Lean Medical Writing: A Review of Principles, Applications, and Future Directions

Abstract

Lean medical writing represents a paradigm shift from traditional storage-based documentation to story-driven, interpretive communication in regulatory and scientific contexts. This review presents established principles of lean medical writing and examines their application in medical and scientific writing, particularly within pharmaceutical regulatory submissions. We explore the foundational concepts, evidence supporting lean approaches, and practical implementation strategies for Clinical Study Reports (CSRs) and other regulatory documents.

Introduction

The modern regulatory environment faces unprecedented information overload. Between 2003 and 2013, the FDA received 342 new molecular entity (NME) applications, with individual electronic common technical document (eCTD) submissions reaching up to 10 GB.¹ Simultaneously, scientific publishing has exploded, with over 2,000,000 papers published annually across approximately 20,000 journals, and cardiovascular research publications alone increasing by 14% annually.¹ This proliferation of information has created a challenge regarding communicating complex medical and scientific data efficiently without sacrificing accuracy or comprehensiveness.

Lean medical writing emerged as a solution to this challenge, drawing inspiration from lean manufacturing principles pioneered by Toyota and adapted for healthcare communication. Unlike traditional redundant medical writing, which is characterized by extensive copying of tabular data into text, lean writing emphasizes on interpretation and context. This review examines the principles of lean writing, evidence supporting its adoption, and practical strategies for implementation.

Defining Lean Medical Writing

The Storage vs. Story Framework

Medical writing exists on a spectrum from "storage" to "story." Traditional verbose approaches, described as “storage-based” medical writing, function like an Amazon warehouse where writers copy numerical values from tables into narrative text without adding interpretive value. This approach generates voluminous documents that provide little analytical value beyond the underlying data tables.

On the other hand, an opposite extreme approach exists. Very minimalist medical writing reduces text to brief statements such as "the data is in the table below". While concise, this approach forces reviewers to independently analyze all data without guidance, potentially missing critical patterns or requiring extensive review time. Lean medical writing occupies the optimal middle ground, providing interpretation while maintaining conciseness. This approach tells reviewers what the data mean, not merely what they are.

Core Principles of Lean Writing

1. Elimination of Wordiness

The foundation of lean writing involves removing unnecessary words, phrases, and repetitions.^2,3 Correia (2024) provides a clear example: instead of stating "The patient experienced a significant reduction in pain levels as a result of the administered medication", lean writing would say "The medication significantly reduced the patient's pain." Another example demonstrates this principle: instead of "There were no deaths in either treatment group during any phase of the study", lean writing simply states "There were no deaths."

This principle extends beyond individual sentences to entire sections. Writers should start by eliminating junk words-modifiers like "it seems," "it may," "might be," "could be", followed by adjectives and adverbs that add no substantive meaning.³ The goal is not terseness for its own sake, but rather precision that respects the reader's time and cognitive resources.

2. Active Voice and Direct Expression 

Lean writing prioritizes active sentence structures for directness and engagement.² Rather than passive constructions like "The medication was prescribed by the doctor," lean writing states directly "The doctor prescribed the medication".² This approach clarifies agency and reduces word count while improving readability.

3. Logical Organization

Information should be structured to guide readers efficiently through complex medical concepts, research findings, or treatment guidelines.² When discussing treatment options, for example, Correia (2024) recommends progressing logically: "The treatment options for this condition include lifestyle changes, medication, surgery, and alternative therapies", starting with initial interventions and progressing to more advanced options. This organizational principle has particular relevance in regulatory documents. Demographic data appears first in CSRs not by convention, but because if the medical writer doesn’t know whether the treatment groups are comparable, they can't say anything about efficacy and safety. A lean approach makes this logical progression explicit.

4. Avoidance of Unnecessary Jargon

While medical writing necessarily employs technical terminology, lean principles emphasize using simple, commonly understood terms when appropriate.² Instead of "myocardial infarction," for general audiences, writers should state "heart attack", or instead of "dyspnoea," writers should state "breathlessness."² For specialized audiences, technical precision remains important, but jargon should never substitute for clear explanation.

Lean writing principles complement plain language approaches, particularly in patient-facing communications where accessibility is paramount.² The combination of lean and plain language techniques result in enhancing clarity for a diverse audiences, including patients.² When medical content employs these principles, it facilitates efficient translation and adaptation into different languages and cultural contexts, ensuring content remains culturally appropriate and easily understood across populations.²

5. Emphasis on Clarity and Unambiguity

Messages must be clear and unambiguous by their intended audience.² Rather than stating "Based on the findings of the research study, it can be concluded that there is a positive correlation between regular exercise and cardiovascular health," lean writing would state:  "The research study found a positive correlation between regular exercise and cardiovascular health".²

The Case for Lean Medical Writing

Regulatory Reviewer Perspectives

Regulatory reviewers have expressed clear preferences for interpretive documentation. At a Drug Information Association (DIA) meeting in Washington, FDA reviewers noted that high-quality CSRs are uncommon, with many documents presenting extensive historical background before reaching clinically relevant information. Reviewers indicated that CSRs often redundantly present tabular data in text form without added interpretation, diminishing their utility for regulatory assessment.

These perspectives reveal a critical gap between current documentation practices and reviewer needs. Regulatory authorities seek contextualized interpretation rather than redundant data presentation.

The Problem with "Well Balanced"

A specific example illustrates the inadequacy of minimalist writing that lacks interpretation. Many CSRs state that "treatment groups were well balanced" for demographics without further explanation. This phrasing is problematic because "well balanced" lacks standardized definition. For example, a difference of 5% may be considered balanced by some reviewers but not others, requiring each reviewer to independently assess the data.

The lean alternative explicitly addresses interpretation: "There were no differences between the treatment groups for demographic or baseline characteristics that would affect the interpretation of efficacy or safety," followed by explicit identification of any differences that might impact interpretation. This approach saves reviewers hours of independent analysis while maintaining transparency.

Efficiency Gains and Resource Implications

The business case for lean medical writing encompasses multiple stakeholders. Bhardwaj et al. (2017) note that "both writers and reviewers of these documents are overwhelmed with data and information overload," particularly when adhering to guidelines that inadvertently increase document volume. Given regulatory agencies, research organizations, and scientific journals operate with finite expert resources for document development and review, volume reduction becomes essential.¹

Latino (2024) emphasizes that lean authoring in CSR development delivers cost efficiency by "focusing on essential information, ensuring CSR documents are straightforward yet thorough" while achieving "timeline reduction" through "reducing redundancy and implementing clear cross-referencing." The result is a win-win-win scenario: benefits for pharmaceutical companies (time and cost savings), reviewers (faster, easier reviews), and ultimately patients (faster drug approvals).

The Challenge of Measuring Impact

While the benefits of lean writing appear intuitive and align with reviewer feedback, quantifying specific improvements remains challenging. Lean writing can reduce review time and improve reviewer satisfaction, but it is important to remember that it cannot guarantee regulatory approval, which ultimately depends on the drug's safety and efficacy profile. Rigorous comparative studies would require identical compounds evaluated by identical regulatory authorities under equivalent conditions, making controlled research impractical.

Nevertheless, logical inference suggests that documents better aligned with reviewer preferences should facilitate faster, more favorable reviews. The FDA's general preference for lean, interpretive documents provides strong qualitative support for this approach.

Lean Writing in Practice

Process-Level Implementation

Bhardwaj et al. (2017) outline a systematic approach to implementing lean principles, drawing on Toyota's lean methodology. The process involves five cyclical steps:

1.        Identify the deliverable (e.g., CSR or manuscript) as specified by customers

2.        Examine the process and mark steps for elimination that don't affect quality

3.        Develop documents according to the new workflow

4.        Evaluate quality and performance based on customer feedback

5.        Seek perfection and update the process iteratively

This framework emphasizes that lean writing requires attention to both process and content.  The goal is not simply to shorten documents, but to fundamentally rethink how information is analyzed, synthesized, and presented.

Lean Authoring Techniques for CSRs

Latino (2024) identifies specific strategies for implementing lean authoring in CSR development. Firstly, rather than repeating data, strategic cross-referencing allows writers to reference other sections or source documents, which reduces document length and helps readers focus on critical insights. However, cross-referencing must be strategic, directing readers to protocols or statistical analysis plans rather than reproducing entire sections in the CSR. Latino (2024) recommends emphasizing "essential findings over exhaustive data tables, keeping regulatory reviewers engaged and informed without overwhelming them." This approach aligns with the principle of story over storage, telling reviewers what matters rather than forcing them to discover it independently. Focused data presentation using summarized tables and cross-references helps avoid overwhelming stakeholders with data repetition. The goal is not data elimination but data contextualization, providing sufficient information while highlighting the most clinically relevant findings.

Challenges and Considerations

The "Mean" Component: When to Be Selective

Bhardwaj et al. (2017) introduce the concept of mean writing, emphasizing strategic selectivity in content inclusion. They note that exhaustive data presentation, comprehensive analyses covering all possible angles, and redundant publication of methods impose significant burdens on all stakeholders, such as authors, reviewers, publishers, and readers alike.

However, they caution against eliminating exploratory and post-hoc analyses entirely. Such analyses, while not preplanned, can reveal subgroup efficacy or selectivity and inform decision on inclusion and exclusion criteria.¹ The solution is clearly demarcating key, exploratory, and post-hoc analyses, with exploratory analyses presented as "short reports that supplement/complement the publications from the main study".¹

Resistance to Change

Despite widespread acceptance of lean principles in other industries, adoption in medical writing remains incomplete. Cultural resistance may stem from several sources. Medical writers often receive traditional training emphasizing comprehensiveness over conciseness, creating ingrained habits that resist change. Concerns about omitting critical information lead to hesitation about adopting shorter document formats. Despite informal reviewer preferences for lean writing, the absence of explicit regulatory guidance creates uncertainty that inhibits adoption. Additionally, established organizational templates and processes create inertia, making systematic changes difficult to implement even when benefits are recognized.

As Bhardwaj et al. (2017) observe: "The concept of lean and mean medical writing is yet evolving and is yet to be globally accepted by the pharmaceutical companies, academics, and scientific communities." Successful implementation depends on coordinated efforts across pharmaceutical companies, regulatory authorities, academic institutions, and scientific communities, facilitated by detailed guidelines tailored to specific document types.¹

Importantly, as advocates work to promote lean writing adoption, the core message must remain clear: lean writing is not about minimalism for its own sake. The James Lind Institute (2012) emphasizes that powerful medical writing contains vivid details and relevant examples that should not be eliminated. The goal is eliminating waste, such as redundancy, unclear expression, unnecessary jargon, while preserving and even emphasizing essential narratives that provide context and meaning.

Technology and the Future of Lean Medical Writing

Electronic Formats and the Future of Lean Writing

Electronic submission formats enable new approaches to lean writing through strategic hyperlinking. Rather than repeating methodological details available in protocols, CSRs can hyperlink to specific protocol sections, reducing redundancy while maintaining accessibility.¹ However, this approach has yet to achieve full acceptance, as stakeholders often still expect complete materials and methods sections despite protocol appendices containing identical information.

Looking forward, Bhardwaj et al. (2017) envision a future where data transparency practices enable publication of clinical trial results with key highlights for patients and medical professionals, while detailed methodologies and raw data remain accessible through web links to publicly disclosed protocols and trial results. This vision represents the ultimate expression of lean principles which include primary data openly accessible, with publications focused purely on interpretation.

AI and Symbolic Systems

While not extensively covered in the reviewed literature, the emergence of AI tools for medical writing raises important questions about lean principles. In an era of information abundance, the challenge has shifted from data availability to finding the needle in the haystack, trying to identify clinically meaningful signals within vast datasets.  Generative AI systems that primarily copy and paste without interpretation risk perpetuating storage-based medical writing at scale. For instance, a generative AI tool might convert all demographic table values into text statements such as "The mean age was 45.3 years in the treatment group and 44.8 years in the control group. The mean BMI was 27.2 kg/m² in the treatment group and 27.5 kg/m² in the control group"—merely reproducing tabular data without interpretive value.

In contrast, systems using symbolic AI combined with interpretive capabilities may better support lean writing by consistently applying interpretive frameworks to data analysis. These systems operate on pre-defined rules rather than probabilistic decision-making. For example, a symbolic AI system might analyze the same demographic data and generate: "Treatment groups showed no clinically meaningful differences in baseline demographics (see Table X for detailed values), indicating groups were well-matched for efficacy and safety interpretation." The system applies consistent, pre-defined criteria for identifying meaningful differences. For instance, a clinically meaningful age difference of more than 5 years or BMI difference of more than 2 kg/m² will be defined and the table will be referenced rather than reproducing all values. This approach applies consistent criteria for identifying meaningful differences and provides context for why these comparisons matter, embodying lean writing principles through automated interpretation rather than mere data transfer.

Recommendations for Implementation

Organizations seeking to implement lean medical writing should consider the following strategic actions:

1.        Develop Clear Standards: Establish document-type-specific guidelines that specify which data require interpretation versus tabular presentation, define criteria for clinically meaningful differences, and provide cross-referencing protocols.¹

2.        Build Writer Capabilities: Train medical writers in interpretive analysis, emphasizing the distinction between clinical and statistical significance, and developing judgment about meaningful differences.

3.        Engage Regulatory Expertise: Attend regulatory forums, consult former FDA/EMA reviewers now in private practice, and contribute to industry working groups developing lean writing standards.

4.        Implement Iteratively: Begin with pilot projects, gather feedback from internal and external reviewers, refine processes based on experience, and gradually expand as organizational comfort grows.¹

5.        Track Meaningful Metrics: Monitor internal review cycle times, quality control finding rates, reviewer feedback quality, and stakeholder satisfaction to demonstrate value and build organizational support.

Conclusion

Lean medical writing represents more than a stylistic preference, as it embodies a fundamental shift in how we conceptualize regulatory and scientific communication. Moving from storage to story, from comprehensive data presentation to focused interpretation, lean writing aligns with regulatory reviewer needs, accelerates development timelines, and ultimately serves patients through faster access to effective therapies.

While challenges remain, particularly around standardization, new challenges are emerging that require proactive attention. For example, as technology evolves, AI tools present both opportunities and risks for lean writing principles. Generative AI systems that merely reproduce tabular data risk perpetuating storage-based approaches at scale, while symbolic AI systems applying consistent interpretive frameworks may advance lean principles through rule-based analysis that prioritizes interpretation over data transfer. The critical distinction lies not in automation itself, but in whether technology supports interpretation and contextualization (the hallmarks of lean writing). By implementing symbolic AI systems that combine pre-defined interpretive rules with analytical capabilities, organizations can scale lean writing practices while ensuring consistent application of clinical judgment across all documentation.

Effective medical writing translates complexity into understanding and meaningful healthcare communication.² In an era of unprecedented information volume, this translation function has never been more critical. The future of medical writing is lean and organizations that embrace these principles position themselves for meaningful contribution to improving patient outcomes through efficient, effective drug development.

References

[1] Bhardwaj, P., Sinha, S., & Yadav, R. K. (2017). Medical and scientific writing: Time to go lean and mean. Perspectives in Clinical Research, 8(3), 113-118.

[2] Correia, A. S. (2024). Translating complexity into understanding: Lean writing and plain language in medical communications. Medical Writing, [publication details].

[3] James Lind Institute. (2012). Medical & scientific writing: What is LEAN writing? Three steps to get your writing in shape.

[4] Latino, M. (2024). Lean authoring: Bringing efficiency and speed to clinical study reports. Precision for Medicine.

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Dr. Barry Drees is the Founder and Advisor at TriloDocs, former President of the European Medical Writers Association (EMWA), and has spent 40 years in medical writing watching the field evolve from hand-constructed tables to AI-enhanced documentation.