Background: Dispatch services (DS’s) form an integral part of emergency medical service (EMS) systems. The role of a dispatcher has also evolved into a crucial link in patient care delivery, particularly in dispatcher assisted cardio-pulmonary resuscitation (DACPR) during out-of-hospital cardiac arrest (OHCA). Yet, there has been a paucity of research into the emerging area of dispatch science in Asia. This paper compares the characteristics of DS’s, and state of implementation of DACPR within the Pan-Asian Resuscitation Outcomes (PAROS) network. Methods: A cross-sectional descriptive survey addressing population characteristics, DS structures and levels of service, state of DACPR implementation (including protocols and quality improvement programs) among PAROS DS’s. Results: 9 DS’s responded, representing a total of 23 dispatch centres from 9 countries that serve over 80 million people. Most PAROS DS’s operate a tiered dispatch response, have implemented medical oversight, and tend to be staffed by dispatchers with a predominantly medical background. Almost all PAROS DS’s have begun tracking key EMS indicators. 77.8% (n = 7) of PAROS DS’s have introduced DACPR. Of the DS’s that have rolled out DACPR, 71.4% (n = 5) provided instructions in over one language. All DS’s that implemented DACPR and provided feedback to dispatchers offered feedback on missed OHCA recognition. The majority of DS’s (83.3%; n = 5) that offered DACPR and provided feedback to dispatchers also implemented corrective feedback, while 66.7% (n = 4) offered positive feedback. Compression-only CPR was the standard instruction for PAROS DS’s. OHCA recognition sensitivity varied widely in PAROS DS’s, ranging from 32.6% (95% CI: 29.9–35.5%) to 79.2% (95% CI: 72.9–84.4%). Median time to first compression ranged from 120 s to 220 s. Conclusions: We found notable variations in characteristics and state of DACPR implementation between PAROS DS’s. These findings will lay the groundwork for future DS and DACPR studies in the PAROS network.

A low bystander cardiopulmonary resuscitation (CPR) rate is one of the factors associated with low cardiac arrest survival. This study aimed to assess knowledge, attitudes, and willingness towards performing CPR and the barriers for implementation of bystander-initiated CPR. Telephone interviews were conducted using an author-designed and validated structured questionnaire in Taiwan. After obtaining a stratified random sample from the census, the results were weighted to match population data. The factors affecting bystander-initiated CPR were analysed using logistic regression. Of the 1073 respondents, half of them stated that they knew how to perform CPR correctly, although 86.7% indicated a willingness to perform CPR on strangers. The barriers to CPR performance reported by the respondents included fear of legal consequences (44%) and concern about harming patients (36.5%). Most participants expressed a willingness to attend only an hour-long CPR course. Respondents who were less likely to indicate a willingness to perform CPR were female, healthcare providers, those who had no cohabiting family members older than 65 years, those who had a history of a stroke, and those who expressed a negative attitude toward CPR. The expressed willingness to perform bystander CPR was high if the respondents possessed the required skills. Attempts should be made to recruit potential bystanders for CPR courses or education, targeting those respondent subgroups less likely to express willingness to perform CPR. The reason for lower bystander CPR willingness among healthcare providers deserves further investigation.

Timely assessment to accurately prioritize patients is crucial for emergency department (ED) management. Urgent (i.e., level-3, on a 5-level emergency severity index system) patients have become a challenge since under-triage and over-triage often occur. This study was aimed to develop a computational model by artificial intelligence (AI) methodologies to accurately predict urgent patient outcomes using data that are readily available in most ED triage systems. We retrospectively collected data from the ED of a tertiary teaching hospital between January 1, 2015 and December 31, 2019. Eleven variables were used for data analysis and prediction model building, including 1 response, 2 demographic, and 8 clinical variables. A model to predict hospital admission was developed using neural networks and machine learning methodologies. A total of 282,971 samples of urgent (level-3) visits were included in the analysis. Our model achieved a validation area under the curve (AUC) of 0.8004 (95% CI 0.7963–0.8045). The optimal cutoff value identified by Youden's index for determining hospital admission was 0.5517. Using this cutoff value, the sensitivity was 0.6721 (95% CI 0.6624–0.6818), and the specificity was 0.7814 (95% CI 0.7777–0.7851), with a positive predictive value of 0.3660 (95% CI 0.3586–0.3733) and a negative predictive value of 0.9270 (95% CI 0.9244–0.9295). Subgroup analysis revealed that this model performed better in the nontraumatic adult subgroup and achieved a validation AUC of 0.8166 (95% CI 0.8199–0.8212). Our AI model accurately assessed the need for hospitalization for urgent patients, which constituted nearly 70% of ED visits. This model demonstrates the potential for streamlining ED operations using a very limited number of variables that are readily available in most ED triage systems. Subgroup analysis is an important topic for future investigation.

With the rapid development of the COVID-19 pandemic, countries are trying to cope with increasing medical demands, and, at the same time, to reduce the increase of infected numbers by implementing a number of public health measures, namely non-pharmaceutical interventions (NPIs). These public health measures can include social distancing, frequent handwashing, and personal protective equipment (PPE) at the personal level; at the community and the government level, these measures can range from canceling activities, avoiding mass gatherings, closing facilities, and, at the extreme, enacting national or provincial lockdowns. Rather than completely stopping the infectious disease, the major purpose of these NPIs in facing an emerging infectious disease is to reduce the contact rate within the population, and reduce the spread of the virus until the time a vaccine or reliable medications become available. The idea is to avoid a surge of patients with severe symptoms beyond the capacity of the hospitals’ medical resources, which would lead to more mortality and morbidity. While many countries have experienced steep curves in new cases, some, including Hong Kong, Vietnam, South Korea, New Zealand, and Taiwan, seem to have controlled or even eliminated the infection locally. From its first case of COVID-19 on the 21 January until the 12 May, Taiwan had 440 cases, including just 55 local infections, and seven deaths in total, representing 1.85 cases per 100,000 population and a 1.5% death rate (based on the Worldometer 2020 statistics of Taiwan’s population of 23.8 million). This paper presents evidence that spread prevention involving mass masking and universal hygiene at the early stage of the COVID-19 pandemic resulted in a 50% decline of infectious respiratory diseases, based on historical data during the influenza season in Taiwan. These outcomes provide potential support for the effectiveness of widely implementing public health precaution measures in controlling COVID-19 without a lockdown policy.

Protocols for managing patients with out-of-hospital cardiac arrest (OHCA) may vary due to legal, cultural, or socioeconomic concerns. We sought to assess international variation in policies and protocols related to OHCA. A brief survey was developed by consensus. Elicited information included protocols for managing patients with nontraumatic OHCA or traumatic OHCA, policies for using automated external defibrillators (AEDs) during transportation of patients with ongoing resuscitation, and application of terminations of resuscitation (TOR) rules in prehospital settings in the respondent's city or country. The populations of interest were emergency physicians, medical directors of emergency medical services (EMS), and policy makers. Responses were obtained from eight cities in six Asian countries. Only one (12.5%) city applied TOR rules for OHCAs. Do-not-resuscitate (DNR) orders were valid in prehospital settings in five (62.5%) cities. All cities used AEDs for nontraumatic OHCAs; seven (87.5%) cities did not routinely use AEDs for traumatic OHCAs. For nontraumatic OHCAs, four (50%) cities performed 2 minutes of on-scene cardiopulmonary resuscitation (CPR) and then transported the patients with ongoing resuscitation to hospitals; three (37.5%) cities performed 4 minutes of on-scene CPR; one (12.5%) city allowed variation in the duration of on-scene CPR. International variation in practices and polices related to OHCAs do exist. Concerns regarding prehospital TOR rules include medical evidence, legal considerations, EMS manpower, public perception, medical oversight, education, EMS characteristics, and cost-effectiveness analysis. Further research is needed to achieve consensus regarding management protocols, especially for EMS that perform resuscitation during transportation of OHCA patients.