Entrepreneurship In Reproductive Medicine 2: Why We Need More Tech In High Tech Reproduction

(Part 1 of this series provided an overview of the reproductive medicine industry.)

Years ago my fund owned a large position in IVF practice management company Integramed, a public company at the time. My thesis was based on the upside potential for the company’s shared risk program, which offered multiple IVF cycles for a single upfront payment larger than that of a single cycle, with a refund of part of the payment if the couple or patient ultimately failed to conceive and deliver. I felt the program could be greatly expanded and be both very profitable for the company and help many more couples access care at lower financial risk.

At the time of our investment the shared risk program was used in a relatively small percentage of cases. The problem, as I saw it, was that the entry criteria for the program were too stringent, seemed arbitrary and not evidence-based, and that the only people allowed access to it likely didn’t need it in the first place. The program would end up charging more to patients or couples likely to conceive quickly than it would pay back those for whom the procedure did not work.

The Integramed network at the time accounted for a large percentage of all the IVF performed in the United States at the time. This footprint gave the company access to a huge database of actuarial data, information that could have been studied to much more precisely analyze the combination of inputs that would in turn predict cycle outcomes for individual patients and couples.


Which in turn would have enabled a rationally-designed payment plan that solved for the simultaneous goals of good outcome for patients and improved risk management for both the patient and the IVF program.

Which in turn would have attracted more patients, provided incentives to more IVF programs to join the Integramed network, and been a catalyst for growth for the company.


To the best of my knowledge, my ideas went no further than the “listen politely to your investor” stage.

Fast forward to 2018, and the opportunities to use data to improve access to IVF, improve outcomes, better define and allocate financial risk between patients and providers and motivate investment into laboratory capacity and program throughput are even more substantial. Except this time, industry is listening. Indeed, several of the panelists from the Columbia Business School Business Of Reproductive Medicine program last week are actively involved in implementing this idea.

Alan Copperman, for example, serves as medical director of Progyny, a fertility benefits company that designs and implements employee-based coverage for assisted reproduction, giving businesses the option of offering egg freezing and IVF as an employee benefit, by applying extensive domain knowledge and real actuarial data analysis to the rational design of programs that will be accessed, be successful, and be cost-effective. (disclosure: I serve as a member of the Progyny medical advisory board.) Similarly, Mylene Yao’s company Univfy analyzes an enormous amount of patient and clinic specific information to provide far more precise predictive data, that both patients and clinics can use to make rational decisions as to how to triage their resources.

When I was a practicing reproductive endocrinologist, I recognized that patients had very little objective data on which to base their expectations of success going into IVF. Faced with $20,000 or more and a month or more of what a patient called “the unpleasant extra job of being an IVF patient,” they found that the CDC Fertility Clinics Success Rates report was much better at population statistics than at individual predictions. Patients deserved then, and deserve now, more accuracy than multi-year age grouped, imprecisely defined diagnostic-grouped percentage outcomes offered.

Data aggregation and interpretation, predictive analytics and support for rational decision-making at the provider, payor and patient level represent a tiny fraction of the benefits of more sophisticated use of information technology in the efficient and cost-effective delivery of care in reproductive medicine.

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