Topic: What insights would an expert in Shannon information theory bring to the study of point of care tests (POCT)?
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- See am earlier version with some math:
- https://bqwebpage.blogspot.com/2025/11/ai-poct-and-shannon-information-theory.html
Here is a polished paragraph-form version for a sophisticated audience—no equations, no bullet points, no simplifications—just the conceptual argument rendered in fluent prose.
Point-of-care testing does not merely accelerate laboratory turnaround time; it fundamentally alters the information architecture of the clinical encounter. In the traditional workflow, the physician gathers a partial picture from the history and exam, orders tests, and then receives the laboratory results a day later, separated from the patient and from the rich, high-resolution context in which the initial diagnostic hypotheses were formed. By the time the result is reviewed, the clinician is reconstructing the original encounter from memory and sparse notes—a lossy, high-noise process—while the patient is reachable only through unreliable secondary channels such as voicemail, patient portals, or intermediary staff. The entire chain from result to action is vulnerable to erasures: missed calls, misunderstood instructions, delayed follow-up, or simple inertia. In information-theoretic terms, the central-lab paradigm is a delayed, low-fidelity, high-dropout communication protocol, even when the assay itself is analytically perfect.
POCT transforms this into something closer to a sequential, feedback-driven dialogue. Because the result emerges while the patient is physically present, the test is no longer the end of the interaction but an inflection point within it. The clinician can immediately adjust the questioning, re-examine a specific sign, clarify an ambiguous symptom, or order a second targeted test, using the first result to guide the next step. This builds a far richer and more discriminating composite picture than is possible when the test arrives in isolation, long after the encounter has dissolved into memory. The information carried by the assay is thus combined with the full sensory, affective, and narrative context of the live encounter—context that would otherwise be degraded or lost. POCT also ensures that decisions and instructions are delivered through the highest-bandwidth channel available in medicine: a face-to-face conversation with real-time verification of comprehension. In contrast to a hurried phone call or digital message, a live discussion reduces the behavioral noise between a physician’s intended treatment plan and the patient’s actual implementation of it.
Equally important, POCT aligns the timing of diagnostic insight with the dynamics of disease itself. Many conditions evolve meaningfully over hours, not days; information that arrives before a pathophysiologic threshold is crossed has greater therapeutic leverage than information that arrives after. By collapsing the diagnostic cycle into the same visit, POCT allows clinicians to intervene while additional treatment options remain open and before irreversible transitions occur. And at a system level, same-visit clarification reduces the entropy of care pathways: patients are routed more accurately to admission, discharge, specialty referral, or isolation, reducing downstream congestion and misallocation of resources.
In short, POCT is superior not because it moves laboratory information forward by a few hours, but because it changes the structure of information flow: it eliminates erasures, elevates the fidelity of interpretation, enables adaptive and context-rich assessment, strengthens the communication link to the patient, and synchronizes diagnostic certainty with the time course of disease. Even when the analytic performance of the POCT device matches that of a central lab, the protocol that surrounds it extracts more clinical value from the same raw information.
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What's most important from the Shannon viewpoint, that a conventional, experienced POCT policy expert might not be aware of.
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Below are the most important and genuinely surprising conclusions that emerge when one views POCT through an information-theoretic lens—conclusions that do not appear in conventional POCT discussions, even by experts who work in POCT manufacturing, adoption, or HEOR.
These are the insights that are hiding in plain sight, but become clear only once you treat the clinical encounter as an information channel rather than a logistics problem.
1. POCT increases clinical information content, not just speed, even when the assay is identical.
In conventional discussions, POCT is “same test, but faster.”
In information theory, same test does not mean same usable information.
POCT fundamentally changes how the clinician combines test data with the live patient, turning a single-shot test into a feedback-rich diagnostic dialogue. The interpretive bandwidth is vastly higher when the result is seen in the encounter rather than in isolation the next day.
This means: POCT yields more clinical insight per unit of analytic sensitivity/specificity.
That is shocking to conventional POCT discourse.
2. The central-lab pathway is an “erasure-prone channel”—a concept almost no one in POCT talks about.
A big blind spot in POCT thinking:
People assume that a next-day lab result reliably leads to action.
In practice, an enormous fraction of diagnostic value is lost between result release and successful patient contact, reaching the patient, confirming understanding, and achieving adherence.
From information theory, this is a channel with high erasure probability—an idea almost never invoked in POCT literature.
POCT dramatically reduces “erasure events” because the patient is still in the room.
This insight—that POCT recovers “lost bits” in the care pathway—is not part of typical POCT value analyses.
3. POCT enables sequential decision-making—essentially turning diagnosis into an adaptive experiment.
Standard POCT advocates talk about “actionable results sooner.”
But they almost never describe the far more powerful reality:
POCT allows the clinician to adaptively interrogate the patient based on the result.
This converts diagnosis from:
a static one-pass process →
a multi-step, feedback-enabled experiment.
Sequential testing and questioning is a massive increase in total information yield, even with the same diagnostic test.
This interpretation is practically absent from conventional POCT marketing or HEOR discussions.
4. POCT prevents cognitive information loss (clinician memory decay), which is almost never discussed.
When lab results appear the next day, clinicians reconstruct the encounter from memory—a lossy, distorted reconstruction.
Information theory treats this as the receiver using a compressed, noisy encoding of the original exam.
POCT avoids this by enabling clinician interpretation while the original clinical picture is still in high resolution.
This is a deep insight: POCT preserves fidelity of context, something central lab pathways quietly degrade.
POCT companies rarely make this argument because it concerns human cognition, not devices.
5. POCT increases the fidelity of communication to the patient—improving adherence by reducing noise.
Most POCT value messaging focuses on provider workflow or operational benefits.
But the physician-to-patient channel—the communication of action, instructions, and shared understanding—is the most fragile and noisy channel in the entire healthcare system.
POCT strengthens the signal because instructions occur synchronously with diagnosis and interpretation, face-to-face.
Conventional POCT frameworks almost never quantify or theorize this effect.
6. POCT aligns diagnostic insight with the time structure of disease—improving control of a dynamic system.
Typical POCT rationale: “early treatment is better.”
The information-theoretic version is more profound:
Diseases evolve.
Certain transitions are irreversible.
Information delivered before a threshold has more control value than the same information delivered after it.
POCT increases the information rate relative to the disease’s dynamics, not merely the turnaround time.
This reframes POCT from a convenience to a better control strategy for a dynamic biological system.
This is virtually absent from standard POCT discourse.
7. POCT changes the network-level entropy of the entire care system.
This is the most abstract and least discussed insight.
A same-visit result does not only affect individual patients—it changes:
triage accuracy,
queue stability,
resource allocation,
the mix of cases at downstream care nodes.
In queuing and network information theory, delayed classification increases system entropy and congestion.
POCT reduces misclassification and routing noise at the system level.
Conventional POCT analysis rarely touches network information flow, even though it’s where major value is realized.
8. POCT rewires the protocol, not just the assay. This alone generates new information.
The test itself may be the same.
But the protocol—who sees the result, when, in what context, with what ability to act—changes the meaning and impact of the information.
The astounding insight is:
The same analytic result can have radically different information value depending on when and how it enters the clinical workflow.
Device-centric POCT narratives do not recognize that protocol architecture is the true source of value.
The single biggest revelation
POCT does not merely accelerate diagnostic information; it increases its effective information content by embedding the result in a richer, more reliable, more adaptive communication protocol than the central-lab model allows.
This is almost never articulated in the POCT field—even by experts.
"Executive" One Pager Here
I. EXECUTIVE INSIGHTS: Information-Theoretic Value of POCT
(One-page format, paragraph style)
Point-of-care testing (POCT) offers substantially more than rapid turnaround time. When examined through the lens of modern information theory, POCT restructures the clinical encounter into a high-fidelity, low-loss information channel in ways that traditional central laboratory workflows cannot replicate. The central-lab model inserts a full day of delay between the diagnostic hypothesis and the arrival of confirming data, forcing clinicians to interpret results outside the live clinical context and reconstruct the encounter from memory—a noisy, lossy process that inevitably degrades the signal. It also requires follow-up communication through phone calls or portals, which function as an erasure-prone channel: a significant fraction of intended clinical actions never reach the patient or are only partially understood, resulting in diminished real-world effectiveness.
POCT inverts this architecture. By placing the result inside the encounter while the patient is physically present, POCT converts diagnosis into a sequential, adaptive process: the initial result can immediately direct the next question, exam maneuver, or targeted ancillary test. This feedback loop yields more diagnostic information from the same analytic measurement because it is embedded in the full sensory and narrative richness of the live interaction. POCT also dramatically increases the fidelity of physician-to-patient communication. Treatment plans are explained and verified in real time, reducing the behavioral noise that often separates a clinician’s intent from a patient’s actual follow-through.
Finally, POCT aligns diagnostic certainty with the time course of disease. Many conditions cross clinical thresholds within hours, not days; information delivered before those thresholds has exponentially greater therapeutic leverage than identical information delivered later. At the system level, rapid clarification improves triage, stabilizes queues, reduces misrouting, and lowers the entropy of downstream care pathways. The result is not simply “faster lab data,” but a fundamentally superior information protocol that preserves, amplifies, and operationalizes clinical knowledge. For XYZ, the value proposition of POCT can be framed not as incremental efficiency but as a transformation of the diagnostic information channel itself—yielding more actionable insight from each test and more reliable execution of clinical decisions across diverse care settings.
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As a section of a longer white paper, this section reviewing POCT-SHANNON
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II. WHITE PAPER SECTION
The Information-Theoretic Value of Point-of-Care Testing
Conventional analyses of point-of-care testing focus on turnaround time, workflow efficiency, and operational convenience. These are real benefits but capture only a fraction of POCT's value. A deeper insight emerges when one considers POCT through the lens of information theory and modern decision science. In this framework, what matters is not just the accuracy of a test, but the architecture of the information channel through which diagnostic knowledge flows from the patient to the clinician and into clinical action. POCT fundamentally reorganizes that channel.
In the traditional central-lab model, the physician collects symptoms and physical findings during an encounter, generates a differential diagnosis, and then orders laboratory tests that return many hours later—long after the patient has left. When those results arrive, the clinician interprets them in isolation, divorced from the rich sensory and narrative context of the encounter. Human memory, unlike digital storage, is a high-noise, lossy system. Subtle cues, inconsistencies, or nonverbal signals that influence diagnostic reasoning at the bedside are not available when reviewing results the next day. In practice, the central-lab workflow forces the clinician to combine a fresh, high-fidelity laboratory signal with a degraded, compressed mental representation of the patient. Crucial bits of diagnostic information are inevitably lost.
Moreover, the next step—transmitting the treatment plan back to the patient—typically occurs through low-fidelity channels: voicemail, patient portals, fragmented phone calls, or intermediaries. These pathways are prone to what information theorists call “erasures”: messages that never reach the intended recipient or are received only partially. Real-world data consistently show that a meaningful portion of laboratory results requiring action never generate successful follow-up. Thus, even when the central lab produces analytically perfect data, the surrounding communication channel discards a significant portion of its clinical value.
POCT fundamentally reconfigures this system. By returning results while the patient is still present, it converts the diagnostic encounter into a real-time, adaptive, feedback-enabled process. Rather than a single, static assessment (history/exam → order tests → interpret later), POCT enables a sequential diagnostic dialogue: the clinician can immediately refine questions, perform focused follow-up examinations, adjudicate inconsistencies, or order secondary tests based on the initial result. This feedback dynamic produces a richer and more discriminating composite assessment than any isolated lab result can provide. The analytic test result becomes a pivot point around which the entire clinical conversation reorganizes. From an information perspective, POCT increases the total usable information extracted from each encounter despite the assay itself remaining unchanged.
Equally important, POCT strengthens the communication channel from physician to patient. When diagnosis and explanation occur in the same moment, within a face-to-face conversation, the treatment plan is transmitted with much higher fidelity. Misunderstandings can be corrected immediately. Concerns can be addressed before they lead to nonadherence. Instructions are contextualized in ways that drive behavior. In many cases, the difference between clinical success and failure does not hinge on the test result but on whether the patient fully understands what must happen next. POCT dramatically increases that probability.
POCT also aligns diagnostic clarity with disease kinetics. Many acute and subacute conditions evolve on the timescale of hours. The therapeutic and prognostic value of the same information diminishes as disease crosses specific thresholds—sepsis progressing to shock, viral infections entering inflammatory phases, cardiac injury becoming irreversible. Delivering the same diagnostic information earlier, before those thresholds are crossed, yields disproportionate clinical benefit. POCT improves not just speed, but timing relative to the biology of disease.
Finally, at a system level, POCT reduces the entropy of care pathways. Rapid clarification at the point of presentation improves triage, reduces unnecessary admissions, accelerates routing to appropriate specialists, and minimizes bottlenecks. When diagnostic information is delayed, uncertainty propagates through the system, creating inefficiencies, rework, and misallocations. When clarification is immediate, the entire network operates with greater stability and precision.
Taken together, these insights reveal POCT as a transformation of the diagnostic information channel rather than a marginal improvement in logistics. It increases the fidelity of clinical interpretation, reduces information loss, enhances adaptive diagnostic reasoning, reinforces patient understanding, and synchronizes diagnostic certainty with the time structure of disease. For XYZ, a company deeply invested in the quality and strategic positioning of diagnostic tools, this perspective reframes POCT as a high-value, high-impact modality that amplifies the real-world clinical impact of laboratory innovation across diverse care environments.
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Separately, we wrote an essay and analysis of POCT adoption, seeking common viewpoints across 8 recent review articles.
https://bqwebpage.blogspot.com/2025/11/ai-reviews-poct-from-perspective-of-8.html
What can "Shannon Theory" add to this 8-paper assessment.
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Below is an integrated, high-level analysis that takes your 8-paper synthesis and asks:
What new insights emerge when the entire essay is reinterpreted through Shannon information theory and modern information-flow thinking?
This commentary builds on the PDF essay you provided (the eight-paper thematic review) and infuses it with the information-theoretic structures we developed earlier.
Reinterpreting the “Eight Foundational Papers” Through a Shannon-Information Lens
Your original essay identifies the dominant themes across eight foundational POCT papers: governance, workflow fit, evidence requirements, economic logic, normalization, acute-care utility, molecular POCT, and REASSURED/global health perspectives.
However, none of these papers—nor typical reviews of POCT—frame the field in terms of information architecture, signal integrity, channel noise, erasure probability, or feedback dynamics. When we overlay Shannon information theory onto your synthesis, several surprising new insights emerge.
Below is what your eight-paper narrative looks like once reframed with Shannon’s concepts of information transmission, noise, compression, channel capacity, and feedback.
1. The Eight Papers Describe POCT as a System Problem — But Shannon Explains Why
Your synthesis observes that Quinn, Korte, Florkowski, Huddy, and Jones all insist that POCT is a system, not a gadget. From an information-theoretic view, this is exactly right, because:
Diagnostics is fundamentally an information-transfer problem:
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The patient’s latent disease state is the hidden variable.
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Signs, symptoms, and tests are noisy encodings of that state.
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The clinical workflow is the communication channel.
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Therapy is the decoded action.
When POCT fails, it is rarely because the test “isn’t good enough”—it’s because the channel architecture degrades or loses information.
Your essay lists organizational and governance problems (ownership, fragmentation, training, EHR connectivity). Shannon gives these a deeper meaning:
These are failures of the information channel, not of the technology.
Seen this way, POCT adoption issues parallel problems in communication systems:
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unclear ownership → no defined encoder/decoder
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poor training → high operator noise
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lack of connectivity → broken transmission links
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no policy → no channel specification
Thus, your original insight that POCT is a “system challenge” obtains a principled theoretical justification once one sees clinical workflow as a communication network.
2. NPT (Jones) and POCKET (Huddy) Are Really About Stabilizing the Information Channel
In your essay, NPT is a theory of embedding new practices; POCKET is a 65-item evidence framework.
Through a Shannon lens, these become mechanisms for reducing channel noise and maximizing information fidelity.
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NPT’s coherence, cognitive participation, collective action, and reflexive monitoring
→ These map exactly to the stability conditions of a high-bandwidth channel:
shared understanding of the protocol, clear ownership of encoding/decoding, reliable transmission steps, and continuous feedback for error correction. -
POCKET’s 65 evidence domains
→ A checklist of every point where information can be corrupted, delayed, or lost.
This is a radical reframing:
NPT and POCKET are not just implementation frameworks—they are systematic tools for optimizing the clinical information pipeline.
Your essay’s theme of “normalization” becomes, in Shannon terms:
turning a lossy, ad-hoc channel into a stable, predictable, low-noise pipeline that preserves diagnostic information.
3. Florkowski on Evidence-Based Lab Medicine Becomes a Discussion of Signal Fidelity
Florkowski’s EBLM reminders—RCTs, outcome data, analytic precision—fit naturally into information theory:
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Analytic sensitivity/specificity is the raw channel signal-to-noise ratio.
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Operational steps (training, QC, governance) are noise reduction techniques.
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Clinical utility measures the mutual information between test result and correct therapeutic decision.
Your essay correctly emphasizes that analytic performance alone is insufficient.
Shannon shows why:
The value of a test is not the bit-quality of the assay but the integrity of the entire channel from patient → test → interpretation → action.
This puts many EBLM struggles in a clearer light: measuring accuracy without analyzing channel degradation (delays, miscommunications, lost follow-up) misses the majority of real-world informational loss.
4. Acute Care (Elrobaa) Is Actually About Information Timeliness Relative to Disease Dynamics
Your essay notes that acute/ED settings are where POCT shines.
The Shannon reinterpretation:
POCT increases the effective information rate relative to the time constants of the underlying biological system.
Central-lab:
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Information arrives after critical physiological transitions.
POCT:
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Information arrives before harmful transitions, when it still changes the state trajectory.
This is a deeper insight than “short TAT helps triage.”
It is:
POCT aligns diagnostic insight with the dynamical evolution of disease.
Your essay’s acute-care emphasis is therefore fully Shannon-consistent: POCT increases the timeliness-adjusted value of information, not merely speed.
5. Economic Barriers (Khan, Korte) Become Channel-Capacity Constraints
Korte and Khan emphasize financial and operational barriers.
From a Shannon viewpoint, these barriers limit channel capacity.
Examples:
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Budget silos → constrict bandwidth for deploying POCT broadly.
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Staffing shortages → reduce the number of trained encoders/decoders.
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Workflow mismatch → increases packet loss (abandoned workflows, unused policy).
Your essay’s point that POCT value must make sense simultaneously to clinicians, administrators, and payers is analogous to ensuring all nodes in a network operate at a compatible bitrate.
The Shannon version:
Economic misalignment is a form of channel mismatch that reduces the amount of clinical information the system can reliably process.
6. Molecular POCT and REASSURED Are Actually About Expanding the Encoding Alphabet
Zu et al.’s molecular POCT challenges—sample prep, extraction, amplification—represent the engineering problem of compressing rich molecular states into portable, robust encodings.
The REASSURED criteria are, in essence, properties of a globally deployable channel:
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robust to noise
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low infrastructure requirements
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affordable
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high accuracy
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deliverable in low-bandwidth settings
Your essay’s recognition of molecular POCT as central aligns with Shannon’s view that diagnostic innovation often consists of expanding the alphabet size (the richness of what can be encoded and transmitted) while compressing the device constraints.
7. The Most Important New Insight (Not in the Original Eight Papers)
Your essay identifies broad implementation themes, but Shannon adds a powerful, unifying insight:
POCT is valuable not because it produces results faster, but because it transforms a noisy, delayed, lossy information channel into a high-fidelity, real-time, feedback-rich channel.
None of the eight papers articulate this fully.
You can now position POCT as:
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an information-preservation technology,
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a noise-reduction technology,
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a feedback-enabled decision technology, and
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a channel-architecture upgrade,
not simply a faster analyzer.
This perspective elevates the entire white paper.
8. What This Means for Your White Paper (and XYZ)
Reinterpreting your eight-paper synthesis through Shannon lets you make several bold statements:
A. POCT transforms the diagnostic channel, not just the diagnostic device.
Governance, training, QC, and workflow matter because they change channel fidelity.
B. Traditional lab workflows introduce large-scale information losses.
Delays, memory decay, failed callbacks, patient no-shows = Shannon erasures.
C. POCT enables adaptive information acquisition.
A feedback loop cannot occur if the test result arrives the next day.
D. Molecular POCT is the future because it expands what can be encoded.
E. The eight papers’ themes all describe parts of the channel—but Shannon unifies them.
This gives your white paper a theoretical coherence that goes beyond what any of the eight papers individually articulate.
If you want, I can now prepare:
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A new Shannon-informed executive summary of the eight papers,
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A white-paper chapter titled “POCT as an Information Architecture”,
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A slide-ready diagram of how each paper maps onto a Shannon concept, or
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A rewritten version of your essay that incorporates these insights for publication.
Just tell me which direction you want to go.
