Modelling of patient outcomes after emergency treatment for out-of-hospital cardiac arrest by paramedics and community first responders

Background The Community First Responder (CFR) provides a small but important ambulance response for out-of-hospital cardiac arrest (OHCA). We aimed to test the influence of CFR attendance at OHCA as part of a regional ambulance response using separate statistical models of Return of Spontaneous Circulation (ROSC) and patient survival by Discharge Alive from hospital (DA). Methods Data were from East Midlands Ambulance Service NHS Trust, involving 9284 patients with OHCA from April 2014 to March 2016. Observational analyses were conducted on the complete records of n=1227 patients treated and transported to hospital. The outcomes we considered were the occurrence of ROSC under emergency care (55.8%) with longer term survival DA (11.8%). We controlled for waiting time (WT; the length of time between 999 and emergency service arrival at the patient’s side). We represented emergency care by total treatment time (TOT; the length of time from emergency service arrival to patient delivery to hospital); where this included any time input due to a CFR attending prior to the paramedics. Independent probit regressions were used to explain both outcomes, with inputs that included WT, TOT and whether a CFR attended. We also controlled for patient age, gender, event location, and day of week. Results For both fitted models, the coefficient estimates of WT were such that patient outcomes worsened as wait time increased; however, while expected in sign neither estimate was statistically significant (in ROSC beta=-0.007, p=0.161; in DA beta=-0.012, p=0.08). Coefficient estimates of TOT were significant (p<0.01) but differed in sign (in ROSC beta=+0.008; in DA beta=-0.015). Estimates of CFR were insignificant but differed in sign (in ROSC beta=-0.328, p=0.089; in DA beta=+0.291, p=0.236). Conclusions Longer resuscitation period was associated with ROSC but we found no statistically significant association between CFR attendance and positive outcomes for OHCA

Mental health emergencies and COVID-19: the impact of ‘lockdown’ in the East Midlands of the UK.

Background: The most immediate response of the research community to COVID-19 has been a focus on understanding the effects, treatment and prevention of infection. Of equal and ongoing importance is elucidating the impact of mitigation measures, such as lockdown, on the wellbeing of societies. Research about mental health and lockdown in the UK has predominately involved large surveys that are likely to encounter self-selection bias. Further, self-reporting does not constitute a clinical judgement. Aims: To 1) compare the age, gender and ethnicity of patients experiencing mental health emergencies prior, compared to during lockdown, 2) determine whether the nature of mental health emergencies has changed during compared to before lockdown, 3) explore the utility of EMS data for identifying vulnerability to mental health emergencies in real-time during a pandemic. Methods: 32,401 clinical records of ambulance paramedics attending mental health emergencies in the East Midlands of the UK between March 23rd and July 31st 2020 and the same period in 2019 were analysed using binary logistic regression. Results: People of younger age, male gender and South Asian and Black ethnicity are particularly vulnerable to acute mental health conditions during lockdown. Acute cases of anxiety have increased during lockdown while suicide and intentional drug overdose have decreased. Conclusions: Self-reported data may underrepresent the true impact of lockdown on male mental health and ethnic minority groups. Emergency medical data can be used to identify vulnerable communities in the context of the extraordinary circumstances surrounding the current pandemic, as well as under more ordinary circumstances

Exploring the Impact of the COVID-19 Pandemic on Male Mental Health Emergencies Attended by Ambulances During the First National “Lockdown” in the East Midlands of the United Kingdom

The novel coronavirus disease 2019 (COVID-19) pandemic and associated mitigation strategies such as “lockdown” are having widespread adverse psychological effects, including increased levels of anxiety and depression. Most research using self-reported data highlights the pandemic’s impact on the psychological well-being of females, whereas data for mental health emergency presentations may reflect the impact on male mental health more accurately. We analyzed records of male mental health emergencies occurring in the East Midlands of the United Kingdom during the first national “lockdown.” We computed two binary logistic regression models to (a) compare male mental health emergencies occurring during “lockdown,” 2020 (5,779) with those occurring in the same period in 2019 (N = 4,744) and (b) compare male (N = 5,779) and female (N = 7,695) mental health emergencies occurring during “lockdown.” Comparisons considered the characteristics of mental health emergencies recorded by ambulance clinicians (Primary Impressions), and the socioeconomic characteristics of communities where emergencies use the Index of Multiple Deprivation. We found that during “lockdown,” male emergencies were more likely to involve acute anxiety (odds ratio [OR]: 1.42) and less likely to involve intentional drug overdose (OR: 0.86) or attempted suicide (OR: 0.71) compared with 2019. Compared with females, male emergencies were more likely to involve acute behavioral disturbance (OR: 1.99) and less likely to involve anxiety (OR: 0.67), attempted suicide (OR: 0.83), or intentional drug overdose (OR: 0.76). Compared with 2019, and compared with females, males experiencing mental health emergencies during “lockdown” were more likely to present in areas of high deprivation. Understanding the presentation of male mental health emergencies could inform improved patient care pathways

An early warning precision public health approach for assessing COVID-19 vulnerability in the UK: the Moore-Hill Vulnerability Index (MHVI)

Background Most COVID-19 vulnerability indices rely on measures that are biased by rates of exposure or are retrospective like mortality rates that offer little opportunity for intervention. The Moore-Hill Vulnerability Index (MHVI) is a precision public health early warning alternative to traditional infection fatality rates that presents avenues for mortality prevention. Methods We produced an infection-severity vulnerability index by calculating the proportion of all recorded positive cases that were severe and attended by ambulances at small area scale for the East Midlands of the UK between May 2020 and April 2022. We produced maps identifying regions with high and low vulnerability, investigated the accuracy of the index over shorter and longer time periods, and explored the utility of the MHVI compared to other common proxy measures and indices. Analysis included exploring the correlation between our novel index and the Index of Multiple Deprivation (IMD). Results The MHVI captures geospatial dynamics that single metrics alone often overlook, including the compound health challenges associated with disadvantaged and declining coastal towns inhabited by communities with postindustrial health legacies. A moderate negative correlation between MHVI and IMD reflects spatial analysis which suggests that high vulnerability occurs in affluent rural as well as deprived coastal and urban communities. Further, the MHVI estimates of severity rates are comparable to infection fatality rates for COVID-19. Conclusions The MHVI identifies regions with known high rates of poor health outcomes prior to the pandemic that case rates or mortality rates alone fail to identify. Pre-hospital early warning measures could be utilised to prevent mortality during a novel pandemic

Calculating real-world travel routes instead of straight-line distance in the community response to out-of-hospital cardiac arrest

Using straight-line distance to estimate the proximity of public-access Automated External Defibrillators (AEDs) or volunteer first-responders to potential out-of-hospital cardiac arrests (OHCAs) does not reflect real-world travel distance. The difference between estimates may be an important consideration for bystanders and first-responders responding to OHCAs and may potentially impact patient outcome. To explore how calculating real-world travel routes instead of using straight-line distance estimates might impact the community response to OHCA. We mapped 4355 OHCA (01/04/2016-31/03/2017) and 2677 AEDs in London (UK), and 1263 OHCA (18/06/2017-17/06/2018) and 4704 AEDs in East Midlands (UK) using ArcGIS mapping software. We determined the distance from OHCAs to the nearest AED using straight-line estimates and real-world travel routes. We mapped locations of potential OHCAs (London: n = 9065, 20/09/2019-22/03/2020; East Midlands: n = 7637, 20/09/2019-17/03/2020) for which volunteer first-responders were alerted by the GoodSAM mobile-phone app, and calculated response distance using straight-line estimates and real-world travel routes. We created Receiver Operating Characteristic (ROC) curves and calculated the Area Under the Curve (AUC) to determine if travel distance predicted whether or not a responder accepted an alert. Real-world travel routes to the nearest AED were (median) 219 m longer (623 m vs 406 m) than straight-line estimates in London, and 211 m longer (568 m vs 357 m) in East Midlands. The identity of the nearest AED changed on 26% occasions in both areas when calculating real-world travel routes. GoodSAM responders' real-world travel routes were (median) 222 m longer (601 m vs 379 m) in London, and 291 m longer (814 m vs 523 m) in East Midlands. AUC statistics for both areas demonstrated that neither straight-line nor real-world travel distance predicted whether or not a responder accepted an alert. Calculating real-world travel routes increases the estimated travel distance and time for those responding to OHCAs. Calculating straight-line distance may overestimate the benefit of the community response to OHCA

Characterizing Unusual Spatial Clusters of Male Mental Health Emergencies Occurring During the First National COVID-19 “Lockdown” in the East Midlands Region, UK: A Geospatial Analysis of Ambulance 999 Data

The widespread psychological effects of contagion mitigation measures associated with the novel coronavirus disease 2019 (COVID-19) are well known. Phases of “lockdown” have increased levels of anxiety and depression globally. Most research uses methods such as self-reporting that highlight the greater impact of the pandemic on the mental health of females. Emergency medical data from ambulance services may be a better reflection of male mental health. We use ambulance data to identify unusual clusters of high rates of male mental health emergencies occurring in the East Midlands of the United Kingdom during the first national “lockdown” and to explore factors that may explain clusters. Analysis of more than 5,000 cases of male mental health emergencies revealed 19 unusual spatial clusters. Binary logistic regression analysis (χ2 = 787.22, df = 20, p ≤ .001) identified 16 factors that explained clusters, including proximity to “healthy” features of the physical landscape, urban and rural dynamics, and socioeconomic condition. Our findings suggest that the factors underlying vulnerability of males to severe mental health conditions during “lockdown” vary within and between rural and urban spaces, and that the wider “hinterland” surrounding clusters influences the social and physical access of males to services that facilitate mental health support. Limitations on social engagement to mitigate effects of the pandemic are likely to continue. Our approach could inform delivery of emergency services and the development of community-level services to support vulnerable males during periods of social isolation

Data quality and 30-day survival for out-of-hospital cardiac arrest in the UK out-of-hospital cardiac arrest registry: A data linkage study

© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted. Objectives The Out-of-Hospital Cardiac Arrest Outcomes (OHCAO) project aims to understand the epidemiology and outcomes of out-of-hospital cardiac arrest (OHCA) across the UK. This data linkage study is a subproject of OHCAO. The aim was to establish the feasibility of linking OHCAO data to National Health Service (NHS) patient demographic data and Office for National Statistics (ONS) date of death data held on the NHS Personal Demographics Service (PDS) database to improve OHCAO demographic data quality and enable analysis of 30-day survival from OHCA. Design and setting Data were collected from 1 January 2014 to 31 December 2014 as part of a prospective, observational study of OHCA attended by 10 English NHS Ambulance Services. 28 729 OHCA cases had resuscitation attempted by Emergency Medical Services and were included in the study. Data linkage was carried out using a data linkage service provided by NHS Digital, a national provider of health-related data. To assess data linkage feasibility a random sample of 3120 cases was selected. The sample was securely transferred to NHS Digital to be matched using OHCAO patient demographic data to return previously missing demographic data and provide ONS date of death data. Results A total of 2513 (80.5%) OHCAO cases were matched to patients in the NHS PDS database. Using the linkage process, missing demographic data were retrieved for 1636 (72.7%) out of 2249 OHCAO cases that had previously incomplete demographic data. Returned ONS date of death data allowed analysis of 30-day survival status. The results showed a 30-day survival rate of 9.3%, reducing unknown survival status from 46.1% to 8.5%. Conclusions In this sample, data linkage between the OHCAO registry and NHS PDS database was shown to be feasible, improving demographic data quality and allowing analysis of 30-day survival status