidelines, the six domains of healthcare quality and the model for improvement (MFI). While these served as the initial framework for extraction, it became evident that it did not fully capture best practices for all aspects of QIRs. We, therefore, supplemented our analysis with additional best practices such as the recommendations by Leis and Shojania7 on conducting Plan-Do-Study-Act (PDSA) cycles. Three team members (KB, MG and NM) completed the initial extraction and two quality consultants (ES and AG) conducted quality control on all 71 articles to ensure accuracy and completeness of the extracted data. Descriptive numerical analyses were conducted on all extracted data.
Stage 6: consultation
A return-of-findings process was conducted with key stakeholders across three sessions: (1) local QI practitioners during a continuing professional development event, (2) current and former QI journal editors, faculty from QI graduate programmes and QI researchers at a provincial meeting and (3) attendees at the Institute for Health Care Improvement (IHI) International Quality Forum in London, England (2024). These sessions aimed to share preliminary findings and to refine key concepts. This process confirmed strong interest in this body of work and emphasised the need for exemplars of rigorous QI reporting, which informed the design of this publication.
Patient and public involvement
Patients were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Results
Description of studies
A total of 718,78 papers were included (12 from the Joint Commission Journal for Quality and Safety, three from the BMJ Quality & Safety and 56 from the BMJ Open Quality), as summarised in figure 1. The details of the included individual QIRs are summarised in online supplemental table 1. Most studies (87%) originated from the USA, the UK and Canada, and were conducted in academic hospitals (65%).
Introduction/Background
Most QIRs (97%) described the nature and significance of a local problem and 87% related that problem to broader challenges faced by others. However, many did so by comparing similar clinical problems across settings rather than situating the problem within larger system-level quality gaps. For example, a study may describe high rates of thyroid-stimulating hormone (TSH) testing in an endocrinology clinic and compare this with overuse in similar clinics but fail to link it to broader concerns such as non-adherence to Endocrine and Metabolism Choosing Wisely recommendations.79
While 92% of QIRs cited literature relevant to the clinical problem, fewer (60%) referenced QI literature from different contexts. For instance, a project aimed at documenting goals-of-care (GOC) discussions with patients with heart failure might cite evidence of the clinical and financial impact of palliating care for patients with heart failure, but neglect literature on GOC documentation in other chronic illness settings.
Most authors clearly articulated project scope (93%) and boundaries (86%). While SQUIRE V.2.01 recommends inclusion of the rationale—such as frameworks, concepts and theories underpinning the intervention—this was often absent or presented elsewhere. In many cases, the rationale evolved from root cause analyses, which were frequently described in the Methods or Results sections rather than the Introduction, leading to duplication or confusing sequencing.
Aim statements
Of the 69 papers with an aim statement, only 16 (23%) included the four key elements of specific aims: what is being improved, by how much, for whom and by when (table 1). Justification for targets was present in 39 studies (57%). Alignment of aim statements with the domains of healthcare quality was mostly with effective care (35%), safety (32%) and timeliness (17%); only one aligned with equity (online supplemental table 1).
Table 1. Summary of key findings by paper section.
| Aim statements | |
Location of aim statements:
|
Components of specific aim statements:
|
| Methodology | |
Explicitly stated QI methodology 24/71 (34%)*:
|
Not explicitly stated 47/71 (66%):
|
| Common QI tools for root cause analysis | |
Diagnostic tools reported 60/71 (85%):
|
Root cause confirmation/validation techniques reported 12/71 (17%)*:
|
| Solutions/Intervention generation | |
| |
| Study of interventions (PDSA cycles): 62/71 (87%) QIRs included PDSA cycles or similar | |
Variability of ‘PDSA’ nomenclature:
Characteristics of ‘authentic’ PDSA cycles†
|
Types of PDSA cycles described:
Characteristics of ‘inauthentic’ PDSA cycles†
|
| Results | |
Data analysis and display methods:
Common weaknesses of sustainability and spread:
|
Common weaknesses of data display:
Common weaknesses of sustainability claims:
|
| Discussions | |
SQUIRE components addressed:
|
Additional observations of the Discussions:
|
| Limitations | |
Limitations described:
| |
| Conclusions | |
SQUIRE V.2.0 components addressed:
| |
Total >100% because authors reported of using more than one method or tool.
The ‘authenticity’ of these PDSA cycles were evaluated using criteria suggested by Leis and Shojania.7
PDSA, Plan-Do-Study-Act; QI, quality improvement; QIR, quality improvement report; SPC, statistical process control; SQUIRE, Standards for Quality Improvement Reporting Excellence.
Methods
Context
While not part of our frequency counts, many papers included a section labelled ‘Context’, but this often resembled a traditional setting description (eg, site size, staffing) and rarely included the necessary contextual information for a QI project such as organisational culture or influence of local champions. Furthermore, this section often replicated information from the introduction.
Stakeholders and project team
Eighty per cent of QIRs described the team members or stakeholders involved, typically using generic terms (eg, ‘residents and nurses’). Few QIRs provided rationale for the team composition or identified missing perspectives. Moreover, inclusion of patient or caregiver voices was rare.
Methodology
Approximately a third (24/71, 34%) of QIRs made explicit mention of the QI methodology or framework used to guide the work (table 1). About half (37/71, 52%) did not explicitly identify the QI methodology used to guide the work but did make use of PDSA cycles or similar iterative cycles (table 1).
Measures
Nearly all (97%) reported baseline performance for their outcome of interest. Approximately one-third (31%) included a balancing measure although these often appeared to fulfil reporting expectations rather than to provide robust insights (eg, measuring clinician satisfaction by Likert scale rather than using validated workload metrics or time-motion data). Process measures were reported in 58% of QIRs and while most aligned to a specific change idea they often lacked adequate detail for assessing fidelity (eg, recording attendance at education sessions but not knowledge acquisition).
Root cause analysis
While not a requirement of SQUIRE V.2.01 guidelines, 85% of QIRs reported using at least one common QI diagnostic tool to identify contributing factors (table 1). Less than one-third (31%) reported using literature review as part of their root cause analysis (RCA), and only two studies cited theory (eg, theory of constraints). Of the QIRs reporting use of a common QI tool, 12 (20%) provided descriptions of how root causes were confirmed or validated.
Published RCAs had several common pitfalls, most of which can be distilled to ‘lack of breadth’ and ‘lack of depth’. Lack of breadth was identified when the paper considered a limited number of perspectives (eg, a cause-and-effect diagram that only contained two to three categories). Lack of depth was identified when a paper described a root cause at a superficial level without applying deeper thinking, such as a 5 Whys approach. For example, when addressing frequent ordering of routine blood tests, a QI team concludes that the root cause is ‘residents are not following Choosing Wisely guidelines’ but fail to ask why. Similarly, process maps often lacked breadth and depth; for example, they lacked sufficient detail to show waste, lacked time data to demonstrate bottlenecks or lacked reference to an ideal state map or benchmark.
Solutions/Intervention generation
Only 17 (24%) included a driver diagram to visually display linkages among brainstormed change ideas/interventions and rarely included commentary about solutions that were considered versus those that were used. Additionally, only 24 (34%) described how solutions/interventions were selected or prioritised (eg, TRIZ, Impact-Effect Matrix) (table 1). As shown in table 1, most interventions targeted modifying behaviours of frontline staff. While 45 QIRs (63%) described how the suggested solution was linked to an underlying root cause, others failed to link to the intended root causes, thereby risking committing type 3 errors (ie, solving the wrong problem).
Study of interventions (using PDSAs)
The use of ‘PDSA’ nomenclature was variable, as was how PDSA cycles were used and reported (table 1). While the majority (58/71, 82%) described use of PDSA cycles or similar iterative cycles, 32% of these failed to describe cycles for each change idea. Many of the papers described important attributes of ‘authentic’ PDSA cycles, but there were also many ‘inauthentic’ cycles described7 (table 1).
Results reporting
Results included quantitative data (82%) and/or qualitative data (40%). As shown in table 1, data analysis and display methods varied and several common weaknesses of data display were identified. Moreover, 32 (45%) failed to describe the methods used to assess data completeness or accuracy. While 45 (63%) claimed their data illustrated sustainability, only 14 (20%) demonstrated this with statistical process control (SPC) charts. Spread of change concepts or plans for spread were rarely described (table 1).
Discussions, limitations and conclusions
As shown in table 1, most QIRs addressed the discussion points suggested by SQUIRE V.2.01; however, there were several notable gaps. While many described the association between interventions and outcomes, the nature of those associations was often omitted. The reasons for differences between the anticipated and observed outcomes—including the influence of context—were also frequently absent. In addition to the SQUIRE V.2.01 components, several other missed opportunities for richer discussions were identified (table 1), including lessons learnt from PDSA cycles, proposed change theories and their relationship to outcomes and reflections of what authors would do differently in the future.
Limitation sections covered most SQUIRE V.2.01 components but were generic and largely lacked in-depth discussion of trade-offs, opportunity costs or efforts made to minimise or adjust for identified limitations. The Conclusion sections nearly universally addressed the usefulness of the work, but other components were less consistent (table 1).
Discussion
The goal of QI publications—like all scholarly work—is to meaningfully contribute to the academic ‘conversation’.80 QI encompasses diverse approaches, from observational and implementation studies to randomised controlled trials informed by QI tools. While SQUIRE V.2.01 aims to accommodate the diversity within this evolving genre, our review highlights gaps in clarity, consistency and depth across published QIRs. Without more tailored guidance and deliberate efforts to convey key insights, QIRs become superficial, with limited value for novice and experienced QI practitioners alike. Drawing on findings from this review, we present eight core lessons to strengthen the rigour, transparency and impact of future QIRs (table 2).
Table 2. Key lessons for writing high-quality QIRs with exemplary references.
| Lesson | Good example | Why it is good |
|---|---|---|
| (1) Situate local problems within broader contexts | Schaeffer and Jolles28 | Integrates prior knowledge effectively and builds on that knowledge with a well-structured RCA, clearly presented in a table format. |
| Guo et al71 | Provides strong context by linking the local issue of medication reconciliation in rehabilitation to broader concerns around medication reconciliation in ambulatory care (quality gap). | |
| (2) A strong aim anchors the QIR | Walters et al78 Al-Otaibi et al11 |
Provides a compelling aim statement that included a clear rationale and justification for the targets set by referencing external benchmarks/guidelines. |
| (3) Be explicit about methodology | Sime et al9 | Explicitly identified methodology. Provided a clear description of stepwise approach, including a detailed description of how each improvement tool was used (eg, process map, cause-and-effect model, driver diagram, project charter, etc). |
| Ho et al18 | Highlights the rationale for methodological choices (eg, using the SEIPS framework) and clearly identified team members’ roles and responsibilities. | |
| (4) Measures matter so make them meaningful (or explain pragmatic choices) | Walters et al78 | Offers a well-defined ‘data dictionary’ outlining the types, definitions and rationale for selected measures. Clearly relates observations to the process measures (mechanism of action) and balancing measures (unintended consequences). |
| Kuehnel et al55 | Developed a custom, pragmatic outcome measure that closely aligned with the ‘actual’ outcome measure of interest to ease the burden of measuring without jeopardising rigour. | |
| Carson et al66 | Explicit about measurement rationale and data collection plan (eg, use of logs). | |
| (5) Make evolution of change ideas clear through ‘authentic’ use of PDSA cycles | Carson et al66 | Demonstrates thoughtful iteration through PDSA cycles and clearly articulates how each cycle evolved the intervention from its previous form. |
| Schaeffer and Jolles28 | Well-structured table demonstrates changes made during each PDSA cycle for each change idea; would have been an even stronger example if they had explained their rationale for modifications. | |
| (6) Reporting of results needs to meet a minimum standard of rigour | Roughan and Stafford19 | Presents robust SPC charts (eg, includes control limits, indicates the type of SPC chart used) with meaningful interpretations. |
| Al-Otaibi et al11 | Uses well-annotated SPC chart for the outcome measure, and appropriate use of run charts to display process measures. | |
| Lee et al14 | Displays data as rational subgroupings enhancing analysis and interpretation. | |
| (7) Depth of discussion is more valuable than a checkbox approach | Zafar et al88 | Includes a table that meaningfully and comprehensively addresses what is needed to transition from implementation to sustainability for each driver. |
| Walters et al78 | Situates their findings within the broader literature and reflects on contextual influences and their impact on the outcome. | |
| Gob et al37 | Reflects, in their ‘third lesson’, the importance of addressing differences in anticipated and real-world outcomes, and the adaptive learning required. | |
| Paluck et al89 | Suggests strategic trade-offs (eg, relinquishing operational control to corporate leadership to ensure sustainability and spread). | |
| (8) Emphasise context—even strong reports leave you wanting more! | Kuehnel et al55 | Illustrates, in their table 1, both successful and abandoned interventions, with rationale for decisions. |
| Lee et al14 | Lists ‘success factors’ for project successes, enriching the paper’s lessons. | |
| Ho et al18 | Provides a robust contextual analysis and RCA; would be strengthened even further by linking change success more explicitly to root causes. | |
| Udayaraj et al77 | Thorough description of patient and public involvement that confers the authentic co-design of interventions. |
PDSA, Plan-Do-Study-Act; QIR, quality improvement report; RCA, root cause analysis; SEIPS, Systems Engineering Initiative for Patient Safety; SPC, statistical process control.
Lesson 1: situate local problems within broader contexts
Introduction/Background sections offer opportunities for authors to define their local problem, explain its significance both locally and broadly, articulate what would constitute ‘meaningful change’ and establish a link to the paper’s aim. Many QIRs, however, made knowledge claims—often citing clinical facts—without explicitly connecting them to a quality gap. Returning to the example of TSH testing: while a story of this clinic’s intervention may only engage a niche readership, situating the issue within the context of unnecessary diagnostic testing across healthcare systems offers a more compelling and generalisable contribution to the literature.
Lesson 2: a strong aim anchors the QIR
A strong aim explicitly defines what is being improved, by how much, for whom and by when, linking the root causes to the measures, methods and results. Without this signpost, papers often lack coherence, making it difficult to follow the narrative. In the QIRs reviewed, aim statements varied considerably in both structure and placement. Given their importance, we recommend highlighting them under a dedicated subheading within the Introduction/Background, as demonstrated by Fan-Lun et al.69
The most effective aim statements also justify their target(s). Arbitrary goals—such as a 25% improvement in an outcome measure—leave readers questioning the relevance. In contrast, targets based on clinical guidelines, high performance benchmarks or expert consensus are more compelling and credible, as demonstrated by Walters et al78 who justified their aims using standardised expectations and pragmatic clinical judgement.
Lesson 3: be explicit about methodology
Most writing guidelines emphasise explicitly stating the methodology. In contrast, SQUIRE V.2.01 does not direct authors to name their QI methodology or framework (eg, MFI, Lean, etc); however, doing so strengthens the coherence of the paper’s narrative. Well-written methods sections also justify the choice of methodology. For example, describing the use of Lean to identify and link sources of waste to specific change ideas provides a clearer rationale for intervention design than reporting MFI tools or PDSA testing alone.
SQUIRE V.2.01 instructs authors to describe the intervention(s) and their effects in the Methods section but foundational RCA leading to the theory of change, and descriptions of how the intervention was developed, tested and implemented is often left out of QIRs. For example, SQUIRE V.2.01 offers no guidance on reporting the root causes that interventions have been designed to address, nor do they prompt authors to provide rationale for prioritising and selecting change ideas. Journals’ word-count limitations may contribute to the omission of this foundational diagnostic work. Expanding word counts or encouraging more liberal use of appendices could improve reproducibility by allowing fuller description of the intervention development and testing. Alternatively, restructuring the conventional ‘Methods’ section as ‘development, testing and implementation’ may create a cleaner narrative link between the RCA, intervention design and iterative PDSA cycles (all are elements key to understanding why an intervention succeeded or failed in its context).
Lesson 4: measures matter so make them meaningful (or explain pragmatic choices)
SQUIRE V.2.01 sets clear expectations for describing outcome and process measures, including the rationale for their selection and the methods used to assess data completeness and accuracy. Despite this, few authors explained why a particular measure was chosen, leaving readers to question whether more appropriate alternatives were overlooked. Authors should clearly state whether their outcome measure(s) were selected for meaningfulness or feasibility, as illustrated by Kuehnel et al.55 This transparency can improve others’ project planning and help navigate measurement challenges in complex projects.
Process measures are equally critical. They distinguish whether an intervention was implemented as intended but was ineffective, or whether implementation failed due to a lack of fidelity. Clarifying implementation fidelity should be a visible feature in every QIR, and yet only 58% listed one or more process measures—even when multiple change ideas were introduced. Strong examples, such as Walters et al78 explicitly linked process measures to specific interventions, offering insight into why downstream outcome measures may or may not have shifted.
Although SQUIRE V.2.01 does not explicitly reference balancing measures, strong Measures sections clearly explain the mechanism by which an intervention might lead to unintended consequences. Again, Walters et al78 provide a strong example. Since QIRs often guide novice practitioners, the absence of meaningful balancing measures in the literature risks influencing real-world QI practice. For example, although 65% of the QIRs were conducted in academic centres, none examined the impact on medical trainees—an oversight that could compromise success or sustainability when replicated elsewhere.
Lesson 5: make evolution of change ideas clear through ‘authentic’ use of PDSA cycles
This review found inconsistencies in how PDSA cycles were applied and reported. Errors ranged from misidentifying change ideas as PDSA cycles (and vice versa) to failing to meet any of the criteria outlined in the self-assessment tool by Leis and Shojania7 for ‘authentic’ PDSA execution. Although most papers reported using PDSA cycles, nearly all would have benefited from applying this self-assessment tool to strengthen methodological rigour and transparency. These findings align with those of Taylor et al,81 who developed a framework to evaluate the quality of PDSA application that demonstrated significant variability in PDSA application and reporting in QI literature.
Quality of PDSA documentation may be inadvertently compromised by journals’ efforts to standardise QIRs. For example, journals using fillable ‘PDSA’ boxes in manuscript submission forms could inadvertently blur the distinction between change ideas and PDSA cycles. To ensure a transparent record of PDSA cycles, this review identified two effective strategies: the first, demonstrated by Carson et al,66 is a clear narrative description of multiple PDSA cycles for each change idea, including the iterative adoption, adaption or abandonment of modifications based on process measures. The second strategy, exemplified by Leis and Shojania,7 is a tabular summary of PDSA cycles organised by change idea.
Lesson 6: reporting of results need to meet a minimum standard of rigour
Healthcare practitioners would not accept the results of an RCT without CIs, yet many QIRs fail to meet minimum standards for presenting time-series data using run charts or SPC charts. To ensure clarity and rigour, authors using these visual tools should follow established guidelines.82 83 At a minimum, run and SPC charts should include mean or median lines, respectively, control limits for SPC charts and annotations indicating when change ideas were introduced. Claims of special cause variation require adequate baseline data, and sustainability should not be inferred from charts lacking sufficient postintervention data points. As with other research, adherence to sound statistical principles also strengthens the interpretation of process and fidelity measures, reinforcing expectations for scientific rigour.
Lesson 7: depth of discussion is more valuable than a checkbox approach
While many Discussion sections addressed core SQUIRE V.2.01 elements—such as key findings, strengths, limitations and next steps—they often lacked the analytical depth needed to inform practice or advance the literature. Statements about generalisability were frequently generic, with little detail about the contextual conditions needed for reproducibility (eg, the project’s dependence on a strong local champion or alignment with organisational KPIs). Few authors reflected on what they would do differently and why, missing opportunities to convey actionable lessons. Limitations of measures or data collection were also rarely acknowledged, offering little guidance for future QI teams. Additionally, although SQUIRE V.2.01 recommends reflecting on costs and strategic trade-offs, only one-third of papers discussed how these factors might limit sustainability, spread or reproducibility in other settings (eg, reliance on temporary grant funding).
Lessons from RCA, intervention design or implementation similarly lacked sufficient depth. Although most QIRs linked interventions to outcomes and offered some explanation for differences between expected and observed results, few analysed why a favourable or unfavourable outcome occurred. For example, some QIRs reported sustainable improvement despite using low-leverage interventions (based on the Hierarchy of Effectiveness84), yet did not explain why these interventions were effective in that particular setting. Others reported delays between intervention and impact without examining why there was a lag. Without explicit reflection on context, such as team culture, leadership support or patient population characteristics, it is impossible to understand which elements were essential for successes or failures, and therefore, impossible to determine whether the improvement could be replicated elsewhere.
Lesson 8: emphasise context—even strong reports leave you wanting more!
Former BMJ Quality & Safety editor David Stevens emphasised that in healthcare improvement reporting the most important contribution—the ‘news’—is found in the author’s deep understanding of the interaction between a strategy for improvement and its unique setting.85 Although SQUIRE V.2.01 recommends authors describe context across the manuscript, most QIRs in our review lacked sufficient detail for reproducibility. This lack of contextual depth reduces interpretability and makes it difficult for others to understand why an intervention succeeded, or why it did not. Word-count constraints may contribute to this, pushing authors to condense or omit foundational diagnostic work. While supplementary materials can offer space, relegating critical elements, like the RCA or rationale for prioritising change ideas, to appendices may inadvertently downplay their importance in explaining outcomes.
In our review, contextual reporting focused primarily on structural features (eg, number of sites, beds capacity, Electronic Health Record (EHR) availability and provider details) with limited attention to other influential factors. To strengthen generalisability and reproducibility, we recommend authors describe, at minimum, four contextual domains identified as critical for patient safety practices: (1) organisational structure, (2) organisational culture, (3) external factors (eg, funding, remuneration) and (4) collaboration and resources.86 We further propose a fifth domain of ‘equity considerations and the patient and caregiver voice’, which was rarely evident in the QIRs included in this review, despite evidence that meaningful partnership enhances relevance, feasibility and sustainability of improvement efforts.87 Attending to these broader contextual domains enables readers to assess the conditions under which an intervention may be adapted in their own setting.
Limitations
There were several notable limitations. First, the purposeful sampling approach does not provide an exhaustive survey of all QIRs published during the study period. As such, findings may not be fully generalisable across this genre. Second, the study focused on three English-language journals, potentially excluding relevant work from other regions or journals with different editorial standards. Third, although data extraction and quality control processes were rigorous, some assessments—such as determining the authenticity of PDSA cycles or depth of RCA—relied on what was reported rather than what may have occurred in practice, which could have led to an underestimation of methodological rigour. Fourth, while efforts were made to include multiple reviewer perspectives, subjective judgements were required for coding and interpretation, particularly in assessing alignment with SQUIRE V.2.01 elements. Fifth, contextual information was inconsistently reported across QIR, limiting our ability to fully evaluate how local factors influenced intervention design, implementation and outcomes. Sixth, because most education-based QIRs did not measure learner knowledge or behaviour change, we could not assess how learning contributed to organisational outcomes. Finally, evaluating the validity or suitability of the SQUIRE guidelines for QIRs was beyond the scope of this review, but given gaps identified in current reporting practice, it represents an important area for future research.
Conclusion
This scoping review examined the reporting practices of published QIRs and found that, despite SQUIRE V.2.01 guidelines, there are several key areas where greater clarity, coherence and methodological transparency are needed to advance this writing genre. While our analysis is limited to what was explicitly reported, recurring gaps were identified across aim composition, methodological descriptions (particularly RCA and intervention development), measure selection, use of PDSA cycles and contextual detail. These shortcomings reduce the interpretability, reproducibility and pragmatic utility of QIRs. In response, we offer eight concrete, actionable lessons to strengthen the rigour and impact of future QIRs for novice improvement practitioners, as well as for those who supervise or mentor them. To support adoption of these recommendations, we highlight strong exemplars (table 2) that illustrate each lesson in practice.
As QI continues to grow as an academic discipline, elevating the standard of published QIRs is essential to fostering learning across contexts, avoiding redundant efforts and accelerating improvement in patient care and safety. Enhanced reporting practices will improve scholarly communication and increase the relevance, influence and sustainability of QI initiatives.
Supplementary material
Acknowledgements
The authors would like to thank Dr Mayur Brahmania for his input into project planning, Maren Goodman for her expertise in scoping review methodology and Dr Matthew Ramer for his thoughtful appraisal of the manuscript. The authors also thank Western University’s Centre for Quality, Innovation and Safety (CQuINS) for in-kind funding support and the reviewers and editors at BMJ Open Quality for their support and feedback during the peer-review process.
Footnotes
Funding: This work was supported by the Academic Realignment Initiative of the London Health Centre, Children’s Hospital, London Health Sciences Foundation and Children’s Health Foundation as well as Western University’s Centre for Quality, Innovation and Safety (CQuINS).
Provenance and peer review: Not commissioned; externally peer reviewed.
Patient consent for publication: Not applicable.
Ethics approval: Not applicable.
Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Data availability statement
Data are available on reasonable request.
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Data Availability Statement
Data are available on reasonable request.