Clinical Decision Support for Familial Hypercholesterolemia

Study Overview
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Brief Summary
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A cluster randomized study in the primary care setting to evaluate a computer-based clinical decision support system to aid in the identification and management of patients with FH. The primary outcome of the study is the number of patients diagnosed with FH at thirty months after study initiation.

Detailed Description
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Familial Hypercholesterolemia (FH) is a common cause of premature coronary artery disease (CAD). The prevalence of heterozygous FH has been estimated to be 1 in 500, but recent studies estimate that the prevalence might be as high as 1 in 200. FH is an autosomal-dominant genetic disorder caused by defects in the hepatic uptake and degradation of LDL, primarily due to mutations in the genes coding for the LDL receptor, apolipoprotein B (APOB), proprotein convertase subtilisin kexin type 9 (PCSK9), or LDL-receptor associated protein 1 (LDLRAP1), resulting in high levels of LDL-C and total cholesterol . As a consequence, patients with heterozygous FH have a significantly increased risk of developing premature coronary artery disease (CAD). FH is both underdiagnosed and undertreated, and it is estimated that only a few percent of patients are diagnosed adequately. In Sweden there are no official figures regarding the prevalence of FH, but the patient association for FH recently published a report estimating that only 21 % of the patients in Sweden have been diagnosed. Early treatment with lifestyle changes and high doses of statins has been shown to be effective in reducing the risk of cardiovascular disease, reducing the risk of CAD with 40 - 70 % or more in treated individuals as compared to not treated. The diagnosis of FH has traditionally been based on a combination of clinical signs, family history and cholesterol concentrations. Recently more emphasis has been placed on genetic testing for establishing definitive diagnosis. In Sweden the long-term aim is to diagnose 80 % of all individuals with FH by 2025 according to the National Guidelines for Cardiac Care 2015 published by The Swedish National Board of Health and Welfare. Clinical decision support (CDS) systems have shown promising results in improving healthcare performance, but results are still conflicting and some studies have not been able to find any clear improvement in quality of care or patient outcomes. Computer-based CDS systems have previously been implemented to aid in the identification and management of patients with FH. The results from these studies are promising; however, to the best of our knowledge, no randomized controlled trial has been conducted investigating the effects of a computer-based CDS in FH. Clinical decision support (CDS) systems are tools that can be used to raise awareness of specific conditions, leading to more individuals being diagnosed and treated in accordance to guidelines. Clinical decision support for Familial hypercholesterolemia (CDS-FH) is a cluster randomized trial that will be conducted in the primary care setting in the county of Östergötland, Sweden. The primary care clinics participating in the study will be randomized 1:1 to CDS intervention or to control. Before the study is initiated all of the physicians working at the participating primary care clinics will receive information regarding FH and the associated risk for cardiovascular disease. Information regarding the study, FH and technical aspects of CDS-FH will be available for the participating physicians throughout the entire study period. The investigators intend to include all primary care clinics in the County of Östergötland (n = 45). Participation is non-compulsory. The population in the County of Östergötland is 467 158 inhabitants (December 2020). The CDS-FH has been developed in collaboration between Cambio Healthcare systems and Evry Healthcare Systems (the suppliers of the EHR in the county of Östergötland), the Cardiology Department at Linköping University hospital, Uppsala University and primary care professionals in the counties of Östergötland. CDS-FH is activated when a physician attests a cholesterol lab result in the laboratory section of the EHR. If the patient has high levels of total cholesterol or LDL-C (Total cholesterol > 8 mmol/l or LDL-C > 5.5 mmol/l, adjusted for age strata and ongoing treatment with cholesterol lowering medications), in combination with other risk factors for FH (according to the Dutch Lipid Clinic Network (DLCN) criteria), a screen warning will appear informing the responsible physician that the patient may have FH. On the other hand, if the patient does not have elevated levels of total cholesterol or LDL-C, or if any exclusion criteria are met, no screen warning will appear when the cholesterol lab-result is attested. By clicking on the warning screen that was activated due to high cholesterol levels, a window will open displaying an overview of the patient's cholesterol values and prior diagnoses recorded in the EHR that are consistent with premature CAD. A link to further information regarding FH from the Swedish National Board of Health and Welfare is also provided. The physician is thereafter urged to consider sending a referral to the local FH clinic, and to prescribe or intensify treatment with lipid lowering medication. The referral is automatically generated by the CDS application and the CDS also makes a short note in the EHR regarding the suspicion of FH. The physician can chose to postpone the decision or make a decision to refrain from sending the referral. In case the choice is made to refrain from sending the referral the physician is asked to specify why in a mandatory short text comment, in order to monitor the main reasons for not continuing the investigation of suspected FH. The FH clinic will receive all the referrals generated by the CDS-FH and all referrals generated as part of the regular routine in the region. All patients diagnosed with FH at the FH-clinic will be registered and assigned to either the CDS intervention group or to the control group. Any relatives currently residing in the County of Östergötland or in the County of Uppsala that are diagnosed with FH as a result of cascade screening will also be registered at the FH-clinic and assigned to either the CDS intervention group or to the control group. The primary outcome of the study is the number of probands (index patients) diagnosed with FH at thirty-four months after study initiation.

Official Title
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Clinical Decision Support for Familial Hypercholesterolemia: A Cluster Randomized Trial in the Primary Care Setting

Conditions
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Hypercholesterolemia, Familial, Clinical Decision Support

Intervention / Treatment
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* Other: Clinical decision support


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria Primary care centers in the county of Östergötland. Exclusion Criteria Primary care centers not using the Cambio Cosmic Electronic Health Record System.

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 80 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Diagnostic
Allocation: Randomized
Intervention Model: Parallel Assignment
Interventional Model Description: Cluster randomized in the primary care setting
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Intervention group<br>Group receiving the Clinical decision support | Other: Clinical decision support<br>* Computer-based support tool for identification of patients with high levels of total cholesterol or LDL-C, at high risk of being affected by FH.<br>|
| No Intervention: Control group<br>Group receiving standard care | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| The number of patients diagnosed with FH (ICD E78.0A) at thirty months after study initiation | The number of probands (index patients) diagnosed with FH (ICD E78.0A) at thirty months after study initiation.The diagnosis of FH will be based on the Dutch Lipid Clinic Network (DLCN) criteria. All patients found to have definite or probable FH according to the DLCN criteria will be diagnosed with FH. This endpoint excludes patients diagnosed secondary to cascade screening. | 30 months after study initiation | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Number of patients diagnosed with FH (ICD E78.0A) based on genetic testing. | We will investigate the number of patients diagnosed with FH based on the presence of a pathogenic FH-causing mutation and evaluate a possible difference between the CDS intervention group and the control group. | 30 months after study initiation | 
| Number of patients diagnosed with FH (ICD E78.0A) including cascade screening. | To evaluate the full effect of the intervention we will investigate the number of patients diagnosed with FH including any relatives to the proband that are diagnosed secondary to cascade screening. The cascade screening will continue in parallel with the inclusion of new probands throughout the study period. | 30 months after study initiation | 
| Cost-effectiveness of using the Clinical decision support for Familial hypercholesterolemia | We will calculate the cost of implementation and usage of the CDS-FH as well as annual fees and costs related to administration of the CDS-FH. The costs-effectiveness will then be calculated in relation to the potential cost-reducing long-term effects of improvements in the identification and management of FH patients. | 30 months after study initiation | 
| Reasons for deviation | We will investigate the main reasons for not sending a referral to the FH-clinic when recommended to do so by the CDS. The mandatory question in the CDS system regarding the reason for refraining from sending the referral will be analysed to identify the main reasons stated by the physicians. | 30 months after study initiation | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Hypercholesterolemia, Familial, Primary care, Clinical decision support