Association between drug poisoning deaths and season, week, weekday, and public holidays: protocol for a time series analysis of daily counts in England and Wales, 1993-2018

The number of deaths due to drug poisoning in England and Wales is increasing rapidly. Annual data shows that deaths plateaued in the decade before 2011 and then sharply increased. To improve our understanding of this problem and identify potential opportunities to prioritise harm reduction and addiction treatment services, we will investigate within-year and cyclical variation in deaths. This is a protocol for a time series analysis to assess whether risk of drug-related varies by season, by week of the month, by day of the week, and at public holidays. These trends have not been widely studied. The results could contribute to our understanding of environmental drivers of death due to drug poisoning, and to the planning of public health and clinical services that aim to prevent drug-related deaths

Health-care resource use among patients who use illicit opioids in England, 2010–20: A descriptive matched cohort study

Background and aims: People who use illicit opioids have higher mortality and morbidity than the general population. Limited quantitative research has investigated how this population engages with health-care, particularly regarding planned and primary care. We aimed to measure health-care use among patients with a history of illicit opioid use in England across five settings: general practice (GP), hospital outpatient care, emergency departments, emergency hospital admissions and elective hospital admissions. // Design: This was a matched cohort study using Clinical Practice Research Datalink and Hospital Episode Statistics. // Setting: Primary and secondary care practices in England took part in the study. // Participants: A total of 57 421 patients with a history of illicit opioid use were identified by GPs between 2010 and 2020, and 172 263 patients with no recorded history of illicit opioid use matched by age, sex and practice. // Measurements: We estimated the rate (events per unit of time) of attendance and used quasi-Poisson regression (unadjusted and adjusted) to estimate rate ratios between groups. We also compared rates of planned and unplanned hospital admissions for diagnoses and calculated excess admissions and rate ratios between groups. // Findings: A history of using illicit opioids was associated with higher rates of health-care use in all settings. Rate ratios for those with a history of using illicit opioids relative to those without were 2.38 [95% confidence interval (CI) = 2.36–2.41] for GP; 1.99 (95% CI = 1.94–2.03) for hospital outpatient visits; 2.80 (95% CI = 2.73–2.87) for emergency department visits; 4.98 (95% CI = 4.82–5.14) for emergency hospital admissions; and 1.76 (95% CI = 1.60–1.94) for elective hospital admissions. For emergency hospital admissions, diagnoses with the most excess admissions were drug-related and respiratory conditions, and those with the highest rate ratios were personality and behaviour (25.5, 95% CI = 23.5–27.6), drug-related (21.2, 95% CI = 20.1–21.6) and chronic obstructive pulmonary disease (19.4, 95% CI = 18.7–20.2). // Conclusions: Patients who use illicit opioids in England appear to access health services more often than people of the same age and sex who do not use illicit opioids among a wide range of health-care settings. The difference is especially large for emergency care, which probably reflects both episodic illness and decompensation of long-term conditions

Socioeconomic position and mortality risk of smoking: evidence from the English Longitudinal Study of Ageing (ELSA).

Background: It is not clear whether the harm associated with smoking differs by socioeconomic status. This study tests the hypothesis that smoking confers a greater mortality risk for individuals in low socioeconomic groups, using a cohort of 18 479 adults drawn from the English Longitudinal Study of Ageing. Methods:- Additive hazards models were used to estimate the absolute smoking-related risk of death due to lung cancer or Chronic Obstructive Pulmonary Disease (COPD). Smoking was measured using a continuous index that incorporated the duration of smoking, intensity of smoking and the time since cessation. Attributable death rates were reported for different levels of education, occupational class, income and wealth. Results: Smoking was associated with higher absolute mortality risk in lower socioeconomic groups for all four socioeconomic indicators. For example, smoking 20 cigarettes per day for 40 years was associated with 898 (95% CI 738, 1058) deaths due to lung cancer or COPD per 100 000 person-years among participants in the bottom income tertile, compared to 327 (95% CI 209, 445) among participants in the top tertile. Conclusions: Smoking is associated with greater absolute mortality risk for individuals in lower socioeconomic groups. This suggests greater public health benefits of smoking prevention or cessation in these groups

Causes of hospital admission and mortality among 6683 people who use heroin: a cohort study comparing relative and absolute risks

Background: Mortality in high-risk groups such as people who use illicit drugs is often expressed in relative terms such as standardised ratios. These measures are highest for diseases that are rare in the general population, such as hepatitis C, and may understate the importance of common long-term conditions. Population: 6683 people in community-based treatment for heroin dependence between 2006 and 2017 in London, England, linked to national hospital and mortality databases with 55,683 years of follow-up. Method: Age- and sex-specific mortality and hospital admission rates in the general population of London were used to calculate the number of expected events. We compared standardised ratios (relative risk) to excess deaths and admissions (absolute risk) across ICD-10 chapters and subcategories. Results: Drug-related diseases had the highest relative risks, with a standardised mortality ratio (SMR) of 48 (95% CI 42–54) and standardised admission ratio (SAR) of 293 (95% CI 282–304). By contrast, other diseases had an SMR of 4.4 (95% CI 4.0–4.9) and an SAR of 3.15 (95% CI 3.11–3.19). However, the majority of the 621 excess deaths (95% CI 569–676) were not drug-related (361; 58%). The largest groups were liver disease (75 excess deaths) and COPD (45). Similarly, 80% (11,790) of the 14,668 excess admissions (95% CI 14,382–14,957) were not drug-related. The largest groups were skin infections (1073 excess admissions), alcohol (1060), COPD (812) and head injury (612). Conclusions: Although relative risks of drug-related diseases are very high, most excess morbidity and mortality in this cohort was caused by common long-term conditions

Conditions associated with the initiation of domiciliary care following a hospital admission: a cohort study in East London, England

OBJECTIVE: Older people and people with complex needs often require both health and social care services, but there is limited insight into individual journeys across these services. To help inform joint health and social care planning, we aimed to assess the relationship between hospital admissions and domiciliary care receipt. DESIGN: Retrospective cohort study, using linked data on primary care activity, hospital admissions and social care records. SETTING: London Borough of Barking and Dagenham, England. PARTICIPANTS: Adults aged 19 and over who lived in the area on 1 April 2018 and who were registered at a general practice in East London between 1 April 2018 and 31 March 2020 (n=140 987). OUTCOME MEASURES: The outcome was initiation of domiciliary care. We estimated the rate of hospital-associated care package initiation, and of care packages unrelated to hospital admission. We also described the characteristics of hospital admissions that preceded domiciliary care, including primary diagnosis codes. RESULTS: 2041/140 987 (1.4%) participants had a domiciliary care package during a median follow-up of 1.87 years. 32.6% of packages were initiated during a hospital stay or within 7 days of discharge. The rate of new domiciliary care packages was 120 times greater (95% CI 110 to 130) during or after a hospital stay than at other times, and this association was present for all age groups. Primary admission reasons accounting for the largest number of domiciliary care packages were hip fracture, pneumonia, stroke, urinary tract infection, septicaemia and exacerbations of long-term conditions (chronic obstructive pulmonary disease and heart failure). Admission reasons with the greatest likelihood of a subsequent domiciliary care package were fractures and strokes. CONCLUSION: Hospitals are a major referral route into domiciliary care. While patients admitted due to new and acute illnesses account for many domiciliary care packages, exacerbations of long-term conditions and age-related and frailty-related conditions are also important drivers

Risk of discharge against medical advice among hospital inpatients with a history of opioid agonist therapy in New South Wales, Australia:a cohort study and nested crossover-cohort analysis

BACKGROUND: People who use illicit opioids have high rates of hospital admission. We aimed to measure the risk of discharge against medical advice among inpatients with a history of opioid agonist therapy (OAT), and test whether OAT is associated with lower risk of discharge against medical advice. METHODS: We conducted a cohort study including all emergency hospital admissions between 1 August 2001 and 30 April 2018 in New South Wales, Australia, among patients with a previous episode of OAT in the community. The main outcome was discharge against medical advice, and the main exposure was whether patients had an active OAT permit at the time of admission. RESULTS: 14,035/116,957 (12.0%) admissions ended in discharge against medical advice. Admissions during periods of OAT had 0.79 (0.76-0.83; p<0.001) times the risk of discharge against medical advice, corresponding to an absolute risk reduction of 3.3 percentage points. Risk of discharge against medical advice was higher among patients who were younger, male, identified as Aboriginal and/or Torres Strait Islanders, admitted for accidents, drug-related reasons, or injecting-related injuries (such as cutaneous abscesses), and those discharged at the weekend. In a subsample of 7,793 patients included in a crossover-cohort analysis, OAT was associated with 0.84 (95% CI 0.76-0.93; p<0.001) times the risk of discharge against medical advice. CONCLUSIONS: Among patients with a history of OAT, one in eight emergency hospital admissions ends in discharge against medical advice. OAT enrolment at the time of admission is associated with a reduction of this risk

Opioid Injection-Associated Bacterial Infections in England, 2002–2021: A Time Series Analysis of Seasonal Variation and the Impact of Coronavirus Disease 2019

BACKGROUND: Bacterial infections cause substantial pain and disability among people who inject drugs. We described time trends in hospital admissions for injecting-related infections in England. METHODS: We analyzed hospital admissions in England between January 2002 and December 2021. We included patients with infections commonly caused by drug injection, including cutaneous abscesses, cellulitis, endocarditis, or osteomyelitis, and a diagnosis of opioid use disorder. We used Poisson regression to estimate seasonal variation and changes associated with coronavirus disease 2019 (COVID-19) response. RESULTS: There were 92 303 hospital admissions for injection-associated infections between 2002 and 2021. Eighty-seven percent were skin, soft-tissue, or vascular infections; 72% of patients were male; and the median age increased from 31 years in 2002 to 42 years in 2021. The rate of admissions reduced from 13.97 per day (95% confidence interval [CI], 13.59-14.36) in 2003 to 8.94 (95% CI, 8.64-9.25) in 2011, then increased to 18.91 (95% CI, 18.46-19.36) in 2019. At the introduction of COVID-19 response in March 2020, the rate of injection-associated infections reduced by 35.3% (95% CI, 32.1-38.4). Injection-associated infections were also seasonal; the rate was 1.21 (95% CI, 1.18-1.24) times higher in July than in February. CONCLUSIONS: This incidence of opioid injection-associated infections varies within years and reduced following COVID-19 response measures. This suggests that social and structural factors such as housing and the degree of social mixing may contribute to the risk of infection, supporting investment in improved social conditions for this population as a means to reduce the burden of injecting-related infections

Black, Asian and Minority Ethnic groups in England are at increased risk of death from COVID-19: indirect standardisation of NHS mortality data

Background: International and UK data suggest that Black, Asian and Minority Ethnic (BAME) groups are at increased risk of infection and death from COVID-19. We aimed to explore the risk of death in minority ethnic groups in England using data reported by NHS England. Methods: We used NHS data on patients with a positive COVID-19 test who died in hospitals in England published on 28th April, with deaths by ethnicity available from 1st March 2020 up to 5pm on 21 April 2020. We undertook indirect standardisation of these data (using the whole population of England as the reference) to produce ethnic specific standardised mortality ratios (SMRs) adjusted for age and geographical region. Results: The largest total number of deaths in minority ethnic groups were Indian (492 deaths) and Black Caribbean (460 deaths) groups. Adjusting for region we found a lower risk of death for White Irish (SMR 0.52; 95%CIs 0.45-0.60) and White British ethnic groups (0.88; 95%CIs 0.86-0.0.89), but increased risk of death for Black African (3.24; 95%CIs 2.90-3.62), Black Caribbean (2.21; 95%CIs 2.02-2.41), Pakistani (3.29; 95%CIs 2.96-3.64), Bangladeshi (2.41; 95%CIs 1.98-2.91) and Indian (1.70; 95%CIs 1.56-1.85) minority ethnic groups. Conclusion: Our analysis adds to the evidence that BAME people are at increased risk of death from COVID-19 even after adjusting for geographical region, but was limited by the lack of data on deaths outside of NHS settings and ethnicity denominator data being based on the 2011 census. Despite these limitations, we believe there is an urgent need to take action to reduce the risk of death for BAME groups and better understand why some ethnic groups experience greater risk. Actions that are likely to reduce these inequities include ensuring adequate income protection, reducing occupational risks, reducing barriers in accessing healthcare and providing culturally and linguistically appropriate public health communications