Criteria for the provision of IVF treatment varies across the UK and since April 2013, are dependent on the local Clinical Commissioning Group (CCG) responsible for authorising NHS services. Controversy over the fairness of what has been dubbed “postcode lotteries” to determine eligibility for NHS funded fertility treatment has further highlighted the need for the NHS to effectively manage costs and treatment as audits reveal that only 52% of CCGs offer just one cycle of IVF and fewer than one in five CCGs are paying for the full number of three IVF cycles as recommended by NICE.
For many fertility specialists, the single biggest contributor to cost savings and resource allocation is the ability to accurately predict the success of IVF or ICSI treatment. Currently, a live birth is dependent on numerous factors specific to the couple being treated however, these factors are based on aggregates and averages relevant to a wide range of patients. But what if there was a way to harness individual patient data in a specific structure that could make costly treatments like fertility more effective?
It’s that exact question that Professor of Reproductive Medicine at Newcastle’s International Centre for Life, Alison Murdoch, took to a local clinical software developer as the premise for designing a solution that meets all the necessary requirements. “Regulation in fertility is far more prescribed than other fields due largely to the Human Fertilisation and Embryology Authority (HFEA) and while there are resounding benefits to going paperless, it was not our main priority. Our goal was to create an innovative system that could combine HFEA data collection requirements with pertinent patient care information.”
“Currently, there are products available for a combination of clinic management and HFEA data but insufficient in the middle about the patient – and that’s where we saw an opportunity to create a system for this highly specialised field that harnesses individual patient data to more accurately predict, and improve efficiency of fertility treatment provision,” said Murdoch.
Murdoch went on to explain that one of the major obstacles to realising a complete data solution is the HFEA requirement to keep hard copies of patient records separately from other records – limiting their use of electronic records because the information can’t be merged into one source. “The upside is that there is less chance of losing records but there’s also the logistical problem of storing vast amounts of paper records. Physically managing the volume limits our ability to carry out clinical work in a reactive manner because of the time it takes to locate a file and respond to a patient’s query.”
“we saw an opportunity to create a system for this highly specialised field that harnesses individual patient data”