Could prioritisation by emergency medicine dispatchers be improved by using computer-based decision support? A cohort of patients with chest pain

Clinical decision support system in emergency telephone triage: A scoping review of technical design, implementation and evaluation

OBJECTIVES

Emergency department overcrowding could be improved by upstream telephone triage. Emergency telephone triage aims at managing and orientating adequately patients as early as possible and distributing limited supply of staff and materials. This complex task could be improved with the use of Clinical decision support systems (CDSS). The aim of this scoping review was to identify literature gaps for the future development and evaluation of CDSS for Emergency telephone triage.

MATERIALS AND METHODS

We present here a scoping review of CDSS designed for emergency telephone triage, and compared them in terms of functional characteristics, technical design, health care implementation and methodologies used for evaluation, following the PRISMA-ScR guidelines.

RESULTS

Regarding design, 19 CDSS were retrieved: 12 were knowledge based CDSS (decisional algorithms built according to guidelines or clinical expertise) and 7 were data driven (statistical, machine learning, or deep learning models). Most of them aimed at assisting nurses or non-medical staff by providing patient orientation and/or severity/priority assessment. Eleven were implemented in real life, and only three were connected to the Electronic Health Record. Regarding evaluation, CDSS were assessed through various aspects: intrinsic characteristics, impact on clinical practice or user apprehension. Only one pragmatic trial and one randomized controlled trial were conducted.

CONCLUSION

This review highlights the potential of a hybrid system, user tailored, flexible, connected to the electronic health record, which could work with oral, video and digital data; and the need to evaluate CDSS on intrinsic characteristics and impact on clinical practice, iteratively at each distinct stage of the IT lifecycle.

The potential of new prediction models for emergency medical dispatch prioritisation of patients with chest pain: a cohort study

Objectives

To develop emergency medical dispatch (EMD) centre prediction models with high sensitivity and satisfying specificity to identify high-priority patients and patients suitable for non-emergency care respectively, when assessing patients with chest pain.

Methods

Observational cohort study of 2917 unselected patients with chest pain who contacted an EMD centre in Sweden due to chest pain during 2018. Multivariate logistic regression was applied to develop models predicting low-risk or high-risk condition, that is, occurrence of time-sensitive diagnosis on hospital discharge.

Results

Prediction models were developed for the identification of patients suitable for high- and low-priority dispatch, using 11 and 10 variables respectively. The area under the receiver-operating characteristic curve (AUROC) for the high-risk prediction model was 0.79 and for the low-risk model it was 0.74. When applying the high-risk prediction model, 56% of the EMS missions were given highest priority, compared with 65% with the current standard. When applying the low-risk model, 7% were given the lowest priority compared to 1% for the current standard. The new prediction models outperformed today’s dispatch priority accuracy in terms of sensitivity as well as positive and negative predictive value in both high- and low-risk prediction. The low-risk model predicted almost six times as many patients as having low-risk conditions compared with today’s standard. This was done without increasing the number of high-risk patients wrongly assessed as low-risk.

Conclusions

By introducing prediction models, based on logistic regression analyses, using variables obtained by standard EMD-questions on age, sex, medical history and symptomology, EMD prioritisation can be improved compared with using current criteria index-based ones. This will allow a more efficient emergency medical services resource allocation.

Guideline adherence among prehospital emergency nurses when caring for patients with chest pain: a prospective cohort study

Background

The emergency medical services (EMS) use guidelines to describe optimal patient care for a wide range of clinical conditions and symptoms. The intent is to guide personnel to provide patient care in line with best practice. The aim of this study is to describe adherence to such guidelines among prehospital emergency nurses (PENs) when caring for patients with chest pain.

Objective

To describe guideline adherence among PENs when caring for patients with chest pain. To investigate whether guideline adherence is associated with patient age, sex or final diagnosis of acute myocardial infarction on hospital discharge.

Methods

Guideline adherence in terms of patient examination and pharmaceutical treatment was analysed in a cohort of 2092 EMS missions carried out in 2018 in Region Halland, Sweden. Multivariate regression was used to describe how guideline adherence is associated with patient age, sex and diagnosis on hospital discharge.

Results

Guideline adherence was high regarding examination of vital signs (93%) and electrocardiogram (ECG) registration (96%) but lower in terms of pharmaceutical treatment (ranging from 28 to 90%). Adherence was increased in cases in which the patient ended up with acute myocardial infarction (AMI) as diagnosis on discharge. Patients with AMI were given acetylsalicylic acid by PENs in 50% of cases. Women were less likely than men to receive treatment with acetylsalicylic acid and oxycodone.

Conclusions

Guideline adherence among PENs when caring for patients with chest pain is satisfactory in terms vital signs and ECG registration. Regarding pharmaceutical treatment guideline adherence is defective. Improved adherence is mainly associated with male sex in patients and a diagnosis of AMI on hospital discharge. Defective adherence excludes measures known to improve patients’ prognoses such as treatment with acetylsalicylic acid.

Accuracy of emergency medical services (EMS) telephone triage in identifying acute coronary syndrome (ACS) for patients with chest pain: a systematic literature review

OBJECTIVE

To systematically appraise the available evidence to determine the accuracy of decision aids for emergency medical services (EMS) telephone triage of patients with chest pain suspected to be caused by acute coronary syndrome (ACS) or life-threatening conditions.

DESIGN

Systematic review.

DATA SOURCES

Electronic searches were performed in Embase 1974, Medline 1946 and CINAHL 1937 databases from 3 March 2020 to 4 March 2020.

ELIGIBILITY CRITERIA

The review included all types of original studies that included adult patients (>18 years) who called EMS with a primary complaint of chest pain and evaluated dispatch triage priority by telephone. Outcomes of interest were a final diagnosis of ACS, acute myocardial infarction or other life-threatening conditions.

DATA EXTRACTION AND SYNTHESIS

Two authors independently extracted data on study design, population, study period, outcome and all data for assessment of accuracy, including cross-tabulation of triage priority against the outcomes of interest. Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 assessment tool.

RESULTS

Searches identified 553 papers, of which 3 were eligible for inclusion. Those reports described the evaluation of three different prediction models with variation in the variables used to detect ACS. The overall results showed that dispatch triage tools have good sensitivity to detect ACS and life-threatening conditions, even though they are used to triage signs and symptoms rather than diagnosing the patients. On the other hand, prediction models were built to detect ACS and life-threatening conditions, and therefore, prediction models showed better sensitivity and negative predictive value than dispatch triage tools.

CONCLUSION

We have identified three prediction models for telephone triage of patients with chest pain. While they have been found to have greater accuracy than standard EMS dispatch systems, prospective external validation is essential before clinical use is considered.

PROSPERO REGISTRATION NUMBER

This systematic review was pre-registered on the International prospective register of systematic reviews (PROSPERO) database (reference CRD42020171184).

Validity and risk factor analysis for helicopter emergency medical services in Japan: a pilot study

Background

Some emergency departments use triage scales, such as the Canadian Triage and Acuity Scale and Japan Urgent Stroke Triage Score, to detect life-threatening situations. However, these protocols have not been used for aeromedical services. Therefore, we investigated the factors predicting these life-threatening situations in aeromedical services as a pilot study for establishing the protocol.

Method

We retrospectively evaluated helicopter emergency medical service cases from 1 April 2015 to 31 March 2020 at Gifu University Hospital using the mission records. We only evaluated cases dealing with suggested internal medicine issues. We excluded cases influenced by external factors such as trauma or cases that included hospital-to-hospital transportation, focusing only on prehospital care. We evaluated the validity of the medical emergencies based on the needs for emergency interventions and hospital admission and of the suggested diagnoses and associated risk factors.

Result

A total of 451 cases were suitable for inclusion in the study. In the analysis for all emergency calls, 235 (52.11%) cases needed emergency intervention and 300 (64.4%) required hospital admission. The suggested diagnosis was valid for 261 (57.87%) cases. After the first assessment by emergency medical technicians, 75 cases were removed. Analysis after this first assessment found that 52.31% cases required emergency intervention, 70.26% needed admission, and the suggested diagnosis was valid for 69.41% of cases. In the analysis of emergency calls, the multivariate analysis of some key variables identified age, playing sports, and gasping as risk factors for emergency intervention. Hospital admission risk factors included being age only. The suggested diagnosis was valid only for sports situations. In the analysis after the first assessment by an emergency medical technician, risk factors for emergency intervention included being age being male, playing sports, and gasping, and those for hospital admission was being age, being male, and experiencing stroke symptoms and/or disturbance of consciousness. The suggested diagnosis was valid only for sports situations.

Conclusion

Some ‘second’ keywords/phrases predict medical emergencies. Therefore, the dispatch commander should gather these keyword/phrases to assess.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12873-021-00471-x.

Characteristics and outcome of patients triaged by telephone and transported by ambulance: a population-based study in Osaka, Japan

Aim

Details such as diagnosis and outcome of patients transported by ambulance after telephone triage have not been fully revealed. The aim of this study was to reveal profile and outcome about patients transported by ambulance via telephone triage with dataset of telephone triage and population‐based registry for emergency patients.

Methods

This retrospective descriptive study with a one‐year study period from January 1, 2016 to December 31, 2016 included patients selected from the telephone triage dataset who were transported by ambulance. Key parameters such as age, sex and date and time of ambulance dispatch were used to identify patient data from the ORION registry. We assessed the profile and outcome of the patients in a descriptive epidemiological analysis.

Results

We included 4,293 patients in the selected datasets whose data were merged, of whom 2,998 patients (69.8%) returned home from the emergency department, 1,255 (29.2%) were hospitalized, 32 (0.7%) were transferred to other hospitals, and 8 (0.2%) died. The most common diagnosis in the emergency departments was “infectious gastroenteritis and colitis, unspecified [A09] (219, 5.1%)”. Among the 1,255 hospitalized patients, 905 patients (72.1%) were discharged home, 254 patients (20.2%) remained hospitalized, 52 patients (4.1%) were transferred to other hospitals, 38 patients (3.0%) died, and 5 patients (0.5%) had missing data. The most common diagnosis was “cerebral infarction [I63.0‐I63.9] (138, 11.0%)”.

Conclusion

This study revealed the profile and outcome of patients transported by ambulance after telephone triage.

Systematic Review of Clinical Decision Support Systems for Prehospital Acute Coronary Syndrome Identification

OBJECTIVES

Timely prehospital diagnosis and treatment of acute coronary syndrome (ACS) are required to achieve optimal outcomes. Clinical decision support systems (CDSS) are platforms designed to integrate multiple data and can aid with management decisions in the prehospital environment. The review aim was to describe the accuracy of CDSS and individual components in the prehospital ACS management.

METHODS

This systematic review examined the current literature regarding the accuracy of CDSS for ACS in the prehospital setting, the influence of computer-aided decision-making and of 4 components: electrocardiogram, biomarkers, patient history, and examination findings. The impact of these components on sensitivity, specificity, and positive and negative predictive values was assessed.

RESULTS

A total of 11,439 articles were identified from a search of databases, of which 199 were screened against the eligibility criteria. Eight studies were found to meet the eligibility and quality criteria. There was marked heterogeneity between studies which precluded formal meta-analysis. However, individual components analysis found that patient history led to significant improvement in the sensitivity and negative predictive values. CDSS which incorporated all 4 components tended to show higher sensitivities and negative predictive values. CDSS incorporating computer-aided electrocardiogram diagnosis showed higher specificities and positive predictive values.

CONCLUSIONS

Although heterogeneity precluded meta-analysis, this review emphasizes the potential of ACS CDSS in prehospital environments that incorporate patient history in addition to integration of multiple components. The higher sensitivity of certain components, along with higher specificity of computer-aided decision-making, highlights the opportunity for developing an integrated algorithm with computer-aided decision support.

Towards definitions of time-sensitive conditions in prehospital care

Background

Prehospital care has changed in recent decades. Advanced assessments and decisions are made early in the care chain. Patient assessments form the basis of a decision relating to prehospital treatment and the level of care. This development imposes heavy demands on the ability of emergency medical service (EMS) clinicians properly to assess the patient. EMS clinicians have a number of assessment instruments and triage systems available to support their decisions. Many of these instruments are based on vital signs and can sometimes miss time-sensitive conditions. With this commentary, we would like to start a discussion to agree on definitions of temporal states in the prehospital setting and ways of recognising patients with time-sensitive conditions in the most optimal way.

Main body

There are several articles discussing the identification and management of time-sensitive conditions. In these articles, neither definitions nor terminology have been uniform. There are a number of problems associated with the definition of time-sensitive conditions. For example, intoxication can be minor but also life threatening, depending on the type of poison and dose. Similarly, diseases like stroke and myocardial infarction can differ markedly in terms of severity and the risk of life-threatening complications. Another problem is how to support EMS clinicians in the early recognition of these conditions. It is well known that many of them can present without a deviation from normal in vital signs. It will most probably be impossible to introduce specific decision support tools for every individual time-sensitive condition. However, there may be information in the type and intensity of the symptoms patients present. In future, biochemical markers and machine learning support tools may help to identify patients with time-sensitive conditions and predict mortality at an earlier stage.

Conclusion

It may be of great value for prehospital clinicians to be able to describe time-sensitive conditions. Today, neither definitions nor terminology are uniform. Our hope is that this commentary will initiate a discussion on the issue aiming at definitions of time-sensitive conditions in prehospital care and how they should be recognised in the most optimal fashion.

Predicting acute coronary syndrome in males and females with chest pain who call an emergency medical communication centre

Background

Chest pain is a frequent reason for calls in emergency medical communication centre (EMCC). Detecting a coronary origin by phone is a challenge. This is especially so as the presentations differ according to gender. We aimed to establish and validate a sex-based model to predict a coronary origin of chest pain in patients calling an EMCC.

Methods

This prospective cohort study enrolled patients at 18 years of age or older who called the EMCC because of non-traumatic chest pain. The main outcome was the diagnosis of acute coronary syndrome (ACS) determined by expert evaluation of patient files.

Results

During 18 months, 3727 patients were enrolled: 2097 (56%) men and 1630 (44%) women. ACS was diagnosed in 508 (24%) men and 139 (9%) women. For men, independent factors associated with an ACS diagnosis were age, tobacco use, severe and permanent pain; retrosternal, breathing non-related and radiating pain; and additional symptoms. The area under the receiver operating characteristic curve (AUC) was 0.76 (95% confidence interval [CI] 0.73–0.79) for predicting ACS. The accuracy of the male model to predict ACS was validated in a validation dataset (Hosmer-Lemeshow test: p = 0.554); the AUC was 0.77 (95%CI 0.73–0.80). For women, independent factors associated with an ACS diagnosis were age ≥ 60 years, personal history of coronary artery disease, and breathing non-related and radiating pain. The AUC was 0.79 (95%CI 0.75–0.83). The accuracy of the female model to predict ACS was not validated in the validation dataset (Hosmer-Lemeshow test: p = 0.035); the AUC was 0.67 (95%CI 0.60–0.74).

Conclusions

Predictors of an ACS diagnosis in patients calling an EMCC for chest pain differ between men and women. We developed an accurate predictive model for men, but for women, the accuracy was poor.

Trial registration

This study is registered with ClinicalTrials.gov (NCT02042209).

Symptom description in patients with chest pain-A qualitative analysis of emergency medical calls involving high-risk conditions

AIMS AND OBJECTIVES

To explore the symptoms descriptions and situational information provided by patients during ongoing chest pain events caused by a high-risk condition.

BACKGROUND

Chest pain is a common symptom in patients contacting emergency dispatch centres. Only 15% of these patients are later classified as suffering from a high-risk condition. Prehospital personnel are largely dependent on symptom characteristics when trying to identify these patients.

DESIGN

Qualitative descriptive.

METHODS

Manifest content analysis of 56 emergency medical calls involving patients with chest pain was carried out. A stratified purposive sampling was used to obtain calls concerning patients with high-risk conditions. These calls were then listened to and transcribed. Thereafter, meaning units were identified and coded and finally categorised. Consolidated criteria for reporting qualitative studies guidelines have been applied.

RESULTS

A wide range of situational information and symptoms descriptions was found. Pain and affected breathing were dominating aspects, but other situational information and several other symptoms were also reported. The situational information and these symptoms were classified into seven categories: Pain narrative, Affected breathing, Bodily reactions, Time, Bodily whereabouts, Fear and concern and Situation management. The seven categories consisted of 17 subcategories.

CONCLUSIONS

Patients with chest pain caused by a high-risk condition present a wide range of symptoms which are described in a variety of ways. They describe different kinds of chest pain accompanied by pain from other parts of the body. Breathing difficulties and bodily reactions such as muscle weakness are also reported. The variety of symptoms and the absence of a typical symptomatology make risk stratification on the basis of symptoms alone difficult.

RELEVANCE TO CLINICAL PRACTICE

This study highlights the importance of an open mind when assessing patients with chest pain and the requirement of a decision support tool in order to improve risk stratification in these patients.

The accuracy of medical dispatch - a systematic review

BACKGROUND

It is a challenge to dispatch Emergency medical Services (EMS) appropriately with limited resources and maintaining patient safety; this requires accurate dispatching systems. The objective of the current systematic review was to examine the evidence, according to GRADE, for medical dispatching systems to accurately dispatch EMS according to level of acuity and in recognition of specific conditions. A systematic search was performed trough PubMed, Web of Science, Embase (free text in all fields), Centre for Reviews and Dissemination (CRD), and Cochrane Central Register of Controlled Trials up to 16th of May, 2017. A combination of keywords and Medical Subject Heading (MeSH) terms relevant to "emergency medical dispatch criteria" were used, to search for articles published between 2012 and 2017. Publications were included according to the inclusion/exclusion criteria using the Systematic Reviews and Meta-Analyses (PRISMA) protocol. Level of evidence was evaluated in accordance with Grading of Recommendations Assessment, Development and Evaluation (GRADE). Articles included were those that provided evidence for at least one of the measures of dispatch system accuracy; i.e. sensitivity, specificity, positive and negative predictive and/or over- and under-triage. The search identified 1445 articles. After the removal of duplicates, 382 titles were reviewed for relevance and an additional 359 articles were excluded based on manuscript title and abstract. An additional five articles were excluded after review of the full text versions of the remaining articles. The current review included 18 publications which all were based on primary research.

CONCLUSIONS

The 18 articles addressed the identification of cardiac arrest, stroke, medical priority and major trauma using different dispatching systems. The results of the current review show that there is a very low to low overall level of evidence for the accuracy of medical dispatching systems. We suggest that it is necessary to create a consensus on common standards for reporting before consensus can be reached for the level of accuracy in medical dispatching systems.

Association between use of pre-hospital ECG and 30-day mortality: A large cohort study of patients experiencing chest pain

BACKGROUND

In the assessment of patients with chest pain, there is support for the use of pre-hospital ECG in the literature and in the care guidelines. Using propensity score methods, we aim to examine whether the mere acquisition of a pre-hospital ECG among patients with chest pain affects the outcome (30-day mortality).

METHODS

The association between pre-hospital ECG and 30-day mortality was studied in the overall cohort (n=13151), as well as in the one-to-one matched cohort with 2524 patients not examined with pre-hospital ECG and 2524 patients examined with pre-hospital ECG.

RESULTS

In the overall cohort, 21% (n=2809) did not undergo an ECG tracing in the pre-hospital setting. Among those who had pain during transport, 14% (n=1159) did not undergo a pre-hospital ECG while 32% (n=1135) of those who did not have pain underwent an ECG tracing. In the overall cohort, the OR for 30-day mortality in patients who had a pre-hospital ECG, as compared with those who did not, was 0.63 (95% CI 0.05-0.79; p<0.001). In the matched cohort, the OR was 0.65 (95% CI 0.49-0.85; p<0.001). Using the propensity score, in the overall cohort, the corresponding HR was 0.65 (95% CI 0.58-0.74).

CONCLUSION

Using propensity score methods, we provide real-world data demonstrating that the adjusted risk of death was considerably lower among the cases in whoma pre-hospital ECG was used. The PH-ECG is underused among patients with chest discomfort and the mere acquisition of a pre-hospital ECG may reduce mortality.