Based on experiences following the Great East Japan Earthquake and nuclear power plant accident in 2011, Nuclear Emergency Core Hospitals (NECHs) were designated as centers for radiation disaster management in Japan. This study aimed to investigate their current status and identify areas for improvement.

This cross-sectional study was conducted in October 2018. Demographic data were collected by a questionnaire with free text responses about attitudes toward NECHs. Considerations regarding risk communications during a radiation disaster were analyzed using qualitative text mining analysis.

A total of 36 hospitals participated in this study. Only 31% of NECHs anticipated a radiation disaster. The importance of business continuity plans and risk communications was shown. Text analysis identified 7 important categories for health care workers during a radiation disaster, including media response, communications to hospital staff, risk communications, radiation effects on children, planning for a radiation disaster in the region, rumors, and the role in the region.

The radiation disaster medical system and NECHs in Japan were surveyed. The importance of risk communications, planning for a radiation disaster in each region, and the role in the region are identified as issues that need to be addressed.

Primary triage in a mass-casualty event setting using low-visibility tags may lead to informational confusion and difficulty in judging triage attribution of patients. In this simulation study, informational confusion during primary triage was investigated using a method described in a prior study that applied Shannon’s Information Theory to triage.

Primary triage using a low-visibility tag leads to a risk of informational confusion in prioritizing care, owing to the intermingling of pre- and post-triage patients. It is possible that Shannon’s entropy evaluates the degree of informational confusion quantitatively and improves primary triage.

The Simple Triage and Rapid Treatment (START) triage method was employed. In Setting 1, entropy of a triage area with 32 patients was calculated for the following situations: Case 1 – all 32 patients in the triage area at commencement of triage; Case 2 – 16 randomly imported patients to join 16 post-triage patients; Case 3 – eight patients imported randomly and another eight grouped separately; Case 4 – 16 patients grouped separately; Case 5 – random placement of all 32 post-triage patients; Case 6 – isolation of eight patients of minor priority level; Case 7 – division of all patients into two groups of 16; and Case 8 – separation of all patients into four categories of eight each. In Setting 2, entropies in the triage area with 32 patients were calculated continuously with each increase of four post-triage patients in Systems A and B (System A – triage conducted in random manner; and System B – triage arranged into four categories).

In Setting 1, entropies in Cases 1-8 were 2.00, 3.00, 2.69, 2.00, 2.00, 1.19, 1.00, and 0.00 bits/symbol, respectively. Entropy increased with random triage. In Setting 2, entropies of System A maintained values the same as, or higher than, those before initiation of triage: 2.00 bits/symbol throughout the triage. The graphic waveform showed a concave shape and took 3.00 bits/symbol as maximal value when the probability of each category was 1/8, whereas the values in System B showed a linear decrease from 2.00 to 0.00 bits/symbol.

Informational confusion in a primary triage area measured using Shannon’s entropy revealed that random triage using a low-visibility tag might increase the degree of confusion. Methods for reducing entropy, such as enhancement of triage colors, may contribute to minimizing informational confusion.

AjimiY, SasakiM, UchidaY, KanekoI, NakaharaS, SakamotoT. Primary Triage in a Mass-casualty Event Possesses a Risk of Increasing Informational Confusion: A Simulation Study Using Shannon’s Entropy. Prehosp Disaster Med. 2016;31(5):498–504.

Reducing uncertainty about information on injury severity or number of patients is an important concern in managing equipment and rescue personnel in a disaster setting. A simplified disaster model was designed using Shannon’s Information Theory to study the uncertainty of information in a triage scenario.

A disaster triage scene with a specific number of injured patients represents a source of information regarding the extent of patients’ disability. It is possible to quantify uncertainty of information regarding patients’ incapacity as entropy if the information source and information arising from the source in Information Theory can be adapted to the disaster situation and the information on patients’ incapacity that arises.

Five different scenarios of a fire disaster in a hospital were modeled. Information on patients’ extent of impairment was converted to numerical values in relation to available equipment and the number of rescue personnel. Victims were 10 hospitalized patients with conditions of unknown severity. Triage criteria were created arbitrarily and consisted of four categories from Level 1 (able to walk) to Level 4 (cardiac arrest). The five situations were as follows: (1) Case 1: no triage officer; (2) Case 2: one triage officer; (3) Case 3: one triage officer and a message that six patients could walk; (4) Case 4: one triage officer and a message that all patients could obey commands; and (5) Case 5: one triage officer and a message that all patients could walk. Entropy in all cases and the amount of information newly given in Cases 2 through 5 were calculated.

Entropies in Cases 1 through 5 were 5.49, 2.00, 1.60, 1.00, and 0.00 bits/symbol, respectively. These values depict the uncertainty of probability of the triage categories arising in each situation. The amount of information for the triage was calculated as 3.49 bits (ie, 5.49 minus 2.00). In the same manner, the amount of information for the messages in Cases 3 through 5 was calculated as 0.4, 1.0, and 2.0 bits, respectively. These amounts of information indicate a reduction in uncertainty regarding the probability of the triage levels arising.

It was possible to quantify uncertainty of information about the extent of disability in patients at a triage location and to evaluate reduction of the uncertainty by using entropy based on Shannon’s Information Theory.

AjimiY , SasakiM , UchidaY , GakumazawaM , SasakiK , FujitaT , SakamotoT . Quantitative Evaluation for Uncertainty of Information About Patients’ Injury Severity in a Hospital Disaster: A Simulation Study Using Shannon’s Information Theory. Prehosp Disaster Med. 2015;30(4):1-4.

Shortening response time to an emergency call leads to the success of resuscitation by chest compression and defibrillation. However, response by ambulance or fire truck is not fast enough for resuscitation in Japan. In rural areas, response times can be more than 10 minutes. One possible way to shorten the response time is to establish a system of first responders (eg, police officers or firefighters) who are trained appropriately to perform resuscitation. Another possible way is to use a system of Community First Responders (CFRs) who are trained neighbors. At present, there are no call triage protocols to decide if dispatchers should activate CFRs.

The aim of this study was to determine the predictability to detect if dispatchers should activate CFRs.

Two CFR call triage protocols (CFR protocol Ver.0 and Ver.1) were established. The predictability of CFR protocols was examined by comparing the paramedic field reports. From the results of sensitivity of CFR protocol, the numbers of annual CFR activations were calculated. All data were collected, prospectively, for four months from October 1, 2012 through January 31, 2013.

The ROC-AUC values appear slightly higher in CFR protocol Ver.1 (0.857; 95% CI, 79.8-91.7) than in CFR protocol Ver.0 (0.847; 95% CI, 79.0-90.3). The number of annual CFR activations is higher in CFR protocol Ver.0 (7.47) than in CFR protocol Ver.1 (5.45).

Two call triage protocols have almost the same predictability as the Medical Priority Dispatch System (MPDS). The study indicates that CFR protocol Ver.1 is better than CFR protocol Ver.0 because of the higher predictability and low number of activations. Also, it indicates that CFRs who are not medical professionals can respond to a patient with cardiac arrest.

NarikawaK, SakamotoT, KubotaK, SuzukawaM, YonekawaC, YamashitaK, ToyokuniY, YasudaY, KobayashiA, IijimaK. Predictability of the Call Triage Protocol to Detect if Dispatchers Should Activate Community First Responders. Prehosp Disaster Med. 2014;29(5):1-5.