Rare Disease Research Partnership (RAinDRoP): a collaborative approach to identify research priorities for rare diseases in Ireland

Somanadhan, Suja; Nicholson, Emma; Dorris, Emma R.; Brinkley, Aoife; Kennan, Avril; Treacy, Eileen P.; Atif, Awan; Ennis, Sean; McGrath, Vicky; Mitchell, Derick; O’Sullivan, Grace; Power, Julie; Lawlor, Anne; Harkin, Paul; Lynch, Sally Ann; Watt, Philip; Daly, Avril; Donnelly, Susie; Kroll, Thilo

doi:10.12688/hrbopenres.13017.2

Cited by 10 publications

(13 citation statements)

References 19 publications

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“…Achieving international consensus on care pathway design methodology is complicated by the heterogeneity of national healthcare systems. However, it is agreed that co-design with patient partners is essential [ 25 , 26 ]. ‘RarERN Path’ has defined a model for care pathway development that is based on capturing existing practice through a narrative medicine approach and achieving patient, carer and HCP consensus on an optimized pathway [ 27 ].…”

Section: Introductionmentioning

confidence: 99%

Designing rare disease care pathways in the Republic of Ireland: a co-operative model

Ward

Murphy

Marron

et al. 2022

Orphanet J Rare Dis

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Background Rare diseases (RDs) are often complex, serious, chronic and multi-systemic conditions, associated with physical, sensory and intellectual disability. Patients require follow-up management from multiple medical specialists and health and social care professionals involving a high level of integrated care, service coordination and specified care pathways. Methods and objectives This pilot study aimed to explore the best approach for developing national RD care pathways in the Irish healthcare system in the context of a lack of agreed methodology. Irish clinical specialists and patient/lived experience experts were asked to map existing practice against evidence-based clinical practice guidelines (CPGs) and best practice recommendations from the European Reference Networks (ERNs) to develop optimal care pathways. The study focused on the more prevalent, multisystemic rare conditions that require multidisciplinary care, services, supports and therapeutic interventions. Results 29 rare conditions were selected across 18 ERNs, for care pathway development. Multidisciplinary input from multiple specialisms was relevant for all pathways. A high level of engagement was experienced from clinical leads and patient organisations. CPGs were identified for 26 of the conditions. Nurse specialist, Psychology, Medical Social Work and Database Manager roles were deemed essential for all care pathways. Access to the therapeutic Health Service Professionals: Physiotherapy, Occupational Therapy, and Speech and Language Therapy were seen as key requirements for holistic care. Genetic counselling was highlighted as a core discipline in 27 pathways demonstrating the importance of access to Clinical Genetics services for many people with RDs. Conclusions This study proposes a methodology for Irish RD care pathway development, in collaboration with patient/service user advocates. Common RD patient needs and health care professional interventions across all pathways were identified. Key RD stakeholders have endorsed this national care pathway initiative. Future research focused on the implementation of such care pathways is a priority.

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Section: Introductionmentioning

confidence: 99%

Designing rare disease care pathways in the Republic of Ireland: a co-operative model

Ward

Murphy

Marron

et al. 2022

Orphanet J Rare Dis

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“…Rare diseases (RD) are individually rare but collectively common [1], with an estimated 6000-8000 RD they affect 3.5-5.9% of the population or 263-446 million persons globally [2]. RD are heterogeneous in aetiology, frequently chronic and debilitating [3].…”

Section: Introductionmentioning

confidence: 99%

Is it possible to implement a rare disease case-finding tool in primary care? A UK-based pilot study

Buendia

Shankar

Mahon

et al. 2022

Orphanet J Rare Dis

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Introduction This study implemented MendelScan, a primary care rare disease case-finding tool, into a UK National Health Service population. Rare disease diagnosis is challenging due to disease complexity and low physician awareness. The 2021 UK Rare Diseases Framework highlights as a key priority the need for faster diagnosis to improve clinical outcomes. Methods and results A UK primary care locality with 68,705 patients was examined. MendelScan encodes diagnostic/screening criteria for multiple rare diseases, mapping clinical terms to appropriate SNOMED CT codes (UK primary care standardised clinical terminology) to create digital algorithms. These algorithms were applied to a pseudo-anonymised structured data extract of the electronic health records (EHR) in this locality to "flag" at-risk patients who may require further evaluation. All flagged patients then underwent internal clinical review (a doctor reviewing each EHR flagged by the algorithm, removing all cases with a clear diagnosis/diagnoses that explains the clinical features that led to the patient being flagged); for those that passed this review, a report was returned to their GP. 55 of 76 disease criteria flagged at least one patient. 227 (0.33%) of the total 68,705 of EHR were flagged; 18 EHR were already diagnosed with the disease (the highlighted EHR had a diagnostic code for the same RD it was screened for, e.g. Behcet’s disease algorithm identifying an EHR with a SNOMED CT code Behcet's disease). 75/227 (33%) EHR passed our internal review. Thirty-six reports were returned to the GP. Feedback was available for 28/36 of the reports sent. GP categorised nine reports as "Reasonable possible diagnosis" (advance for investigation), six reports as "diagnosis has already been excluded", ten reports as "patient has a clear alternative aetiology", and three reports as "Other" (patient left study locality, unable to re-identify accurately). All the 9 cases considered as "reasonable possible diagnosis" had further evaluation. Conclusions This pilot demonstrates that implementing such a tool is feasible at a population level. The case-finding tool identified credible cases which were subsequently referred for further investigation. Future work includes performance-based validation studies of diagnostic algorithms and the scalability of the tool.

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“…Rare diseases (RD) are individually rare but collectively common [1], with an estimated of 6,000-8000 RD and affecting 3.5-5.9% or 263-446 million persons globally [2]. RD are heterogeneous in aetiology, frequently chronic and debilitating [3].…”

Section: Introductionmentioning

confidence: 99%

Is It Possible to Implement a Rare Disease Case-finding Tool in Primary Care? A UK-based Pilot Study

Buendia¹,

Shankar²,

Mahon³

et al. 2021

Preprint

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Introduction:This study implemented MendelScan, a primary care rare disease case-finding tool, into a UK NHS population. Rare disease diagnosis is challenging due to disease complexity and low physician awareness. The 2021 UK Rare Diseases Framework highlights a global need for faster diagnosis to improve clinical outcomes as a key priority.Methods & Results:A UK primary care locality with 68,705 patients was examined. MendelScan encodes diagnostic/screening criteria for multiple rare diseases, mapping clinical terms to appropriate SNOMED CT codes (UK primary care standardised clinical terminology) to create digital algorithms. These algorithms were applied to a pseudo-anonymised structured data extract of the electronic health records (EHR) in this locality to "flag" at-risk patients who may require further evaluation. All flagged patients then underwent internal clinical review; for those that passed this review, a report was returned to their GP. 55 of 76 disease criteria flagged at least one patient. 227 (0.33% of the total population) patients were flagged; 18 EHR were already diagnosed with the disease. 75/227 (33%) passed our internal review. Thirty-six reports were returned to the GP. Feedback was available for 28/36 of the reports sent. GP categorised nine reports as "Reasonable possible diagnosis" (advance for investigation), six reports as "diagnosis has already been excluded", ten reports as "patient has a clear alternative aetiology", and three reports as "Other" (patient left study locality, unable to reidentify accurately). All the 9 cases considered as "reasonable possible diagnosis" had a further actionable evaluation.Conclusions:This pilot demonstrates that implementing such a tool is feasible at a population level in an ethical, technical and efficient manner. The case-finding tool identified credible cases which were subsequently referred for further investigation. Future work includes performance-based validation studies of diagnostic algorithms and the scalability of the tool.

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Rare Disease Research Partnership (RAinDRoP): a collaborative approach to identify research priorities for rare diseases in Ireland

Cited by 10 publications

References 19 publications

Designing rare disease care pathways in the Republic of Ireland: a co-operative model

Designing rare disease care pathways in the Republic of Ireland: a co-operative model

Is it possible to implement a rare disease case-finding tool in primary care? A UK-based pilot study

Is It Possible to Implement a Rare Disease Case-finding Tool in Primary Care? A UK-based Pilot Study

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