Social Inequalities in Emergency Call and Emergency Response Patterns

Overview

Background: Inequality in access to healthcare is a challenge internationally. Despite that medical emergency calls can be considered as access point to pre-hospital emergency care and hospital admission in emergency situations, no data on inequality in access to healthcare through emergency calls is reported in the international literature. Study aims: The aim of this study is two-fold: 1. to evaluate the association between socio-economic characteristics of citizens and first-time emergency call in the Capital Region of Denmark 2. to evaluate the association between socio-economic characteristics of citizens with an emergency call and the priority level of the response provided by the emergency medical dispatch center in the Capital Region of Denmark. Method: Observational register based study of adult citizens in the Capital Region of Denmark. Educational level, household income and employment are used as socioeconomic indicators. The unique civil registration number will be used to link data from the Emergency Medical Dispatch Center with data from the Civil Registration System, Danish registers on personal labor market affiliation, the Danish Populations Education Register, the Danish Income Statistics Registry and the national patient registry. Logistic regression models will be used for the association between socio economic indicators and first time emergency calls and the association between socioeconomic indicators and the priority level of the response provided.

Background: In prehospital emergency medicine, emergency medical dispatchers play an essential role as gatekeepers to emergency care from the emergency medical services and possibly hospital admissions. Dispatching is the task of handling emergency calls in terms of appropriate triage, delivery of pre-arrival instructions and management of resources to citizens calling for help. Research within out-of-hospital cardiac arrest has shown that medical dispatchers can contribute to increased survival, if cardiac arrest is identified through the emergency call, and telephone assisted cardiopulmonary resuscitation is initiated. Optimal performance in the links of the chain of survival is not only dependent on good performance of healthcare professionals in the prehospital setting, but also on the persons initiating resuscitation and calling for help. This is not only true for OHCA but also other life-threatening situations and the outcome may be affected by the interaction between the person calling for help and the medical dispatcher responding to the call and providing advice and an adequate response from the emergency medical services. Research in this area is, however, at an early stage. Inequality in access to healthcare is a challenge internationally. Despite that medical emergency calls can be considered as access point to pre-hospital emergency care and hospital admission in emergency situations, no data on inequality in access to healthcare through emergency calls is reported in the international literature. Study Objective: The aim of the study is two-fold: 1. To evaluate the association between socio-economic characteristics of citizens and first-time emergency call in the Capital Region of Denmark 2. To evaluate the association between socio-economic characteristics of citizens with an emergency call and the emergency response provided by the emergency medical dispatch center in the Capital Region of Denmark. Hypotheses: 1. Low socioeconomic position (measured by educational level, employment, household income as social indicators) is associated with a high incidence of emergency calls, compared to high socioeconomic position. 2. Within the most common medical contact causes (chest pain, intoxication, breathing difficulties, abdominal pain/back pain, altered level of consciousness, seizures and unconscious/lifeless adult), low socioeconomic position (measured by educational level, employment, household income as indicators) is associated with a lower level of emergency response, compared to high socioeconomic position. Study design: The study is an investigation of the population in the Capital Region of Denmark performed by combining data from the Emergency Medical Services and Danish central registries in a two-year period (December 2011-November 2013). Setting: The study is based on data from the Capital Region of Denmark with a population of 1.8 million. In Denmark, healthcare services are covered by income taxes. In case of an emergency, there is a single emergency phone number (1-1-2) to a call center that identifies the need for police, fire or medical assistance. In case of a medical problem, the caller is re-directed to an Emergency Medical Dispatch Center where medical dispatchers answer, process and respond to the call by activating the appropriate Emergency Medical Services. The medical dispatchers are specially trained nurses or paramedics with experience within emergency medicine. Their decision-making process is supported by a criteria-based, nationwide Emergency Medical Dispatch System (Danish Index for Emergency Care), which is a validated tool for managing emergency calls for the most urgent cases of emergencies. Analysis, study part 1: • Logistic regression models will be used with emergency call as outcome variable (yes/no) and socioeconomic indicators as explanatory variables, calculating odds ratios for the probability of a first-time emergency call for each socioeconomic indicator. The analysis will be performed unadjusted and adjusted for age, gender, civil status, country of origin, and comorbidity. Analysis, study part 2: * Ordinal logistic regression models will be used with emergency response as outcome variable (four levels) and socioeconomic indicators as explanatory variables to calculate the probability of each emergency response. The analysis will be performed unadjusted and adjusted for age, gender, civil status, country of origin and comorbidity. * The analysis will primarily be performed as complete case analysis and secondarily as a weighted analysis according to the proportion of missing personal identification numbers within each response type in the original dataset.