Work

Five products and the lessons I still use

These case studies follow my career, and each turned on who would carry the work: ownership of a hospital’s install after go-live, approval for a physician’s own phone line, the attention of a frightened family, accountability for a nurse’s queue, and who pays. The lessons still shape how I build products.

  • 100+ organizations in federal quality reporting Epic — the quality-reporting curriculum and escalation path I ran for its clients
  • 300,000+ calls on an average workday Doximity Dialer, which I originated — Doximity’s figure, February 2026
  • 30 million annual visitors CancerCompass — I directed digital products
  1. Epic

    2012–2013

    01 Decided by ownership

    After the software is installed

    Outcome An account at risk of cancelling became a reference account, a 134-year-old health system took its MyChart patient portal and EpicCare Link live, and all eight client organizations were still reporting on the federal quality programs when I left.

    The rule I kept Deployment is the start of the obligation, not the end of it. Name the trigger, the owner, and the notification before the problem arrives.

    MyChart as Epic presents it today. The version I took live for the research hospital was the 2012–13 one.
  2. Doximity

    2013–2017

    02 Decided by approval

    The patient sees the office, not the cell phone

    Outcome Dialer still carries more than 300,000 calls on an average workday across 250+ hospitals and health systems, 9 years after I left.

    The rule I kept Adoption may come before official approval only while the risk stays with the person choosing. When the risk is clinical, approval comes first.

    The identity decision in the product’s own words: the clinician picks which number the patient sees, with the office line preselected.
  3. CancerCompass / CTCA

    2019–2021

    03 Decided by attention

    Scaling oncology navigation for 30 million annual visitors

    Outcome Chat conversions up 267% and bounce rate down 25% across 30 million annual visitors after the rebuild I led.

    The rule I kept A frightened person is not short of information. The scarce resource is attention and trust, so the product’s job is the next step and a person to call.

    The homepage in July 2019, as the Wayback Machine archived it: the article-and-message-board site my rebuild replaced.
  4. Transcarent

    2021–2022

    04 Decided by accountability

    Four specialty programs on one routing architecture

    Outcome Routing delays stopped being the primary bottleneck, and the gap between the best and worst service lines narrowed.

    The rule I kept One system can carry many programs once every decision point has a named owner.

    Surgery high-complexity own protocols Oncology high-complexity own protocols Behavioral Health high-complexity own protocols Urgent care lower-complexity own protocols four programs, one architecture Shared routing role-based routing rules tied to clinical accountability every case assigned to a named clinical role Unified member record nurse and navigator working from the same facts Behind it exception handling · escalation protocols · real-time exception dashboards
    The shared decision architecture, drawn from the case study rather than from a surviving document: four programs with four sets of protocols enter one routing layer, and the layer assigns each case to a clinical role. The alternative on the table was four products, one per lane. The record beneath is what let a nurse and a navigator see the same case.
  5. Andwise

    2022–2024

    05 Decided by who pays

    Reading the contract before the physician signed it

    Outcome 1,200+ physician users; sustained engagement and funding fell short. I wound it down in 2024.

    The rule I kept Who pays decides who the product works for. Sign-ups show people want it; they do not settle that.

    The Contract Analyzer as specified in January 2023. This is the design artifact, not a screenshot of a live analysis — the document body is placeholder text.

Two of them carry straight into what I build now. Ambit applies the approval rule to AI agents, whose risk is not the user’s alone: an agent’s autonomy grows one authorized action at a time. NextConsensus applies the ownership rule to medical evidence: it keeps watching a guideline after publication, for the point where the evidence moves past it.

Continued Current work Ambit, NextConsensus, and the active systems

Revised