How many emergency dispatches occurred per cardiac arrest?

Ambulance response times and 30-day mortality: a Copenhagen (Denmark) registry study

BACKGROUND AND IMPORTANCE

Ensuring prompt ambulance responses is complicated and costly. It is a general conception that short response times save lives, but the actual knowledge is limited.

OBJECTIVE

To examine the association between the response times of ambulances with lights and sirens and 30-day mortality.

DESIGN

A registry-based cohort study using data collected from 2014-2018.

SETTINGS AND PARTICIPANTS

This study included 182 895 individuals who, during 2014-2018, were dispatched 266 265 ambulances in the Capital Region of Denmark.

OUTCOME MEASURES AND ANALYSIS

The primary outcome was 30-day mortality. Subgroup analyses were performed on out-of-hospital cardiac arrests, ambulance response priority subtypes, and caller-reported symptoms of chest pain, dyspnoea, unconsciousness, and traffic accidents. The relation between variables and 30-day mortality was examined with logistic regression.

RESULTS

Unadjusted, short response times were associated with higher 30-day mortality rates across unadjusted response time quartiles (0-6.39 min: 9%; 6.40-8.60 min: 7.5%, 8.61-11.80 min: 6.6%, >11.80 min: 5.5%). This inverse relationship was consistent across subgroups, including chest pain, dyspnoea, unconsciousness, and response priority subtypes. For traffic accidents, no significant results were found. In the case of out-of-hospital cardiac arrests, longer response times of up to 10 min correlated with increased 30-day mortality rates (0-6.39 min: 84.1%; 6.40-8.60 min: 86.7%, 8.61-11.8 min: 87.7%, >11.80 min: 85.5%). Multivariable-adjusted logistic regression analysis showed that age, sex, Charlson comorbidity score, and call-related symptoms were associated with 30-day mortality, but response time was not (OR: 1.00 (95% CI [0.99-1.00])).

CONCLUSION

Longer ambulance response times were not associated with increased mortality, except for out-of-hospital cardiac arrests.

Variations in stakeholders' priorities and views on randomisation and funding decisions in out-of-hospital cardiac arrest: An exploratory study

BACKGROUND AND AIMS

Prehospital critical care for out-of-hospital cardiac arrest (OHCA) is a complex and largely unproven intervention. During research to examine this intervention, we noted significant differences in stakeholders' views about research, randomisation, and the funding of prehospital critical care for OHCA. We aimed to answer the following questions: What are stakeholders' priorities for prehospital research? What are stakeholders' views on randomisation of prehospital critical care? How do stakeholders consider allocation of resources in prehospital care?

METHODS

We undertook an explanatory qualitative framework analysis of interviews and focus group with 5 key stakeholder groups: patients and public, air ambulance charities, ambulance service commissioners, prehospital researchers, and prehospital critical care providers.

RESULTS

We undertook 3 focus group discussions with a total of 23 participants and 8 interviews with a total of 9 participants. Despite sharing a common appreciation of the concepts of scientific enquiry, fairness, and beneficence, the 5 relevant stakeholder groups displayed divergent views of research and funding strategies regarding the intervention of prehospital critical care for the condition of OHCA. The reasons for this divergence could largely be explained through the different personal experiences and situational contexts of each stakeholder group. Many aspects of the strategies suggested by the stakeholder groups only partially aligned with principles of traditional evidence-based medicine, but were held with strong conviction.

DISCUSSION

Analysis of the views of 5 stakeholder groups regarding research and the funding of prehospital critical care for OHCA revealed shared values but a variety of different strategies to achieve these. This knowledge can help researchers in similar fields in the planning and presentation of their research, to maximise impact on decision making.

Association between ambulance dispatch priority and patient condition

OBJECTIVE

To compare chief complaints of the Medical Priority Dispatch System in terms of the match between dispatch priority and patient condition.

METHODS

This was a retrospective whole-of-population study of emergency ambulance dispatch in Perth, Western Australia, 1 January 2014 to 30 June 2015. Dispatch priority was categorised as either Priority 1 (high priority), or Priority 2 or 3. Patient condition was categorised as time-critical for patient(s) transported as Priority 1 to hospital or who died (and resuscitation was attempted by paramedics); else, patient condition was categorised as less time-critical. The χ² statistic was used to compare chief complaints by false omission rate (percentage of Priority 2 or 3 dispatches that were time-critical) and positive predictive value (percentage of Priority 1 dispatches that were time-critical). We also reported sensitivity and specificity.

RESULTS

There were 211 473 cases of dispatch. Of 99 988 cases with Priority 2 or 3 dispatch, 467 (0.5%) were time-critical. Convulsions/seizures and breathing problems were highlighted as having more false negatives (time-critical despite Priority 2 or 3 dispatch) than expected from the overall false omission rate. Of 111 485 cases with Priority 1 dispatch, 6520 (5.8%) were time-critical. Our analysis highlighted chest pain, heart problems/automatic implanted cardiac defibrillator, unknown problem/collapse, and headache as having fewer true positives (time-critical and Priority 1 dispatch) than expected from the overall positive predictive value.

CONCLUSION

Scope for reducing under-triage and over-triage of ambulance dispatch varies between chief complaints of the Medical Priority Dispatch System. The highlighted chief complaints should be considered for future research into improving ambulance dispatch system performance.

The impact of a pre-hospital critical care team on survival from out-of-hospital cardiac arrest

AIM

To assess the impact of a pre-hospital critical care team (CCT) on survival from out-of-hospital cardiac arrest (OHCA).

METHODS

We undertook a retrospective observational study, comparing OHCA patients attended by advanced life support (ALS) paramedics with OHCA patients attended by ALS paramedics and a CCT between April 2011 and April 2013 in a single ambulance service in Southwest England. We used multiple logistic regression to control for an anticipated imbalance of prognostic factors between the groups. The primary outcome was survival to hospital discharge. All data were collected independently of the research.

RESULTS

1851 cases of OHCA were included in the analysis, of which 1686 received ALS paramedic treatment and 165 were attended by both ALS paramedics and a CCT. Unadjusted rates of survival to hospital discharge were significantly higher in the CCT group, compared to the ALS paramedic group (15.8% and 6.5%, respectively, p<0.001). After adjustment using multiple logistic regression, the effect of CCT treatment was no longer statistically significant (OR 1.54, 95% CI 0.89-2.67, p=0.13). Subgroup analysis of OHCA with first monitored rhythm of ventricular fibrillation or pulseless ventricular tachycardia showed similar results.

CONCLUSION

Pre-hospital critical care for OHCA was not associated with significantly improved rates of survival to hospital discharge. These results are in keeping with previously published studies. Further research with a larger sample size is required to determine whether CCTs can improve outcome in OHCA.

Which emergency medical dispatch codes predict high prehospital nontransport rates in an urban community?

BACKGROUND

The Medical Priority Dispatch System (MPDS) is a commonly used computer-based emergency medical dispatch (EMD) system that is widely used to prioritize 9-1-1 calls and optimize resource allocation. There are five major priority classes used to dispatch 9-1-1 calls in the San Francisco System; Alpha codes are the lowest priority (lowest expected acuity) and Echo are the highest priority.

OBJECTIVE

We sought to determine which MPDS dispatch codes are associated with high prehospital nontransport rates (NTRs).

METHODS

All unique MPDS call categories from 2009 in a highly urbanized, two-tier advanced life support (ALS) system were sorted according to highest NTRs. There are many reasons for nontransport, such as "gone on arrival," and "patient denied transport." Those categories with greater than 100 annual calls were further evaluated. MPDS groups that included multiple categories with NTRs exceeding 25% were then identified and each category was analyzed. Results. EMS responded to a total of 81,437 calls in 2009, of which 18,851 were not transported by EMS. The majority of the NTRs were found among "cardiac/ respiratory arrest/death," "assault/sexual assaults," "unknown problem/man down," "traffic/transportation accidents," and "unconscious/fainting." "Cardiac or respiratory arrest/death -obvious death" (9B1) had the highest overall nontransport rate, 99.25% (1/134), most likely due to declaration of death. "Unknown problem -man down -medical alert notification" had the second highest NTR, 67.22% (138/421). However, Echo priority codes had the highest overall nontransport rates (45.45%) and Charlie had the lowest (13.84%).

CONCLUSIONS

The nontransport rates of individual MPDS categories vary considerably and should be considered in any system design. We identified 52 unique call categories to have a 25% or greater NTR, 18 of which exceeded 40%. The majority of NTRs occurred among the "cardiac/respiratory arrest/death," "assault/sexual assaults," "unknown problem/man down," "traffic/transportation accidents," and "unconscious/fainting" categories. The higher the priority code within each subset (AB vs. CDE), the less likely the patient was to be transported. Charlie priority codes had a lower NTR than Delta, and Delta was lower than Echo. Charlie codes were therefore the strongest predictors of hospital transport, while Echo codes (highest priority) were those with the highest nontransport rates and were the worst predictors of hospital transport in the emergent subset.

Emergency medical dispatch codes association with emergency department outcomes

BACKGROUND

Emergency medical dispatch systems are used to help categorize and prioritize emergency medical services (EMS) resources for requests for assistance.

OBJECTIVE

We examined whether a subset of Medical Priority Dispatch System (MPDS) codes could predict patient outcomes (emergency department [ED] discharge versus hospital admission/ED death).

METHODS

This retrospective observational cohort study analyzed requests for EMS through a single public safety answering point (PSAP) serving a mixed urban, suburban, and rural community over one year. Probabilistic matching was used to link subjects. Descriptive statistics, 95% confidence intervals (CIs), and logistic regression were calculated for the 107 codes and code groupings (9E vs. 9E1, 9E2, etc.) that were used 50 or more times during the study period.

RESULTS

Ninety percent of PSAP records were matched to EMS records and 84% of EMS records were matched to ED data, resulting in 26,846 subjects with complete records. The average age of the cohort was 46.2 years (standard deviation [SD] 24.8); 54% were female. Of the transported patients, 70% were discharged from the ED, with nine dispatch codes demonstrating a 90% or greater predictive power. Three code groupings had more than 60% predictive power for admission/death. Subjects aged 65 years and older were found to be at increased risk for admission/death in 33 dispatch codes (odds ratio [OR] 2.0 [95% confidence interval 1.3-3.0] to 19.6 [5.3-72.6]).

CONCLUSIONS

A small subset (8% of codes; 7% by call volume) of MPDS codes were associated with greater than 90% predictive ability for ED discharge. Older adults are at increased risk for admission/death in a separate subset of MPDS codes, suggesting that age criteria may be useful to identify higher-acuity patients within the MPDS code. These findings could assist in prehospital/hospital resource management; however, future studies are needed to validate these findings for other EMS systems and to investigate possible strategies for improvements of emergency response systems.

The methodology of the Australian Prehospital Outcomes Study of Longitudinal Epidemiology (APOStLE) Project

This paper describes the methodology of a large emergency medical services (EMS) data linkage research project currently under way in the statewide EMS system of New South Wales, Australia. The paper is intended to provide the reader with an understanding of how linkage techniques can be used to facilitate EMS research. This project, the Australian Prehospital Outcomes Study of Longitudinal Epidemiology (APOStLE) Project, links data from six statewide sources (computer-assisted dispatch, EMS patient health care reports, emergency department data, inpatient data, and two death registries) to enable researchers to examine the patient's entire journey through the health care system, from the emergency 0-0-0 call to the emergency department and inpatient setting, through to discharge or death, for approximately 2.6 million patients transported by the Ambulance Service of New South Wales to emergency departments between June 2006 and July 2009. Manual, deterministic, and probabilistic data linkages are described, and potential applications of linked data in EMS research are outlined.