How to Launch Direct-to-Consumer Lab Testing From an Existing Clinical Laboratory: The 2026 Guide

For an established clinical laboratory, launching direct-to-consumer testing is not primarily a laboratory problem.

The testing infrastructure may already exist. The harder problem is building everything between the consumer and the laboratory: test discovery, ordering authorization, pricing, checkout, patient identity, collection, requisitions, specimen status, results delivery, support, repeat testing, and the operational workflows that connect those experiences back to the laboratory.

That distinction matters.

A direct-to-consumer program is not simply a laboratory website with a shopping cart. It is a new commercial and operational channel layered onto regulated clinical infrastructure.

The laboratories best positioned to launch successfully are typically those that treat DTC as an operating model, not just a storefront.

This guide explains the major decisions an existing U.S. clinical laboratory should work through before launch.

What is direct-to-consumer laboratory testing?

In the context of an established clinical laboratory, direct-to-consumer laboratory testing generally means creating a channel through which an individual can discover and initiate laboratory testing outside the traditional physician-referral workflow.

CMS uses the term direct access testing (DAT) for consumer-initiated testing of human specimens and notes that DAT is also referred to as direct-to-consumer or patient-authorized testing. Importantly, CMS also states that some states do not permit DAT and that state laboratory laws may determine who is authorized to order tests or receive results.

Direct-to-consumer does not necessarily mean that every consumer can legally self-order every laboratory test in every state.

Depending on the jurisdiction, test, and operating model, a DTC program may use:

• true consumer self-ordering where permitted;
• an authorized healthcare professional who reviews or issues the laboratory order;
• a hybrid model that changes according to the patient's location or test;
• existing provider relationships combined with a consumer-facing commerce and collection experience.

The correct model should be determined before a laboratory begins designing checkout.

DTC does not remove the laboratory from CLIA

CMS regulates laboratory testing performed on humans in the United States through the Clinical Laboratory Improvement Amendments. CLIA requirements apply according to the complexity and type of testing being performed.

CMS is explicit that CLIA does not create a separate lower standard for direct access testing. A facility that meets the CLIA definition of a laboratory must hold the appropriate certificate before performing patient testing, including DAT, and comply with the applicable requirements for waived or non-waived testing.

For an established clinical laboratory, that is an important strategic advantage: much of the difficult clinical infrastructure may already exist.

The DTC challenge is building the consumer and operational layer around it.

The 12 decisions that determine whether a DTC laboratory program works

A practical launch can be broken into 12 connected decisions:

1. Define the commercial model.
2. Establish the ordering and geographic rules.
3. Build the initial test catalog.
4. Validate pricing and unit economics.
5. Design the consumer experience.
6. Select the collection model.
7. Connect ordering to the LIS/LIMS.
8. Orchestrate the complete order and specimen workflow.
9. Build patient identity and secure access.
10. Design results delivery and escalation.
11. Create repeat-testing and longitudinal engagement.
12. Establish operational ownership, measurement, and governance.

They should be designed as one system.

A failure at any one point can compromise the entire consumer experience.

1. Start with the business model, not the website

The first question is not:

What should the DTC site look like?

It is:

What consumer laboratory business are we trying to operate?

An established laboratory could pursue several models.

À-la-carte testing

Consumers purchase individual tests or panels when needed.

This is the simplest commercial model to understand, but it can produce highly transactional behavior unless the laboratory creates a reason for patients to return.

Curated health panels

Instead of exposing the entire laboratory test menu, the laboratory creates consumer-friendly panels around recognizable use cases such as metabolic health, cardiovascular health, thyroid function, hormones, nutrient status, or general wellness.

This can make test discovery easier, but the clinical and marketing rationale for every panel still needs to be defensible.

Repeat-testing programs

A program can organize testing around a defined cadence or monitoring objective where repeat testing is clinically and operationally appropriate.

The important distinction is that the laboratory is no longer optimizing only for the first transaction.

It is designing for:

Baseline → result → understanding → follow-up → retest → longitudinal comparison

Membership or hybrid programs

Some laboratories may combine individual purchases, member pricing, repeat-testing programs, or other benefits.

Membership is not automatically a better business model. It only works if there is continuing value beyond discounting the original test.

Before building anything, define:

• target consumer;
• initial catalog;
• geographic footprint;
• ordering model;
• collection model;
• expected average order value;
• contribution margin;
• expected acquisition economics;
• expected repeat-testing behavior;
• internal operational owner;
• what the laboratory will do itself versus through partners.

If those answers are unclear, the storefront is premature.

2. Establish the ordering model and geographic rules before launch

This is one of the most consequential decisions in the entire program.

CMS states that CLIA regulates laboratories conducting testing rather than determining who may order a test, and that state law may regulate ordering authority and limit direct access testing. For non-waived testing, CLIA requires a written or electronic test request from an “authorized person,” with authorization determined under state law.

The Association for Diagnostics & Laboratory Medicine similarly notes that the decision as to whether consumers can directly order laboratory testing remains a state-level issue.

That means a national DTC program should not treat geographic availability as a marketing preference.

It is part of the ordering architecture.

Build a state-and-test availability matrix

Before enabling checkout, determine for each target jurisdiction:

• whether the consumer may directly order the test;
• whether an authorized provider order is required;
• which professional may issue that order;
• whether additional laboratory licensure applies;
• whether the test has additional restrictions;
• whether the chosen collection method is permitted;
• how results may be released;
• whether any special consent or disclosure applies.

This matrix should control actual product availability inside the consumer system.

If a test cannot be sold using the configured workflow in a patient's jurisdiction, the system should prevent that order rather than relying on staff to catch the problem later.

Provider authorization should be part of the workflow

Where a provider order is required, do not treat physician authorization as a manual back-office afterthought.

It should have a defined state within the order lifecycle.

For example:

Purchased → authorization pending → authorized → collection eligible → collected → accessioned → processing → released

The exact workflow depends on the laboratory and jurisdiction, but the principle is consistent: regulatory requirements should be represented in the operational system, not tracked through spreadsheets and inboxes.

3. Launch a focused test catalog

Established laboratories often have large test menus.

That does not mean the entire menu belongs on a DTC storefront.

A laboratory catalog is designed for clinicians and ordering systems. A consumer catalog serves a different function.

Start by selecting tests and panels that make sense across five dimensions.

Consumer relevance

Can the intended customer understand why the test exists and when it may be appropriate?

Clinical appropriateness

Is the offering clinically supportable for the intended use, and are its limitations communicated accurately?

ADLM recommends that consumer laboratory providers clearly communicate clinical indications, specimen collection information, results interpretation, and cost.

Operational fit

Can the laboratory reliably perform the test within the consumer workflow?

Consider:

• specimen type;
• preparation requirements;
• collection requirements;
• stability;
• shipping or courier requirements;
• turnaround expectations;
• recollection risk;
• reflex or confirmatory testing;
• critical-result handling.

Commercial fit

Does the price support the actual cost structure after including:

• laboratory cost;
• collection;
• physician authorization where applicable;
• payment processing;
• technology;
• customer support;
• refunds and recollections;
• marketing and acquisition.

Repeatability

Is this inherently a one-time purchase, or could it fit into a legitimate longitudinal monitoring relationship?

The objective is not to maximize the number of products visible at launch.

It is to create a catalog the laboratory can operate exceptionally well.

4. Design pricing around contribution margin, not retail price alone

A laboratory entering DTC is moving from a primarily clinical workflow into a consumer transaction model.

The economics therefore need to be modeled differently.

A simple starting framework is:

Consumer price

minus

• testing cost
• collection cost
• ordering-provider cost
• payment fees
• fulfillment/logistics
• customer support
• expected refund/recollection cost
• technology cost

equals

contribution before customer acquisition

Then subtract the cost required to acquire the customer.

The resulting number determines whether the program can scale.

Avoid copying competitor prices blindly

A competitor's $149 panel tells you almost nothing about its economics.

It may have:

• different laboratory costs;
• different collection agreements;
• different physician-order economics;
• different acquisition costs;
• different margin targets;
• different bundled biomarkers;
• a membership subsidy;
• cross-selling economics unavailable to your laboratory.

Price should follow your operating model.

Keep the underlying catalog structured

From a technology perspective, a DTC test should not be modeled as a generic ecommerce SKU.

It should connect to structured laboratory information such as:

• laboratory test or panel identifier;
• constituent biomarkers;
• specimen requirements;
• preparation instructions;
• collection eligibility;
• geographic rules;
• ordering requirements;
• price;
• expected workflow;
• result mapping.

That becomes increasingly important once the laboratory begins managing dozens of products, multiple regions, promotions, member pricing, or recurring programs.

5. Build the consumer experience around informed action

The laboratory storefront has two jobs:

help the right person understand the offering and move an eligible order into the laboratory correctly.

The first job is where many traditional laboratory websites struggle.

Consumers should not need to understand laboratory nomenclature to shop.

A strong test page should answer, in plain language:

• What is this test?
• What does it measure?
• Who may consider it?
• What biomarkers are included?
• What specimen is required?
• Is fasting or preparation needed?
• How is the specimen collected?
• What does the price include?
• Is an ordering provider involved?
• What happens after purchase?
• How and when are results delivered?
• What are the limitations?
• What should a consumer do with the result?

ADLM specifically recommends transparent, understandable consumer information covering indications, collection, interpretation, costs, and test limitations.

Marketing claims require discipline

The temptation in consumer health is to turn a laboratory panel into a promise.

That is dangerous.

FTC health-products guidance applies broadly to health-related marketing, including diagnostic tests and health applications. The FTC states that objective health-related claims must be truthful, not misleading, and supported by appropriate scientific evidence.

That means the entire consumer experience should be reviewed for both explicit and implied claims.

“Measure biomarkers associated with cardiovascular risk” and “prevent heart disease” are not interchangeable statements.

Design and copy should increase clarity without overstating what the test establishes.

6. Choose a collection strategy the laboratory can actually operate

The collection experience determines whether a consumer purchase becomes a usable specimen.

Possible models include:

• laboratory-owned patient service centers;
• third-party collection sites;
• mobile phlebotomy;
• workplace collection;
• home collection where appropriate;
• combinations of these models according to geography and test.

ADLM notes that modern consumer testing may use local collection centers, home services, or mobile collection approaches, while emphasizing the importance of validated sample collection and processing practices.

The commercial promise should never run ahead of operational coverage.

Collection should be eligibility-aware

A consumer should see collection options that actually apply to:

their location + selected test + specimen type + service area + ordering status

rather than selecting from a generic scheduling directory.

Define the complete specimen handoff

For every collection model, map:

• appointment or collection selection;
• preparation instructions;
• patient identification;
• requisition availability;
• specimen labeling;
• collection confirmation;
• specimen handoff;
• transport;
• laboratory receipt;
• accessioning;
• rejection or recollection;
• status communication.

A beautifully designed checkout does not matter if specimens arrive without the correct order context.

7. Integrate the consumer order with the LIS/LIMS

The laboratory system should remain authoritative for laboratory testing and official results.

The DTC platform should not create a second competing clinical record.

The objective is to create a controlled exchange between the consumer layer and the laboratory layer.

A typical architecture might look like:

This is also the architecture Solia Direct is designed around: the consumer platform sits above existing laboratory infrastructure rather than replacing the LIS/LIMS.

Decide system ownership explicitly

For every important data object, identify its source of truth.

For example:

The exact answer may differ by laboratory.

What matters is that there is an answer.

Without clear system boundaries, teams eventually create reconciliation problems, duplicated records, inconsistent statuses, and uncertainty about which version is authoritative.

8. Model the full workflow, including failure states

The happy path is straightforward:

Order → collect → test → release result

Real laboratory operations are not.

A production DTC system has to account for exceptions such as:

• provider authorization not completed;
• appointment not scheduled;
• patient no-show;
• wrong collection location;
• specimen not received;
• insufficient quantity;
• hemolysis or other specimen issue;
• rejected specimen;
• recollection;
• partial result;
• delayed result;
• amended result;
• refund request;
• payment failure;
• result requiring urgent escalation.

These states should not live entirely in support tickets.

They should exist in the operating workflow.

Build one order-state model

Define every meaningful state from checkout to completion and determine:

• which system creates the state;
• which event changes it;
• whether the patient can see it;
• whether staff action is required;
• whether communication is triggered;
• how exceptions are resolved;
• whether the event is auditable.

CMS requires laboratories to follow applicable requirements around test requests, reporting, critical or alert values, and delays in reporting. For example, CLIA provisions cited by CMS require immediate notification to the appropriate party when a result indicates an imminent life-threatening condition or panic/alert value.

A DTC platform therefore cannot treat results release as simply sending an email that says “your results are ready.”

Clinical escalation requirements have to remain connected to laboratory policy and workflow.

9. Treat patient identity as core infrastructure

Consumer commerce makes identity more complicated, not less.

The person purchasing the test may need to become the patient attached to:

• an authorized laboratory order;
• a specimen;
• an accession;
• an official result;
• a longitudinal record.

The system needs a reliable way to maintain that relationship.

Common problems include:

• duplicate accounts;
• spelling differences;
• changed names;
• reused email addresses;
• dependents or minors;
• order records that do not match laboratory demographics;
• manually created accessions;
• results returned without a reliable consumer-account match.

The architecture should define identity matching before volume increases.

Authentication and authorization are different

Authentication answers:

Who is this person?

Authorization answers:

What is this person allowed to access or do?

A mature system should define both.

This becomes especially important when supporting caregivers, dependents, provider access, internal laboratory personnel, or multiple laboratory organizations.

10. Separate the official result from the consumer explanation

Traditional laboratory reports are designed primarily for clinical use.

Consumers often need a different presentation layer.

That does not mean changing the clinical result.

It means presenting authoritative laboratory data in a way that is easier to navigate and understand while maintaining a clear boundary between the official record and educational context.

HHS notes that individuals have rights to access health information under HIPAA when the laboratory is a covered entity, including completed laboratory reports, but HIPAA does not require a clinical laboratory to interpret those test results for the patient.

ADLM nevertheless recommends understandable result presentation and access to professional guidance because consumers may otherwise misinterpret normal or abnormal findings.

A modern consumer results experience can therefore include:

• official laboratory result;
• reference interval;
• clear high/low indicators;
• historical results;
• biomarker trends;
• plain-language education;
• limitations and context;
• appropriate next-step guidance;
• access to qualified professional support where appropriate.

The key principle is:

Enhance the understanding of the laboratory record without altering the laboratory record.

If AI-generated explanation is introduced, the same boundary should remain explicit. Educational or navigational output should not become the source of truth for clinical results.

11. Design for the second test, not just the first

A DTC laboratory can choose to operate like a one-time ecommerce business.

Or it can build a longitudinal relationship around laboratory data.

The second model can be strategically stronger because laboratory testing naturally produces structured measurements over time.

A consumer who returns can potentially see:

January → April → August

instead of three disconnected PDF reports.

That enables useful experiences such as:

• biomarker trends;
• previous-order comparison;
• repeat-testing reminders;
• program progress;
• persistent health profiles;
• personalized test discovery based on prior activity, where appropriate;
• memberships or recurring programs where the economics and clinical model support them.

The objective should not be to maximize testing frequency.

It should be to make legitimate repeat testing easier to understand and operate.

Retention begins with the first order

Repeat engagement is largely determined during the original experience.

If consumers encounter:

• confusing test descriptions;
• unexpected collection fees;
• difficult scheduling;
• unclear status;
• delayed support;
• unusable results;
• unclear next steps,

retention tactics will not repair the underlying problem.

The first-order workflow is the retention strategy.

12. Build an internal operating system, not just a patient portal

Every consumer action creates operational work somewhere.

A DTC program therefore requires tools for laboratory and support personnel.

Depending on the model, administrators may need to manage:

• catalog;
• pricing;
• promotions;
• geographic availability;
• provider authorization status;
• orders;
• collection locations;
• appointments;
• payment status;
• refunds;
• specimen exceptions;
• recollections;
• result status;
• customer support;
• user access and permissions;
• operational analytics.

One common failure mode is investing heavily in the patient-facing website while forcing the internal team to operate the program through disconnected vendor dashboards, spreadsheets, email, and manual reconciliation.

That architecture can work at very low volume.

It becomes increasingly expensive and fragile as the business grows.

Privacy, security, and data governance must be designed before production

Consumer-facing laboratory systems handle unusually sensitive information.

Privacy and security architecture should therefore be designed into the deployment rather than added after checkout is working.

The HIPAA Privacy Rule applies to covered health plans, clearinghouses, and healthcare providers that conduct certain electronic healthcare transactions. It establishes safeguards and limits around protected health information and grants individuals specific rights over their information.

Where a vendor performs functions for a covered entity that involve protected health information, HIPAA may require an appropriate business associate relationship and contractual safeguards. HHS describes business associates as entities performing certain functions or services involving PHI on behalf of covered entities and states that covered entities and business associates generally must enter into business associate contracts.

A DTC architecture should therefore establish:

• which entities are covered entities;
• which vendors are business associates;
• which systems hold PHI;
• minimum necessary data flows;
• encryption requirements;
• authentication;
• authorization;
• auditability;
• data retention;
• incident response;
• vendor responsibilities;
• patient rights workflows.

Do not use “HIPAA compliant” as a substitute for actual architecture and governance.

Compliance is deployment-specific and depends on the systems, contracts, processes, people, and responsibilities involved.

Do not build your 2026 strategy around outdated LDT assumptions

Laboratory-developed-test regulation changed materially after many DTC strategy articles were written.

FDA issued an LDT final rule in May 2024. A federal district court vacated that rule on March 31, 2025, and FDA subsequently issued a September 2025 final rule restoring the relevant regulatory text to its pre-2024 wording.

That history is important because older implementation guides may describe the vacated phaseout framework as though it were still in effect.

It is not.

At the same time, the vacatur should not be interpreted as eliminating the rest of the regulatory environment surrounding laboratory testing, test systems, state requirements, clinical claims, marketing, or laboratory quality.

Before adding a test to a consumer catalog, the laboratory should determine the regulatory status and requirements applicable to that specific test and use case.

Build vs. buy: three ways to create the DTC operating layer

Once the operating model is defined, the laboratory has three broad technology strategies.

These three strategies are examined side by side in the build vs. buy comparison for DTC laboratory platforms.

Option 1: Build internally

The laboratory develops the consumer commerce, identity, scheduling, workflows, integrations, results experience, administration, and ongoing product infrastructure itself.

Advantages

• maximum architectural control;
• full ownership of product decisions;
• highly specific workflows;
• no dependency on a core platform vendor.

Risks

• significant engineering requirement;
• ongoing maintenance burden;
• healthcare integration complexity;
• security and compliance overhead;
• slower time to market;
• risk of building a storefront while underestimating operational tooling.

Internal development is most appropriate when the laboratory has the capital, product leadership, engineering capacity, integration experience, and long-term commitment required to operate a software platform.

Option 2: Assemble multiple point solutions

The laboratory combines:

• ecommerce;
• scheduling;
• provider authorization;
• collection;
• identity;
• results;
• CRM;
• analytics;
• integrations.

Advantages

• best-of-breed components can be selected;
• individual systems may already be familiar;
• lower initial development requirement.

Risks

The laboratory itself becomes the systems integrator.

Every new vendor creates another:

• identity boundary;
• data flow;
• contract;
• support dependency;
• synchronization requirement;
• failure mode.

The point-solution model can work, but the integration and operational burden should be priced into the decision.

Option 3: Use a laboratory consumer platform

A dedicated platform provides the shared consumer and workflow layer while connecting to existing laboratory infrastructure.

The laboratory continues to own the clinical operation.

The platform handles the consumer operating layer.

This is the model Solia Direct is designed around: consumer commerce, scheduling and collection, patient accounts, workflow orchestration, results and longitudinal health, intelligence, and administration can sit above existing LIS/LIMS, payments, scheduling, collection, and clinical systems.

The trade-off is that the laboratory must evaluate the platform's architecture, configurability, integrations, security model, implementation approach, and long-term economics rather than assuming every platform fits every laboratory.

A practical DTC launch roadmap

The safest way to launch is usually progressive.

Phase 1: Strategy and readiness

Define:

• business model;
• target patient;
• geographic market;
• initial catalog;
• ordering model;
• collection model;
• pricing;
• internal ownership;
• technology architecture;
• compliance requirements;
• success metrics.

Do not begin by designing the homepage.

Phase 2: Workflow mapping

Map the full lifecycle:

Discover → purchase → authorize → schedule → collect → accession → test → release → understand → follow up

Then map the exception states.

Document which system and team owns each stage.

Phase 3: Integration

Connect the systems required for the initial launch.

Prioritize the smallest production architecture capable of supporting the full workflow reliably.

Avoid integrating systems simply because they may be useful someday.

Phase 4: Consumer experience

Build:

• catalog;
• test pages;
• account creation;
• checkout;
• location and collection selection;
• preparation;
• order tracking;
• results;
• support.

Validate the complete experience on mobile.

A large portion of consumer interaction will occur through a phone even if laboratory operations remain desktop-centric.

Phase 5: Operational testing

Before public launch, run real workflow simulations.

Test scenarios including:

• successful order;
• failed payment;
• physician authorization;
• no-show;
• rejected specimen;
• recollection;
• delayed testing;
• partial results;
• amended results;
• critical result;
• refund;
• duplicate patient;
• support escalation.

A DTC platform is ready when the exceptions work, not merely when the demo path works.

Phase 6: Controlled launch

Start with a deliberate scope.

For example:

• limited geography;
• selected catalog;
• known collection coverage;
• controlled acquisition;
• staffed support.

Measure operational failures before scaling traffic.

Do not spend heavily on acquisition to discover that the collection or fulfillment workflow is broken.

Phase 7: Optimize and expand

Once the initial system is stable, evaluate:

• additional tests;
• additional states;
• collection expansion;
• repeat-testing programs;
• memberships;
• employer or partner channels;
• provider functionality;
• longitudinal engagement;
• automation;
• operational intelligence.

Scale the model that works rather than launching every possible feature simultaneously.

The metrics that actually matter

Traffic alone is not a useful measure of DTC success.

A laboratory should understand the complete funnel.

Acquisition

• qualified traffic;
• acquisition cost;
• branded versus non-branded demand.

Commerce

• product-view-to-cart rate;
• checkout conversion;
• average order value;
• payment failure;
• refunds.

Collection

• scheduling completion;
• time to collection;
• no-show rate;
• specimen rejection;
• recollection.

Laboratory workflow

• successful accession rate;
• turnaround time;
• exception rate;
• delayed-result rate.

Patient experience

• result-access rate;
• support volume;
• satisfaction;
• repeat-testing behavior.

Economics

• contribution margin by test/panel;
• contribution after acquisition;
• repeat purchase rate;
• lifetime gross contribution;
• operational cost per order.

The objective is not simply to generate more orders.

It is to generate profitable, operationally reliable laboratory volume while building a durable consumer relationship.

Common mistakes laboratories make when launching DTC

Mistake 1: Treating DTC as ecommerce

Generic ecommerce can process a payment.

It does not inherently understand:

• laboratory orders;
• authorized ordering parties;
• specimens;
• accessions;
• collection;
• requisitions;
• results;
• critical values;
• patient identity;
• recollections.

Commerce is one component of the operating model.

Mistake 2: Launching too much catalog

A huge catalog creates:

• decision complexity for consumers;
• more regulatory variation;
• more collection requirements;
• more result-support complexity;
• more operational exceptions.

A focused catalog is easier to explain, operate, measure, and expand.

Mistake 3: Solving the consumer experience but ignoring operations

The patient sees one website.

Staff may see five vendor dashboards and a spreadsheet.

That is not a unified platform.

Map internal workflows with the same care as consumer UX.

Mistake 4: Hard-coding regulatory rules into marketing copy

Geographic and ordering requirements change.

Eligibility should be represented as structured configuration wherever possible so the system can control availability and workflows without requiring a complete product redesign.

Mistake 5: Treating the PDF report as the end of the relationship

The laboratory result is the clinical output.

It does not have to be the end of the customer experience.

Longitudinal visualization, education, history, and appropriate repeat-testing workflows can make laboratory data considerably more useful over time.

Mistake 6: Scaling acquisition before validating fulfillment

More traffic amplifies whatever already exists.

If the workflow is efficient, traffic creates growth.

If the workflow is broken, traffic creates support tickets, refunds, recollections, and reputational damage.

Validate operations first.

Is your laboratory ready to launch direct-to-consumer testing?

A laboratory is substantially closer to launch readiness when it can answer yes to these questions:

• We know exactly which consumers we want to serve.
• We have selected an initial DTC catalog.
• We have validated the ordering model for our launch jurisdictions.
• We know where provider authorization is required.
• We understand applicable laboratory licensure requirements.
• We know how every offered specimen will be collected.
• We have defined our pricing and contribution economics.
• Every consumer product maps to a laboratory test or panel.
• We know how orders reach the LIS/LIMS.
• We know how patients map to laboratory records.
• We have defined the complete specimen lifecycle.
• We have designed exception and recollection workflows.
• Official results remain authoritative in the laboratory system.
• We have defined how consumers securely receive results.
• Critical and urgent result workflows remain connected to laboratory policy.
• We know which systems and vendors will handle PHI.
• We have defined internal operational ownership.
• We know what success will be measured against.
• We have tested failure states, not just the successful order path.

If several of these answers are still unclear, the laboratory probably needs an architecture and workflow phase before a public DTC launch.

Where Solia Direct fits

Established laboratories already possess the hardest piece of the model:

the infrastructure that actually performs laboratory testing.

Solia Direct is designed to provide the consumer operating layer around that infrastructure.

The platform connects:

Consumer Commerce
→ Scheduling & Collection
→ Patient Accounts
→ Workflow Orchestration
→ Results & Longitudinal Health
→ Intelligence
→ Admin & Operations

to the LIS/LIMS, laboratory APIs, payments, scheduling, collection networks, and other systems already in operation.

The goal is not to replace the laboratory.

It is to make the laboratory capable of operating a modern consumer channel under its own brand, catalog, pricing, workflows, and customer relationship.