Medical Emergency Calls Clinical Trial
Official title:
Social Inequalities in Emergency Call and Emergency Response Patterns
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.
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Observational Model: Cohort, Time Perspective: Retrospective