Danny Decision Support for FH

Empowering physicians
to reinforce early FH identification
to improve future patient outcomes

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Familial hypercholesterolemia (FH) is a common genetic disorder with often delayed diagnosis. However, the risks for patients affected are enormous.

The condition is triggered by high levels of LDL-cholesterol in the blood (also known as “bad” cholesterol) and can cause serious cardiovascular events. Patients with FH are twice as likely to have a heart attack before the age of 50. Timely diagnosis is a challenge. With systematic screening, the early identification of FH would improve patients’ treatment and outcomes. 

Sqilline has developed a special algorithm in Danny Platform to identify FH in patients with acute cardiovascular events during hospitalization.

Danny Decision Support for FH is programmed to calculate test results result following the Dutch Lipid Clinic Network (DLCN) score and inform physicians about a possible, probable, and definitive FH diagnosis.

Its main objective is to structure and filter information, so the physicians only analyze data relevant to the specific case.

Danny Decision Support Application for FH empowers physicians with a clinical decision support application to improve systematic screening during hospitalization.



  • Extensive computing power and NLP algorithms structure and filter EHR data to support physicians in improving early FH diagnosis by identifying patients with arcus cornealis, tendon xanthoma, or stated FH 

Accelerate Diagnosis

  • The application prompts physicians to review abnormal Dutch Score calculation while the patient is still hospitalized (limited to 48-72 h)
  • Physicians then make further test to make final conclusions

App Integration

  • Can be installed on-premises at every EHR system

Operating System

  • Danny Decision Support application for FH runs on iOS, Android and any web client version


Identification of high-risk FH patients
  • Hospitalized patient's daily list view 
  • Highlight abnormal cases
Automated process
  • NLP algorithm searches for patients with arcus Cornealis, tendon xanthoma, or stated FH
Dutch Score Calculation
  • Integrated Dutch Score calculator
  • Automatic calculation of Duch Score value  
  • Physician acceptance of suggestion necessary as a final step

Use Cases


Danny Decision Support for FH empowers physicians with evidence-based data technology to screen and identify FH in patients during hospitalization.
It provides structured visualization of clinical data to support the physician's workflow, assist in early diagnosis and timely treatment, reduce medical errors and overlooked items and contain costs. Screening for FH during hospitalization may allow for rapid and effective lipid management, prevention of recurrent events and reducing the burden on the healthcare system.


Danny Decision Support for FH enables pharmaceutical companies to better track and to uncover patient pathways on a statistical level of high risk for Familial hypercholesterolemia. It provides epidemiological analysis, patient profile for specific patient group and better RWE insights of patients’ pathway.


Danny Decision Support for FH accelerates the path to medical diagnosis for patients during hospitalization. Earlier diagnosis combined with ontime treatment can be crucial for easing the life of patients and their families. Identifying hard-to-diagnose diseases using AI and ML learning models are completely beneficial for patients.

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Danny Decision Support for FH

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