A mixed-methods evaluation of the child-parent screening service for familial hypercholesterolemia

Familial hypercholesterolemia

Familial hypercholesterolemia (FH) is a genetic condition resulting in high atherogenic low-density lipoprotein (LDL) cholesterol levels in the blood, increasing the risk of myocardial infarction and stroke. The NHS Long Term Plan aimed for 25% of FH patients to be identified in the next five years (2019 to 2024) through the NHS genomics programme.

Testing children for FH allows both parent and child to be identified and treated together. This is commonly known as the child-parent screening service (CPSS), which was implemented between October 2021 to October 2024.

How Unity Insights worked with Health Innovation North East North Cumbria

Unity Insights were commissioned by Health Innovation North East and North Cumbria to understand the impact of the child-parent screening service within 67 GP practice pilot sites across the NHS in England. A mixed-methods design was employed, combining quantitative statistical analysis of screening data with qualitative analysis of stakeholder surveys and semi-structured staff interviews. The evaluation aimed to understand:

Which clinical care pathways were the most successful and why?

What lessons have been learned from the implementation of the child-parent screening service?

To what extent has the child-parent screening service contributed to the NHS Long Term Plan’s ambition for 25% of predicted FH patients to be identified by 2024?

The findings from the evaluation were collated to create recommendations that could be used to inform the future of the child-parent screening service, should the pathway be implemented again.

1. Demonstrating success in clinical care pathways

Success in clinical pathways was related to screening uptake. Overall uptake was 27% (weighted average = 27%; median = 11%) across all GP practices that engaged in the child-parent screening service, albeit with considerable variation in individual rates. Excluding statistical outliers, the highest uptake was 75%, while the lowest uptake (excluding practices which enrolled but did not complete any screenings) was 1%.

Within the evaluation, quantitative analysis identified what occurred in terms of screening figures; however, it did not explain why these figures varied across GP practices or highlight the experiences from other stakeholders involved in the service. To understand why uptake was greater in some sites but not others, qualitative surveys and interviews offered perspectives from individuals within different areas of the pathway.

GP practice staff involved in the child-parent screening service were surveyed (n = 18) and interviewed (n = 4)

HIN staff involved in the child-parent screening service were interviewed (n = 7)

Genomic Laboratory Hub (GLH; where samples were sent for genetic testing) staff were interviewed (n = 5)

Leadership staff who were involved in the child-parent screening service were interviewed (n = 3)

Qualitative analysis revealed that communication and buy-in from all involved in the child-parent screening service were positively correlated with screening uptake. One GP practice interviewee highlighted that they were not successful in the child-parent screening service due to a lack of staff engagement. In this GP practice, four screenings were completed, resulting in an uptake of 12% (much lower than the overall uptake of 27%). Interviewees noted the importance of a motivated driver to encourage screening. Motivated drivers at GP practices were typically individuals with a passion for CVD, or who had or knew someone with FH. If the key driver left the GP practice, the number of screenings was suggested to decrease.

2. Illustrating lessons learned from implementing the child-parent screening service

The open-ended nature of interview responses, unlike the structured format of surveys, gives respondents the flexibility to answer in a way that truly reflects their experiences. This leads to richer, more detailed insights, often revealing unexpected perspectives that might not emerge in a multiple-choice survey. Allowing staff members the flexibility to respond in a way that genuinely reflects their experiences results in higher-quality insights. The main lessons learned from implementation were:

Staff and parent buy-in is essential for high uptake

Clear communication between all sites is vital for smooth implementation

Staff must see the value of the incentives to buy-in to the child-parent screening service

Staff were satisfied with the training provided

3. Revealing the extent the child-parent screening service contributed to the NHS Long Term Plan’s ambition

Approximately 220,000 people in the UK have FH, but less than 8% are currently diagnosed. It was vital to compare the pilot against related NHS documents and similar studies to understand the extent to which the child-parent screening service contributed to the NHS Long Term Plan’s ambition of identifying 25% of FH cases between 2019 and 2024. The child-parent screening service identified two cases of FH in 1,820 child screenings, resulting in a diagnosis rate of 0.11%. The pilot identified 0.001% of the England population with previously unidentified FH. If the child-parent screening service were to be implemented in all GP practices across England, the pilot could have identified 62,817 (29% of the 220,000) people with genetic FH and high cholesterol levels. This means that the child-parent screening service did not contribute directly to the NHS Long Term Plan‘s ambition, however provided proof of concept for one method by which this could be achieved if scaled up. By identifying FH cases early, the child-parent screening service facilitates timely interventions, such as lifestyle advice and cholesterol-lowering medication, significantly lowering the risk of myocardial infarction and strokes.

What value did the evaluation add?

One Health Innovation Network staff interviewee noted that obtaining buy-in with low diagnostic figures was challenging, referencing the 0.40% figure from Wald et al. (2016). Unity Insights were able to identify that the current comparator, a diagnostic rate from Wald et al. (2016; 0.40%), was not an accurate comparator for the child-parent screening service. This was because the diagnostic rate used identified FH through several pathways, whereas the child-parent screening service identified FH through one high cholesterol reading, leading to DNA screening for genetic FH. Therefore, the more accurate diagnostic rate within Wald et al. (2016) that the pilot can be compared to is 0.20%. This explained why the diagnosis rate was much lower compared to the previous study that used a similar methodology.

Unity Insights suggested that including a new diagnosis pathway, diagnosing FH through two high cholesterol level readings within three months, could increase the diagnosis rate and identify FH for those who would have gone unnoticed in the current child-parent screening service pathway.

This finding, alongside others formed from quantitative and qualitative analysis methods, were used to create recommendations that formed a roadmap to success, which could be used to improve the existing service and scale up implementation to further sites.

These evidence-based recommendations were focused on improving screening numbers, which would enable earlier diagnosis in a greater number of patients, allowing these individuals to make vital lifestyle changes before it is too late.

“Unity Insights have developed a meaningful and robust evaluation of the CPSS and their quantitative analysis has provided reasons as to why diagnosis rates of FH were lower than originally anticipated. Key recommendations for a future service implementation and role out show their deep level of understanding of the programme and mobilisation of information received from interviewing a broad selection of participants. HI NENC were updated via weekly meetings and communication was excellent – a pleasure to work with them.“

Catherine Kelly, Deputy National Programme Manager for Lipid Management at Health Innovation North East North Cumbria