Adjusting expected deaths for mortality displacement during the COVID-19 pandemic: a model based counterfactual approach at the level of individuals.

BACKGROUND: Near-real time surveillance of excess mortality has been an essential tool during the COVID-19 pandemic. It remains critical for monitoring mortality as the pandemic wanes, to detect fluctuations in the death rate associated both with the longer-term impact of the pandemic (e.g. infection, containment measures and reduced service provision by the health and other systems) and the responses that followed (e.g. curtailment of containment measures, vaccination and the response of health and other systems to backlogs). Following the relaxing of social distancing regimes and reduction in the availability of testing, across many countries, it becomes critical to measure the impact of COVID-19 infection. However, prolonged periods of mortality in excess of the expected across entire populations has raised doubts over the validity of using unadjusted historic estimates of mortality to calculate the expected numbers of deaths that form the baseline for computing numbers of excess deaths because many individuals died earlier than they would otherwise have done: i.e. their mortality was displaced earlier in time to occur during the pandemic rather than when historic rates predicted. This is also often termed "harvesting" in the literature. METHODS: We present a novel Cox-regression-based methodology using time-dependent covariates to estimate the profile of the increased risk of death across time in individuals who contracted COVID-19 among a population of hip fracture patients in England (N = 98,365). We use these hazards to simulate a distribution of survival times, in the presence of a COVID-19 positive test, and then calculate survival times based on hazard rates without a positive test and use the difference between the medians of these distributions to estimate the number of days a death has been displaced. This methodology is applied at the individual level, rather than the population level to provide a better understanding of the impact of a positive COVID-19 test on the mortality of groups with different vulnerabilities conferred by sociodemographic and health characteristics. Finally, we apply the mortality displacement estimates to adjust estimates of excess mortality using a "ball and urn" model. RESULTS: Among the exemplar population we present an end-to-end application of our methodology to estimate the extent of mortality displacement. A greater proportion of older, male and frailer individuals were subject to significant displacement while the magnitude of displacement was higher in younger females and in individuals with lower frailty: groups who, in the absence of COVID-19, should have had a substantial life expectancy. CONCLUSION: Our results indicate that calculating the expected number of deaths following the first wave of the pandemic in England based solely on historical trends results in an overestimate, and excess mortality will therefore be underestimated. Our findings, using this exemplar dataset are conditional on having experienced a hip fracture, which is not generalisable to the general population. Fractures that impede mobility in the weeks that follow the accident/surgery considerably shorten life expectancy and are in themselves markers of significant frailty. It is therefore important to apply these novel methods to the general population, among whom we anticipate strong patterns in mortality displacement - both in its length and prevalence - by age, sex, frailty and types of comorbidities. This counterfactual method may also be used to investigate a wider range of disruptive population health events. This has important implications for public health monitoring and the interpretation of public health data in England and globally.

Persistent inequalities in consultation incidence and prevalence of low back pain and osteoarthritis in England between 2004 and 2019.

Objective: We wanted to determine whether socioeconomic inequalities in primary care consultation rates for two major, disabling musculoskeletal conditions in England narrowed or widened between 2004 and 2019. Methods: We analysed data from Clinical Practice Research Datalink Aurum, a national general practice electronic health records database, linked to national deprivation ranking of each patient's registered residential postcode. For each year, we estimated the age- and sex-standardized consultation incidence and prevalence for low back pain and OA for the most deprived 10% of neighbourhoods through to the least deprived 10%. We then calculated the slope index of inequality and relative index of inequality overall and by sex, age group and geographical region. Results: Inequalities in low back pain incidence and prevalence over socioeconomic status widened between 2004 and 2013 and stabilized between 2014 and 2019. Inequalities in OA incidence remained stable over socioeconomic status within the study period, whereas inequalities in OA prevalence widened markedly over socioeconomic status between 2004 and 2019. The widest gap in low back pain incidence and prevalence over socioeconomic status was observed in populations resident in northern English regions and London and in those of working age, peaking at 45-54 years. Conclusion: We found persistent, and generally increasing, socioeconomic inequalities in the rate of adults presenting to primary care in England with low back pain and OA between 2004 and 2019.

Trends in the Annual Consultation Incidence and Prevalence of Low Back Pain and Osteoarthritis in England from 2000 to 2019: Comparative Estimates from Two Clinical Practice Databases.

PURPOSE: To compare estimates of annual person-consulting incidence and prevalence of low back pain (LBP) and osteoarthritis for two national English electronic health record databases (Clinical Practice Research Datalink (CPRD) Aurum and CPRD GOLD). PATIENTS AND METHODS: Retrospective, population-based, longitudinal cohort study. LBP and osteoarthritis cases were defined using established codelists in people aged ≥15 and ≥45 years, respectively. Incident cases were new recorded cases in a given calendar year with no relevant consultation in the previous 3 years (denominator = exact person-time in the same calendar year for the at-risk population). Prevalent cases were individuals with ≥1 consultation for the condition of interest recorded in a given calendar year, irrespective of prior consultations for the same condition (denominator = all patients with complete registration history in the previous 3 years). We estimated age-sex standardised incidence and annual (12-month period) prevalence for both conditions in 2000-2019, overall, and by sex, age group, and region. RESULTS: Standardised incidence and prevalence of LBP from Aurum were lower than those from GOLD until 2014, after which estimates were similar. Both databases showed recent declines in incidence and prevalence of LBP: declines began earlier in GOLD (after 2012-2014) than Aurum (after 2014-2015). Standardised incidence (after 2011) and prevalence of osteoarthritis (after 2003) were higher in Aurum than GOLD and showed different trends: incidence and prevalence were stable or increasing in Aurum, decreasing in GOLD. Stratified estimates in CPRD Aurum suggested consistently higher occurrence among women, older age groups, and those living in the north of England. CONCLUSION: Comparative analyses of two English databases produced conflicting estimates and trends for two common musculoskeletal conditions. Aurum estimates appeared more consistent with external sources and may be useful for monitoring population musculoskeletal health and healthcare demand, but they remain sensitive to analytic decisions and data quality.

Inequalities in excess premature mortality in England during the COVID-19 pandemic: a cross-sectional analysis of cumulative excess mortality by area deprivation and ethnicity.

OBJECTIVES: To examine magnitude of the impact of the COVID-19 pandemic on inequalities in premature mortality in England by deprivation and ethnicity. DESIGN: A statistical model to estimate increased mortality in population subgroups during the COVID-19 pandemic by comparing observed with expected mortality in each group based on trends over the previous 5 years. SETTING: Information on deaths registered in England since 2015 was used, including age, sex, area of residence and cause of death. Ethnicity was obtained from Hospital Episode Statistics records linked to death data. PARTICIPANTS: Population study of England, including all 569 824 deaths from all causes registered between 21 March 2020 and 26 February 2021. MAIN OUTCOME MEASURES: Excess mortality in each subgroup over and above the number expected based on trends in mortality in that group over the previous 5 years. RESULTS: The gradient in excess mortality by area deprivation was greater in the under 75s (the most deprived areas had 1.25 times as many deaths as expected, least deprived 1.14) than in all ages (most deprived had 1.24 times as many deaths as expected, least deprived 1.20). Among the black and Asian groups, all area deprivation quintiles had significantly larger excesses than white groups in the most deprived quintiles and there were no clear gradients across quintiles. Among the white group, only those in the most deprived quintile had more excess deaths than deaths directly involving COVID-19. CONCLUSION: The COVID-19 pandemic has widened inequalities in premature mortality by area deprivation. Among those under 75, the direct and indirect effects of the pandemic on deaths have disproportionately impacted ethnic minority groups irrespective of area deprivation, and the white group the most deprived areas. Statistics limited to deaths directly involving COVID-19 understate the pandemic's impact on inequalities by area deprivation and ethnic group at younger ages.

Changes in health in the countries of the UK and 150 English Local Authority areas 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016.

BACKGROUND: Previous studies have reported national and regional Global Burden of Disease (GBD) estimates for the UK. Because of substantial variation in health within the UK, action to improve it requires comparable estimates of disease burden and risks at country and local levels. The slowdown in the rate of improvement in life expectancy requires further investigation. We use GBD 2016 data on mortality, causes of death, and disability to analyse the burden of disease in the countries of the UK and within local authorities in England by deprivation quintile. METHODS: We extracted data from the GBD 2016 to estimate years of life lost (YLLs), years lived with disability (YLDs), disability-adjusted life-years (DALYs), and attributable risks from 1990 to 2016 for England, Scotland, Wales, Northern Ireland, the UK, and 150 English Upper-Tier Local Authorities. We estimated the burden of disease by cause of death, condition, year, and sex. We analysed the association between burden of disease and socioeconomic deprivation using the Index of Multiple Deprivation. We present results for all 264 GBD causes of death combined and the leading 20 specific causes, and all 84 GBD risks or risk clusters combined and 17 specific risks or risk clusters. FINDINGS: The leading causes of age-adjusted YLLs in all UK countries in 2016 were ischaemic heart disease, lung cancers, cerebrovascular disease, and chronic obstructive pulmonary disease. Age-standardised rates of YLLs for all causes varied by two times between local areas in England according to levels of socioeconomic deprivation (from 14 274 per 100 000 population [95% uncertainty interval 12 791-15 875] in Blackpool to 6888 [6145-7739] in Wokingham). Some Upper-Tier Local Authorities, particularly those in London, did better than expected for their level of deprivation. Allowing for differences in age structure, more deprived Upper-Tier Local Authorities had higher attributable YLLs for most major risk factors in the GBD. The population attributable fractions for all-cause YLLs for individual major risk factors varied across Upper-Tier Local Authorities. Life expectancy and YLLs have improved more slowly since 2010 in all UK countries compared with 1990-2010. In nine of 150 Upper-Tier Local Authorities, YLLs increased after 2010. For attributable YLLs, the rate of improvement slowed most substantially for cardiovascular disease and breast, colorectal, and lung cancers, and showed little change for Alzheimer's disease and other dementias. Morbidity makes an increasing contribution to overall burden in the UK compared with mortality. The age-standardised UK DALY rate for low back and neck pain (1795 [1258-2356]) was higher than for ischaemic heart disease (1200 [1155-1246]) or lung cancer (660 [642-679]). The leading causes of ill health (measured through YLDs) in the UK in 2016 were low back and neck pain, skin and subcutaneous diseases, migraine, depressive disorders, and sense organ disease. Age-standardised YLD rates varied much less than equivalent YLL rates across the UK, which reflects the relative scarcity of local data on causes of ill health. INTERPRETATION: These estimates at local, regional, and national level will allow policy makers to match resources and priorities to levels of burden and risk factors. Improvement in YLLs and life expectancy slowed notably after 2010, particularly in cardiovascular disease and cancer, and targeted actions are needed if the rate of improvement is to recover. A targeted policy response is also required to address the increasing proportion of burden due to morbidity, such as musculoskeletal problems and depression. Improving the quality and completeness of available data on these causes is an essential component of this response. FUNDING: Bill & Melinda Gates Foundation and Public Health England.

National public health system responses to diabetes and other important noncommunicable diseases : Background, goals, and results of an international workshop at the Robert Koch Institute.

Diabetes mellitus and other noncommunicable diseases (NCDs) represent an emerging global public health challenge. In Germany, about 6.7 million adults are affected by diabetes according to national health surveys, including 1.3 million with undiagnosed diabetes. Complications of diabetes result in an increasing burden for individuals and society as well as enormous costs for the health care system. In response, the Federal Ministry of Health commissioned the Robert Koch Institute (RKI) to implement a diabetes surveillance system and the Federal Center for Health Education (BZgA) to develop a diabetes prevention strategy. In a two-day workshop jointly organized by the RKI and the BZgA, representatives from public health institutes in seven countries shared their expertise and knowledge on diabetes prevention and surveillance. Day one focused on NCD surveillance systems and emphasized both the strengthening of sustainable data sources and the timely and targeted dissemination of results using innovative formats. The second day focused on diabetes prevention strategies and highlighted the importance of involving all relevant stakeholders in the development process to facilitate its acceptance and implementation. Furthermore, the effective translation of prevention measures into real-world settings requires data from surveillance systems to identify high-risk groups and evaluate the effect of measures at the population level based on analyses of time trends in risk factors and disease outcomes. Overall, the workshop highlighted the close link between diabetes prevention strategies and surveillance systems. It was generally stated that only robust data enables effective prevention measures to encounter the increasing burden from diabetes and other NCDs.

Using routine data to measure ethnic differentials in access to coronary revascularization.

BACKGROUND: Ethnic inequalities in access to health services are difficult to monitor and address because of limited data. Within the health service, ethnicity data have been poor quality, partly because they are not seen as useful. METHODS: The analysis related age- and sex-standardized coronary revascularization procedures to defined measures of need, using proportional ratios derived from Hospital Episode Statistics records for London residents admitted to any hospital nationally in 2002-03 or 2003-04. RESULTS: Although 2001 Ethnicity Categories were mandatory for the NHS from April 2001, by 2003-04 >20% of coronary heart disease (CHD) records still had no ethnic category coded. Hospital admission for CHD and revascularization by ethnicity varied widely, following known patterns of CHD incidence and mortality. There is much less variation between ethnic groups when comparing revascularization rate relative with CHD admission rates (whether all or emergencies). However, Bangladeshi patients had only two-thirds [proportional ratio 66.8, 95% confidence interval (CI) 60.7-73.3] and Black Caribbean and Black African patients four-fifths (proportional ratios 80.5, 72.0-89.9 and 80.7, 68.0-95.2, respectively) the revascularization rate in comparison with apparent need as the general population. CONCLUSION: Even with imperfect data, the analysis of routine data can identify inequalities that warrant further investigation.

Ethnicity coding in a regional cancer registry and in Hospital Episode Statistics.

BACKGROUND: The collection of ethnicity information as part of cancer datasets is important for planning services and ensuring equal access, and for epidemiological studies. However, ethnicity has generally not been well recorded in cancer registries in the UK. The aim of this study was to determine the completeness of ethnicity coding in the Thames Cancer Registry (TCR) database and within the Hospital Episode Statistics (HES) data as held by the London Health Observatory, and to investigate factors associated with ethnicity being recorded. METHODS: Records for 111821 hospital admissions of London residents with a malignant cancer as a primary diagnosis between April 2002 and March 2003 and records for 25581 London residents diagnosed with cancer in 2002 were examined. Data on sex, age, cancer network of residence, deprivation, proportion of non-whites in the local authority population, and site of cancer were available. The proportion of patients in each group with a valid ethnicity code was calculated. In the TCR data proportions were also calculated adjusted for all other variables. RESULTS: Ethnicity was recorded for 90661 (81.1%) of the hospital admissions in the HES data and 5796 (22.7%) patients on the TCR database. Patients resident in areas with a higher proportion of non-white residents and the most deprived populations were more likely to have an ethnic code on the TCR database, though this pattern was not seen in the HES data. Adjustment did not materially affect the association between deprivation and ethnicity being recorded in the TCR data. CONCLUSION: There was a large difference in completeness of ethnicity between the data sources. In order to improve the level of recording in TCR data there needs to be better recording of ethnicity in sources TCR data collection staff have access to, or use of information from other sources e.g. electronic data feeds from hospitals or pathology laboratories, or HES data itself supplied directly to TCR. Efforts to collect ethnicity data should be encouraged in all healthcare settings. Future research should explore where the difficulties collecting ethnicity information lie, whether with patients, healthcare professionals or the recording procedure, and how such problems can be overcome.

Association of population and practice factors with potentially avoidable admission rates for chronic diseases in London: cross sectional analysis.

OBJECTIVES: To examine the association between underlying ill health, material deprivation and primary care supply factors and hospital admission rates for potentially avoidable admissions in primary care trusts in London. DESIGN: Cross sectional analysis at primary care trusts level using routine data from multiple sources. SETTING: All 31 primary care trusts in London with a total resident population of 7 million patients. MAIN OUTCOME MEASURES: Age-standardized hospital admission rates for asthma, diabetes, heart failure, hypertension and chronic obstructive pulmonary disease. RESULTS: Admission rates varied widely for the conditions examined across the 31 primary care trusts. In 2001, age adjusted admission rates for asthma varied from 76 to 189 per 100,000 and for diabetes from 38 to 183 per 100,000. There was a significant association between higher admission rates and measures of underlying ill health and material deprivation but not quantitative measures of primary care service provision. Provision of specialist chronic disease services in primary care for diabetes but not for asthma were significantly associated with reduced admission rates. There was no association of prescribing levels in primary care trusts with admission rates for any of the conditions examined. CONCLUSIONS: Although hospital admission for some chronic diseases is potentially avoidable and rates of hospital admission for these conditions are possible indicators of the quality of care, they should be interpreted in conjunction with measures of population composition and deprivation. Failure to do this may result in primary care trusts and general practitioners being criticized for aspects of health care utilization that are not under their direct control.

The ecological relationship between deprivation, social isolation and rates of hospital admission for acute psychiatric care: a comparison of London and New York City.

We report on comparative analyses of small area variation in rates of acute hospital admissions for psychiatric conditions in Greater London around the year 1998 and in New York City (NYC) in 2000. Based on a theoretical model of the factors likely to influence psychiatric admission rates, and using data from the most recent population censuses and other sources, we examine the association with area indicators designed to measure access to hospital beds, socio-economic deprivation, social fragmentation and ethnic/racial composition. We report results on admissions for men and women aged 15-64 for all psychiatric conditions (excluding self-harm), drug-related substance abuse/addiction, schizophrenia and affective disorders. The units of analysis in NYC were 165 five-digit Zip Code Areas and, in London, 760 electoral wards as defined in 1998. The analysis controls for age and sex composition and, as a proxy for access to care, spatial proximity to hospitals with psychiatric beds. Poisson regression modeling incorporating random effects was used to control for both overdispersion in the counts of admissions and for the effects of spatial autocorrelation. The results for NYC and London showed that local admission rates for all types of condition were positively and significantly associated with deprivation and the association is independent of demographic composition or 'access' to beds. In NYC, social fragmentation showed a significant association with admissions due to affective disorders and schizophrenia, and for drug dependency among females. Racial minority concentration was significantly and positively associated with admissions for schizophrenia. In London, social fragmentation was associated positively with admissions for men and women due to schizophrenia and affective disorders. The variable measuring racial/ethnic minority concentration for London wards showed a negative association with admission rates for drug dependency and for affective disorders. We discuss the interpretation of these results and the issues they raise in terms of the potential and limitations of international comparison.