— The Previty Method
The Logic Behind
Every Tool We Build.
A physician-designed framework of principles and a structured approach to clinical problem-solving — governing how physician expertise becomes health technology, responsibly and at scale.
The Previty Method is not a product. It is the standard we hold every product to. It comprises two components: the Previty Principles — ten commitments every Previty physician follows in every engagement — and the Previty Approach — a structured, six-stage methodology for evaluating, advising on, and building clinical AI. Together they define what it means to practice physician-led clinical intelligence.
— Two Components. One Standard.
Component One
The Previty Principles
Fixed. Non-negotiable. Physician-held.
Ten ethical and clinical commitments that every Previty physician follows in every engagement — regardless of the organization, the technology, or the commercial context. These do not flex.
Component Two
The Previty Approach
Structured. Iterative. Problem-specific.
A six-stage methodology for applying those principles to a specific clinical technology problem — whether advising a health tech company, validating an algorithm, or building a new tool in the Studio.
— Why a Framework Matters
Anyone Can Build a Tool.
Not Everyone Can Build One Worth Trusting.
AI has made it easier than ever to build health tools. It has not made it easier to build health tools that are clinically sound, ethically grounded, and safe to deploy at scale.
The Previty Method exists to answer that challenge. It is the logic framework that governs everything Previty creates and everything Previty physicians advise on — a set of ten principles that define how physician expertise enters the design process, and a structured six-stage approach that defines how Previty physicians evaluate and engage with every clinical technology problem they encounter.
It is not a checklist. It is a standard of practice — applied at every stage, by every physician in the network, in every tool that carries the Previty name.
— The Previty Principles
Ten Commitments Every
Previty Physician Keeps.
These ten principles are the professional code of every physician in the Previty network. They apply in every engagement — when advising a health tech company, reviewing a clinical algorithm, building a tool in the Studio, or consulting on population health strategy. They are not aspirational. They are operational.
Principle I
Physician Intelligence First
Every engagement begins with a clinical question — defined by physician judgment, not by data availability or technology capability. Previty physicians bring that judgment to bear before any system, tool, or algorithm is evaluated, endorsed, or advised upon.
Principle VI
People First by Design
Every tool is evaluated from the patient's perspective — not just the clinician's or the system's. Clinical value is measured by what reaches the patient, not what impresses the platform. Health equity is a design value held present in every engagement.
Principle II
Evidence as Foundation
Previty physicians advise on what is established — and name clearly what is not. Clinical claims, risk logic, and decision frameworks must be grounded in peer-reviewed evidence. Where evidence is limited or emerging, that boundary is stated explicitly, not obscured.
Principle VII
Transparent Logic
Previty physicians require that every tool they advise on is explainable and documented — designed to be understood by the people who depend on it. Transparency without accountability is incomplete. Every engagement includes clear lines of responsibility for when performance, bias, or unexpected outcomes arise.
Principle III
Intentional Input-Output Pairing
What enters a clinical algorithm determines what comes out. Every input — data source, variable, assumption — must be explicitly chosen, documented, and evaluated for quality and bias before it shapes an output. Previty physicians will not endorse tools where this logic is hidden, assumed, or undocumented.
Principle VIII
Consistent Performance
A clinical tool must perform reliably across populations, settings, and time — not just in the conditions it was designed for. Previty physicians validate for real-world generalizability, not benchmark performance alone. A tool that works for some populations and not others is not a finished tool.
Principle IV
Scale Amplifies Everything
What benefits one patient can transform a population. What harms one patient can harm millions. Previty physicians evaluate every tool not just for individual clinical value but for what happens when it operates at scale — including unintended consequences, equity gaps, and systemic risk.
Principle IX
Continuous Validation
Clinical tools are not static. Evidence evolves, populations shift, and real-world performance diverges from design assumptions. Previty physicians treat ongoing validation as a professional obligation — including alignment with FDA guidance, HIPAA requirements, and emerging AI governance frameworks. Validation is never finished.
Principle V
Do No Harm
Ethics and safety are design requirements built in from the first decision — not compliance layers added at the end. This means evaluating tools for clinical harm, algorithmic bias, and equity implications, and treating patient data with the highest standard of protection. If a tool cannot meet these standards, Previty physicians will not endorse it — regardless of who built it.
Principle X
Amplify, Never Replace
The purpose of every tool Previty physicians advise on is to extend the reach of clinical expertise — not substitute for it. Technology is the amplifier. The physician is always the signal. Any tool that positions itself as a replacement for physician judgment falls outside the Previty standard.
— The Previty Approach
Clinical Reasoning,
Applied to Technology.
Physicians are trained in a structured diagnostic and decision-making process. They don't evaluate a tool the way a software engineer would — they interrogate it the way they'd interrogate a clinical problem. The Previty Approach applies that clinical reasoning to health technology: a six-stage methodology used by every Previty physician when advising a health tech company, reviewing an algorithm, or building a tool in the Studio.
Define the Clinical Question
What problem are we actually solving — in clinical terms?
Before evaluating any technology, a Previty physician defines the clinical problem the tool is meant to solve — in clinical terms, not technology terms. What is the presenting problem? Who is the patient population? What does success look like at the individual and population level? What are the risks of a wrong answer? Most technology engagements skip this stage entirely. Previty starts with the problem and works forward to whether any tool, including the one already built, is the right answer.
Interrogate the Evidence
What does the science actually support — and where does it stop?
What clinical evidence supports the tool's underlying logic? Is the evidence peer-reviewed, population-representative, and current? Where are the evidence gaps — and does the tool acknowledge them or obscure them? Previty physicians apply the same evidence standards used in clinical practice: source quality, study design, applicability to the target population. A tool built on weak or outdated evidence is a clinical liability regardless of how well the technology performs.
Audit the Logic
What goes in, what comes out, and what decisions happen in between?
How does the tool work? What enters the algorithm, what assumptions are made, and what outputs are generated? Previty physicians map the input-output logic of every tool they advise on — identifying undocumented assumptions, evaluating data sources for quality and bias, and flagging where the algorithm makes choices that clinical judgment would make differently. No black boxes. If the logic cannot be explained, it cannot be endorsed.
Stress-Test for Scale and Harm
What happens when this tool operates on millions of patients?
What happens when this tool operates on thousands or millions of patients? Who benefits, who is disadvantaged, and where are the failure modes? Previty physicians apply a population lens that most point-of-care evaluations miss — because tools that perform well in controlled conditions can fail, cause harm, or widen equity gaps when deployed at scale. This stage also evaluates data privacy and security implications: a tool that is clinically sound but data-unsafe is not a safe tool.
Evaluate Workflow and Usability
Does it fit into how medicine actually works?
Clinical soundness is necessary but not sufficient. A tool must also fit into the real-world environments where physicians work — without adding cognitive burden, disrupting care flow, or creating conditions for automation bias. Previty physicians evaluate every tool for workflow integration: how it surfaces information, when it intervenes, and whether it supports or undermines clinical decision-making at the moment of care. A tool that clinicians cannot or will not use in practice has no clinical value, regardless of its technical performance.
Define the Accountability Structure
Who is responsible — and what happens when something goes wrong?
Who is responsible for this tool's performance after it ships? What triggers a review, a pause, or a withdrawal? Previty physicians will not complete an advisory engagement without a clear answer to these questions. A tool without an accountability structure is a liability, not an asset. This stage also confirms alignment with applicable regulatory frameworks including FDA guidance on software as a medical device, HIPAA, and relevant state AI governance requirements.
The Approach is structured, not linear. Findings at any stage can and should send a Previty physician back to an earlier one. Clinical judgment governs when to advance, when to revisit, and when to stop. The stages provide structure — the physician provides the reasoning.
— The Method in Practice
Principles Are Only as Strong
as the Physicians Behind Them.
The Previty Method is not applied in isolation. It is the operating standard for every physician in the Previty network — the framework they follow when they advise a health technology company, validate a clinical algorithm, join a product team, or evaluate a tool for deployment. When a health tech company engages Previty, they are not just getting an advisor. They are getting a methodology — structured, principled, and validated against international standards.
Clinical Validation
Our physician advisors evaluate AI algorithms and clinical tools against the Previty Method — assessing input-output integrity, evidence grounding, real-world performance, and regulatory alignment before and after deployment.
Design Guidance
Physician advisors bring the Method into health tech product development — shaping clinical requirements, identifying failure modes, evaluating workflow fit, and ensuring that what gets built reflects how medicine actually works.
Population-Level Oversight
Before tools are deployed at scale, our physicians evaluate population-level impact — assessing equity implications, systemic risks, and whether clinical benefit holds across diverse patient populations.
Continuous Governance
The Method treats validation as a continuous obligation. Our physicians serve as ongoing governance partners — monitoring real-world performance, flagging evidence updates, and ensuring tools evolve as the science does.
— Built on the Method
Where Principles Become
Deployable Clinical Intelligence.
The Previty Clinical Algorithm Studio is where the Method moves from framework to product. Every tool Previty develops is built against the ten principles and walked through the six-stage approach — producing clinical IP that is grounded in evidence, validated by physicians, and designed for real-world deployment. Tools developed in the Studio are available for licensing and white-label deployment by health technology companies, health plans, and health systems.
The Previty Method is the standard. Everything we build is measured against it.