The Future of Point-of-Care Testing: Promise, Reality, and the Systemic Barriers That Shape Adoption

A balanced white paper for health-system leaders, payers, and diagnostics executives

Point-of-care testing (POCT) has entered a period of rapid technological advancement. Molecular miniaturization, CRISPR-based detection, microfluidic lab-on-a-chip systems, integrated electrochemical biosensors, and connected digital readers are transforming the performance, speed, and versatility of tests used in outpatient, emergency, and even home settings. Over the next five years, these platforms will increasingly support same-visit diagnosis, syndromic decision-making, and more decentralized disease management. Yet despite the technical progress and strong theoretical value, POCT adoption in the United States remains uneven and in some settings surprisingly low. A central lesson is that innovation alone does not move care delivery; reimbursement structures, workflow design, regulatory expectations, quality reporting systems, and cultural norms often dominate.

A vivid example is POCT hemoglobin A1c, a technology introduced nearly two decades ago (CPT 83037, circa 2006) and technically well-suited for same-visit diabetes management. Despite these advantages, in 2023 Medicare Part B claims show that POCT A1c represents ~1% of the volume of reference-lab A1c (83036). The A1c case is not merely an outlier—it is a diagnostic parable illustrating several structural barriers that recur across the POCT landscape. But it is equally important not to overgeneralize: many POCT domains—particularly molecular respiratory panels, rapid strep, flu/COVID combos, D-dimer, troponin, and emerging CRISPR panels—have experienced robust growth where they align with clinical urgency and operational workflows.

Below is a framework for understanding what enables POCT to thrive, what holds it back, and how diagnostics companies and health systems can realistically shape the next five years of decentralized testing.

1. The Promise: Why POCT Should Be Transformative

Recent advances are narrowing the historical gap between POCT and central laboratory platforms.

• Molecular POCT now delivers sample-to-answer PCR or isothermal amplification in 10–25 minutes.
• CRISPR-based diagnostics offer programmable assays ideal for emerging pathogens and resistance markers.
• Microfluidics supports multiplex panels in small, inexpensive cartridges.
• Electrochemical biosensors and wearables allow more frequent or continuous monitoring.
• Digital connectivity integrates POCT into EHRs, population health registries, and public-health surveillance.

These technologies materially improve care in settings such as urgent care, ED triage, pharmacy-based clinics, and safety-net environments where time-to-result directly affects disposition, antibiotic stewardship, or follow-up reliability. When POCT aligns with a clear clinical question and a workflow designed around same-visit action, adoption can be rapid and durable.

2. The A1c Counterexample: When POCT Fails Despite Technical Suitability

The A1c story shows how even an analytically sound POCT device can fail commercially when system-level conditions are misaligned.

Key barriers illuminated by 83037’s stagnation include:

Pricing without margin: Congressional action tied 83037’s price to 83036, eliminating the intended financial differential and leaving practices with higher costs but no increased reimbursement.
Workflow friction: Running A1c during rooming requires staff time, training, QC, and device placement that many practices cannot operationalize.
Quality-measure uncertainty: In some systems, POCT data do not reliably populate diabetes registries or count toward HEDIS/ACO measures.
Reference-lab economics: LabCorp, Quest, and hospital labs offer low-cost venipuncture and bundled panels, making single-test POCT comparatively unattractive.
Low clinical urgency: A1c trends matter more than real-time results, weakening the intrinsic value of “same-visit A1c.”

This case illustrates that POCT adoption is primarily governed by system design—payment, workflow, contracts—not technology.

3. Generalizable Barriers Across the POCT Landscape

The barriers illuminated by A1c are not unique. Across other POCT domains—infectious disease, cardiology, nephrology, anticoagulation, and metabolic disease—several systemic obstacles recur:

A. Economics rarely favor POCT unless incentives are explicit

POCT devices have higher per-test costs, require QC and consumables, and lack the economies of scale available to central labs. Without add-on payments, bundled codes, or quality-related incentives, POCT is frequently a financial loss for clinics.

B. Workflow integration is often underestimated

Successful POCT requires:

training of MAs or nurses,
physical space near exam rooms,
predictable instrument uptime,
rapid-result workflows aligned with clinician timing.
Small misalignments cascade into underuse or abandonment.

C. CLIA compliance, QC, and literacy demands

POCT shifts responsibility for precision and reliability onto the clinic or pharmacy. Many primary-care practices lack the staffing, documentation culture, and procedural discipline to sustain CLIA workflows.

D. EHR data capture determines whether results “count”

If POCT results don’t reliably integrate into flowsheets, sepsis dashboards, antimicrobial stewardship systems, ACO quality reporting, or MA Stars, institutional leaders discourage POCT, even if clinicians favor it.

E. Reference-lab contracting and politics matter

Many health systems negotiate volume-based pricing with large labs, including supplies, couriers, and onsite phlebotomy. POCT disrupts these arrangements and is sometimes explicitly discouraged by internal policy.

F. Cultural trust and perceptions of analytical rigor

Laboratorians and clinicians may view POCT as “less real” than central lab data, especially for biomarkers used in diagnosis or chronic-disease metrics. Even when modern POCT devices meet NGSP, IFCC, or CLIA standards, perception lags reality.

G. Single-test devices create operational fragmentation

A device that only does one test (like A1c or CRP) creates siloed workflows. Adoption is highest when platforms offer multiplexing, shared controls, unified QC, and a clear family of tests.

4. Conditions Under Which POCT Flourishes

Despite these barriers, several domains have shown strong uptake. POCT succeeds when four conditions align:

**A. The result meaningfully changes today’s clinical decision**

Examples: strep, influenza/COVID combos, RSV in pediatrics, troponin in chest pain pathways, CRP/D-dimer in European triage models.

B. The clinical workflow is engineered around the test

High-performing POCT sites redesign intake, vitals collection, and provider timing so results appear exactly when needed.

C. Payment or quality incentives reward same-visit action

ACO models, MA Stars metrics, pharmacy-care pathways, and risk-sharing arrangements make rapid decisions financially meaningful.

D. Health systems or pharmacies value decentralized care

Retail clinics, urgent care chains, and integrated systems (Kaiser, Intermountain, Geisinger) benefit from reduced referrals, fewer missed follow-ups, and improved patient flow.

5. Strategy: How to Accelerate POCT Adoption Over the Next Five Years

A realistic roadmap for diagnostics companies and health systems includes:

1. Developing multianalyte POCT ecosystems

Consolidated platforms that run multiple tests (A1c + lipid + albumin/creatinine + CRP) dramatically improve the business case.

2. Designing POCT-first clinical workflows

Embedding POCT into rooming protocols, staffing models, and appointment timing ensures consistent use.

3. Building plug-and-play EHR integration

Seamless HL7/FHIR feeds that auto-populate registries and quality measures remove the biggest hospital-level objection.

4. Shaping incentives

Modest add-on payments, quality credits, or ACO-aligned bonuses would transform uptake for chronic-disease POCT.

5. Leveraging distributed care models

Home POCT, pharmacy-based diagnostics, and telehealth titration programs will become major growth drivers—especially in diabetes, COPD, CKD, and cardiovascular risk management.

6. Prioritizing equity and missed-follow-up populations

POCT adoption is strongest where follow-up failure is high—FQHCs, rural clinics, and safety-net systems.

Conclusion: A Balanced Outlook

POCT is entering a promising technological era, with rapid advances in molecular diagnostics, CRISPR detection, multiplex microfluidics, and connected biosensors. These tools offer unprecedented potential for fast, decentralized clinical decision-making. But the real-world A1c example demonstrates that innovation does not guarantee adoption. System-level forces—reimbursement, workflow, contracting, cultural trust, and data integration—ultimately determine whether POCT becomes standard-of-care or remains underutilized.

The next five years will reward companies and health systems that approach POCT not as a device to place in clinics, but as a clinical service model requiring redesign of incentives, workflows, and informatics. The technology is ready; aligning the system around it is the next frontier.

If you'd like, I can also produce:
• a two-page executive summary,
• a slide deck version for board or investor meetings,
• or a policy briefing tailored to CMS, MolDx, or CMMI.

Tailored to CMMI

Below is a CMMI-tailored white paper—strategic, concise, and written in the policy-analytic tone you use in CMS/CMMI briefings. It highlights POCT’s promise, its structural barriers, the A1c case as a cautionary data point, and how CMMI (under current statutory authority) could realistically use model design, waivers, incentives, and data aggregation to accelerate high-value POCT adoption only where it improves total cost of care.

Point-of-Care Testing and

the Center for Medicare & Medicaid Innovation:

Opportunities, Barriers, and Model-Design Levers**

Executive Summary
Point-of-care testing (POCT) has advanced rapidly—molecular, CRISPR-based, microfluidic, and multianalyte platforms now enable accurate, fast diagnostics at the site of care. In theory, POCT should support faster treatment decisions, reduce unnecessary referrals and acute utilization, and improve chronic-disease management. In practice, adoption in Medicare remains uneven. The extreme underutilization of POCT hemoglobin A1c (83037) relative to central-lab A1c (83036) despite two decades of availability illustrates persistent system-level barriers. For CMMI, POCT represents neither a universal solution nor a simple technology insertion; it is a leverage point for models that reward same-visit care, close gaps in chronic disease management, and reduce preventable ED revisits and admissions—but only if embedded in payment, workflow, and data structures that CMMI can influence.

This paper outlines (1) the promise of modern POCT, (2) the structural barriers that suppress adoption even when devices are analytically excellent, (3) lessons from the A1c “belly flop” case, and (4) specific CMMI levers that could meaningfully increase high-value POCT use in targeted models.

1. The Promise: Why POCT Matters for CMMI

Modern POCT aligns with several CMMI priorities:

Reducing total cost of care through earlier diagnosis, fewer repeat visits, and fewer avoidable admissions (e.g., respiratory panels in high-risk older adults, POCT BNP/CRP/D-dimer for chest-pain and dyspnea algorithms).
Advancing team-based care where pharmacists, RNs, and community clinics manage chronic disease with rapid diagnostics.
Supporting care in new settings—home, retail clinics, mobile units—especially relevant for rural and underserved populations.
Improving chronic-disease control by reducing follow-up failure, especially in ACO and MA settings.
Data-enabled population health, when POCT systems deliver structured, real-time data streams to EHRs and registries.

CMMI does not need to “promote POCT” for its own sake, but can use POCT strategically to shorten diagnostic loops, improve adherence to clinical pathways, and support decentralized care models that improve Medicare outcomes.

2. Structural Barriers: Why Adoption Lags (Even When Technology is Strong)

CMMI has seen this pattern in prior models: strong technology, weak uptake. Across POCT domains, several barriers consistently suppress adoption:

A. Misaligned reimbursement

POCT devices are often financially irrational relative to send-outs:

Higher per-test costs with no payment differential
Reference-lab contracts that reward volume centralization
Lack of incentives for same-visit decision-making

B. Workflow incompatibility

Most primary-care practices are not engineered for POCT:

No idle staff capacity
No standardized rooming protocols for sample collection
Delays while waiting for results interrupt the visit flow
QC and CLIA obligations add friction

C. EHR integration failures

If POCT results do not populate registries, flowsheets, ACO dashboards, or MA Stars metrics, institutional leaders discourage their use.

D. CLIA/JCAHO compliance burdens

Quality management, documentation, controls, and proficiency testing fall on staff who are not laboratory professionals.

E. Siloed test platforms

Single-test devices (e.g., A1c-only) create operational fragmentation; adoption is easier with multianalyte platforms that unify QC and consumables.

F. Cultural and analytic skepticism

Even with excellent analytical validity, many clinicians simply trust the central laboratory more—especially for chronic-disease biomarkers.

Collectively, these barriers explain why analytically strong technologies do not penetrate routine practice.

3. The A1c POCT “Belly Flop”: A Clarifying Case for CMMI

A1c POCT is a vivid example of how technology fails without system design:

In Medicare claims, POCT A1c (83037) is ~1% of lab A1c (83036).
Congressional action eliminated the intended pricing differential, removing the economic rationale.
POCT A1c often does not integrate into diabetes registries, so quality teams do not “count” it for HEDIS/ACO performance.
The test is operationally misaligned with typical primary-care workflows focused on bundled metabolic panels.
Chronic-disease management does not always require immediate A1c, weakening the value of same-visit testing.

The lesson for CMMI is not that POCT is ineffective, but that payment, workflow, and data integration determine adoption, not analytic performance. If CMMI intends to use POCT in chronic-disease models, the model must “solve for” these barriers explicitly.

4. CMMI Levers: How Innovation Center Models Could Accelerate High-Value POCT

CMMI has several tools—payment flexibility, waivers, attribution rules, quality measures, and care-transformation requirements—to overcome barriers where POCT supports model goals.

A. Incentivize same-visit clinical action

CMMI can test modest episode-based add-on payments for same-visit diagnostic-action bundles:

Diabetes visits using same-visit A1c plus documented medication intensification
COPD and heart-failure visits using POCT BNP, CRP, or viral panels to drive evidence-based treatment
UTI/STI pathways in primary care and retail settings using rapid molecular POCT to reduce unnecessary antibiotics

This approach ties the incentive to clinical outcomes, not device use.

B. Require or reward POCT workflows in model-participant redesign plans

CMMI models often require “care delivery transformation plans.” These could specify:

Standardized POCT workflows for chronic-disease follow-ups
Rooming protocols that obtain samples before provider entry
Delegated testing by pharmacists and RNs under standing orders
Structured EHR integration using a common FHIR profile

The goal is workflow reliability, not technology promotion.

C. Provide waivers for expanded clinician types

Allow pharmacists, RNs, and community health workers to use POCT under expanded practice flexibilities—especially in rural/mobile settings or under SDOH-targeted models.

D. Align POCT with model quality measures

CMMI could specify that POCT results be counted for performance measurement if devices meet interoperability standards.
This removes a key barrier that currently suppresses A1c POCT and other tests.

E. Use POCT to support community-, retail-, and home-based care

In models emphasizing:

Hospital-at-home
Mobile chronic-disease units
Pharmacy-enabled primary care

CMMI can incorporate POCT as a required or optional capability, enabling these decentralized care channels.

F. Build real-time population-data streams

CMMI models can require POCT to feed into real-time registries for:

Respiratory illness surveillance
AMR detection in community settings
Chronic-disease risk stratification
Emergency department diversion pathways

POCT becomes a data asset, not merely a device.

5. Where POCT Aligns With CMMI Priority Conditions

Based on current priorities (chronic disease, behavioral health integration, rural health, and care in new settings), POCT may have particularly high ROI in:

Diabetes: same-visit titration and reduction of no-show follow-ups.
COPD/CHF: rapid differentiation of decompensation vs infection vs volume overload.
Infectious disease: molecular POCT panels preventing ED boarding, unnecessary antibiotics, and hospital admissions.
Kidney disease: microalbumin/creatinine and biochemical panels in mobile nephrology or community units.
Behavioral health + primary care integration: POCT lipids, metabolic panels, and tox testing that support coordinated care.

These areas offer measurable reductions in acute utilization, aligning with total-cost benchmarks.

6. Policy Caution: Avoid Technology-First Model Design

CMMI should not base models on mandatory technology adoption. Instead:

Tie incentives to clinical behavior (e.g., same-visit titration, reduced ED revisits).
Allow clinicians to choose technology (POCT, central lab, home kit) that meets model goals.
Require POCT only where speed of result is a known driver of better outcomes.
Use POCT for operational efficiency, not as a scoring item.

This protects clinicians and health systems from being locked into technologies that may not fit their workflows.

Conclusion: A Targeted, High-Value POCT Strategy for CMMI

POCT is not a universal fix, but it is a powerful enabler for many of the care-delivery models CMMI wishes to advance. The A1c POCT experience demonstrates that technology without incentives, workflows, and interoperable data has little real-world impact. But in the right clinical settings—urgent care, chronic-disease management, respiratory illness pathways, retail clinics, rural/mobile units—POCT can materially reduce total cost of care and improve beneficiary experience.

For CMMI, focusing on situations where speed changes outcomes, coupled with payment incentives, workflow redesign requirements, interoperability standards, and expanded team-based authority, can unlock the benefits of modern POCT while avoiding the pitfalls of indiscriminate promotion.

Thursday, November 20, 2025

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