From data to decisions: “Accessing HFEA data has allowed me to move beyond research questions and focus on what evidence can genuinely offer patients”

Every year, thousands of people in the UK place their trust in fertility treatment, often making difficult decisions without knowing what the outcome will be.

Understanding what happens after fertility treatment requires more than small studies or individual clinic data, it requires high-quality, population-level evidence. Having access to the HFEA’s IVF data through the Register Research Panel has been central to this work, enabling research that would not otherwise have been possible and helping to turn complex data into evidence that can inform real-world decisions.

As a medical statistician, much of my research has focused on using routinely collected national level IVF data to answer important questions that matter to patients, clinicians, and policymakers. These questions usually fall into one of two broad groups – prediction and explanation. An example of a research question for prediction would be ‘what is the chance of a 35-year-old woman with tubal infertility having a baby with IVF treatment?’, whereas an example of a research question for explanation would be ‘is IVF treatment more likely to result in a healthy baby than an alternative treatment?’.

While explanation questions are very important, it is the prediction questions that interest me most. This is because the answer provides a more personalised chance of having a baby (or some other important outcome) that is tailored to a patient(s) own history. Since one of the biggest challenges patients face when starting IVF is uncertainty, this information may help them make informed decisions and help them manage their expectations.

Prediction questions can be answered using routinely collected data to create a mathematical equation called a prediction model. I led the development of several models using HFEA Register data and converted them into a suite of user-friendly online calculators, called OPIS. These can easily be used by couples and clinicians to estimate the chance of having a baby following IVF up to a total of six completed cycles. They can also act as a reference point during consultations and patients may feel able to ask more informed questions about their treatment as a result, as well as helping them prepare emotionally and financially for the likelihood of needing multiple IVF cycles.

Obtaining access to the HFEA Register through the RRP in 2012 made my research possible. Not only does it play a central role in enabling high quality fertility research while protecting patient trust and confidentiality, but we would not have had access to an equivalent size dataset of patients that would allow our model to represent the IVF population in the UK and make accurate predictions.

Accessing HFEA data has allowed me to move beyond abstract research questions and focus on what evidence can genuinely offer patients who are undergoing IVF treatment. By using national data responsibly and transparently, my work aims to turn population-level evidence into practical tools that help patients understand their options, set realistic expectations, and feel more informed in their decision-making. This vision would not be possible without the trust placed in the HFEA to steward fertility data and the governance structures that ensure this data can be used securely for clear public benefit.

Since our first approval in 2012, we’ve gone on to create a website for our IVF calculators, which has been updated with more recent HFEA data, and we have just launched a new version. Looking ahead, continued access to high-quality national IVF data will be essential to further developing inclusive, patient-focused tools that reflect the real experiences of people undergoing fertility treatment in the UK.

About the author:

Dr. David McLernon is a senior research fellow in medical statistics at the University of Aberdeen specialising in clinical prediction modelling in reproductive medicine. He has over 12 years' experience developing methods to predict pregnancy and live birth outcomes, with the aim of supporting couples and informing fertility treatment decisions. His work includes the OPIS calculators, which estimate the chance of having a baby across multiple IVF cycles, and dynamic models for unexplained infertility. David has co-authored over 100 peer-reviewed publications and contributes to the STRATOS initiative, which provides guidance on best practice for analysing observational health data. He is a member of the Royal Statistical Society and serves as statistical advisor for Reproductive BioMedicine Online.