Brijesh Patel

I lead product and ship code.

I lead product and engineering through healthcare deployments, working directly with partner executive sponsors and their strategy, clinical, operations, and IT teams to define the problem, set the scope, and put the product into use.

Working alongside the team, I build high-fidelity prototypes, contribute frontend and backend code, and create tools we can reuse across engagements.

At Pyx Health, I led product, engineering, and data science for an AI platform deployed across 25+ health plans during my tenure. Earlier, I co-founded InquisitHealth, which Pyx acquired.

Explore the work

Now

  • Enterprise behavioral health
  • Partner strategy, operations, clinical, and IT
  • Clinician product pod
  • Frontend and backend code

A group scribe for in-person care

Partner need
One of the largest behavioral health companies needed a way to document in-person group sessions. The project was behind schedule, and the team still had to work out a process clinicians could use.
Strategy
Resolve the clinical workflow early enough to deliver under deadline. I made clinician feedback the starting point, working through the full path from attendance to EHR submission.
Execution
I built the prototype in one week, embedded Pinflow, and iterated with in-house clinicians. I set the scope and roadmap, led product and engineering through delivery, and contributed frontend and backend code. The scribe let clinicians attribute important utterances, review individual notes, and submit them to the EHR. A coding agent helped port a substantial portion of the prototype’s frontend into the product. The team delivered it in one month.
Outcome
The scribe launched across multiple sites. Solving the documentation problem opened a conversation about a patient app the partner had initially declined.

Group scribe

An ambient scribe that captures a group therapy session and drafts one note per patient for the clinician to review and sign before it reaches the EHR.

  • Clinician platform, behavioral health
  • In-person and virtual groups
  • Deployed across multiple sites

Make the next release easier for the team

I built the workflow our coding agents use, including codebase conventions, design guidance, and review rules. Engineers and agents worked from shared product specifications and prototype screens.

Roster and record

Create the group session

Map utterances

Attribute who said what

Lock and sign

Finish the notes

A three-screen group-scribe workflow, built by a frontend engineer from shared specifications and prototype screens. This timing covers the frontend; the month above covers the full release. Delivery included code review, automated checks, user acceptance testing, and a feature flag.
Frontend workflow: under three days. Previous comparable: more than two weeks.
How the prototype carried into engineering

I walked internal clinicians through the prototype, collected their feedback with Pinflow, and iterated on the workflow. JavaScript facades stood in for live integrations, so we could test with realistic data and make things fail on purpose.

We tested logic and edge cases in the prototype, including a workspace with 50 records instead of five. The product spec captured those decisions, and product and engineering used it through implementation and user acceptance testing.

Live use still turned up differences across devices and working habits. We kept collecting feedback and refining after launch.

The engineering workflow draws on Addy Osmani’s open-source agent skills, adapted to the team’s system.

Now

  • Enterprise behavioral health
  • A separate partner
  • Clinician and patient workflows
  • Frontend and backend code

Give clinicians and patients a reason to use Sage

Partner need
At another large behavioral health company, clinicians weren’t inviting patients into Sage, the clinician and patient platform. They couldn’t see enough value for their patients and worried that monitoring safety events would add to their workload.
Strategy
Give clinicians a reason to invite patients by connecting what happens in session to care between visits. The experience had to be useful to both clinician and patient.
Execution
I brought the product team’s ideas into a working prototype, set the scope and roadmap, and worked with clinicians to refine it. I led product and engineering through delivery and contributed frontend and backend code. After signing a note, clinicians could recommend an activity and see completed activities and patient progress in Sage.
Outcome
In the next clinician onboarding cohort, app activation reached 48%, compared with a 24% average across prior cohorts. Activation meant downloading the app and completing the “getting to know you” onboarding.

Clinician review loop

Shows a clinician-reviewed next step reaching a patient and the patient’s response returning before the next visit.

  • Clinician platform
  • Patient experience
  • EHR workflow reconstruction

From the signed note to the next visit

To explore connected workflows with partners, I built an integration lab, using screenshots and videos to guide AI-assisted reconstructions of EHR interfaces. The lab let our product team show how a clinician’s decision could reach a patient and return before the next visit.

This is an independently written portfolio reconstruction with fictional records. Start the guide to follow one individual next step. Expand EHR opens the full chart and demo studio; use Scene settings to try another story.

A little space before saying yes
  1. 01Review evidence
  2. 02Approve the next step
  3. 03Bring the response back
01Start with the visit42 SEC · NO SOUND NEEDED
Jordan LeeClinician

I’m in athenaOne, starting with Taylor’s visit and the existing chart.

Real workflow patterns · Fictional records
Clinician in athenaOne
athenaOneclinical workspacePatient search
TR
Taylor Reed34 years · MRN 10428Patient chart · Active encounter
Individual follow-upJordan Lee, LCSWOctober 12, 2026 · In progress
In roomReviewHPIROSPEA/PSign-off
Patient chart / Encounter review

Encounter review

10/12/2026 · 09:00
Visit information
Visit type
Individual follow-up
Provider
Jordan Lee, LCSW
Visit focus
A little space before saying yes
Follow-up
October 19, 2026
Encounter documents1 document
Next encounter: Oct 19Patient context available to connected apps
Taylor Reed · Encounter 10/12/2026athenaOne workflow simulation
Patient’s phone
9:41
your spaceHi, Taylor.Your care, between conversations.
MONDAY, OCTOBER 12
AFTER YOUR VISIT

Good things take a little practice.

Your clinician is putting together a next step for you. It will be here when it’s ready.

Being thoughtfully prepared
YOUR NEXT CONVERSATIONMonday, October 19With Jordan Lee

Small steps count.
You don’t have to have it all figured out.

HomeYour next step
Open the chart around the app.Visit history, note previews, encounter context. Your current run comes with you.
Built to simulate the EHR around the product.Switch Oracle Health and athena workflows. Set a story, then play it.

2024 to 2026

  • Pyx Health
  • Applied AI: product, engineering, and data science
  • Data engineering and machine learning

Resolve the barrier behind the referral

A referral can be opened without helping the person who received it. At Pyx Health, I led the team that built an AI platform to find what stood in the way and connect members with support.

Partner need
Health plans needed to close gaps in care. Pyx also needed a more affordable way to support members than relying on people to make every call.
Strategy
Build around the barriers keeping members from getting care. Use AI to support more members through the app, reserve human outreach for those who need it, and tie food-box incentives to an activity that helps address a care gap.
Execution
I worked with health plans to understand their members’ needs and share early prototypes. I led product, engineering, and data science in building the Continuous Activation Platform. The system connected members with support; callers followed up on whether their barriers were resolved, and those outcomes informed future recommendations.
Outcome
The platform reached 25+ health plans during my tenure. More members engaged through the app, reducing call-center outreach and the cost of support.

Continuous Activation Platform

An AI platform that works out what is keeping a member from acting on a referral, matches them with support, and follows up on whether they got it.

  • Pyx Health
  • Dozens of health plans
  • Text conversations in English and Spanish

A completed task counts as progress, but the case stays open until we know whether the member got help. The outcome informs future recommendations.

Start from what the member has already shared

The system uses the need on file, such as an unused referral, plus ninety days of care-coordinator notes, prior conversations, and recorded social needs. That context helps it choose a response that fits the member’s circumstances.

Where the system stops and a person starts

The system chooses what to say, when to say it, and how much support to offer. A policy gate checks each message for clinical advice and protected information before delivery. I kept benefit enrollment with a human navigator: the agent identifies the need and routes the request, then waits. Members below the readiness threshold also go to a person.

Decide what is ready to ship

Offline tests and live guardrails covered quality, safety, latency, and cost, backed by audit logs. We made a weekly go or no-go decision for each release and judged routing by whether the member’s barrier resolved.

A member may know where the food pantry is and still have no way to get there. Answer for a fictional member and watch the routing change.

  1. 09:14

    A referral goes unused

    A member has not acted on a food referral. Her coordinator’s notes mention cut hours and no car. The agent’s first message starts from those facts, in Spanish, after a policy check.

  2. 11:52

    She answers three questions

    Answer for her. Each choice maps to a defined value; the system does not need to interpret a free-text answer.

    When it comes to food, what feels like the biggest challenge right now?

    If I shared the steps for the next thing to do, how comfortable would you feel doing it on your own?

    Do you have a phone or computer you could use to get it done?

    Readiness, as recorded

    Can she do it65%
    Can she get to it40%
    Does she want to80%

    Lowest score 40%. Guided, resources with follow-up.

    The marks on each bar: under 30% a person takes over; under 50%, guided.

  3. 11:52

    A navigator books the ride

    The resource she needs is a ride, and the ride comes through a plan benefit that requires enrollment. I kept enrollment with a human navigator, so the agent routes the request and waits.

    The text she receives

    Thank you. Your plan can cover a ride to the food pantry. A navigator is setting it up and will text you the pickup time today. I’ll check in Thursday to see how it went.

    pass message policy: tone, clinical-advice and privacy checksrefused a ride requires a person

  4. 15:07

    The outcome stays open

    The ride is booked. Food access is still pending, so the system keeps tracking it.

Build the data foundation behind the conversation

I built high-throughput ETL and ELT pipelines for large incoming datasets, including AI-assisted header parsing. I also built the platform’s HIPAA-compliant cloud infrastructure on Azure.

Read the full run, annotated
09:14:02
care_gap.detectedsource plan CRM sync · type food_insecurity · member D. Morales, 58, es-US
Outreach starts from a recorded care gap, such as the unused food referral in this example. That recorded need sets the scope of the outreach.
09:14:03
context.retrievecare-coordinator transcripts 90d · prior conversations 2 · social needs hours cut, no car
The first message mentions her cut hours and the missing car. The context comes from ninety days of coordinator notes.
09:14:05
policy.gatepassscope food_insecurity · clinical_advice deny · phi_egress deny · tone checked
Every generated message clears a policy gate before the member can see it. The gate checks tone and blocks messages that violate its clinical-advice or privacy rules.
09:14:06
message.sendchannel sms · locale es-US · length 212 chars
Every message is available in English and Spanish. Both language versions are required before release.
11:52:40
member.replystage barrier_probe · choice 3 of 5 · → barrier transport_to_pantry
Members reply by picking one of three to five choices instead of typing. Each choice maps to a defined barrier, so the system does not need to interpret a free-text response.
11:52:41
comb.scorecapability 0.65 · opportunity 0.40 · motivation 0.80 · → min 0.40 · → tier guided
Three scores assess what she can do, what she can access, and whether she wants to act. The lowest score determines the support level. Below 0.30, a person takes over.
11:52:41
tactic.selectrefusedrequested schedule_ride_via_benefit · reason benefit_enrollment requires human→ escalate.human · navigator queue · SLA 4h · agent waits
I kept benefit enrollment with a navigator. The agent can identify the need and route the request, then must wait. The navigator queue has a four-hour response target.
15:07:12
outcome.captureopen 30 daysviewed yes · engaged yes · task_done ride booked · resolved pending
The ride is booked; the food-access outcome is still pending. Barrier resolution carries more weight than a message view in the reward used to train future decisions.

Fictional member data. In the recorded run, one check passed and one was refused.

2012 to 2024

  • InquisitHealth
  • Co-founder, CTO and CPO
  • 12-person product and engineering team
  • $5M ARR, acquired by Pyx Health

A peer coaching platform that reached 50,000 members

I co-founded InquisitHealth to pair people managing a chronic condition with trained peers who had lived with it.

The need
Peers needed a way to deliver evidence-based support and arrange follow-up while staying focused on their conversations with members.
Strategy
Bring a member’s history, a call guide, and care actions into one workspace, so peers could act on what came up during a conversation.
Execution
I led product and engineering to build the platform for outreach, matching, peer coaching, and care coordination. In Peer Copilot, a peer could review open issues, follow a guide, and arrange support during a call.
Outcome
The platform served more than 50,000 members, and the business reached $5M ARR before its acquisition by Pyx Health.

Peer Platform

The system behind InquisitHealth’s peer coaching. It found and matched members, guided peers through every call, and coordinated care afterward. Peer Copilot, the call workspace, was one feature of it.

  • InquisitHealth
  • More than 50,000 members
  • Peers, members, and care teams

The call clock starts with her first answer.

R. Okafor

  • 61, type 2 diabetes
  • A1c 8.4 in March, down from 9.1
  • Peer since January, 6 calls

Last call: gas bill was past due; she planned to call the utility.

Open issues

Housing guide

“Last time you mentioned the gas bill. Where does that stand now?”

What she said

Saves as you type

Care actions

Actions appear here as the conversation surfaces them. Taking one adds it to the checklist.

Post-call checklist

Empty until the peer takes a care action.

Notes, linked to issues

Each note carries the issue it belongs to.

A fictional member with three open issues. Pick one, follow the guide, and record what she says; number keys pick her answer. End the call for a summary you can copy.

I built the HIPAA-compliant cloud infrastructure on AWS that supported the platform.

1.71 percentage points average reduction in HbA1c, a measure of blood sugar, among participants with diabetes. A published evaluation of InquisitHealth’s remote diabetes program at Montefiore found this change among the 179 participants with HbA1c results from before and after the program. It was a before-and-after comparison with no control group.

JAMIA · Published study

The platform grew to include care coordination, operations, and content management before Pyx Health acquired InquisitHealth in 2024. I led the product and technical integration into Pyx Health afterward.

v1.1

  • Independent
  • Open source, MIT
  • Running on this site

Feedback with enough context to act on

Pinflow

A feedback tool I built to attach a comment to a page element and export it with the context a coding agent needs to act on it.

  • npm package pinflowjs, v1.1
  • MIT license
  • Installs with one script tag
Pinflow’s feedback editor attached to text on this portfolio, with comment and export controls
Feedback attached to the element being discussed

Option/Alt-click any element, or press and hold on a phone, to leave a note. The comment, the element, and the surrounding page travel together to the agent.

Background

Before InquisitHealth, I worked in healthcare digital strategy, enterprise data engineering, and product management. I have been a co-investigator on research funded through the NIH Small Business Innovation Research (SBIR) program.

A LEGO WeDo robot with a motor, wheels, and a motion sensor

I run Bricks & Motors, after-school LEGO robotics and STEM classes for elementary-aged children in northern New Jersey, Rockland County, and southern Connecticut.

Bricks & Motors