Prince George's County, Maryland

Helping health organizations navigate AI with clarity, equity, and evidence

PCN Enterprises helps health organizations make evidence-grounded decisions about AI, and builds the technology to close the care gaps that fragmented systems leave behind.

Our Services Start a Conversation
32M+

Patients served by FQHCs in 2024, the highest in the program's 60-year history. Most health centers are navigating AI adoption without a framework.

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AI Workforce Advisory A structured, fixed-scope engagement that tells you exactly where AI helps, where it harms, and what to do next.
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PCN Navigation Services Clinical NLP research to surface missed vascular findings in unstructured radiology reports.

The moment we're in

Why this decision can't wait

Three developments in the past 12 months have made AI evaluation an urgent priority for health organizations of every type.

1
September 2025
NACHC publishes its AI Action Guide, naming the gap PCN Enterprises fills
The guide calls for a strategic, system-wide approach to AI and explicitly recommends health centers identify subject matter experts to guide the process. It endorses the Duke Health AI Partnership's Eight Key Decision Points and the HEAAL Framework as the gold standard for responsible AI evaluation. PCN Enterprises' methodology is built on both.
2
November 2025
NACHC partners with eClinicalWorks to bring AI documentation tools to FQHCs nationwide
Vendors are actively approaching health centers. Organizations without a framework to evaluate these pitches are making consequential decisions blind.
3
2025–2026
Workforce budgets shrink as patient volumes hit record highs
Every dollar of staff time that AI can responsibly recover matters. Every dollar wasted on mis-deployed tools is a dollar thin margins cannot absorb.

What we do

Two capabilities. One mission.

PCN Enterprises combines a health AI advisory practice with a clinical NLP research initiative, each informing the other, both grounded in real organizational and clinical context.

Advisory

AI Workforce Readiness Assessment

A 6-week, fixed-scope engagement for FQHCs and community health organizations. We assess where AI augmentation can reduce frontline burden, where it introduces risk for vulnerable populations, and how to implement responsibly under HRSA compliance requirements.

  • Task-to-AI fit scoring rubric by role
  • Workforce cost impact projection
  • 12-month implementation roadmap
  • AI vendor shortlist
Learn more →
Research & Technology

PCN Navigation Services

A clinical NLP research initiative building tools to surface missed findings in diagnostic imaging reports, connecting information to care before it disappears.

  • Clinical NLP model development
  • De-identified radiology report analysis
  • Outpatient clinical workflow integration
  • NSF SBIR Phase I research pipeline
Learn more →

The cost of a bad AI decision

A bad AI decision is more expensive than a good framework

The AI Workforce Readiness Assessment is a decision framework that protects organizations from the staff disruption, vendor failure, and compliance exposure that follow a poorly evaluated AI deployment.

1 in 3
Healthcare organizations report significant staff disruption following a poorly planned technology rollout
60%
Of health organizations cite lack of internal expertise as the primary barrier to evaluating AI tools effectively
70%
Of FQHCs facing critical clinical vacancies, leaving no margin for a technology decision that worsens retention
Request an Assessment

About PCN Enterprises

Rigorous. Independent. Rooted in public health.

PCN Enterprises, LLC is a minority-owned health advisory and technology company based in Prince George's County, Maryland. We combine public health expertise, clinical technology research, and a commitment to equity-grounded practice.

Dr. Phatsimo Masire-Nwosu, Founder & Principal Consultant, PCN Enterprises
Dr. Phatsimo Masire-Nwosu
PhD, MPH | Founder & Principal Consultant
Federal global health program management Academic and pediatric health systems Health equity, M&E, and AI governance Prince George's County, Maryland
Clinical Anchor
VascuHealth | Partner Practice
Board-certified specialist physician practice Prince George's County, MD | Outpatient clinical practice Minimally invasive outpatient procedures De-identified data partnership for NLP research

Why PCN Enterprises exists

AI is reshaping health organizations faster than most can evaluate it responsibly. The decisions are consequential and genuinely difficult: which tools are safe for which populations, which workflows must stay human, which vendor claims are evidence-based and which are not. Getting it wrong means staff disruption, patients poorly served, and compliance exposure no organization can afford.

PCN Enterprises exists for the leaders who refuse to decide without a framework, and for the patients whose findings get lost when fragmented systems fail to connect the right information to the right care. We hold AI to the same standard of evidence as clinical care. And we build the tools to prove it.

What makes our approach different

Vendor-independent
No financial relationship with any AI vendor. Every recommendation is grounded in your organization's specific needs, not a product roadmap.
Locally grounded
Based in Prince George's County. We understand the demographics, the barriers to care, and the operational realities of Maryland and DC health organizations from the ground up.
Equity-centered
Every engagement includes an explicit review of AI tool risks for vulnerable populations. The patients most likely to be harmed by a poorly deployed tool deserve the most rigorous evaluation.
Practice Informs Research
Our advisory work shapes our NLP research, and the research sharpens our advisory recommendations. Both are stronger for it.

Our services

Two capabilities. Both grounded in evidence, equity, and real clinical context.

PCN Enterprises runs a health AI advisory practice and a clinical NLP research initiative, each designed to inform the other.

Advisory Service

AI Workforce Readiness Assessment

A 6-week, fixed-scope engagement for health organizations of all types. We assess where AI augmentation genuinely reduces burden, where it introduces unacceptable risk, and how to implement responsibly, delivering a prioritized action plan your team can use immediately.

We do not evaluate tools in the abstract. Every recommendation is grounded in your specific roles, your EHR environment, your patient demographics, and your HRSA compliance requirements.

Methodology grounded in NACHC-endorsed frameworks

Our assessment maps directly to two frameworks NACHC's 2025 AI Action Guide endorses as the gold standard for health center AI adoption:

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Duke Health AI Partnership: Eight Key Decision Points

Our six-week engagement follows the four adoption stages: Procurement, Development, Integration, and Lifecycle Management, ensuring no critical decision point is skipped.

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HEAAL Framework: Five Assessment Domains

Accountability, fairness, fitness for purpose, reliability and validity, and transparency are embedded into every deliverable, with particular emphasis on the equity and compliance review.

What is Clinical NLP?

Plain-language explainer

NLP stands for Natural Language Processing, a branch of artificial intelligence that helps computers understand and interpret human language, including both written text such as patient charts and spoken words during an appointment. As NACHC's 2025 AI Action Guide describes it, NLP can automatically summarize long patient histories for quicker review, or extract concepts from free text notes for billing and missed coding.

Clinical NLP applies this specifically to healthcare documentation and the large volumes of unstructured narrative that clinicians generate every day: physician notes, diagnostic imaging reports, discharge summaries, and referral letters. Most of the meaningful clinical information in a patient record is not in a coded checkbox. It is buried in free-form prose.

Clinical NLP reads that prose and turns it into something a computer can act on: surfacing findings, flagging risk, or routing a patient to the right care, at a scale and speed no human team could match manually.

Why it matters in healthcare

Clinicians write thousands of notes, reports, and summaries every year. Significant findings, such as a secondary diagnosis, an abnormal measurement, or a recommended follow-up, are often noted in passing and then lost in the volume. Clinical NLP is designed to catch what humans miss.

The hard problem: negation

Clinical text is full of hedged and negated language: "no evidence of," "cannot rule out," "possible early-stage." A naive system flags all of these as positive findings. A well-designed clinical NLP model understands the difference, and that distinction has direct consequences for patient care.

What PCN Navigation Services is building

A domain-adapted clinical NLP model trained on real, de-identified practice data, validated specifically for the linguistic patterns found in outpatient diagnostic reports, where general-purpose AI tools have not been tested.

Research & Technology

PCN Navigation Services

A clinical NLP research initiative investigating whether domain-adapted language models can reliably surface clinically significant findings in unstructured diagnostic imaging narratives before they are lost in administrative handoff.

Independent outpatient practices generate large volumes of free-text diagnostic narrative in which clinically significant secondary findings are frequently buried in dense, hedge-laden prose. Existing tools either rely on keyword matching that fails on negated language, or general-purpose LLMs unvalidated for this clinical domain. PCN Navigation Services is building and validating a domain-specific model against real practice data.

The research is anchored by a clinical data partnership with a board-certified specialist practice in Prince George's County, MD, and is being developed toward an NSF SBIR Phase I application.

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Phase I: NLP Model Development & Benchmarking
Training and benchmarking domain-adapted transformer models against annotated data, with explicit focus on negation scope detection, the primary failure mode for clinical NLP in radiology text.
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Phase I: Workflow Feasibility Validation
Assessing whether model outputs are reliable enough to support downstream care coordination and characterizing the human oversight required for safe clinical deployment.

Send us a message

Email us directly and we will respond within 2 business days. Please include your organization name and a brief description of what you are working on.

Email services@pcn-enterprises.org

Your information is never shared with third parties.

Resources

From the NACHC AI Action Guide to action

NACHC's September 2025 AI Action Guide gives health centers a clear mandate, along with a set of recommended frameworks. PCN Enterprises translates both into a practical first step. The following resources ground our work in the evidence base NACHC endorses.

NACHC · September 2025
AI Action Guide for Community Health Centers

The definitive guide for FQHCs on AI adoption, covering what AI is, how it can help health centers, key risk considerations, and a step-by-step adoption framework. PCN Enterprises' methodology is built to implement its recommendations.

nachc.org →
Duke Health AI Partnership
Eight Key Decision Points for AI Adoption

A structured decision framework covering four adoption stages: Procurement, Development, Integration, and Lifecycle Management. PCN Enterprises' six-week engagement maps directly to these stages.

healthaipartnership.org →
Health AI Partnership
HEAAL Framework: Health Equity Across the AI Lifecycle

A community-informed framework evaluating AI across five domains: accountability, fairness, fitness for purpose, reliability and validity, and transparency. Embedded into every PCN Enterprises deliverable.

HEAAL Framework →
NIST
AI Risk Management Framework

The federal standard for managing AI risk to individuals, organizations, and society. Referenced in NACHC's guide as a foundational governance resource for health center AI programs.

nist.gov →

Ready to move from the NACHC guide to implementation?

PCN Enterprises helps health organizations take the structured first step NACHC recommends, with a methodology built on the frameworks the guide endorses.

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