The Waiting Economy of Fertility Treatment

This essay was originally published in Fertility Intelligence, Fertiligent™'s newsletter on the demographics, science, and economics shaping how we build families. It is reproduced here in full.

What patients actually live

The public imagines fertility treatment as a sequence of medical events: appointments, bloodwork, ultrasounds, retrievals, transfers. The brochures reinforce that picture. So do the consent forms. So does the way most clinicians describe the process when they talk to the press.

Patients live something else. They live in the gaps between those events — waiting for follicles to grow, waiting for fertilization reports, waiting through the two-week wait, waiting for the beta-hCG call that decides whether another month of physical, financial, and emotional investment moved the outcome at all.

The visible part of fertility treatment, the part the system is built around, accounts for a small fraction of the patient's time and almost none of the cognitive load. The rest happens in unresolved space, alone, between appointments. This is the part the system has not seriously priced.

Jacqueline Boivin and Deborah Lancastle quantified the asymmetry directly: anxiety levels in the last seven days of the two-week wait are significantly higher than in the last seven days of stimulation — when patients are actively injecting hormones, attending monitoring visits, and undergoing egg retrieval.¹ The most clinically demanding phase of an IVF cycle is not where patients suffer most. The waiting is.

The hidden architecture

Modern medicine is organized around diagnosis and intervention: a linear path from problem to resolution. Fertility care does not fit that architecture. It is cyclical, probabilistic, and fundamentally delayed. A strong scan can be followed by disappointing labs. Excellent fertilization can yield poor embryo quality. A successful transfer can still end in silence. Progress arrives in fragments, and the fragments contradict each other. The emotional journey is non-linear because the information flow is non-linear.

Daniel Grupe and Jack Nitschke established two decades ago what every fertility patient already knows: chronic uncertainty is more corrosive to the nervous system than clear negative outcomes.² A "no" allows grief, recovery, and the resumption of agency. A "maybe" — held for fourteen days, then thirty, then ninety — does none of those things. It runs simulations. It scans portal messages. It searches forums at 3 a.m. It re-reads the wording of a nurse's note for the third time, looking for signal that was never encoded there to begin with.

Patients, in other words, are not being irrational. They are extracting what they can from an information vacuum the system did not deliberately build but has not bothered to fix.

The work of Alice Domar at Harvard Medical School and the Domar Center has been the most important and most under-applied body of research in this space for thirty-five years. Her 1992 cohort found that 37% of women presenting for infertility treatment met the threshold for clinically significant depressive symptoms — roughly twice the rate of fertile controls.³ A 2025 meta-analysis pooling more than a dozen studies put the prevalence of clinically significant anxiety in infertile women at 41% and depression at 42%.⁴ Distress at this level is comparable to that reported by patients managing cancer, HIV, and chronic cardiac disease.

Reproductive medicine has, in the privacy of its own literature, conceded the point. It is running one of the highest-distress care experiences in modern healthcare. It has not yet built the operating model that fact requires.

The cost of unmanaged uncertainty

This is not only a humanitarian story. It is a measurable economic one. Pierre Troude and colleagues, working with five thousand French couples whose first IVF cycle failed, found that 26% of couples discontinued treatment immediately after the first failed cycle.⁵ Subsequent point-of-failure work raised the figure to 35% after a second failed cycle.⁶ Many of those patients had remaining covered cycles, remaining medical odds, and remaining desire to have a child. They left the system anyway, and the dominant reasons cited in the discontinuation literature are not medical or financial. They are psychological — the burden of repeated, unsupported uncertainty.

At the same time, patients who stay in treatment routinely pay for clinical add-ons that the evidence does not support. Sarah Lensen's national survey of 1,590 Australian IVF patients found that 82% used at least one add-on, and 72% paid extra for it, despite the fact that most of these treatments — endometrial scratching, immunological infusions, particular assays — have no high-quality randomized evidence of improving live birth rates.⁷ More than 70% of fertility clinics worldwide offer at least one add-on at additional cost.⁸ The honest read is not that patients are gullible. It is that they are buying the only thing the system actually sells in the gap between cycles: the feeling that something is being done.

The cost of unmanaged uncertainty is measured in cycles abandoned, in dollars spent on procedures that will not move the outcome, and in births that do not happen. Domar's own randomized trial of cognitive-behavioral group support during IVF, published in Fertility and Sterility in 2000, reported viable pregnancy rates of 55% in the CBT arm against 20% in the no-treatment control.⁹ Few interventions in reproductive medicine produce a delta of that size. None of the ones that do are technological.

The system has been pricing the wrong inputs.

The strongest counter, and why it falls short

Some clinicians, in good faith, believe the silence between events is itself part of the treatment. The reasoning is that constant contact would over-medicalize a process that is already psychologically loaded, that nurses are not therapists, and that some uncertainty is intrinsic to fertility biology in a way no software can dissolve.

The first half of that argument is real. Aggressive engagement that adds noise — scripted check-ins, vibration, marketing dressed as care — can absolutely make the patient experience worse. The second half is not. The biological uncertainty is fixed; the informational uncertainty around it is mostly an artifact of how the system is built.

Patients are not asking to know whether the embryo will implant. They are asking to understand what the lab report says, what the next step is, what their numbers mean relative to others at their age, and whether the symptom they are noticing is normal. Almost all of that is answerable. Most of it is not being answered, because the human capacity to do so does not exist at the scale the demand requires.

The choice is not between silence and over-medicalization. It is between unsupported waiting and supported waiting. The current default is the first only because the second has, until very recently, not been technologically feasible at population scale.

Clinical infrastructure has outpaced human infrastructure

Fertility medicine has spent two decades building extraordinary clinical capability — preimplantation genetic testing, time-lapse embryology, AI-assisted embryo grading, ever-more-precise hormonal protocols. The lab is unrecognizable from the one that produced the first IVF babies. The patient experience around it is not.

The clinical infrastructure has evolved faster than the human infrastructure surrounding it. A fertility patient in 2026 generates and receives an order of magnitude more data than a patient at the same stage in 2006 — and still navigates that data through fragmented portal messages, voicemail, and the gap between a twelve-minute consultation and the next one three weeks out. The gap between scientific capability and emotional experience has widened, not narrowed, with every advance.

This is what the most forward-looking clinics are starting to fix. The model that wins the next decade is not the clinic that runs the best lab. It is the clinic that runs the best continuous coordination system around the lab — the layer where expectation management, information synthesis, longitudinal context, and emotional support actually happen at scale, between the visits rather than only inside them.

Intelligence at the edge

In the previous issue of this newsletter, I argued that the wealth of nations in the twenty first century will be rebuilt by intelligence pushed to the edge of the reproductive journey — into the exam room, into the clinic workflow, into the patient's pocket at midnight. The waiting economy is where that argument becomes operational.

The opportunity in fertility medicine is not generating more data. The lab already produces more than the human side of the system can absorb. The opportunity is reducing the psychological cost of the data the system already has — translating it into language patients can use, surfacing it at the moments that matter, and absorbing the cognitive load that today drives roughly one in three patients out of treatment before their medical odds run out.

Medically, fertility treatment is a biological process. Structurally, it is an exercise in helping people live inside unresolved probabilities for months or years without breaking. In an era when desired fertility continues to outpace actual fertility across the developed world, the gap between intention and outcome will increasingly be closed — or not — by the systems we build for the waiting itself. That is the work. It is also, I suspect, the place in this industry where the next decade of compounding actually happens.

— Sergei

Sources and citations

1. Boivin, J. & Lancastle, D., "Medical waiting periods: imminence, emotions and coping," Women's Health (2010); cited in Gameiro et al., "Why do patients discontinue fertility treatment? A systematic review of reasons and predictors of discontinuation in fertility treatment," Human Reproduction Update (2012).
2. Grupe, D.W. & Nitschke, J.B., "Uncertainty and anticipation in anxiety: an integrated neurobiological and psychological perspective," Nature Reviews Neuroscience (2013).
3. Domar, A.D., Broome, A., Zuttermeister, P.C., Seibel, M., Friedman, R., "The prevalence and predictability of depression in infertile women," Fertility and Sterility (1992).
4. "Prevalence and risk factors of negative emotions in infertile women: a systematic review and meta-analysis," 2025; pooled prevalence: anxiety 41% (95% CI 0.35–0.47), depression 42% (95% CI 0.36–0.48).
5. Troude, P. et al., "Medical factors associated with early IVF discontinuation," Reproductive BioMedicine Online (2014); cohort of 5,135 French couples, 26% discontinuation after first failed cycle.
6. Bedrick, B.S. et al., "Point of failure as a predictor of in vitro fertilization treatment discontinuation"; 24% discontinuation after cycle 1, 35% after cycle 2.
7. Lensen, S. et al., "How common is add-on use and how do patients decide whether to use them? A national survey of IVF patients," ESHRE 37th Annual Meeting (2021); n = 1,590 Australian IVF patients, 82% used at least one add-on, 72% incurred additional cost.
8. Armstrong, S.C. et al., "VALUE study: a protocol for a qualitative semi-structured interview study of IVF add-ons use by patients, clinicians and embryologists in the UK and Australia," BMJ Open (2021); over 70% of fertility clinics provide at least one add-on.
9. Domar, A.D., Clapp, D., Slawsby, E.A., Dusek, J., Kessel, B., Freizinger, M., "Impact of group psychological interventions on pregnancy rates in infertile women," Fertility and Sterility (2000); viable pregnancy rates 55% (CBT) vs 54% (support) vs 20% (control).

See it in action: Try Eva, the patient companion — built for the support between visits — or talk to our team about bringing it to your clinic.

Related:

• The Wealth of Nations Was Always a Fertility Story
• Fertility Data Sovereignty: The Most Sensitive Data in Medicine Meets the Least Sovereign Infrastructure
• Breaking the Silence: Why Emotional Support Matters in Fertility Care

Sergei Gorlovetsky, CEO, Fertiligent