Lucinda Hiam

Background: The migration status of the 9.8 million migrants living in England is not consistently recorded in primary care electronic health records (EHRs). Codelist approaches enable creation of cohorts of individuals who have had a predefined, optional migration-related code (for example, ‘refugee’) added to their EHR. Aim: To explore the use of migration-related Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) codes to inform future research using primary care data. Design & setting: We used our OpenCodeCounts tool to explore data published by NHS England on SNOMED CT code usage in English primary care. Method: We created migration-related codelists and described their use from 1 August 2011 to 31 July 2025. To understand code usage in the context of known information on migrants in England, we compared code usage with trends in migration-related statistics from the Home Office and the 2021 census. Results: There were 34.2 million uses of 1119 migration-related codes from 2011–2025. Migration-related coding increased over time, generally exceeding the increase observed for coding overall, with a sharp increase from 2020, particularly for country of birth and language. Language-related coding represented 65% of code usage, and where country of birth was recorded there was mixed agreement with the 2021 census. Coding of immigration legal statuses was low and overwhelmingly about asylum or refugee status. Conclusion: Utilising OpenCodeCounts, we demonstrate the feasibility of using migration-related SNOMED CT codelists within primary care EHRs and highlight some of the potential biases that cohorts created based on these codelists may have to inform future research.

Objectives: To examine all-cause mortality differences among migrants from different countries/regions compared with native-born populations in England and Wales from 2007 to 2021 and assess whether migrant mortality patterns converge with or diverge from native-born trends over the study period. Design: Descriptive, observational study analysing mortality trends over a 15-year period. Setting: England and Wales, using national mortality records and Census data. Participants: The study included all recorded deaths in England and Wales from 2007 to 2021, stratified by sex and country/region of birth. Main outcome measures: European age-standardised rates (EASRs) and standardised mortality ratios (SMRs) for all-cause mortality, with and without COVID-19-related deaths. Linear regressions were used to assess mortality trends over time. Results: Mortality patterns varied significantly by country/region of birth. While most migrant groups had lower mortality rates than the native-born population at the beginning of the study period, this advantage declined for many in recent years. Migrants from Ireland, Scotland and Northern Ireland exhibited consistently worse mortality outcomes. Excluding COVID-19 deaths, 14 out of 19 migrant groups retained a mortality advantage, though trends indicate substantial heterogeneity. Some migrant groups, particularly from North and Central America and parts of Europe, showed improving mortality rates, whereas others, such as those from Bangladesh, converged towards native-born mortality levels. Conclusions: Despite lacking data on individual-level factors (e.g. duration of residence, socio-economic status and co-morbidities), this national-level study demonstrates important trends in migrant mortality. The findings highlight the urgent need for improved data to capture migration-related variables and enable a deeper understanding of the drivers behind observed trends. The decline in migrant mortality advantage over time for some groups highlights the importance of monitoring structural health inequalities and can inform targeted public health policies and more granular future research.

Background: The migration status of the 9.8 million migrants living in England is not systematically recorded in primary care electronic health records (EHRs). Codelist approaches enable us to create cohorts of individuals who have had a predefined, optional migration-related code (e.g. “refugee”) added to their EHR. Aims: We aimed to explore the use of migration-related SNOMED CT codes to inform future research using primary care data. Design and Setting: We used our Open Code Counts tool and R package to explore data published by NHS England on SNOMED CT code usage in English primary care. Method: We created migration-related codelists and described their use from 1st August 2011 to 31st July 2024. We compared code usage to trends in migration-related statistics from the Home Office and the 2021 Census. Results: There were 29.1 million uses of 1,114 migration-related codes from 2011 to 2024. Migration-related coding increased over time, exceeding the increase observed for coding overall, with a sharp increase from 2020, particularly for country-of-birth and language. Language coding represented 71% of code usage and where country of birth was recorded, there was mixed agreement with the census estimates. Coding of immigration legal statuses was low and overwhelmingly about asylum or refugee status. Conclusion: Rapid assessment of migration-related coding using Open Code Counts highlights that a non-English first language is the most strongly represented characteristic in migrant cohorts in English primary care EHRs, which should be considered when interpreting future research findings. How this fits in: This study offers population-wide insights into migration-related SNOMED CT coding in primary care in England from 2011 to 2024 using our new open-source tool, Open Code Counts. Here, we show that a first language that is not English is the most commonly recorded aspect of migration, which must be considered when interpreting results from studies that use this methodology for researching migrants’ health in primary care EHRs. We also show that migration-related coding has increased, particularly after the start of the pandemic and for country-of-birth and language codes. The increased use of these code types offers the opportunity for GP practices to better identify patients requiring language support and potential screening and service needs based on their country of birth. Summary sentence: Language is the most commonly coded aspect of migration in primary care, which must be considered when interpreting primary care data studies.

Seventeen percent of people living in the UK are migrants. In high-income countries, migrants have been shown to have better all-cause mortality but worse mortality for some specific causes such as infectious diseases. This observational study aims to quantify the extent to which mortality from coronavirus disease 2019 (COVID-19) differed between migrants and non-migrants for the population of England and Wales, 2020-2021. We use Official National Statistics data to compare mortality from COVID-19 in 2020 and 2021 by country/region of birth, expressed as the standardized mortality ratio with those born in England and Wales as the reference population. Migrants from 17 of 19 countries/regions examined had higher mortality from COVID-19 than non-migrants. The highest mortality was those born in Bangladesh (females SMR = 3.39, 95% CIs 3.09–3.71; males 4.41, 95% CIs 4.09–4.75); Pakistan (females 2.73, 95% CIs 2.59–2.89; males 3.02, 95% CIs 2.89–3.14); and the Caribbean (females 2.03, 95% CIs 1.87–2.20; males 2.48, 95% CIs 2.37–2.60). Migrants born in Antarctica and Oceania (females 0.54, 95% CI 0.42–0.40; males 0.71, 95% CI 0.51–0.88), and North and Central America (females 0.95, 95% CI 0.80–1.11; males 0.85, 95% CI 0.72–0.99) had lower mortality than non-migrants. Most migrant populations had higher mortality from COVID-19 than non-migrants in England and Wales. Policy-makers must work to integrate migration status into routine data collection to inform future research and understand the causes of the inequalities seen.

Health is going in the wrong direction in the UK, and reversing the trend requires political and societal commitment to deal with the underlying causes

Background: England and Wales experienced a stagnation of previously improving life expectancy during the 2010s. Public bodies cited influenza as an important cause.Sources of data: We used data from the Office for National Statistics to examine mortality attributed directly to influenza and to all influenza-like diseases for the total population of England and Wales 2010–19. Several combinations of ICD-10 codes were used to address the possibility of under-counting influenza deaths.Areas of agreement: Deaths from influenza and influenza-like diseases declined between 2010 and 2019, while earlier improvements in mortality from all causes of death were stalling and, with some causes, worsening. Our findings support existing research showing that influenza is not an important cause of the stalling of mortality rates 2010–19.Areas of controversy: Influenza was accepted by many as an important cause of stalling life expectancy for much of the 2010s, while few in public office have accepted austerity as a key factor in the changes seen during that time.Growing points: This adds to the mounting evidence that austerity damaged health prior to COVID-19 and left the population more vulnerable when it arrived.Areas for developing timely research: Future research should explore why so many in public office were quick to attribute the change in trends in overall mortality in the UK in this period to influenza, and why many continue to do so through to 2023 and to deny the key role of austerity in harming population health.

Objectives: The number of deaths occurring in private homes in England and Wales had been rising for years, increasingly rapidly from 2020. Media stories and research linked decomposing bodies found in private homes with pandemic-related social isolation. We aim to explore whether these incidents are one-offs or part of a wider trend. Design: Descriptive analysis of publicly available Office for National Statistics (ONS) data. Setting: England and Wales. Participants: All residents of England and Wales, 1979 to 2020. Main outcome measures: Using data from the Office for National Statistics, we calculate European Age Standardised Rates for deaths coded as R98 (‘unattended death’) and R99 (‘other ill-defined and unknown causes of mortality’) in the 10th version of the International Classification of Diseases (ICD-10), and the corresponding codes in ICD-9, by sex and age group from 1979 (when ICD-9 began) to 2020. These are proxy markers for deaths where decomposition precludes attribution of a specific cause at postmortem. Results: While mortality from all other causes decreased from 1979 to 2020, the opposite was seen for deaths from R98 and R99 (or ‘undefined deaths’), with men more affected than women. There was a sharp rise in these deaths in both sexes but in men particularly in the 1990s and 2000s, coinciding with a time when overall mortality was rapidly improving. Conclusions: The increase in people found dead from unknown causes suggests wider societal breakdowns of both formal and informal social support networks. They are concerning and warrant urgent further investigation. We call on national and international authorities to consider measures that would make it possible to identify these deaths more easily in routine data.