Fertility clinic pricing strategies enter a new era with assistance from AI company
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With the prominence of sophisticated artificial intelligence (AI) systems like AIVF’s EMA progressing the fertility industry from standardization to personalization, fertility clinics can shift to a “pay for baby model” over the traditional “pay per treatment” pricing structure.
Today’s fertility industry has struggled to keep up with treatment demands. In the US, clinics are only serving 20% of the need for IVF, leaving 80% of patients giving up on starting the process of having a child, Daniella Gilboa, CEO and co-founder of AIVF, conveyed.
However, as AI-powered scoring systems, such as AIVF’s EMA, lower uncertainties, expedite embryo evaluation, and provide clear, accurate information, clinics now have the potential to meet this demand. Clinics utilizing AIVF’s software have seen a 30% increase in success rates, Gilboa said in a July 2023 New York post article.
Non-invasive AI systems analyze multiple parameters that, when put together, give much more predictive information about embryo development.
The in-depth operating systems help doctors understand implantation failures and multiple failed cycles.
“The timing of the cell divisions, the evenness of the cell divisions and the amount fragmentation of certain features will give us ideas as to the embryo’s true quality and genetic potential,” Dr Conor Harrity, Consultant Gynecologist and Subspecialist in Reproductive Medicine at Rotunda and Beaumont hospitals in Dublin, Ireland, told Inside Reproductive Health.
Predictive power
Dr. Harrity sought a non-invasive tool that would provide more information on blastocysts than standard morphology. “AIVF stands out because it gives us much more information about the potential of the embryo without the need to biopsy the embryo with the extra risk of embryo damage or the extra cost involved with preimplantation genetic testing technology (PGT),” said Dr. Harrity.
“If the embryo is not good enough, you can modify and personalize the regime,” said Dr Harrity. Therefore, AIVF helps clinicians identify scenarios where good embryos haven’t worked, and they need to modify the transfer regime. With AI scoring, the tool also lets clinicians see that embryos they thought were good morphologically weren’t as good as they had thought.
“AIVF gives more confidence to both the doctor and the patient about how to shorten their journey to either success or to knowing why it’s not working, and then changing tack and doing something that will help them succeed,” said Dr. David Walsh, Director of FirstIVF.
The use of AI and tools like AIVF indicate a move to a 'pay per baby' pricing model over a 'pay per treatment' model, Walsh confirmed. “The closer you can get to a higher probability of outcome and shared risk between the fertility clinic and patient, the more likely we are to see the move to a ‘pay per baby model”, Walsh said.
Due to its expense, clinics cannot afford to return this cost to patients, Walsh said, if treatment does not result in pregnancy. “Anything that gets closer to the prediction of outcome allows clinics to make calculated outcomes, therefore increasing their predictive power”.
Time-lapse capabilities
Progressing beyond PGT, AIVF enables retrospective use by recording time-lapse videos. Over the past year, Dr. Harrity confirmed that the industry has started to see instances where it has been very useful to look retrospectively at embryos and learn more about previous failed transfers.
AIVF’s EMA uses time-lapse monitoring to understand an embryo’s development. Several cameras record the embryo to give a multi-dimensional view of the embryo’s growth. The system shows how the embryo divides from a single cell into multiple cells until it forms a blastocyst.
Rather than just using snapshots at certain points of development, embryologists continuously monitor the embryo’s growth over five to six days until it reaches the blastocyst stage, providing much more information.
Non-clinical benefits
EMA’s automated embryo evaluation and quality scoring modules (AIVF Day-3, AIVF Day-5 and AIVF Genetics) automate the embryo evaluation process, entirely replacing manual steps, such as visual inspections, morphokinetic and morphological annotations, and manual data recording and transfer into the electronic medical record (EMR).
The integrated system directly transfers all embryo evaluations and scores from the time-lapse incubator to the EMR through the EMA platform, eliminating redundant data recording and transfer between multiple operating systems within the IVF laboratory. “It is documented in the patient’s information record, another data point,” said Walsh.
A 2023 research study found the average manual evaluation and recording time without and with EMA was 3.1 minutes versus 30.9 seconds per embryo, respectively. Overall, using AIVF reduces the average embryo evaluation time per cycle by 83%, a case study on efficiency revealed.
By utilizing EMA's automated messaging dashboard, IVF analytics tool, and laboratory documentation for performance monitoring and calculation, clinics can also lower administrative time for each cycle from 9.0 hours to just 5.58 hours, a 38% reduction. (1)
AIVF audits field transfers; offering information about embryos that did not implant.
Developers are adding features to AVIF’s time-lapsed five-minute videos to increase predictive power. Standing out in a way that isn’t true for all other non-invasive programmes, Walsh said, “AIVF is constantly learning, so it is getting better over time”.
“The big thing about non-invasive testing is that it can become universal,” said Walsh. It is accessible to everybody going through a fertility lab because it is relatively low cost, particularly compared to genetic testing. As long as the information is stored securely, non-invasive testing enables clinicians to look back in time and use it in the future. Clinicians can receive that information and run the data. “It’s eternal,” said Walsh.
While a move to subscription pricing models is uncertain at the moment, Walsh said, “clinics may justify this move based on confidence and outcomes”. He said confidence in AI technology like AIVF and its outcomes will help clinics move to different financial models, with ‘pay for baby’ treatment a permissible and viable alternative to the 'pay for baby' treatment option.
(1) Validated by AIVF partners. Internal data on file
This News Digest Story is paid featured content. The advertiser has had editorial input and control over its creation. However, the views and opinions expressed in this article do not necessarily represent the views of Inside Reproductive Health. The sponsorship of this content does not imply an endorsement by Inside Reproductive Health.
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