We are a UK-based digital health company dedicated to shortening the path to diagnosis of patients affected by rare and hard to diagnosis diseases. MendelScan, our primary care case finding tool, helps doctors identify rare disease patients earlier.

Rare diseases are individually rare but collectively common affecting 1 in 17 people during their lifetime, similar to asthma. Rare diseases can present with a range of complex, and apparently disconnected symptoms spread across different organ systems and the life of the patient. This makes them difficult to diagnose, creating a diagnostic odyssey that is both burdensome and costly to patients, families, doctors, and healthcare providers. We work with the NHS and other organisations to support clinicians to get their patients on the right diagnostic pathway.

Our aim is to build a future where every patient can expect the right treatment, from the right specialist, at the right time.

Read our manifesto here

Mendelian is a team of clinicians, including GPs, computer scientists and health economists. We have worked with a range of primary care organisations, GP practices, federations, PCNs and CCGs across the UK.

We have established contractual agreements with primary care organisations representing more than 900,000 patients and have NHS England funded projects in conjunction with two genetic medicine service alliances (GMSA).

This has led us to having a deep understanding of the NHS, primary care organisations and ways of working, as well as the necessary information governance considerations.

The Mendelian Team

We run through a rigorous process before adopting and implementing a disease criteria in our suite of diseases searched for.

1)The first step in criteria development is reviewing the literature in a disease area.

2) We then score the disease for its suitability for such an approach. Incorporating insights from the literature, the mendelian clinical team and disease experts.

3) When we identify a suitable diagnostic or suspicion criteria we assess this criteria against a set framework.

3) If the criteria meets our accepted level, then we digitise the criteria, mapping clinical terms to the coded terms that would be used to describe each feature in the EHR. This is performed by a clinician experienced with primary care EHR and then reviewed by another clinician.

4) The criteria is then applied in an anonymised data set to assess its performance with known cases. For diseases that have a very low frequency, where there are too few cases in anonymised data sets, the criteria is validated by a disease expert reviewing the flagged cases for their suitability.

5) As we return cases we continue to evaluate the performance, suitability of flagged cases. We have two measures for this. Firstly those advanced by their GP for further investigation and referral, and secondly those that actually receive the proposed diagnosis.

Yes! Patients are central to everything we do. Our relationships with the patient groups ensures we stay connected to patient challenges, needs, and values. This includes hearing from affected patients at our weekly mendelian team meeting, and partnering with patient advocacy groups on several projects. We are always keen to speak with patients who have an interest in what we are doing.

MendelScan is a digital platform that uses structured data (no free text) integrating with a range of sources of health care data (incl EMIS and TPP electronic health records). MendelScan enables structured data to be analysed, with those at risk of rare diseases identified and patient specific reports generated. This information is then sent confidentially back to their GP to review, empowering the GP with details of the appropriate referral pathway.. The patient is not flagged as a pop up in their EHR, and the report can be reviewed at a time suitable to the clinician and practices needs and demands.

MendelScan enables the identification of rare disease patients earlier, improving their care and access to treatments. Earlier diagnosis also reduces health care utilisation in primary care.

A retrospective analysis of the primary care records of 348 patients diagnosed with 1 of 9 rare disorders highlighted that MendelScan could have identified 37 of these patients earlier than standard care, the time saving on average, for these patients was 4.4 years (range 2-7 years).

Healthcare resource utilisation:

By diagnosing these patients 4 years earlier, we can avoid on average per patient:

• 19 Tier- 1 tests (Routine blood tests)
• 3 Tier -2 tests (immunologic, serologic tests, diagnostic imaging)
• 9 clinical visits (appointments with, nurses, pharmacists, HCA and other primary care practitioners)
• 3 referrals (specialist referrals)
• 8 GP appointments or 80 min of GP appointments

This equates to a primary care cost saving of £837 per patient.

Secondary care healthcare utilisation savings are currently under investigation.

This is designed to be of minimal burden to the practice team.

We need an administrative point of contact to ensure reports are returned to the correct person and the re-identification process is seamless and straightforward.

The identified clinician reviewing the cases will need to engage with a brief explanation of the process, including how to feedback their experience and patient outcomes to Mendelian.

Support from Mendelian will be present throughout this process.This is designed to be of minimal burden to the practice team.

We need an administrative point of contact to ensure reports are returned to the correct person and the re-identification process is seamless and straightforward.

The identified clinician reviewing the cases will need to engage with a brief explanation of the process, including how to feedback their experience and patient outcomes to Mendelian.

Support from Mendelian will be present throughout this process.

Alpa-1-antitrypsin deficiency

Behcets disease

Common variable inmmunodeficiency

Dermatomyositis

Fibrodysplasia ossificans progressiva

Good syndrome

Hereditary angioedema

Hereditary hemorragic telangectasia

Loeys-Dietz syndrome

Lynch syndrome

Turner syndrome

Di George syndrome (22q11 deletion)

Ehlers-Danlos syndrome

Marfan syndrome

Neuro endocrine tumors - Midgut - Functional

Niemann-Pick C disease

Wiskott aldrich syndrome

X-linked agammaglobulinemia

(NB This list is being constantly updated)

All members of Mendelian are aware of our information governance responsibilities. MendelScan is an MHRA registered medical device (ref no: 11233). We have established data sharing agreements (DSA) and data protection impact assessments (DPIA) with NHS organisations with more than 900,000 patients. Mendelian is also an EMIS approved partner company, having passed their data processing testing procedures.

We are compliant withDSPT.

Mendelian is:

• Aware and compliant with Caldicott principles.
• Most pertinently deals with pseudo-anonymised patient structured data only. Re-identification can only be performed at the level of the primary care organisation caring for the patient.
• Access to this information is restricted to the data and clinical team at Mendelian who are aware of their responsibilities.
• Access to personal data in the context we use it is legal and compliant with the Data Protection Act (2018)/GDPR. The legal basis:
• GDPR Article 6 1(e) Necessary for performance of a task carried in public interest.
• GDPR Article 9 2(h). Necessary for provision of health and/or social care, including preventative medicine.
• Data is stored securely and only kept for the purpose and duration of the project.
• Data is transferred securely.

·Data is disposed of securely at the end of the project.

We require a structured (no free text) data extract of pseudo-anonymised data for all patients who have not opted out of data sharing through the national data opt out.

We have processes and systems in place to do this via EHR providers, and have also extracted data via third party population health organisations. We have straightforward data sharing agreements and data processing impact assessment templates, to enable smooth adoption.

As many of the diseases we search for have clinical features not only spread across the patient’s biology (multisystemic diseases) but also their lifetime, we require as complete as structured data cut that is available for each patient. Obviously we are aware there are limitations to the amount and duration of structured data available but we need as much of the data extract as is possible for our approach to work

Data is stored securely, and only kept for the purpose and duration of the project.

Mendelian develops, maintains and operates the MendelScan platform which runs on Amazon Web Services (AWS) public cloud. Both Mendelian and AWS are DSPT compliant.

Data is transferred securely and at the end of the project disposed of securely.