Healthcare activities before familial hypercholesterolemia diagnosis: a nationwide register-based study in Denmark.

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Learn more: PMC Disclaimer | PMC Copyright Notice BMC Prim Care . 2026 Mar 6;27:136. doi: 10.1186/s12875-026-03256-y Search in PMC Search in PubMed View in NLM Catalog Add to search Healthcare activities before familial hypercholesterolemia diagnosis: a nationwide register-based study in Denmark Simon Graff Simon Graff 1 Research Unit for General Practice, Bartholins Allé 2, Aarhus C, 8000 Denmark 2 Department of Public Health, Aarhus University, Aarhus, Denmark Find articles by Simon Graff 1, 2, ✉ , Kirsten Høj Kirsten Høj 3 Department of Clinical Pharmacology, Aarhus University Hospital, Aarhus, Denmark Find articles by Kirsten Høj 3 , Bo Christensen Bo Christensen 1 Research Unit for General Practice, Bartholins Allé 2, Aarhus C, 8000 Denmark 2 Department of Public Health, Aarhus University, Aarhus, Denmark Find articles by Bo Christensen 1, 2 , Flemming Bro Flemming Bro 1 Research Unit for General Practice, Bartholins Allé 2, Aarhus C, 8000 Denmark 2 Department of Public Health, Aarhus University, Aarhus, Denmark Find articles by Flemming Bro 1, 2 , Helle Lynge Kanstrup Helle Lynge Kanstrup 4 Department of Clinical Medicine, Aarhus University, Aarhus, Denmark 5 Department of Cardiology, Aarhus University Hospital, Aarhus, Denmark Find articles by Helle Lynge Kanstrup 4, 5 , Henrik Schou Pedersen Henrik Schou Pedersen 1 Research Unit for General Practice, Bartholins Allé 2, Aarhus C, 8000 Denmark 2 Department of Public Health, Aarhus University, Aarhus, Denmark Find articles by Henrik Schou Pedersen 1, 2 Author information Article notes Copyright and License information 1 Research Unit for General Practice, Bartholins Allé 2, Aarhus C, 8000 Denmark 2 Department of Public Health, Aarhus University, Aarhus, Denmark 3 Department of Clinical Pharmacology, Aarhus University Hospital, Aarhus, Denmark 4 Department of Clinical Medicine, Aarhus University, Aarhus, Denmark 5 Department of Cardiology, Aarhus University Hospital, Aarhus, Denmark ✉ Corresponding author. Received 2025 Mar 26; Accepted 2026 Mar 2; Collection date 2026. © The Author(s) 2026 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ . PMC Copyright notice PMCID: PMC13077805  PMID: 41792624 Abstract Background Familial hypercholesterolemia is a common yet underdiagnosed genetic disorder that significantly increases the risk of premature atherosclerotic cardiovascular disease. General practitioners could play a central role in early familial hypercholesterolemia identification, yet it remains unclear how frequently these patients engage with primary and secondary care before their diagnosis. Our aim is to investigate healthcare activities in general practice and secondary care for patients with future familial hypercholesterolemia in the five years preceding diagnosis. Method We performed a nationwide, register-based cohort study in Denmark using national healthcare registries from 2011 to 2021. We identified 3,185 incident familial hypercholesterolemia patients and 31,850 matched references based on age, sex, calendar time, and general practitioner affiliation. Healthcare activities included general practice consultations, LDL-C testing, lipid-lowering therapy prescriptions, atherosclerosis-related hospitalisations, and secondary care procedures. Poisson regression, yielding incidence rate ratios (IRRs), was used to compare healthcare activity rates over the five years before diagnosis. Results Familial hypercholesterolemia patients had significantly higher consultation rates (IRR 1.6, 95% CI 1.5–1.8 in the year before diagnosis) and more frequent LDL-C testing (IRR 5.2, 95% CI 5.0–5.4). Statin use was consistently elevated. Atherosclerosis-related hospitalisations and coronary procedures increased progressively before familial hypercholesterolemia diagnosis. Conclusion Our study supports the role of general practice as a primary site for familial hypercholesterolemia detection and intervention. The consistently higher activity rates in consultations and diagnostic tests suggest opportunities for earlier identification. Implementing systematic screening tools in primary care may improve timely familial hypercholesterolemia detection, reducing the burden of atherosclerotic cardiovascular disease. Trial registration Not relevant. Supplementary Information The online version contains supplementary material available at 10.1186/s12875-026-03256-y. Keywords: Familial hypercholesterolemia, General practice, Diagnosis, LDL cholesterol, Cardiovascular disease, Health services research, Registries Background Familial hypercholesterolemia (FH) is a serious but often overlooked cardiovascular condition affecting 1 in 200 to 250 of the general population [ 1 , 2 ]. FH is a dominant genetic disorder characterised by persistently elevated levels of low-density lipoprotein cholesterol (LDL-C) from birth, resulting in a significantly increased risk of premature atherosclerotic cardiovascular disease (ASCVD) [ 3 ]. The clinical diagnosis of FH is based on elevated LDL-C ≥ 5 mmol/l (≥ 4.0 under 40 years), premature ASCVD, and a family history of early ASCVD [ 4 ]. Despite the availability of free and accessible primary care [ 5 ], FH remains markedly underdiagnosed in Denmark and other Western countries [ 6 – 8 ]. If targeted and timely treatment is initiated for FH patients, it reduces their risk of ASCVD to nearly the same level as that of the general population [ 9 ]. Therefore, early identification of FH patients and their relatives is fundamental to reducing their significantly increased risk of cardiovascular disease [ 10 ]. Unfortunately, the diagnosis is often made after patients have developed cardiovascular disease [ 7 ]. Previous studies have shown that general practice can play a significant role in identifying FH [ 11 ]. In Denmark, most of the population is registered with a specific general practice [ 5 ]. The general practitioners (GPs) are patients’ first and primary healthcare providers and act as gatekeepers to the secondary healthcare system. Further specialised services require a referral from the patient's GP, except for emergency care and certain specialists who can be accessed directly. Most LDL-C blood samples are ordered from the GP for primary prevention or chronic disease management (e.g., diabetes, hypertension, ischemic heart disease) [ 12 ]. Still, known barriers such as low awareness, competing practice demands, and lack of clear care pathways from primary to secondary care reduce FH identification rates [ 13 , 14 ]. The GPs opportunity and ability to suspect FH and refer to further diagnostic investigation are key to ensuring early diagnosis [ 15 ]. Yet, it remains unclear how often these patients see their GP leading up to FH suspicion and which healthcare activities are performed before the formal diagnosis is established. Furthermore, it remains unclear how these patients are assessed before FH diagnosis, including how many LDL-C blood samples are taken, how often they exceed LDL-C risk levels, and which cardiovascular medications they receive. Therefore, we aimed to investigate healthcare activities for future FH patients in the 5-year period leading up to an FH diagnosis to explore the role of general practice in the pre-diagnostic phase. Methods Study aim, design and setting We conducted a nationwide register-based cohort study to examine the healthcare activities and contact patterns in Danish general practice and the secondary healthcare system before a formal FH diagnosis [ 16 ]. We linked information across several national registers using the unique personal identification number (CPR number) assigned to all Danish residents at birth or immigration [ 17 ]. The Danish healthcare system is tax-funded and offers residents free access to healthcare services. The majority (98%) of the Danish population is listed with a specific general practice [ 5 ]. GPs are self-employed but operate on health activity-based contracts with the public funding authorities, with 1600 patients assigned to each GP [ 5 ]. The GP has access to various laboratory tests, including LDL-C testing and ECG. Most primary FH diagnoses are made at regional lipid clinics in hospitals with specialised secondary care settings [ 18 ]. If a GP suspects FH, the GP should refer the patient to a lipid clinic to ensure the formal diagnosis is established by a clinical assessment and genetic testing. Study population The study population consisted of all patients aged ≥ 18 who lived in Denmark from 1 January 2011 to 31 December 2021 and was restricted to patients with at least five consecutive years of affiliation with a GP. FH patients FH patients were selected from the study population when registered with a first-time primary hospital diagnosis of FH. In Denmark, FH diagnoses are issued in secondary care, typically by lipid specialists or specialised hospital clinics. The diagnosis was defined as their index date, according to the International Classification of Diseases, 10th revision (ICD-10: DE780B Familial hypercholesterolemia) in the National Patient Register (NPR) ( n = 3,185) [ 19 ]. The index date represents an operational and register-defined time point. The first-time FH diagnosis was restricted to first-time hospital contacts only, i.e., the primary diagnosis leading to hospitalisation, the need for care or outpatient contact, and the main reason for the completed examination and treatment in a secondary hospital care setting. Cohortees were excluded at the time of a secondary FH admission diagnosis, e.g., diseases relevant to the primary contact disease but not the main reason for contact or care. Reference group. Ten non-FH patients were found for each FH patient in the study population using incidence density sampling matched on age, gender, calendar time, and GP affiliation ( n = 31,850). The reference group was identified using the NPR and Danish Civil Registration System (DCRS) [ 17 ]. The DCRS contains continuously updated information on the date of birth, immigration and emigration, sex, and vital status of all Danish residents. For the matched references, the index date was defined as the date of FH diagnosis for the corresponding FH patient. Outcomes The main outcomes were primary care services obtained from the Danish National Health Service Register [ 10 ]. These included daytime consultations (face-to-face), annual chronic care consultations, and ECG (point-of-care test) in general practice. The Supplementary data contains ​​a complete list of the register-based codes used to identify the selected outcomes – see Table 1.B. Information on the number of LDL-C (NPU-01568) measurements was obtained from the National Laboratory database [ 20 ]. The outcome Risk LDL-C was defined as LDL-C ≥ 5.0 mmol/L in cohortees aged ≥ 40 years and ≥ 4.0 mmol/L in individuals aged 18–39 years. The outcome reflects an analytical construct to capture events based on guideline-relevant thresholds and does not constitute a clinical diagnosis. Data regarding lipid-lowering therapy (C10AA + BA), anti-angina (C01D), and anti-platelet drugs (B01AC) in the study population were registered from active prescriptions in the Danish National Prescription Registry (DNPR) [ 21 ]. The medications are all available by prescription only. Additionally, data used to identify outcomes in secondary care were obtained from the NPR [ 19 ] and included diagnostic investigations performed at a hospital: Coronary CT scan (UXCC00A), Coronary arteriography (UXAC85), and echocardiography (UXUC80). Information on prior cardiovascular diagnosis, defined as first-time primary hospital admissions, was obtained from the NPR [ 19 ] (ICD-10 codes: Angina Pectoris (DI200-DI209), Acute Coronary Syndrome (DI210- DI219), Ischemic disease (DI251-DI259). For all outcomes, we counted the number of activities per year in the five years before the index date. Covariates Sociodemographic and socioeconomic variables Information on sex and age was extracted from the DCRS [ 17 ]. Information on the highest attained education level and cohabitation status was obtained from the annually updated registers at Statistics Denmark [ 22 ]. We divided educational status into three categories based on the United Nations Educational, Scientific, and Cultural Organisation’s International Standard Classification of Education (0–10 years, 11–15 years, ≥ 16 years) [ 23 , 24 ]. Cohabitation status was divided into single, married, or living with a partner (cohabitating). Comorbidity Data on comorbidity originated from NPR and DNPR. The included data were selected through an algorithm developed by Prior et al. [ 25 ] This algorithm identifies 39 conditions in 9 disease groups: the circulatory system, endocrine system, pulmonary and respiratory system, gastrointestinal system, urogenital system, musculoskeletal system, haematological system, neurological system, cancers, and mental health conditions treated in primary and secondary care. Selected circulatory conditions (Dyslipidemia E78, Ischemic heart disease I20-I25) were removed from the original index if they corresponded to an outcome measure. All covariates except sex and index date were treated as time-dependent and updated at the beginning of each 12-month period over the 5-year period. Statistical analysis We used a Poisson regression model, applying cluster-robust variance estimation at the patient level and the logarithm of risk time as an offset, to calculate yearly rates and incidence rate ratios (IRRs) to compare healthcare use between FH patients and the reference group over 12-month periods from 5 years before the index date. For each outcome (face-to-face consultations, annual chronic care examinations, prescriptions for lipid-lowering therapy, LDL measurements, ECGs, cardiovascular diagnoses, and diagnostic investigations performed at the hospital level), the crude yearly rates were estimated. The adjusted analyses for IRRs included age, sex, calendar time, educational level, cohabitation status, and comorbidity categories and represent the main estimates reported. All estimates were presented with 95% confidence intervals (CI). All yearly rates and IRR estimates are presented in Table 1.A and 1.B in the Supplementary data. All analyses were conducted with Stata statistical software, release 17. Results Study population characteristics The study included 3,185 patients with incident FH and 31,850 references, with 54.7% being females and a median age at index date of 52 years. A total of 1,819 (57.1%) in the FH group were married, compared with 17,363 (54.5%) in the reference group. In the FH group, 707 (22.2%) had 0–10 years of education, compared with 7,291 (22.9%) in the reference group, and 971 (30.5%) had more than 15 years of education, compared with 8,938 (28.1%) in the reference group. Among cohortees from the FH-group, 315 (9.9%) were classified with an endocrinology condition. The corresponding number was 2,917 (9.2%) among the reference group. A higher number of cohortees from the FH group were classified with a circulatory condition 372 (11.7%). The corresponding number was 2,917 (5.8%) among the reference group. Sociodemographic variables and comorbidities are listed in Table 1 . Table 1. Characteristics of the study population at index date FH Group Reference Group Total Age at index date Median / [IQR] 52 [41; 61] 52 [41; 61] 52 [41; 61] Total. n / (%) 3,185 (9.1) 31,850 (90.9) 35,013 (100.0) Sex Female 1,742 (54.7) 17,420 (54.7) 19,162 (54.7) Male 1,443 (45.3) 14,430 (45.3) 15,873 (45.3) Year of Index date* 2011 71 (2.2) 710 (2.2) 781 (2.2) 2012 114 (3.6) 1,140 (3.6) 1,254 (3.6) 2013 152 (4.8) 1,520 (4.8) 1,672 (4.8) 2014 95 (3.0) 950 (3.0) 1,045 (3.0) 2015 165 (5.2) 1,650 (5.2) 1,815 (5.2) 2016 247 (7.8) 2,470 (7.8) 2,717 (7.8) 2017 387 (12.2) 3,870 (12.2) 4,257 (12.2) 2018 423 (13.3) 4,230 (13.3) 4,653 (13.3) 2019 628 (19.7) 6,280 (19.7) 6,908 (19.7) 2020 484 (15.2) 4,840 (15.2) 5,324 (15.2) 2021 419 (13.2) 4,190 (13.2) 4,609 (13.2) Cohabitation ¥ Single 869 (27.3) 9,523 (29.9) 10,392 (29.7) Married 1,819 (57.1) 17,363 (54.5) 19,182 (54.8) Cohabitating 497 (15.6) 4,964 (15.6) 5,461 (15.6) Education (years)† 0-10 707 (22.2) 7,291 (22.9) 7,998 (22.8) 11-15 1,507 (47.3) 15,621 (49.0) 17,128 (48.9) >15 971 (30.5) 8,938 (28.1) 9,909 (28.3) Comorbidity Δ Circulatory system 372 (11.7) 1,852 (5.8) 2,224 (6.3) Endocrine system 315 (9.9) 2,917 (9.2) 3,232 (9.2) Pulmonary system and allergy 305 (9.6) 2,938 (9.2) 3,243 (9.3) Gastrointestinal system 207 (6.5) 1,983 (6.2) 2,193 (6.3) Urogenital system 71 (2.2) 624 (2.0) 695 (2.0) Musculoskeletal system 435 (13.7) 3,825 (12.0) 4,260 (12.2) Haematological system 22 (0.7) 228 (0.7) 250 (0.7) Cancers 159 (5.0) 1,713 (5.4) 1,872 (5.3) Neurological disorders 348 (10.9) 3,326 (10.4) 3,674 (10.5) Mental health conditions 353 (11.1) 3,111 (9.8) 3,464 (9.9) Open in a new tab Abbreviations FH Familial Hypercholesterolemia, IQR Interquartile range *Year of Index Date indicates the number of patients and references enrolled in each respective year ¥ Cohabitation status defined at study entry, e.g., index date † Educational level is defined as the highest completed level of education at study entry, e.g., index date Δ Comorbidity status is defined as 39 disorders and conditions treated in primary and secondary care General practice outcomes In the five years leading up to the diagnosis, the FH group had consistently higher yearly rates of general practice consultations, chronic care consultations, LDL-C and Risk LDL-C tests, ECG tests, and statin use compared to the reference group. The estimated IRRs showed a gradual increase over the five years, with IRRs for most outcomes peaking in the last year before diagnosis. All yearly rates and IRRs for general practice outcomes are shown in Table 1.A in the Supplementary data. Consultation rates In the FH group, the consultation rates increased progressively from 4.1 (95% CI 4.0–4.3) contacts/year five years before diagnosis to 4.5 (95% CI 4.3–4.6) contacts/year two years before diagnosis. In the final year before diagnosis, the consultation rate increased to 5.5 (95% CI 5.4–5.7) contacts/year. The overall IRR for consultation in the 0–5 years was 1.3 (95% CI 1.2–1.3). In the reference group, the consultation rates were stable, with around 3.5 contacts/year throughout the observation period. The adjusted IRR ranged from 1.2 (95% CI 1.1–1.3) five years before diagnosis to 1.6 (95% CI 1.5–1.8) in the year prior to diagnosis. See Fig. 1 . Fig. 1. Open in a new tab Consultation rates in general practice in the 5 years preceding a familial hypercholesterolemia diagnosis. Legends: The rate of contracts is presented as crude rates of the mean number of contacts per year. Incidence rate ratios were adjusted for age, comorbidity, educational level, and cohabitant status. Black lines represent 95% confidence intervals. Abbreviations: (FH) Familial Hypercholesterolemia, (CI) Confidence Interval The absolute yearly rates of both FH and reference cohortees were low for annual chronic care examinations but showed a gradual increase for the FH group over the five-year period. The IRR for annual chronic care examinations increased from 1.5 (95% CI 1.5–1.7) five years before diagnosis to IRR 1.6 (95% CI 1.5–1.7) two years before and 2.2 (95% CI 2.1–2.4) in the year prior to diagnosis. See Fig. 1 . Testing rates Among cohortees from the FH group, the rate of LDL-C tests performed increased progressively from 0.4 (95% CI 0.4–0.5) tests/year five years before diagnosis to 0.8 (95% CI 0.8–0.9) tests/year two years before diagnosis. In the final year before diagnosis, LDL-C testing increased further to 1.7 (95% CI 1.6–1.8) tests/year. The IRR for LDL-C testing increased from 2.3 (95% CI 2.2–2.5) five years before diagnosis to 5.2 (95% CI 5.0–5.4) one year prior to diagnosis. The overall IRR for LDL-C testing in the 0–5 years was 3.2 (95% CI 3.1–3.4). See Fig. 2 . Fig. 2. Open in a new tab LDL-C test rates in general practice in the 5 years preceding a familial hypercholesterolemia diagnosis. Legends: Test rates are presented as crude rates, the mean number of tests per year. Incidence rate ratios were adjusted for age, comorbidity, educational level, and cohabitant status. Black lines represent 95% confidence intervals. The outcome Risk LDL-C was defined as LDL-C ≥ 5.0 mmol/L in cohortees aged ≥ 40 years and ≥ 4.0 mmol/L in individuals aged 18–39 years. Abbreviations: (FH) Familial Hypercholesterolemia, (CI) Confidence Interval, (LDL-C) Low-Density Lipoprotein Cholesterol The Risk LDL-C test rates had a low absolute number of events, which resulted in high IRRs when comparing the two groups. The results showed that five years before an FH diagnosis, 444 tests were recorded in the FH group compared with 190 in the reference group, corresponding to an IRR of 23.3 (95% CI 19.1–28.4). One year before diagnosis, this difference increased: 2,027 tests in the FH group versus 296 in the reference group, corresponding to an IRR of 68.7 (95% CI 59.0–80.0). See Fig. 2 . ECG tests also had a low absolute number of events but showed a similar pattern, with more tests performed in the FH group compared to the reference group in the years prior to diagnosis. The corresponding IRRs showed a gradual increase from IRR 1.3 (95% CI 1.2–1.5) five years before to IRR 2.1 (95% CI 2.0–2.2) one year before diagnosis. See Fig. 3 . Fig. 3. Open in a new tab Statins and ECG rates in general practice in the 5 years preceding a familial hypercholesterolemia diagnosis. Legends: The rate of tests or prescriptions is presented as crude rates of the mean number of tests/prescriptions per year. Incidence rate ratios were adjusted for age, comorbidity, educational level, and cohabitant status. Black lines represent 95% confidence intervals. Abbreviations: (FH) Familial Hypercholesterolemia, (CI) Confidence Interval, (ECG) Electrocardiogram Statin use For statins, the yearly rates showed a higher number of prescriptions from 1.4 (95% CI 1,3–1.5) prescriptions/year five years before diagnosis up to 1.9 (95% CI 1.9–2.0) prescriptions/year one year before diagnosis. Statin prescriptions were stable and constantly elevated among cohortees from the FH group, similar to the reference group over the five years. The IRR was 4.2 (95% CI 3.9–4.4) five years before the diagnosis, and 4.1 (95% CI 3.8–4.3) the year before the diagnosis. See Fig. 3 . Secondary care outcomes In the five years leading up to the diagnosis, hospital procedures, ASCVD-related hospitalisations, and ischemic-related medication use were all more frequent in the FH group compared to the reference group, with rates progressively increasing as the diagnosis approached. Detailed yearly rates and IRRs are provided in Table 1.B in the Supplementary data. ASCVD-related procedures Hospital procedures were more frequent among the FH group, with rates gradually increasing over time and peaking in the year before diagnosis. While the events were low, the IRRs for these evaluations steadily rose as diagnosis approached, with coronary angiogram (CAG) displaying the most pronounced increase. The yearly rates and IRRs are shown in Table 1.B in the Supplementary data. ASCVD-related hospitalisations Hospitalisations related to ischemic heart disease, angina, and acute coronary syndrome (ACS) also occurred more frequently in the FH group compared to the references. Although hospitalisation rates remained low overall, the FH group showed a progressive increase in admissions, particularly in the final year leading to diagnosis. The IRRs for ischemic heart disease and angina were consistently elevated across the five years, while ACS hospitalisations exhibited a sharp increase in both the yearly rate and IRR in the year preceding diagnosis. The yearly rates and IRRs are shown in Table 1.B in the Supplementary data. Ischemic-related medications Prescription rates for ischemic-related medications, including anti-angina drugs and thrombocyte inhibitors, were similarly higher in the FH group compared to the references. Usage of these medications rose progressively for FH cohortees, while prescription rates for the reference cohortees remained stable and low throughout the period. The IRRs for both anti-angina medications and thrombocyte inhibitors were consistently higher in comparison, peaking as the diagnosis approached. The yearly rates and IRRs are shown in Table 1.B in the Supplementary data. Discussion Main findings In this nationwide, register-based study, we explored healthcare activities in the pre-diagnostic period preceding a FH diagnosis. We found that individuals later diagnosed with FH consistently had higher yearly rates of consultations, annual chronic care examinations, statin use, ECGs, LDL-C and Risk LDL-C testing, ASCVD-related procedures and diagnoses, and medication redemptions compared with matched references. For most outcomes, activity levels increased gradually as diagnosis approached, except for statin prescriptions, which remained consistently elevated throughout the observation period. It shows that GPs see their future FH patients more often and have higher rates of FH-related tests, i.e., the frequency of LDL-C and Risk LDL-C tests, compared to the reference group. The prolonged increase in healthcare activities among future FH patients underscores the role of general practice as a platform for FH identification. Given that GPs often serve as a first point of contact, act as gatekeepers to secondary care, and provide opportunistic screening of chronic cardiometabolic diseases (e.g., type 2 diabetes, hypertension, hypercholesterolemia), they are ideally positioned to detect FH at an earlier stage. Strengths and limitations Our study has several key strengths that contribute to the robustness of our findings. First, extensive and comprehensive population-based healthcare registries are a major strength. The nationwide Danish registries are known for their high quality, accuracy, and completeness [ 5 , 16 , 19 , 26 ]. The broad data coverage lowers the risk of information and selection bias. Since the data were collected independently of this study and not reliant on the recollection of GPs or the study population, bias related to diagnosis and healthcare services is deemed minimal. Furthermore, the information on healthcare services provided in general practice is considered valid since their registration forms the basis for reimbursements [ 5 ]. By matching on age, sex, calendar time, and general practice affiliation, we substantially reduced confounding from these factors. This approach ensures that any observed differences are more likely driven by FH-related variables or intermediate influences, such as health behaviours or unadjusted comorbidities along the causal pathway (e.g., ischemic-related conditions). Nonetheless, the higher prevalence of residual circulatory diseases in the FH group (11.7% vs. 5.8% in the reference group) raises the possibility that comorbid conditions may confound or mediate the association between healthcare utilisation and FH diagnosis. To explore this, we conducted sensitivity analyses using covariate adjustment and restriction to assess the impact of these circulatory conditions. These adjustments did not meaningfully alter the IRRs (results not shown). However, some limitations must be considered. Outcomes were reported as the mean number of activities in 12-month spans, five years before the index date. While this approach provides a clear comparison between groups, it does not capture individual-level variation. Consequently, results should be interpreted with the notion that aggregated measures may oversimplify healthcare use and overlook potential heterogeneity at the individual patient level. The Danish healthcare registries do not capture detailed clinical information, such as the specific indications for consultations or the rationale or interpretation behind diagnostic tests like LDL-C and ECGs. The ECG tests were included as indicators of relevant diagnostic investigations and considerations made in general practice, although they are not specific to FH diagnostics. Interpretive caution is warranted in the period immediately preceding diagnosis, as increased healthcare utilisation may reflect pre-diagnostic activity. The rise may reflect a combination of evaluative and therapeutic processes, including investigation of elevated LDL-C levels at referral or waiting period for specialist assessment. We were unable to distinguish between genetically confirmed FH and clinically defined phenotypic FH, therefore the cohort includes patients with polygenic hypercholesterolaemia, introducing diagnostic heterogeneity. Even with our matching process, there may still be unmeasured factors from residual confounding that could influence the observed outcomes. Comparison with existing literature This is the first study to investigate healthcare activities before a formal FH diagnosis. The difference in healthcare activity between the groups underscores the challenges of diagnosing FH in general practice. We observed more frequent consultations, LDL-C tests, and Risk LDL-C levels for several years prior to an FH diagnosis. Notably, the Risk LDL-C IRRs were consistently high at around 25, escalating markedly in the year before diagnosis (IRR 68.68, 95% CI (58.97–79.99)). This potential lack of FH awareness mirrors other findings, and a recent study [ 13 ] identified a knowledge gap among Dutch GPs regarding FH. In the Netherlands, a country recognised for its FH screening programs, many GPs struggled with understanding the prevalence, heritability, and cardiovascular risks associated with FH. Comparisons between the two groups suggest that diagnostic opportunities in general practice may be underutilised. Our findings indicate that FH identification remains largely reactive, with testing and consultations only intensifying over the study period. Brett et al. [ 11 ] demonstrated the value of a GP-led screening program in Australia, which employed a data extraction tool to identify high-risk individuals. Their model significantly enhanced FH detection and management. In our study, ASCVD-related procedures (e.g., coronary CT) and hospitalisations for IHD occurred more frequently in the FH group than in the reference group before the formal FH diagnosis. These findings underscore the already recognised challenge that ASCVD often manifests before FH is formally diagnosed, highlighting the need for earlier detection and intervention. This aligns with data from a large U.S. study [ 27 ], which reported that up to 38% of FH patients in the CASCADE-FH Registry had an ASCVD diagnosis before receiving a formal FH diagnosis. Our findings indicate that although GPs routinely recognise and treat hypercholesterolaemia with statins, they often fail to assess patients promptly for FH. This delay hinders targeted, long-term management and opportunities for cascade screening among relatives. These results align with a Danish study by Mülverstedt et al. [ 8 ], in which only three of 34 individuals with probable or definite FH were correctly diagnosed in general practice. Such under-recognition underscores the need for greater awareness of elevated LDL-C levels, early onset CVD and family history of early CVD and their clinical implications for FH in primary care. Targeted education for GPs on FH risk factors could improve early detection and reduce the burden of ASCVD. Implications for research and practice The known underdiagnosis of FH internationally [ 28 ] highlights the need for more proactive, systematic screening approaches [ 29 , 30 ]. Implementing GP-led programs, such as those evaluated by Brett et al., would enable earlier identification of at-risk individuals, particularly if supported by electronic health records identification tools and follow-up outreach [ 11 , 31 ]. Our results support that improved awareness in general practice is essential to ensure timely diagnosis and management of FH, which could significantly reduce the risk of premature ASCVD and improve patient outcomes [ 32 ]. Conclusion Our study found that future FH patients had consistently higher rates of specific healthcare activities than the reference group. Our study indicates an opportunity to diagnose FH earlier in general practice, with frequent consultations and increasing healthcare engagement in the years leading up to diagnosis. Our findings show that GPs performed more specific healthcare activities, such as LDL-C testing and consultations in the FH group, but these activities may be diagnostically underutilised. Our findings show that GPs consistently prescribed statins during the five-year period, interpreted as a proactive and pragmatic approach to mitigating cardiovascular risk before a formal FH diagnosis. Our results indicate that general practice is an appropriate platform for identification interventions and implies earlier opportunities for FH diagnosis. Future studies should explore dynamics and reasoning at the consultation level, including how GPs perceive their role in FH identification and management. Supplementary Information 12875_2026_3256_MOESM1_ESM.docx (41.3KB, docx) Supplementary Material 1. Table 1A and Table 1B: All yearly rates and Incidence rate ratios with 95% confidence intervals for all outcomes performed in the five years before an FH diagnosis compared to the reference group in general practice and secondary care. The outcome Risk LDL-C was defined as LDL-C ≥5.0 mmol/L in cohortees aged ≥40 years and ≥4.0 mmol/L in individuals aged 18–39 years. Acknowledgements None. Abbreviations ASCVD Atherosclerotic cardiovascular disease ACS Acute coronary syndrome CAG Coronary angiogram CI Confidence Interval DCRS Danish civil registration system DNPR Danish National Prescription Registry ECG Electrocardiogram FH Familial hypercholesterolemia GP General Practitioner ICD-10 International Classification of Diseases, 10th revision IRR Incidence rate ratio LDL-C Low-Density Lipoprotein Cholesterol NPR National Patient Register Authors’ contributions All authors contributed to the conception or design of the study. HSP acquired the data and managed the database together with SG. HSP performed statistical analyses. SG drafted the manuscript under the supervision of HSP, KH, and BC. All authors critically revised the manuscript. All authors gave final approval and agreed to be accountable for all aspects of the work, ensuring integrity and accuracy. Funding SG was funded by unrestricted grants from the Lilly and Herbert Foundation, The Carpenter Sophus Jacobsen and Wife Astrid Jacobsen Foundation, The Lecbech Sørensen Foundation, The Karl G. Andersen Foundation, The KiAP Organisation (Kvalitet I Almen Praksis organisation), and the General Practice Research Foundation of the Central Denmark Region (Region Midtjyllands Praksisforskningsfond). All authors were independent of the funders, who had no role in the design, analyses, or decision to publish. Data availability In accordance with Danish regulations, all data were stored at Statistics Denmark on secure servers. Hence, the data supporting the findings of this study are not publicly available in accordance with Danish research regulations. The corresponding author can be contacted for further information. Declarations Ethics approval and consent to participate The study is part of the project ID 707253, which is recorded in the research database at the Research Unit for General Practice Aarhus (ID: 704858) in accordance with the Danish regulations on data protection and the General Data Protection Regulation (GDPR) of the European Union. According to Danish law, approval from the Committee on Health Research Ethics in the Central Denmark Region was not required because no biomedical intervention was performed. Statistics Denmark approved the project and the registers used in the study. According to the Danish Data Protection Act, no patient consent was required because scientific studies of significant societal importance are exempt from this requirement. Consent for publication Register-based studies need no consent for publication from included patients according to the Danish Data Protection Act, as stated above. 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Data Availability Statement In accordance with Danish regulations, all data were stored at Statistics Denmark on secure servers. Hence, the data supporting the findings of this study are not publicly available in accordance with Danish research regulations. The corresponding author can be contacted for further information. 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