Clinical Ontologies Improve Case Finding of Primary Biliary Cholangitis in UK Primary and Secondary Care

Algorithmic approach to finding people with multiple sclerosis using routine healthcare data in Wales

BACKGROUND

Identification of multiple sclerosis (MS) cases in routine healthcare data repositories remains challenging. MS can have a protracted diagnostic process and is rarely identified as a primary reason for admission to the hospital. Difficulties in identification are compounded in systems that do not include insurance or payer information concerning drug treatments or non-notifiable disease.

AIM

To develop an algorithm to reliably identify MS cases within a national health data bank.

METHOD

Retrospective analysis of the Secure Anonymised Information Linkage (SAIL) databank was used to identify MS cases using a novel algorithm. Sensitivity and specificity were tested using two existing independent MS datasets, one clinically validated and population-based and a second from a self-registered MS national registry.

RESULTS

From 4 757 428 records, the algorithm identified 6194 living cases of MS within Wales on 31 December 2020 (prevalence 221.65 (95% CI 216.17 to 227.24) per 100 000). Case-finding sensitivity and specificity were 96.8% and 99.9% for the clinically validated population-based cohort and sensitivity was 96.7% for the self-declared registry population.

DISCUSSION

The algorithm successfully identified MS cases within the SAIL databank with high sensitivity and specificity, verified by two independent populations and has important utility in large-scale epidemiological studies of MS.

Defining and characterising a toolkit for the development of a successful European registry for rare liver diseases: a model for building a rare disease registry

INTRODUCTION

A rare disease is defined by the European Health Commission as a disorder affecting less than 5/10,000 of the population. There are at least 20 rare liver diseases (RLDs) seen frequently in the adult and paediatric liver clinic, signifying that the hepatology community can be influential in developing such patient databases for registering patients with rare hepatic conditions. The aim of this review was, first, to identify registries for RLDs in Europe, and, second, to design a universal blueprint for the development of a registry for RLD by using lessons learnt from the European registries that have already been established.

METHODS

We searched PubMed, Google Scholar and clinicaltrials.gov using the MESH terms 'registries', 'database management systems', 'database' and the non-MESH terms 'database$', 'registry', 'repository' and 'repositories'. We only included studies in English from countries/consortia of the European Union (EU). Our literature search was performed in 2020.

RESULTS

We identified 37 registries for RLDs in Europe. Using information from the design of these registries we designed a blueprint for the development of a patient registry for an RLD consisting of a theoretical, technical and maintenance phase.

DISCUSSION

It is believed that rare diseases may affect as much as 6-8% of the EU population across its 28 member states. Here we have provided a toolkit for designing a registry for an RLD. Our article will complement the efforts of loco-regional, national and international groups seeking to establish robust systems for data collection and analysis for orphan liver diseases.