Biostrategenix

I would be stating the obvious when I say that human errors are a challenge in both pharmaceutical manufacturing as well as in pharmaceutical quality control labs. Quality professionals struggle to pinpoint why things go wrong – 40% say they can’t find true root causes. The statistics get worse: human error accounts for more than 80% of process deviations and 25% of quality faults. The financial impact hits hard too. One pharma company’s yearly losses from human error reached $2.2 million, while another reported losses over $150 million.

Something doesn’t add up. Real human errors happen in FDA-regulated manufacturing, but they are blamed nowhere near as often as reports suggest. This points to a deeper issue – teams aren’t really breaking down what’s going wrong.

Human error root cause analysis has become critical to quality teams’ success. Learning about different error types and stopping them before they happen isn’t just about following rules anymore. It’s about keeping patients safe, delivering quality products, and protecting the company’s finances.

Lean methods are reshaping pharmaceutical quality control labs and manufacturing floors. What started as a business target has become something regulators expect. This piece will help you spot error patterns, use root cause analysis tools, and build prevention strategies that deliver results.

Why Human Errors Happen in Pharma

“Human error is the consequence, but rarely the cause, of mistakes.” — NSF International (GMP training authority, quoting industry best practice), Global public health and safety organization; leading pharma GMP trainer

Human errors in the pharmaceutical industry create more than quality problems – they’re a financial disaster. Companies typically spend $25,000 to $55,000 on each deviation, but these costs can shoot up to $1 million when product loss happens ^[1]. Studies show human error causes over 80% of process deviations and 25% of all quality issues ^[2].

The cost of errors in pharmaceutical manufacturing

Pharmaceutical companies face multiple financial challenges beyond immediate costs:

• Production slowdowns lead to lost sales and higher costs

• External consultants drain resources

• Regulatory actions create intense pressure

• Staff morale drops and turnover rises

A single deviation investigation can cost thousands of dollars ^[1]. Many companies estimate yearly error-related losses at $2.2 million, while others report losses that reach $150 million ^[3].

Why blaming individuals doesn’t solve the problem

These enormous costs haven’t stopped many organizations from pointing fingers at employees ^[2]. This creates a dangerous cycle. Staff members become hesitant to report issues. Management stays in the dark about system weaknesses. More errors happen.

Human error points to deeper problems rather than being the root cause ^[2]. The systems and processes that guide pharmaceutical workers need careful examination. Without system changes, errors will keep repeating with different people ^[4].

Operational excellence has evolved beyond a business target – regulators now expect it. Lean methods show that employee blame doesn’t fix systemic problems.

Example: Transcription or Transposition Errors

Pharmaceutical industry, examples of human errors are hard to come by. However, in my experience some of those errors involve transcription errors e.g. copying 1.8 instead of 1.3 from the HMI (human-machine interface) on to the paper batch record; or transposition error e.g. typing 8.1 instead of correct value of 1.8, etc.

Typical response if to discipline the employee which results in a missed opportunity. In the example above of transposition error, poka-yoke can be implemented by programming the batch record for exception-based review. Disciplining or firing the employee is never the answer. Focusing on blame instead of prevention strategies simply keeps the cycle of errors going.

Types of Human Errors and How to Recognize Them

You might wonder why smart, well-trained professionals still make mistakes. It’s important to understand that these errors are not deliberate. We are human, and humans make mistakes. What we can do is implement systems to catch those mistakes. In our effort to deploy these systems, it’s crucial to classify the types of human errors, as this will guide us in choosing the right solutions. The answer lies in how our brains process information and execute tasks. Pharmaceutical professionals need to recognize these patterns as the first step to effectively prevent errors.

Skill-based, rule-based, and knowledge-based errors

Cognitive scientist Jens Rasmussen’s framework shows human errors fall into three distinct categories:

• Skill-based errors happen during routine, automatic actions and demonstrate themselves as slips or lapses ^[5]. This is similar to running on “autopilot” – a lab technician might transpose numbers while recording data or skip a procedural step ^[6]. We noticed these errors mainly stem from momentary inattention or distractions.

• Rule-based mistakes occur when people use the wrong rule in a situation ^[5]. To cite an instance, an operator might program a new pump incorrectly because they followed directions meant for an older model ^[6].

• Knowledge-based mistakes surface when people face unfamiliar situations that need problem-solving ^[5]. Knowledge gaps often cause these errors – such as prescribing too much medication because the doctor didn’t know about a patient’s recent weight loss ^[6].

Unintentional vs intentional actions

Most errors in pharmaceutical settings happen without any thought-out intention. Unintentional actions include task slips, memory lapses, knowledge gaps, or poor decisions in non-routine situations ^[7].

Intentional actions, however, fall into three categories: tasks not done as described, incomplete tasks due to time pressure, or attempts to fix mistakes without following proper procedures ^[7].

Example: QC lab analyst misinterpreting color change

Let’s look at this scenario: A QC analyst misinterprets a color change indicator during a titration test, which leads to an incorrect endpoint determination ^[8]. This knowledge-based error could result from insufficient training on color interpretation or environmental factors like poor lighting. An easy poka-yoke is to have a reference color swatch available for the analyst to compare against or even better, detect colors via a spectrophotometer or a colorimeter.

Lean methodologies have become more prevalent in pharmaceutical quality control labs, making it crucial to learn about these error types ^[9]. Operational excellence has evolved beyond a business objective – it’s now a regulatory expectation.

Root Cause Analysis Tools for Quality Teams

Quality teams need the right investigative tools to solve recurring quality issues. It’s similar to a detective with a complete toolkit. Pharmaceutical quality teams now use proven methods that reveal the true mechanisms behind human errors.

Using the 5 Whys and Fishbone Diagram

The 5 Whys technique reveals root causes through repeated questioning ^[10]. The process starts with a simple question about procedure failure or SOP compliance. Each answer leads to deeper practical insights.

Complex problems need the Fishbone (Ishikawa) Diagram’s structured approach. The diagram splits potential causes into six categories: Man, Machine, Methods, Materials, Measurement, and Mother Nature ^[11]. This visual tool ensures teams catch all critical factors during deviation investigations.

Applying the Behavior Engineering Model

Gilbert’s Behavior Engineering Model looks at environmental factors (data, instruments, incentives) alongside behavioral components (knowledge, capacity, motives) ^[12]. Teams should focus on environmental changes first because they’re easier to implement.

How DMAIC supports error investigation

DMAIC (Define, Measure, Analyze, Improve, Control) adds structure to investigation processes ^[13]. Quality teams use tools like fishbone diagrams and 5 Whys during the analyze phase. These methods help identify root causes through systematic analysis ^[14].

Biostrategenix’s experts hold Lean Black Belt certification with years of human error reduction experience. Let us show you how we can help.

Example: Using ABC analysis to uncover training gaps

ABC analysis helps teams prioritize training needs and identifies knowledge gaps that substantially contribute to errors ^[15].

Strategies to Prevent Human Errors in Pharma

“Error reduction isn’t a single project, but a matter of corporate culture.” — NSF International (GMP training authority, quoting industry best practice), Global public health and safety organization; leading pharma GMP trainer

Preventing errors beats dealing with their consequences. Let’s look at proven ways to cut down human errors in pharmaceutical operations.

Implementing Poka-Yoke in biopharmaceutical manufacturing

Poka-Yoke, which means “mistake-proofing” in Japanese, makes errors almost impossible. The process design stops mistakes before they happen. This approach has:

• Color-coded shared storage areas to prevent mix-ups

• Connectors designed to fit only one way

• Automated validation checks

These simple yet effective techniques can boost product yields by a lot while cutting down rework and scrap ^[2]. Poka-Yoke respects workers’ intelligence by handling repetitive tasks that need constant watchfulness or memory ^[2].

Pre-job briefings and after-action reviews

Pre-job briefings (PJBs) bring the team together before starting tasks to discuss requirements and potential risks. These quick 5-10 minute sessions help arrange team understanding and raise situational awareness ^[1].

After Action Reviews (AARs) let teams reflect on completed tasks and spot what worked well and what needs improvement ^[1]. These practices work together to create an ongoing learning cycle.

Lean Six Sigma for continuous improvement

Lean Six Sigma merges waste reduction with quality improvement methods. The pharmaceutical industry uses this integration to:

• Spot and remove activities that don’t add value

• Cut down cycle times and improve productivity

• Keep outputs consistent by reducing variation ^[16]

Our experts at Biostrategenix hold Lean Black Belt certification with years of experience in reducing human error. Reach out to us to learn how we can help.

Building a non-blame culture

Creating a transparent environment helps employees feel safe when they report potential issues. Jim Morris of NSF International puts it well: “Quality culture comes from leaders, and you won’t get that crowdsourcing of problem solving and proactivity from the ground floor up if it isn’t sponsored from the top down” ^[17].

Conclusion

Human errors in pharma aren’t just quality headaches – they’re financial tsunamis waiting to strike. Our analysis shows how these errors can cost companies millions while putting patient safety at risk. Notwithstanding that, most errors can be prevented by looking beyond individual blame.

The root cause rarely points to human error. It usually stems from weaknesses in the system itself. Quality teams must look beyond “who” and focus on “why” during deviation investigations. Tools like 5 Whys, Fishbone Diagrams, and DMAIC help teams dig deeper than surface-level explanations.

Prevention works better than correction – quality professionals know this well. Reliable error-prevention systems emerge from combining Poka-Yoke principles, pre-job briefings, and after-action reviews. A non-blame culture where staff feel safe to report issues forms the foundations of continuous improvement.

Lean methodologies have evolved from optional business initiatives to regulatory requirements in pharma manufacturing floors and QC labs. Companies that embrace these approaches don’t just meet compliance – they save costs too. CAPA implementation showed this by cutting repeat errors by 67%.

Error reduction requires steadfast dedication to excellence. Quality teams that use these root cause analysis techniques and prevention strategies stay ahead of regulatory expectations while protecting profits. They fulfill their ultimate purpose: getting safe, effective medications to patients who need them.

Key Takeaways

Understanding and preventing human errors in pharmaceutical manufacturing is critical for patient safety, regulatory compliance, and financial sustainability. Here are the essential insights quality teams need to implement effective error prevention strategies:

• Human error costs pharma companies millions annually – with deviation costs ranging from $25,000 to $1 million per incident, making prevention a financial imperative.

• Focus on systems, not individuals – treating human error as a symptom of system weaknesses rather than individual blame leads to more effective solutions.

• Use structured root cause analysis tools – implement 5 Whys, Fishbone Diagrams, and DMAIC methodology to uncover true underlying causes of quality issues.

• Implement mistake-proofing (Poka-Yoke) techniques – design processes that prevent errors before they happen through color-coding, automated checks, and fail-safe connectors.

• Build a non-blame culture with continuous improvement – create environments where employees safely report issues, supported by pre-job briefings and after-action reviews.

Companies implementing comprehensive error prevention strategies, like CAPA methodology, have achieved remarkable results – reducing repeat errors by 67% and saving over $1.2 million in just six months. The shift from reactive correction to proactive prevention isn’t just good business practice; it’s becoming a regulatory expectation in today’s pharmaceutical landscape.

References

[1] – https://www.qualityexecutivepartners.com/thought-leadership/human-error-prevention-tools-for-cgmp-manufacturing
[2] – https://www.mastercontrol.com/gxp-lifeline/the-use-of-poka-yoke-with-medical-device-design-and-manufacturing/
[3] – https://www.nsf.org/knowledge-library/reducing-human-error-health-care-pharma
[4] – https://pmc.ncbi.nlm.nih.gov/articles/PMC6802475/
[5] – https://taproot.com/skill-rule-and-knowledge-models/
[6] – https://home.ecri.org/blogs/ismp-alerts-and-articles-library/the-differences-between-human-error-at-risk-behavior-and-reckless-behavior-are-key-to-a-just-culture
[7] – https://www.waters.com/blog/perspectives-on-pharma-identifying-and-minimizing-human-errors-in-quality-control-laboratories/?srsltid=AfmBOoqwZgNnYfpBq04UtG0rxTloTdyguCbZJ62QSLEzm_VJAeabXEvC
[8] – https://www.ligolab.com/post/top-10-medical-laboratory-mistakes-and-how-to-prevent-them-from-happening-in-your-lab
[9] – https://www.thefdagroup.com/blog/an-informed-guide-to-human-error-in-capa
[10] – https://www.qualityze.com/blogs/mastering-root-cause-analysis-review-of-best-investigation-tools
[11] – https://www.eviview.com/pharmaceutical-manufacturing-root-cause-analysis-software/
[12] – https://www.vectorsolutions.com/resources/blogs/human-performance-improvement-hpi-basics-gilberts-behavioral-engineering-model-bem/
[13] – https://pmc.ncbi.nlm.nih.gov/articles/PMC5584345/
[14] – https://www.6sigma.us/healthcare/dmaic-in-healthcare/
[15] – https://www.researchgate.net/publication/394632097_Application_of_ABC_Inventory_Analysis_for_Effective_Pharmaceutical_Procurement_Across_Hospitals_in_Tasikmalaya
[16] – https://www.pharmafocusamerica.com/articles/efficiency-and-quality-in-pharma
[17] – https://www.pharmtech.com/view/human-centered-work-how-pharma-can-move-blame-free-culture