The increasing significance of disease severity in a burden of disease framework.

Recent estimates have reiterated that non-fatal causes of disease, such as low back pain, headaches and depressive disorders, are amongst the leading causes of disability-adjusted life years (DALYs). For these causes, the contribution of years lived with disability (YLD) - put simply, ill-health - is what drives DALYs, not mortality. Being able to monitor trends in YLD closely is particularly relevant for countries that sit high on the socio-demographic spectrum of development, as it contributes more than half of all DALYs. There is a paucity of data on how the population-level occurrence of disease is distributed according to severity, and as such, the majority of global and national efforts in monitoring YLD lack the ability to differentiate changes in severity across time and location. This raises uncertainties in interpreting these findings without triangulation with other relevant data sources. Our commentary aims to bring this issue to the forefront for users of burden of disease estimates, as its impact is often easily overlooked as part of the fundamental process of generating DALY estimates. Moreover, the wider health harms of the COVID-19 pandemic have underlined the likelihood of latent and delayed demand in accessing vital health and care services that will ultimately lead to exacerbated disease severity and health outcomes. This places increased importance on attempts to be able to differentiate by both the occurrence and severity of disease.

Inequalities in population health loss by multiple deprivation: COVID-19 and pre-pandemic all-cause disability-adjusted life years (DALYs) in Scotland.

BACKGROUND: COVID-19 has caused almost unprecedented change across health, education, the economy and social interaction. It is widely understood that the existing mechanisms which shape health inequalities have resulted in COVID-19 outcomes following this same, familiar, pattern. Our aim was to estimate inequalities in the population health impact of COVID-19 in Scotland, measured by disability-adjusted life years (DALYs) in 2020. Our secondary aim was to scale overall, and inequalities in, COVID-19 DALYs against the level of pre-pandemic inequalities in all-cause DALYs, derived from the Scottish Burden of Disease (SBoD) study. METHODS: National deaths and daily case data were input into the European Burden of Disease Network consensus model to estimate DALYs. Total Years of Life Lost (YLL) were estimated for each area-based deprivation quintile of the Scottish population. Years Lived with Disability were proportionately distributed to deprivation quintiles, based on YLL estimates. Inequalities were measured by: the range, Relative Index of Inequality (RII), Slope Index of Inequality (SII), and attributable DALYs were estimated by using the least deprived quintile as a reference. RESULTS: Marked inequalities were observed across several measures. The SII range was 2048 to 2289 COVID-19 DALYs per 100,000 population. The rate in the most deprived areas was around 58% higher than the mean population rate (RII = 1.16), with 40% of COVID-19 DALYs attributed to differences in area-based deprivation. Overall DALYs due to COVID-19 ranged from 7 to 20% of the annual pre-pandemic impact of inequalities in health loss combined across all causes. CONCLUSION: The substantial population health impact of COVID-19 in Scotland was not shared equally across areas experiencing different levels of deprivation. The extent of inequality due to COVID-19 was similar to averting all annual DALYs due to diabetes. In the wider context of population health loss, overall ill-health and mortality due to COVID-19 was, at most, a fifth of the annual population health loss due to inequalities in multiple deprivation. Implementing effective policy interventions to reduce health inequalities must be at the forefront of plans to recover and improve population health.

Risk factors for resistance and MDR in community urine isolates: population-level analysis using the NHS Scotland Infection Intelligence Platform.

BACKGROUND: Urinary tract infections (UTIs) are common. Antibiotic treatment is usually empirical, with the risk of under-treatment of resistant infections. OBJECTIVES: To characterize risk factors for antibiotic-resistant community urine isolates using routine record-linked health data. METHODS: Within the NHS Scotland Infection Intelligence Platform, national surveillance patient-level data on community urine isolates (January 2012-June 2015) were linked to hospital activity and community prescribing data. Associations between age, gender, comorbidity, care home residence, previous hospitalizations, antibiotic exposure and resistant (any antibiotic) or MDR (≥1 antibiotic from ≥3 categories) urinary isolates were quantified using multivariable logistic regression. RESULTS: Of 40984 isolates, 28% were susceptible, 45% were resistant and 27% were MDR. Exposure to ≥ 4 different antibiotics in the prior 6 months increased MDR risk (OR 6.81, 95% CI 5.73-8.11). MDR was associated with ≥29 DDD cumulative exposure, in the prior 6 months, for any antibiotic (OR 6.54, 95% CI 5.88-7.27), nitrofurantoin (OR 8.56, 95% CI 6.56-11.18) and trimethoprim (OR 14.61, 95% CI 10.53-20.27). Associations persisted for 10-12 months for nitrofurantoin (OR 2.31, 95% CI 1.93-2.76) and trimethoprim (OR 1.81, 95% CI 1.57-2.09). Increasing age, comorbidity, previous hospitalization and care home residence were independently associated with MDR. For resistant isolates the factors were the same, but with weaker associations. CONCLUSIONS: To our knowledge, we have demonstrated, using national capability at scale, the risk of MDR in community urine isolates for the first time and quantified the cumulative and sustained impact of antibiotic exposure. These data will inform the development of decision support tools for UTI treatment.

Retrospective cohort study of breast cancer incidence, health service use and outcomes in Europe: a study of feasibility.

Background: Comparisons of outcomes of health care in different systems can be used to inform health policy. The EuroHOPE (European Healthcare Outcomes, Performance and Efficiency) project investigated the feasibility of comparing routine data on selected conditions including breast cancer across participating European countries. Methods: Routine data on incidence, treatment and mortality by age and clinical characteristics for breast cancer in women over 24 years of age were obtained (for a calendar year) from linked hospital discharge records, cancer and death registers from Finland, the Turin metropolitan area, Scotland and Sweden (all 2005), Hungary (2006) and Norway (2009). Age-adjusted breast cancer incidence and 1-year survival were estimated for each country/region. Results: In total, 24 576 invasive breast cancer cases were identified from cancer registries from over 13 million women. Age-adjusted incidence ranged from 151.1 (95%CI 147.2-155.0) in Hungary to 234.7 (95%CI 227.4-242.0)/100 000 in Scotland. One-year survival ranged from 94.1% (95%CI 93.5-94.7%) in Scotland to 97.1% (95%CI 96.2-98.1%) in Italy. Scotland had the highest proportions of poor prognostic factors in terms of tumour size, nodal status and metastases. Significant variations in data completeness for prognostic factors prevented adjustment for case mix. Conclusion: Incidence of and survival from breast cancer showed large differences between countries. Substantial improvements in the use of internationally recognised common terminology, standardised data coding and data completeness for prognostic indicators are required before international comparisons of routine data can be used to inform health policy.

Individual and Regional-level Factors Contributing to Variation in Length of Stay After Cerebral Infarction in Six European Countries.

Using patient-level data for cerebral infarction cases in 2007, gathered from Finland, Hungary, Italy, the Netherlands, Scotland and Sweden, we studied the variation in risk-adjusted length of stay (LoS) of acute hospital care and 1-year mortality, both within and between countries. In addition, we analysed the variance of LoS and associations of selected regional-level factors with LoS and 1-year mortality after cerebral infarction. The data show that LoS distributions are surprisingly different across countries and that there is significant deviation in the risk-adjusted regional-level LoS in all of the countries studied. We used negative binomial regression to model the individual-level LoS, and random intercept models and ordinary least squares regression for the regional-level analysis of risk-adjusted LoS, variance of LoS, 1-year risk-adjusted mortality and crude mortality for a period of 31-365 days. The observed variations between regions and countries in both LoS and mortality were not fully explained by either patient-level or regional-level factors. The results indicate that there may exist potential for efficiency gains in acute hospital care of cerebral infarction and that healthcare managers could learn from best practices.

Parameter Heterogeneity In Breast Cancer Cost Regressions - Evidence From Five European Countries.

We investigate parameter heterogeneity in breast cancer 1-year cumulative hospital costs across five European countries as part of the EuroHOPE project. The paper aims to explore whether conditional mean effects provide a suitable representation of the national variation in hospital costs. A cohort of patients with a primary diagnosis of invasive breast cancer (ICD-9 codes 174 and ICD-10 C50 codes) is derived using routinely collected individual breast cancer data from Finland, the metropolitan area of Turin (Italy), Norway, Scotland and Sweden. Conditional mean effects are estimated by ordinary least squares for each country, and quantile regressions are used to explore heterogeneity across the conditional quantile distribution. Point estimates based on conditional mean effects provide a good approximation of treatment response for some key demographic and diagnostic specific variables (e.g. age and ICD-10 diagnosis) across the conditional quantile distribution. For many policy variables of interest, however, there is considerable evidence of parameter heterogeneity that is concealed if decisions are based solely on conditional mean results. The use of quantile regression methods reinforce the need to consider beyond an average effect given the greater recognition that breast cancer is a complex disease reflecting patient heterogeneity.

Variations and Determinants of Mortality and Length of Stay of Very Low Birth Weight and Very Low for Gestational Age Infants in Seven European Countries.

The EuroHOPE very low birth weight and very low for gestational age infants study aimed to measure and explain variation in mortality and length of stay (LoS) in the populations of seven European nations (Finland, Hungary, Italy (only the province of Rome), the Netherlands, Norway, Scotland and Sweden). Data were linked from birth, hospital discharge and mortality registries. For each infant basic clinical and demographic information, infant mortality and LoS at 1 year were retrieved. In addition, socio-economic variables at the regional level were used. Results based on 16,087 infants confirm that gestational age and Apgar score at 5 min are important determinants of both mortality and LoS. In most countries, infants admitted or transferred to third-level hospitals showed lower probability of death and longer LoS. In the meta-analyses, the combined estimates show that being male, multiple births, presence of malformations, per capita income and low population density are significant risk factors for death. It is essential that national policies improve the quality of administrative datasets and address systemic problems in assigning identification numbers at birth. European policy should aim at improving the comparability of data across jurisdictions.

Widening of inequalities in COVID-19 years of life lost from 2020 to 2021: a Scottish Burden of Disease Study.

BACKGROUND: Previous studies have highlighted the large extent of inequality in adverse COVID-19 health outcomes. Our aim was to monitor changes in overall, and inequalities in, COVID-19 years of life lost to premature mortality (YLL) in Scotland from 2020 and 2021. METHODS: Cause-specific COVID-19 mortality counts were derived at age group and area deprivation level using Scottish death registrations for 2020 and 2021. YLL was estimated by multiplying mortality counts by age-conditional life expectancy from the Global Burden of Disease 2019 reference life table. Various measures of absolute and relative inequality were estimated for triangulation purposes. RESULTS: There were marked inequalities in COVID-19 YLL by area deprivation in 2020, which were further exacerbated in 2021; confirmed across all measures of absolute and relative inequality. Half (51%) of COVID-19 YLL was attributable to inequalities in area deprivation in 2021, an increase from 41% in 2020. CONCLUSION: Despite a highly impactful vaccination programme in preventing mortality, COVID-19 continues to represent a substantial area of fatal population health loss for which inequalities have widened. Tackling systemic inequalities with effective interventions is required to mitigate further unjust health loss in the Scottish population from COVID-19 and other causes of ill-health and mortality.

Measuring disability-adjusted life years (DALYs) due to COVID-19 in Scotland, 2020.

BACKGROUND: Disability-adjusted life years (DALYs) combine the impact of morbidity and mortality and can enable comprehensive, and comparable, assessments of direct and indirect health harms due to COVID-19. Our aim was to estimate DALYs directly due to COVID-19 in Scotland, during 2020; and contextualise its population impact relative to other causes of disease and injury. METHODS: National deaths and daily case data were used. Deaths were based on underlying and contributory causes recorded on death certificates. We calculated DALYs based on the COVID-19 consensus model and methods outlined by the European Burden of Disease Network. DALYs were presented as a range, using a sensitivity analysis based on Years of Life Lost estimates using: cause-specific; and COVID-19 related deaths. All COVID-19 estimates were for 2020. RESULTS: In 2020, estimates of COVID-19 DALYs in Scotland ranged from 96,500 to 108,200. Direct COVID-19 DALYs were substantial enough to be framed as the second leading cause of disease and injury, with only ischaemic heart disease having a larger impact on population health. Mortality contributed 98% of total DALYs. CONCLUSIONS: The direct population health impact of COVID-19 has been very substantial. Despite unprecedented mitigation efforts, COVID-19 developed from a single identified case in early 2020 to a condition with an impact in Scotland second only to ischaemic heart disease. Periodic estimation of DALYs during 2021, and beyond, will provide indications of the impact of DALYs averted due to the national rollout of the vaccination programme and other continued mitigation efforts, although new variants may pose significant challenges.

How bad are life expectancy trends across the UK, and what would it take to get back to previous trends?

BACKGROUND: Within the UK, there has been debate on whether life expectancy is increasing or decreasing in particular single or 3-year periods, but there has been less thinking whether overall trends have changed. This paper considers the extent to which the trends in life expectancy for the UK and its nations have changed before and after 2011. METHODS: We used the Office for National Statistics period life expectancy data for the UK and its nations. We used Lee's approach to project life expectancy based on repeated sampling of year-to-year change in the baseline periods (1990-2011 and 1980-2011) and applied that to 2012 onwards. FINDINGS: Improvements in period life expectancy were substantially and consistently lower between 2012 and 2018 than predicted from the trends from 1980 and, especially, from 1990. By 2018, life expectancy was lower than projected for females and males, respectively, by 1.22 and 1.52 years (England), 1.44 and 0.95 years (Northern Ireland), 1.30 and 1.44 years (Scotland), 1.53 and 1.63 years (Wales) and 1.24 and 1.49 years (UK overall), based on the 1990-2011 baseline period. Using a longer baseline period, which includes the slower rates of improvement during the 1980s, slightly reduces the gap between the current life expectancies and the projected medians. INTERPRETATION: Future academic and policy focus should be on the deviation of the life expectancy trends from the baseline projection rather than on year-to-year variation. Concerted policy focus to return life expectancy to the projected trends is now urgently required.

Correction to: Prioritising the development of severity distributions in burden of disease studies for countries in the European region.

[This corrects the article DOI: 10.1186/s13690-019-0385-6.].

Prioritising the development of severity distributions in burden of disease studies for countries in the European region.

Severity distributions are a means of summarising the range of health loss suffered to disease which enables estimates of disease occurrence to be paired with disability weights to estimate Years Lost to Disability (YLD) in burden of disease studies. There is a lack of current data exploring severity distributions, which has led to the Global Burden of Disease (GBD) study relying on using the same severity distributions across countries and regions across the world. This is also largely true for some national studies, although there are exceptions. Recent evidence has raised concerns that severity distributions are unlikely to be generalisable as major differences arise when using country-specific data to develop severity distributions. These issues raise uncertainties over interpreting YLD estimates, particularly if they are being used to develop and influence policies and to determine priorities across diseases and populations. It is clear that GBD researchers and those carrying out national studies need to work towards ensuring that estimates are based upon country-specific data, and, if possible, that the impact of assumptions are fully tested and understood. There is a lack of strategy about if, where, and how, this could be achieved, particularly around how efforts should be prioritised. This commentary advocates and presents a possible strategic approach to better understanding how efforts may be best placed.

How do world and European standard populations impact burden of disease studies? A case study of disability-adjusted life years (DALYs) in Scotland.

BACKGROUND: Disability-Adjusted Life Years (DALYs) are an established method for quantifying population health needs and guiding prioritisation decisions. Global Burden of Disease (GBD) estimates aim to ensure comparability between countries and over time by using age-standardised rates (ASR) to account for differences in the age structure of different populations. Different standard populations are used for this purpose but it is not widely appreciated that the choice of standard may affect not only the resulting rates but also the rankings of causes of DALYs. We aimed to evaluate the impact of the choice of standard, using the example of Scotland. METHODS: DALY estimates were derived from the 2016 Scottish Burden of Disease (SBoD) study for an abridged list of 68 causes of disease/injury, representing a three-year annual average across 2014-16. Crude DALY rates were calculated using Scottish national population estimates. DALY ASRs standardised using the GBD World Standard Population (GBD WSP) were compared to those using the 2013 European Standard Population (ESP2013). Differences in ASR and in rank order within the cause list were summarised for all-cause and for each individual cause. RESULTS: The ranking of causes by DALYs were similar using crude rates or ASR (ESP2013). All-cause DALY rates using ASR (GBD WSP) were around 26% lower. Overall 58 out of 68 causes had a lower ASR using GBD WSP compared with ESP2013, with the largest falls occurring for leading causes of mortality observed in older ages. Gains in ASR were much smaller in absolute scale and largely affected causes that operated early in life. These differences were associated with a substantial change to the ranking of causes when GBD WSP was used compared with ESP2013. CONCLUSION: Disease rankings based on DALY ASRs are strongly influenced by the choice of standard population. While GBD WSP offers international comparability, within-country analyses based on DALY ASRs should reflect local age structures. For European countries, including Scotland, ESP2013 may better guide local priority setting by avoiding large disparities occurring between crude and age-standardised results sets, which could potentially confuse non-technical audiences.

Correction to: Population vulnerability to COVID-19 in Europe: a burden of disease analysis.

[This corrects the article DOI: 10.1186/s13690-020-00433-y.].

Population vulnerability to COVID-19 in Europe: a burden of disease analysis.

BACKGROUND: Evidence has emerged showing that elderly people and those with pre-existing chronic health conditions may be at higher risk of developing severe health consequences from COVID-19. In Europe, this is of particular relevance with ageing populations living with non-communicable diseases, multi-morbidity and frailty. Published estimates of Years Lived with Disability (YLD) from the Global Burden of Disease (GBD) study help to characterise the extent of these effects. Our aim was to identify the countries across Europe that have populations at highest risk from COVID-19 by using estimates of population age structure and YLD for health conditions linked to severe illness from COVID-19. METHODS: Population and YLD estimates from GBD 2017 were extracted for 45 countries in Europe. YLD was restricted to a list of specific health conditions associated with being at risk of developing severe consequences from COVID-19 based on guidance from the United Kingdom Government. This guidance also identified individuals aged 70 years and above as being at higher risk of developing severe health consequences. Study outcomes were defined as: (i) proportion of population aged 70 years and above; and (ii) rate of YLD for COVID-19 vulnerable health conditions across all ages. Bivariate groupings were established for each outcome and combined to establish overall population-level vulnerability. RESULTS: Countries with the highest proportions of elderly residents were Italy, Greece, Germany, Portugal and Finland. When assessments of population-level YLD rates for COVID-19 vulnerable health conditions were made, the highest rates were observed for Bulgaria, Czechia, Croatia, Hungary and Bosnia and Herzegovina. A bivariate analysis indicated that the countries at high-risk across both measures of vulnerability were: Bulgaria; Portugal; Latvia; Lithuania; Greece; Germany; Estonia; and Sweden. CONCLUSION: Routine estimates of population structures and non-fatal burden of disease measures can be usefully combined to create composite indicators of vulnerability for rapid assessments, in this case to severe health consequences from COVID-19. Countries with available results for sub-national regions within their country, or national burden of disease studies that also use sub-national levels for burden quantifications, should consider using non-fatal burden of disease estimates to estimate geographical vulnerability to COVID-19.

The impact of worldwide, national and sub-national severity distributions in Burden of Disease studies: A case study of cancers in Scotland.

BACKGROUND: Increasingly Burden of Disease (BOD) measures are being used to influence policy decisions because they summarise the complete effects of morbidity and mortality in an equitable manner. An important element of producing non-fatal BOD estimates are severity distributions. The Global Burden of Disease (GBD) study use the same severity distributions across countries due to a lack of available country-specific data. In the Scottish BOD (SBOD) study we developed national severity distributions for cancer types. The main aim of this study was to consider the extent to which the use of worldwide severity distributions in BOD studies are influencing cross-country comparisons, by comparing weighted-average disability weights (DW) based on GBD severity distributions with nationally derived severity distributions in Scotland for cancer types. METHODS: We obtained individual records from the Scottish Cancer Registry for 21 cancer types and linked these to registered deaths. We estimated prevalent cancer cases for 2016 and assigned each case to sequelae using GBD 2016 study definitions. We compared the impact of using severity distributions based on GBD 2016, a Scotland-wide distribution, and distributions specific to deprivation strata in Scotland, on the weighted-average DW for each cancer type. RESULTS: The relative difference in point estimates of weighted-average DW based on GBD 2016 worldwide severity distributions compared with Scottish national severity distributions resulted in overestimates in the majority of cancers (17 out of 21 cancer types). The largest overestimates were for gallbladder and biliary tract cancer (70.8%), oesophageal cancer (31.6%) and pancreatic cancer (31.2%). Furthermore, the use of weighted-average DW based on Scottish national severity distributions rather than sub-national Scottish severity distributions stratified by deprivation quintile overestimated weighted-average DW in the least deprived areas (16 out of 18 cancer types), and underestimated in the most deprived areas (16 out of 18 cancer types). CONCLUSION: Our findings illustrate a bias in point estimates of weighted-average DW created using worldwide severity distributions. This bias would have led to the misrepresentation of non-fatal estimates of the burden of individual cancers, and underestimated the scale of socioeconomic inequality in this non-fatal burden. This highlights the importance of not interpreting non-fatal estimates of burden of disease too precisely, especially for sub-national estimates and those comparing populations when relying on data inputs from other countries. It is essential to ensure that any estimates are based upon country-specific data as far as possible.

Risk of infection following semi-invasive ultrasound procedures in Scotland, 2010 to 2016: A retrospective cohort study using linked national datasets.

INTRODUCTION: Outbreak reports indicate a risk of cross-infection following medical procedures using semi-invasive ultrasound probes. This study aimed to evaluate the risk of infection, using microbiological reports and antibiotic prescriptions as proxy measures, associated with semi-invasive ultrasound probe procedures, including transoesophageal echocardiography, transvaginal and transrectal ultrasound. METHODS: Patient records from the Electronic Communication of Surveillance in Scotland and the Prescribing Information System were linked with the Scottish Morbidity Records for cases in Scotland between 2010 and 2016. Three retrospective cohorts were created to include inpatients/day-cases and outpatients in the following specialties: Cardiology, Gynaecology and Urology. Cox regression was used to quantify the association between semi-invasive ultrasound probe procedures and the risk of positive microbiological reports and community antibiotic prescriptions in the 30-day period following the procedure. RESULTS: There was a greater hazard ratio of microbiological reports for patients who had undergone transoesophageal echocardiography (HR: 4.92; 95% CI: 3.17-7.63), transvaginal (HR: 1.41; 95% CI: 1.21-1.64) and transrectal ultrasound (HR: 3.40; 95% CI: 2.90-3.99), compared with unexposed cohort members after adjustment for age, co-morbidities, previous hospital admissions and past care home residence. Similarly, there was a greater hazard ratio of antibiotic prescribing for those who had received transvaginal (HR: 1.26; 95% CI: 1.20-1.32) and transrectal (HR: 1.75; 95% CI: 1.66-1.84) ultrasound, compared with unexposed patients. CONCLUSION: Analysis of linked national datasets demonstrated a greater risk of infection within 30 days of undergoing semi-invasive ultrasound probe procedures, using microbiological reports and antibiotic prescriptions as proxy measures of infection.

Correction: Mortality and Length of Stay of Very Low Birth Weight and Very Preterm Infants: A EuroHOPE Study.

[This corrects the article DOI: 10.1371/journal.pone.0131685.].

Mortality and Length of Stay of Very Low Birth Weight and Very Preterm Infants: A EuroHOPE Study.

The objective of this paper was to compare health outcomes and hospital care use of very low birth weight (VLBW), and very preterm (VLGA) infants in seven European countries. Analysis was performed on linkable patient-level registry data from seven European countries between 2006 and 2008 (Finland, Hungary, Italy (the Province of Rome), the Netherlands, Norway, Scotland, and Sweden). Mortality and length of stay (LoS) were adjusted for differences in gestational age (GA), sex, intrauterine growth, Apgar score at five minutes, parity and multiple births. The analysis included 16,087 infants. Both the 30-day and one-year adjusted mortality rates were lowest in the Nordic countries (Finland, Sweden and Norway) and Scotland and highest in Hungary and the Netherlands. For survivors, the adjusted average LoS during the first year of life ranged from 56 days in the Netherlands and Scotland to 81 days in Hungary. There were large differences between European countries in mortality rates and LoS in VLBW and VLGA infants. Substantial data linkage problems were observed in most countries due to inadequate identification procedures at birth, which limit data validity and should be addressed by policy makers across Europe.