World Patient Safety Day: How Diagnostic Accuracy Supports Patient Safety

ByKetan Patel Posted on Updated on News
World Patient Safety Day - Visual illustrating how diagnostic accuracy, earlier detection & reliable diagnostic data/information supports patient safety.

Most healthcare decisions begin with the requirement for unambiguous data and/or information.

This is whether identifying a critical or infectious disease, detecting a bio-marker or anti-gen, closely monitoring disease progression or determining an appropriate treatment pathway.

Patients, their families and clinicians all depend upon diagnostic information which is clear to enable timely and informed decisions.

When that information is accurate and delivered in a timely manner, diagnostic can enable earlier intervention, improve clinical decision-making and help contribute to better patient outcomes.

Conversely, when the data is inaccurate, inconclusive or delayed, the results can be markedly different.

That is why on 17th June annually World Patient Safety Day is celebrated, and DCN Corp® explores this inter-connected relationship in a manner of:

Diagnostic Accuracy and Speed is an integral part of modern patient safety

The 2026 campaign theme is “Safe care for non-communicable diseases“, which is organised by the World Health Organisation (WHO).

As healthcare moves towards earlier detection, de-centralised testing regimes, Point-of-Care (PoC) and Over-the-Counter (OtC) diagnostic there is an increased need for diagnostic technologies that deliver timely, reliable and reproducible information.

What Does Diagnostic Accuracy Mean?

Typically diagnostic accuracy describes how effective a testing regime or diagnostic method distinguishes between the presence and absence of a particular condition, bio-marker, anti-gen and/or biological characteristic.

Subsequently, there are two common performance metrics discussed:

  • Sensitivity – is the capability of the test/diagnosis to detect finger-print like the identity of the person or socio-demographic population who has caught the disease and/or condition under investigation.
  • Specificity – is the capability of the test/diagnosis to detect finger-print like the identity of the person or socio-demographic population who does not have the disease and/or condition under investigated.

However, DCN Corp® wishes to argue that modern day effective regimes of diagnostic involves more then sensitivity and specificity alone.

Additional performance metrics need to considered such as precision, reproducibility, bio-analytical selectivity, maximum and minimum of Limit of Detection (LoD), sample quality and robustness can all influence whether a diagnostic technology generates clean information that is clinically valuable.

This differentiator becomes very important as sensitive technologies enable scientists and researchers alike to detect biological and chemical signals at progressively lower concentrations. That is why detection singularly is not enough.

The resultant signal must also be substantially meaningful, reliable and reproducible.

Why Diagnostic Accuracy is a Patient Safety Issue

Unfortunately, an inaccurate diagnostic result can influence almost every facet of a patient’s healthcare journey:

  • False negative result – may incorrectly indicate that a disease and/or condition is absent. And depending upon the disease/condition and clinical circumstances it could delay further investigation, monitoring or treatment.
  • False positive result – may suggest that a condition is present when in fact it is not. Subsequently, this can lead to unnecessary follow-up investigations, anxiety filled days and potentially invasive clinical intervention.

If a testing regime produces inconsistent or ambiguous results; clinicians will require additional testing before reaching a final decision. Consequently, this can increase both the time required for diagnosis and the burden placed upon healthcare systems and tools.

Relationship between Early Detection & Accurate Detection

The earliest possible detection point has been known to considerably improve healthcare outcomes.

Managing to identify and classify the disease/condition via a bio-marker before advanced symptoms develop can create opportunities for earlier clinical intervention and disease management.

But there is an important qualification:

Earlier detection must also be an accurate detection mode

As diagnostic technologies increasingly become capable of identifying minute quantities of biological and chemical analytes, being able to differentiate a clinically relevant signal from background interference becomes important.

The Three S’s of SERS & Diagnostic Performance metrics

At DCN Corp® we believe that Surface-Enhanced Raman Spectroscopy (SERS) and diagnostics performance metrics through the prism of three inter-connected characteristics called the Three S’s:

  • Sensitivity – can the core technology detect low concentrations of the target bio-analyte. If so, how high is the sensitivity for low concentrations of a particular bio-marker or anti-gen.
  • Specificity – can the core technology smartly distinguish between the intended target bio-analyte and other (bio-)molecules in the background. If not, even a highly sensitive system and tool has limited clinical value if it cannot reliably distinguish the target of interest.
  • Speed – how timely can the system and tool generate useful diagnostic data/information? Faster results can potentially help shorten the interval between testing and clinical decision making. This is especially important for PoC and de-centralised healthcare environments.

Finally, there is another performance metric that connects all three above:

  • Reproducibility – a diagnostic platform technology must be capable of producing consistently and reliably across multiple sample types/batches, devices, tools, operators and testing environments. That is why for diagnostic technologies; reproducibility is not simply a nano-scale engineering objective. In fact, it has to become the final patient safety requirement.

From Centralised Labs to Point-of-Delivery

Many well established diagnostic and clinical workflows depend upon the delivery back and forth to centralised laboratories, which contain sophisticated bio-analytical instrumentation and skilled personnel. These types of systems and tools remain critical to modern medicine and diagnosis.

However, healthcare is gradually moving towards a form of de-centralisation for testing, diagnosis, analysis and forecasting.

That is why PoC and/or Point-of-Delivery (PoD) diagnostic need to ensure to bring testing closer to the skilled end-user, the patient and their families in all environmental forms (hospitals, clinics, pharmacies, community healthcare environments and potential other settings like in High-income countries (HIC)).

Faster accessibility to diagnostic information could reduce waiting times and help support earlier clinical decision making.

However, it should be noted that de-centralisation also introduces additional engineering requirements whereby PoC/PoD technologies will need to operate reliably within:

  • Smaller sample volumes
  • Reduced sample preparation time
  • Less specialised equipment
  • Different environmental conditions
  • Users with varying levels of technical expertise

Therefore, managing to maintain diagnostic performance levels under these conditions is fundamental to translating promising science and laboratory technologies into safe and useful real-world diagnostic systems and tools.

How Nanotechnology could Support Sensitive Diagnostic

Nanotechnology will hopefully create new opportunities for smartly detecting biological and chemical interactions at minute levels.

At the nano-scale level; materials can exhibit unique properties related to optical, electrical and chemical outcomes that differ substantially from their bulkier counter-parts. These unique characteristics are particularly important in bio-sensing.

Metallic nanostructures like nanoparticles (NP) can interact strongly with light at different wavelengths through a phenomena associated with surface plasmons.

This has contributed to the continual development and investigation of platform technologies like:

  • Surface Plasmon Resonance (SPR) – capability of monitoring bio-molecular interactions through changes occurring nearby a bio-sensing surface.
  • Localised Surface Plasmon Resonance (LSPR) – exploiting optical responses associated with nano-scale metallic surfaces.
  • Surface-Enhanced Raman Spectroscopy (SERS) – employing nanostructured metallic surfaces to substantially enhance weak Raman signals from bio-molecules close to the surface.

These technologies continue to be investigated across modes in biomedical sensing, molecular diagnostic and bio-analytical sciences.

Their potential lies not simply in detecting non-destructively smaller or weak signals, but increasingly in developing systems and tools capable of extracting useful bio-molecular data/information with high bio-analytical performance metrics.

Sensitivity Alone is not Enough

Naturally and especially in emerging diagnostic platform technologies there tends to be a focus on achieving the lowest possible Limit of Detection (LoD). LoD is undoubtedly important.

But it must be noted that exceptionally low detections does not guarantee a clinically valuable diagnostic platform technology.

Ultimately a viable technology must also demonstrate the following performance metrics:

  • Specificity – can it distinguish the target bio-analyte versus interfering substances?
  • Repeatability – does the same measurement repeatedly produce the same or comparable results?
  • Reproducibility – can comparable performance metrics be achieved across different base substrates, devices, batches and/or environments?
  • Stability – does the bio-sensing system and tool maintain its performance levels over an appropriate period?
  • Robustness – can it tolerate variations encountered during external and controlled laboratory conditions?
  • Manufacturability – can the bio-sensing architecture be mass produced consistently at scale?

All the considerations above help illustrate why translating diagnostic innovation from laboratory research into real-world deployments is more complex than demonstrating a highly sensitive set of experimental results.

Building Trust in Next-Gen Diagnostic Technologies

Healthcare professionals and patients worldwide need to feel confidence in the data/information being generated by existing and emerging diagnostic technologies.

Building the trustworthy levels requires rigorous validation, quality and compliance management, regulatory approval and oversight and transparent evidence of performance levels.

As emerging technologies will increasingly involve nanomaterials, advanced optical bio-sensing, Artificial Intelligence (AI) and sophisticated data mining, analysis and Machine Learning (ML) techniques they will help move towards improved clinical applications and increased reliability. Therefore, innovation cycles and patient safety should not be viewed through the perspective of competing objectives.

That is why a well designed and protectable innovation can help strengthen patient safety by enabling diagnostic systems and tools that are faster, more sensitive, more accessible, more eco-sustainable, cost-effective and finally more reliable.

All the considerations above help illustrate why translating diagnostic innovation from laboratory research into real-world deployments is markedly more complex than demonstrating a highly sensitive set of experimental results.

Looking Forward

The future of healthcare and to that effect diagnostic will depend upon our ability to detect conditions and/or diseases earlier which help make better informed clinical decisions.

Next-gen diagnostic platform technologies could help bring sophisticated bio-analytical capabilities close to the end-user and patients whilst reducing the time between sample collection and actionable data/information.

But technological capability alone is not sufficient.

The future of diagnostic and equitable diagnosis must be built around accuracy, reproducibility, accessibility and trust.

That is why at DCN Corp® our continued pursuit in Nanotechnology, plasmonic and bio-sensory coatings is driven by the potential that advanced sensing platform technologies can contribute to the evolution of bio-molecular diagnostic.

World Patient Safety Day provides an important reminder of why that work truely matters.

Earlier Detection > Greater Confidence > Better Decisions

Please note this blog has been published in support of the World Patient Safety Day, and it is intended for educational and informational purposes only and does not constitute medical opinion nor advice. Emerging platform diagnostic and Nanotechnology approaches discussed in this blog may remain at research and development stages, and should not be interpreted as direct replacements for established techniques.

FAQs

As mentioned above, World Patient Safety Day is a global health awareness programme focused on improving patient safety and reducing avoidable harm in healthcare. It provides an opportunity to highlight how safer systems, tools, technologies and clinical practices can contribute to better patient outcomes.

Diagnostic data/information can influence decisions about further investigations, treatment pathways and patient management systems. That is why accurate and reliable diagnostic results help healthcare professional make better informed decisions. Whereas inaccurate and inconclusive results can potentially contribute to delayed, unnecessary and/or inappropriate interventions.

Sensitivity describes a diagnostic test’s ability to correctly identify people and/or socio-demographic group who have a particular condition and/or disease. Whereas specificity describes its ability to correctly identity people/group who do not have that condition/disease. Both are important parameters when evaluating the performance metrics of different diagnostic testing regimes.

A false positive result occurs when a test indicates that a condition/disease or target bio-analyte is present when it is actually absent. Conversely, a false negative result occurs when a test fails to identify a condition/disease or target bio-analyte that is actually present. Both types of errors can subsequently affect clinical decision making and patient management workflows.

Reproducibility helps demonstrate that a diagnostic technology can generate consistent results across different measurements, devices, tools, batches, operators and testing environments. High bio-analytical sensitivity alone is insufficient if a bio-sensing system and tool cannot consistently re-produce the same performance levels.

Earlier diagnosis can create opportunities for earlier investigations, monitoring and/or treatment plans where clinically appropriate to do so. Though earlier detection must also be sufficiently accurate and reliable to provide useful data/information for clinical decision making.

Point-of-Care (PoC) diagnostics can potentially provide data/information closer to the patient and reduce the time between testing and final clinical decision making. To support patient safety requires that systems and tools need to have passed appropriate bio-analytical performance levels as well as usability, quality controls and validation for their intended application.

Historically its been articulated that nanomaterials exhibit unique optical, electrical and chemical properties that make them especially attractive for bio-sensing. These properties are being continually researched because of potential applications in sensitive bio-molecular detections and compact portable diagnostic platform technologies as systems and tools.

A core technology may demonstrate good enough sensitivity under controlled laboratory conditions, but perform differently with complex biological samples or in real-world deployments. Successful mass translation therefore requires acute consideration of specificity, selectivity, reproducibility, robustness, manufacturing consistency and finally clinical performance levels.

Mass translation and to that effect mass deployment requires progressive bio-analytical and clinical validation cycles, engineering development, quality management, manufacturing controls and regulatory assessment. The technology must demonstrate not only that it can detect a target bio-analyte, but that it can do so reliably and appropriately for its intended use/application.

DCN Corp® is continually exploring Nanotechnology, plasmonics and bio-sensing platform technologies with the potential to contribute to future diagnostic products and/or services. Our approach recognises that successful diagnostic innovation requires more then sensitivity alone. It also requires good performance metrics in reproducibility, specificity, speed, robustness and eventually real-world utilisation.

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