Does Emergency Medical Dispatch Priority Predict Delphi Process-Derived Levels of Prehospital Intervention?

Association between initial presenting level of consciousness and patient acuity - A potential application for secondary triage in emergency ambulance calls

INTRODUCTION

Conscious state assessment is important for the triage of emergency patients. In this study, we measured the association between ambulance patients' conscious state and high versus lower acuity, with a view to informing telephone triage assessment of conscious state.

METHODS

Data were analysed from one year of emergency ambulance incidents in Perth, Western Australia. Patient conscious state at the time of paramedic arrival was compared to acuity (based on paramedic assessment and management). We determined the proportion of high-acuity patients across six levels of consciousness (Alert, Confused, Drowsy, Voice Response, Pain Response, Unresponsive) overall, and within individual protocols of the Medical Priority Dispatch System (MPDS).

RESULTS

The proportion of high acuity patients increased with each step across the consciousness scale. Applying conscious state as a binary predictor of acuity, the largest increases occurred moving the threshold from Alert to Confused (22.0-48.6% high acuity) and Drowsy to Voice Response (61.9-89.5% high acuity). The Area Under the Curve (AUC) of the Receiver Operating Characteristic was 0.65. Within individual protocols, the highest AUC was in Cardiac Arrest (0.89), Overdose/Poisoning (0.81), Unknown Problem (0.76), Diabetic Problem, (0.74) and Convulsions/Fitting (0.73); and lowest in Heart problems (0.55), Abdominal Pain (0.55), Breathing Problems (0.55), Back Pain (0.53), and Chest Pain (0.52).

CONCLUSION

Based on these proportions of high acuity patients, it is reasonable to consider patients with any altered conscious state a high priority. The value of conscious state assessment for predicting acuity varies markedly between MPDS protocols. These findings could help inform secondary triage of ambulance patients during the emergency call.

Paramedic management of back pain: a scoping review

BACKGROUND

Research examining paramedic care of back pain is limited.

OBJECTIVE

To describe ambulance service use and usual paramedic care for back pain, the effectiveness and safety of paramedic care of back pain, and the characteristics of people with back pain who seek care from paramedics.

METHODS

We included published peer-reviewed studies of people with back pain who received any type of paramedic care on-scene and/or during transport to hospital. We searched MEDLINE, EMBASE, CINAHL, Web of Science and SciELO from inception to July 2022. Two authors independently screened and selected the studies, performed data extraction, and assessed the methodological quality using the PEDro, AMSTAR 2 and Hawker tools. This review followed the JBI methodological guidance for scoping reviews and PRISMA extension for scoping reviews.

RESULTS

From 1987 articles we included 26 articles (25 unique studies) consisting of 22 observational studies, three randomised controlled trials and one review. Back pain is frequently in the top 3 reasons for calls to an ambulance service with more than two thirds of cases receiving ambulance dispatch. It takes ~ 8 min from time of call to an ambulance being dispatched and 16% of calls for back pain receive transport to hospital. Pharmacological management of back pain includes benzodiazepines, NSAIDs, opioids, nitrous oxide, and paracetamol. Non-pharmacological care is poorly reported and includes referral to alternate health service, counselling and behavioural interventions and self-care advice. Only three trials have evaluated effectiveness of paramedic treatments (TENS, active warming, and administration of opioids) and no studies provided safety or costing data.

CONCLUSION

Paramedics are frequently responding to people with back pain. Use of pain medicines is common but varies according to the type of back pain and setting, while non-pharmacological care is poorly reported. There is a lack of research evaluating the effectiveness and safety of paramedic care for back pain.

Improving ambulance dispatch triage to trauma: A scoping review using the framework of development and evaluation of clinical prediction rules

OBJECTIVE

Ambulance dispatch algorithms should function as clinical prediction rules, identifying high acuity patients for advanced life support, and low acuity patients for non-urgent transport. Systematic reviews of dispatch algorithms are rare and focus on study types specific to the final phases of rule development, such as impact studies, and may miss the complete value-added evidence chain. We sought to summarise the literature for studies seeking to improve dispatch in trauma by performing a scoping review according to standard frameworks for developing and evaluating clinical prediction rules.

METHODS

We performed a scoping review searching MEDLINE, EMBASE, CINAHL, the CENTRAL trials registry, and grey literature from January 2005 to October 2021. We included all study types investigating dispatch triage to injured patients in the English language. We reported the clinical prediction rule phase (derivation, validation, impact analysis, or user acceptance) and the performance and outcomes measured for high and low acuity trauma patients.

RESULTS

Of 2067 papers screened, we identified 12 low and 30 high acuity studies. Derivation studies were most common (52%) and rule-based computer-aided dispatch was the most frequently investigated (23 studies). Impact studies rarely reported a prior validation phase, and few validation studies had their impact investigated. Common outcome measures in each phase were infrequent (0 to 27%), making a comparison between protocols difficult. A series of papers for low acuity patients and another for pediatric trauma followed clinical prediction rule development. Some low acuity Medical Priority Dispatch System codes are associated with the infrequent requirement for advanced life support and clinician review of computer-aided dispatch may enhance dispatch triage accuracy in studies of helicopter emergency medical services.

CONCLUSIONS

Few derivation and validation studies were followed by an impact study, indicating important gaps in the value-added evidence chain. While impact studies suggest clinician oversight may enhance dispatch, the opportunity exists to standardize outcomes, identify trauma-specific low acuity codes, and develop intelligent dispatch systems.

The Development of Consensus-Based Descriptors for Low-Acuity Emergency Medical Services Cases for the South African Setting

INTRODUCTION

Emergency Medical Services (EMS) are designed to respond to and manage patients experiencing life-threatening emergencies; however, not all emergency calls are necessarily emergent and of high acuity. Emergency responses to low-acuity patients affect not only EMS, but other areas of the health care system. However, definitions of low-acuity calls are vague and subjective; therefore, it was necessary to provide a clear description of the low-acuity patient in EMS.

AIM

The goal of this study was to develop descriptors for "low-acuity EMS patients" through expert consensus within the EMS environment.

METHODS

A Modified Delphi survey was used to develop call-out categories and descriptors of low acuity through expert opinion of practitioners within EMS. Purposive, snowball sampling was used to recruit 60 participants, of which 29 completed all three rounds. An online survey tool was used and offered both binary and free-text options to participants. Consensus of 75% was accepted on the binary options while free text offered further proposals for consideration during the survey.

RESULTS

On completion of round two, consensus was obtained on 45% (70/155) of the descriptors, and a further 30% (46/155) consensus was obtained in round three. Experts felt that respiratory distress, unconsciousness, chest pain, and severe hemorrhage cannot be considered low acuity. For other emergency response categories, specific descriptors were offered to denote a case as low acuity.

CONCLUSION

Descriptors of low acuity in EMS are provided in both medical and trauma cases. These descriptors may not only assist in the reduction of unnecessary response and transport of patients, but also assist in identifying the most appropriate response of EMS resources to call-outs. Further development and validation are required of these descriptors in order to improve accuracy and effectiveness within the EMS dispatch environment.

Enhancing predictions of patient conveyance using emergency call handler free text notes for unconscious and fainting incidents reported to the London Ambulance Service

OBJECTIVE

Pre-hospital emergency medical services use clinical decision support systems (CDSS) to triage calls. Call handlers often supplement this by making free text notes covering key incident information. We investigate whether machine learning approaches using features from such free text notes can improve prediction of unconscious patients who require conveyance.

MATERIALS AND METHODS

We analysed a subset of all London Ambulance Service calls that were triaged through the Medical Priority Dispatch System (MPDS) as involving an unconscious or fainting patient in 2018. We use and compare two machine learning algorithms: random forest (RF) and gradient boosting machine (GBM). For each incident, we predict whether the patient will be conveyed to a hospital emergency department or equivalent using as features 1) the MPDS code, 2) the free text notes and 3) the two together. We evaluate model performance using the area under the curve (AUC) metric. Given the imbalance of outcomes (patient conveyed 71 %, not conveyed 29 %), we also consider sensitivity and specificity.

RESULTS

Using only the MPDS code resulted in an AUC of 0.57. Using the text notes gave an improved AUC score of 0.63 and combining the two gave an AUC score of 0.64 (scores were similar for RF and GBM). GBM models scored better on sensitivity (0.93 vs 0.62 for RF in the combined model), but specificity was lower (0.17 vs. 0.56 for RF in the combined model).

CONCLUSIONS

Using information contained in the free text notes made by call handlers in combination with MPDS improves prediction of unconscious and fainting patients requiring conveyance to a hospital emergency department (or equivalent) when compared with machine learning models using MPDS codes only. This suggests there is some useful information in unstructured data captured by emergency call handlers that complements MPDS codes. Quantifying this gain can help inform emergency medical service policy when evaluating the decision to expand or augment existing CDSS.

Intensity of care delivered by prehospital emergency medical service physicians to patients with deliberate self-poisoning: results from a 2-day cross-sectional study in France

Emergency management of deliberate self-poisoning (DSP) by drug overdose is common in emergency medicine. There is a paucity of data about the prehospital care of these patients. The principal aim was to describe the intensity of care received by patients with DSP who were managed by prehospital emergency medical service (EMS) physicians. A 48-h cross-sectional study was conducted in 319 EMS and emergency units in France. Patient and poisoning characteristics and treatments administered were recorded. Complications of poisoning, hospitalization, intensive care unit admission and death were recorded until day 30. The primary endpoint was the probability of receiving prehospital intensive care, including fluid resuscitation, vasopressor therapy, invasive ventilation, or antidotal treatments, depending whether prehospital treatment was carried out by an EMS physician or not. Data from 703 patients (median age was 43 [30-52] years, 288 (40%) men) were analyzed. One hundred and fifteen (16%) patients were attended by an EMS physician. Patients attended by EMS physicians were more likely to receive intensive treatment in the prehospital setting [odds ratio (OR) 7.4, 95% confidence interval 4.3-12.9]. These patients had more severe poisoning as suggested mainly by a lower Glasgow Coma Score (13 [8-15] vs. 15 [15-15]; p < 0.001) and a higher rate of admission to an intensive care unit [29 (25%) vs. 15 (2%), p < 0.001]. Patients with DSP attended by prehospital EMS physicians frequently received intensive care. The level of care seemed appropriate for the severity of the poisoning.

The appropriateness of low-acuity cases referred for emergency ambulance dispatch following ambulance service secondary telephone triage: A retrospective cohort study

Objective

Ambulance-based secondary telephone triage systems have been established in ambulance services to divert low-acuity cases away from emergency ambulance dispatch. However, some low-acuity cases still receive an emergency ambulance dispatch following secondary triage. To date, no evidence exists identifying whether these cases required an emergency ambulance. The aim of this study was to investigate whether cases were appropriately referred for emergency ambulance dispatch following secondary telephone triage.

Methods

A retrospective cohort analysis was conducted of cases referred for emergency ambulance dispatch in Melbourne, Australia following secondary telephone triage between September 2009 and June 2012. Appropriateness was measured by assessing the frequency of advanced life support (ALS) treatment by paramedics, and paramedic transport to hospital.

Results

There were 23,696 cases included in this study. Overall, 54% of cases received paramedic treatment, which was similar to the state-wide rate for emergency ambulance cases (55.5%). All secondary telephone triage cases referred for emergency ambulance dispatch had transportation rates higher than all metropolitan emergency ambulance cases (82.2% versus 71.1%). Two-thirds of the cases that were transported were also treated by paramedics (66.5%), and 17.7% of cases were not transported to hospital by ambulance following paramedic assessment.

Conclusions

Overall, the cases returned for emergency ambulance dispatch following secondary telephone triage were appropriate. Nevertheless, the paramedic treatment rates in particular indicate a considerable rate of overtriage requiring further investigation to optimize the efficacy of secondary telephone triage.

Patient and case characteristics associated with 'no paramedic treatment' for low-acuity cases referred for emergency ambulance dispatch following a secondary telephone triage: a retrospective cohort study

BACKGROUND

Predicting case types that are unlikely to be treated by paramedics can aid in managing demand for emergency ambulances by identifying cases suitable for alternative management pathways. The aim of this study was to identify the patient characteristics and triage outcomes associated with 'no paramedic treatment' for cases referred for emergency ambulance dispatch following secondary telephone triage.

METHODS

A retrospective cohort analysis was conducted of cases referred for emergency ambulance dispatch following secondary telephone triage between September 2009 and June 2012. Multivariable logistic regression modelling was used to identify explanatory variables associated with 'no paramedic treatment'.

RESULTS

There were 19,041 cases eligible for inclusion in this study over almost three years, of which 8510 (44.7%) were not treated after being sent an emergency ambulance following secondary triage. Age, time of day, pain, triage guideline group, and comorbidities were associated with 'no paramedic treatment'. In particular, cases 0-4 years of age or those with psychiatric conditions were significantly less likely to be treated by paramedics, and increasing pain resulted in higher rates of paramedic treatment.

CONCLUSIONS

This study highlights that case characteristics can be used to identify particular case types that may benefit from care pathways other than emergency ambulance dispatch. This process is also useful to identify gaps in the alternative care pathways currently available. These findings offer the opportunity to optimise secondary telephone triage services to support their strategic purpose of minimising unnecessary emergency ambulance demand and to match the right case with the right care pathway.

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.

Complementarity of Clinician Judgment and Evidence Based Models in Medical Decision Making: Antecedents, Prospects, and Challenges

Early accounts of the development of modern medicine suggest that the clinical skills, scientific competence, and doctors' judgment were the main impetus for treatment decision, diagnosis, prognosis, therapy assessment, and medical progress. Yet, clinician judgment has its own critics and is sometimes harshly described as notoriously fallacious and an irrational and unfathomable black box with little transparency. With the rise of contemporary medical research, the reputation of clinician judgment has undergone significant reformation in the last century as its fallacious aspects are increasingly emphasized relative to the evidence based options. Within the last decade, however, medical forecasting literature has seen tremendous change and new understanding is emerging on best ways of sharing medical information to complement the evidence based medicine practices. This review revisits and highlights the core debate on clinical judgments and its interrelations with evidence based medicine. It outlines the key empirical results of clinician judgments relative to evidence based models and identifies its key strengths and prospects, the key limitations and conditions for the effective use of clinician judgment, and the extent to which it can be optimized and professionalized for medical use.

Factors Influencing the Timeliness of Emergency Medical Service Response to Time Critical Emergencies

OBJECTIVE

While emergency medical service (EMS) response times (ERT) remain a leading measure of system performance in many developed countries, relatively few studies have explored the factors associated with meeting benchmark performance for potentially time critical incidents. The purpose of this study was to identify system-level and patient-level factors associated with ERT, which are readily available at the time of ambulance dispatch.

METHODS

Between July 2009 and June 2014, we included data from 1,000,458 EMS responses to time critical "lights and sirens" incidents in Melbourne, Australia. The primary outcome measure was ERT, defined as the time from emergency call to the arrival of the first EMS team on scene. Quantile regression models were used to identify system-level and patient-level factors associated with 10-percentile intervals of ERT.

RESULTS

The median ERT was 10.6 minutes (IQR: 8.1-14.0), increasing from 9.6 minutes (IQR: 7.6-12.5) in 2009/10 to 11.0 minutes (IQR: 8.4-14.7) in 2013/14 (p < 0.001). System-level factors independently associated with the 90th percentile ERT were distance to scene, activation time, turnout time, case upgrade, hour of day, day of week, workload in the previous hour, ambulance skill set, priority zero case (e.g., suspected cardiac or respiratory arrest), and average hospital delay time in the previous hour. Patient-level factors such as age, gender, chief medical complaint, and severity of complaint were also significantly associated with ERT.

CONCLUSIONS

System-level and patient-level factors available at the time of ambulance dispatch are useful predictors of ERT performance, which could be used to improve the timeliness of EMS response.

Intentional drug poisoning care in a physician-manned emergency medical service

OBJECTIVES

Severely poisoned patients can benefit from intensive and specific treatments. Emergency medical services (EMS) may therefore play a crucial role by matching prehospital care and hospital referral to the severity of poisoned patients. Our aim was to investigate EMS accuracy in this condition.

METHODS

A 3-year retrospective study was conducted in a university hospital. Emergency telephone calls about adult patients with intentional drug poisoning (IDP) were included. In daily practice, an emergency physician answers such telephone calls and dispatches either first responders or a mobile intensive care unit (MICU). According to on-scene evaluation, patients are referred to the emergency department (ED) or to an intensive care unit (ICU). We therefore calculated global EMS accuracy according to patients' actual medical needs. We further evaluated the performance of dispatch and hospital referral decision. We also performed a regression analysis to identify factors of inappropriate dispatch.

RESULTS

A total of 2,227 patients were studied. Median age was 41 years old (range 30-49) and 63% were women. Dispatch was appropriate for 1,937 (87%) patients. Sensitivity and specificity of dispatch decision were 0.43 and 0.93, respectively. Decision of patients' referral to an appropriate hospital facility had a sensitivity of 0.67 and a specificity of 0.98. Toxicological data, age, and Glasgow coma scale were significantly associated with inappropriate EMS decisions.

CONCLUSIONS

A physician-operated EMS is an accurate system to provide prehospital care to IDP patients. However, dispatch physicians should pay attention, especially to toxicological anamnesis, to anticipate proper patient care.

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.

Comparing emergency medical service systems--a project of the European Emergency Data (EED) Project

AIM

The aim of this prospective study was the comparison of four emergency medical service (EMS) systems-emergency physician (EP) and paramedic (PM) based-and the impact of advanced live support (ALS) on patients status in preclinical care.

METHODS

The EMS systems of Bonn (GER, EP), Cantabria (ESP, EP), Coventry (UK, PM) and Richmond (US, PM) were analysed in relation to quality of structure, process and performance when first diagnosis on scene was cardiac arrest (OHCA), chest pain or dyspnoea. Data were collected prospectively between 01.01.2001 and 31.12.2004 for at least 12 month.

RESULTS

Over all 6277 patients were included in this study. The rate of drug therapy was highest in the EP-based systems Bonn and Cantabria. Pain relief was more effective in Bonn in patients with severe chest pain. In the group of patients with chest pain and tachycardia ≥ 120 beats/min, the heart rate was reduced most effective by the EP-systems. In patients with dyspnoea and S(p)O(2) <90% the improvement of oxygen saturation was most effective in Bonn and Richmond. After OHCA significant more patients reached the hospital alive in EMS systems with EPs than in the paramedic staffed (Bonn = 35.6%, Cantabria = 30.1%; Coventry = 11.9%, Richmond = 9.2%). The introduction of a Load Distributing Band chest compression device in Richmond improved admittance rate after OHCA (21.7%) but did not reach the survival rate of the Bonn EMS system.

CONCLUSIONS

Higher qualification and greater training and experience of ALS unit personnel increased survival after OHCA and improved patient's status with cardiac chest pain and respiratory failure.