Title: Evaluating alternative protocols for identifying and managing patients with familial hypercholesterolaemia: cost-effectiveness analysis with qualitative study
Funder: Department of Health and Social Care

Abstract: AIMS: To identify the most cost-effective protocol for cascade testing for familial hypercholesterolaemia. HEALTH TECHNOLOGY: A protocol for FH cascade testing and subsequent management. ECONOMIC MODELLING: Design & Rationale: Cost-effectiveness models will be developed to compare alternative cascade testing protocols to each-other. The models will synthesise evidence from cascade testing services that are already operating in three UK regions, the literature and a linked observational dataset of UK primary and secondary care data describing the management and outcomes of patients with FH. The models will provide estimates of lifetime quality adjusted life years (QALYs) and costs incurred by the NHS and personal social services for each evaluated protocol. Results will be interpreted using a range of cost–effectiveness thresholds to identify a cost-effective FH cascade testing protocol for the NHS. Setting: UK Primary (General Practices) and Secondary Care Target population: Individuals with possible or definite FH and their relatives. Sources for process and outcome data: 1. Two cohorts: (a) Simon-Broome register: 3,564 FH patients’ linked to National Institute of Cardiovascular Outcomes Research (NICOR) Myocardial Infarction dataset and Hospital Episodes Statistics (HES); (b) General Practice dataset: 5,050 FH patients in Clinical Practice Research Datalink (CPRD) linked to Office for National Statistics (ONS) Mortality datasets and Hospital Episodes Statistics (HES). 2. Routine service datasets: Routine FH cascade testing service datasets: 6,408 cases & 1,902 relatives tested retrospectively from Scotland, Wales and Wessex with additional prospective testing during the study period. 3. Literature: focus on searching for (a) yield of relatives by mode of contact; (b) outcomes in undiagnosed patients; (c) outcomes in paediatric patients. Sources for cost data: Data on staff input from Wessex and Welsh FH service; resource use from linked datasets; and standard sources for drug, staff and cardiovascular event costs, supplemented by data from our related British Heart Foundation economic analysis [3]. Sources for quality of life data: Published EQ-5D data conditioned upon age and cardiovascular event history. Phases of modelling: Build conceptual model with expert input and review literature; generate parameters for model using routine service data (from specialist FH datasets with linked primary care records) and FH cohorts linked to national datasets on management and outcomes; model programming and analysis to ascertain cost-effectiveness of a range of protocols. Primary Outcomes: Cost-effectiveness of alternative protocols of cascade testing using incremental cost effectiveness ratios (ICERs) comparing all evaluated protocols. Secondary Outcomes: Yield of FH relatives; acceptability of cascade testing protocols, long term cardiovascular events and survival; QALYs due to lipid lowering therapy initiation at different ages; costs by components and over time. QUALITATIVE STUDY: Acceptability of cascade testing protocols will be explored with patients/family members, primary care/specialist providers, commissioners and other stakeholders in semi-structured interviews/focus groups using purposeful sampling, thematic analysis and respondent validation [4-6]. PROJECT TIMETABLE: DATA RETRIEVAL & ECONOMIC MODELLING: literature review and model conceptualisation [1-12m]; preparation of retrospective routine linked databases and cohorts [1-18m]; preparation of prospective databases [10-21m]; analysis of data [15-24m]; build models and generate results [22-31m]; reporting [30-36m]. QUALITATIVE STUDY: ethical approval [6-10m]; interviews with up to 30 patients/relatives & 10 specialist providers [18-32m]; up to 10 commissioners/other stakeholders [24-33m]; data analysis [18-34m]; reporting [34-36m]. TEAM EXPERTISE: The study bring together expertise in cardiovascular/FH economic modelling (MS, BW, MK, SH, RP, PR, AN*, CB) with those leading quantitative and qualitative health service research and evidence synthesis in this and related areas (NQ, JK, SH, JLB, BW). Also, expertise in interrogating routine databases (NQ, PR, ZM, KH*), delivering regional FH services (MW, ZM, RP, CB, SH, DD*, DN*, KH*, JP*, JW*) and engaging service users (PR, MW, ZM, RP, NQ, SH, JP*, JW*, PG*). *denotes collaborators

Lay abstract: Familial Hypercholesterolaemia (FH) is a common inherited cause of raised cholesterol, affecting up to 320,000 people in the UK. However over 80% of individuals are not identified, leading to many avoidable heart attacks and early deaths. Use of cholesterol lowering medication can dramatically reduce this toll. National (NICE) guidelines recommend general practitioners (GPs) identify people with possible FH by using cholesterol levels, family information and physical examination. If FH seems likely, the GP should refer patients to a specialist to confirm diagnosis, usually by genetic testing. If FH is confirmed, treatment should be given and their relatives contacted for genetic testing – known as “cascade” testing. Currently, once individuals with suspected FH are referred to specialists, the process for genetic testing varies. Relatives are usually invited for testing “indirectly” through those already diagnosed with FH. This doesn’t always work well, and children or relatives outside the specialist’s area are not normally tested. This means many with FH are not identified and remain untreated. This study will examine different ways of identifying people with FH, contacting and testing their relatives and managing their treatment. We will compare the effect these methods have on the numbers of people identified and treated, and estimate the heart attacks and early deaths prevented. We will weigh up the benefits against the costs. The costs include costs of identification, diagnosis and care – such as appointments, staff training, referrals, genetic testing, drug treatments, and follow up. We will capture accurate data on all these factors from different existing services. In Scotland, Wales and Wessex lipid specialists have already collected data for around 8,300 patients which we will use. We will also collect more detailed data on new patients identified in these large regions over the first 18 months of study. We can thus assess what influences how many new FH cases and their relatives are identified when different approaches are used. To examine the impact of finding and treating FH patients on cholesterol levels and heart attacks, we will look at two national databases. Firstly, the Simon-Broome register, with health information on over 3,500 patients with FH, recorded over the past 30 years. Secondly, we will identify over 5,000 FH patients recorded in General Practice electronic health records. We will also link these to other national databases on heart disease and causes of death. This will help us make a detailed analysis of the benefits of diagnosing and treating FH, and evaluate how well different ways to identify relatives work. We will also interview patients, their relatives, and health care staff involved about the acceptability of these different approaches, supplemented by interviewing commissioners of health services, policy makers and FH charities. This will help identify and overcome any barriers to implementing an improved service. This research benefits from being developed in partnership with FH patients using the specialist services, a national representative and colleagues at Heart UK and BHF charities. By the end of the study, we will be able to recommend the most cost-effective and acceptable approach to set up a better service for FH in the NHS. This will inform new national guidelines for care of FH and be reported to commissioners directly and through Heart UK and BHF.

Research activity codes: 7.3 MANAGEMENT AND DECISION MAKING
Health categories: METABOLIC AND ENDOCRINE