Challenges in Providing Care for Patients with Chronic Diseases during Disasters: A Qualitative Study with Focus on Diabetes and Chronic Respiratory Diseases in Iran.

Background: Non-communicable diseases are of the major health challenges and the leading cause of death in Iran and at the global level. Moreover, Iran is a disaster-prone country and considering the exacerbation of diabetes and chronic respiratory diseases in natural disasters, its healthcare system is facing challenges. This study was designed to explore challenges in providing healthcare services to patients with diabetes and chronic respiratory diseases during disasters in Iran. Materials and Methods: The conventional content analysis is used in this qualitative study. Participants included 46 patients with diabetes and chronic respiratory diseases, and 36 of stakeholders were experienced and had theoretical knowledge. Participants' selection started by means of purposive sampling and continued to the point of data saturation. Data collection was carried out employing semi-structured interviews. Data analysis was performed using Graneheim and Lundman method. Results: Based on participants' experiences, four major challenges in providing care to patients with diabetes and chronic respiratory diseases during natural disasters include integrated management (with three subcategories: control and supervision, patient data management, volunteer management), physical, psychosocial health (with three subcategories: psychological impacts, exacerbation of signs and symptoms, special patient characteristics), health literacy and the behavior (with three subcategories: risk perception, values and beliefs, education and awareness) and barriers to healthcare delivery (with three subcategories: facilities and human resources, financial and living problems and insurances, accessibilities and geographic access). Conclusion: Developing countermeasures against medical monitoring system shutdown in order to detect medical needs and problems faced by chronic disease patients including those with diabetes and chronic obstructive pulmonary disease (COPD), is essential in preparedness for future disasters. Developing effective solutions may result in improved preparedness and better planning of diabetic and COPD patients for disasters, and potentially promote health outcomes during and after disasters.

Spiritual rehabilitation of affected people after natural disasters: a protocol for a systematic review.

BACKGROUND: Knowledge about the spiritual rehabilitation of affected people after disasters is scare. The objective of the present study is to identify the factors affecting the spiritual rehabilitation of affected people after natural disasters employing a systematic review study. METHODS: The protocol of this review has been registered in the International Prospective Register of Systematic Review (PROSPERO) with the code CRD42021228552. Using MEDLIN (PubMed), Web of Science, Google Scholar, Embase, ProQuest, Scopus and ISC database as well as studies related to the research topic till the end of 2022. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was used to find articles related to the research objective. Thematic content analysis then was used for concepts extraction. RESULTS: This systematic review identifies factors affecting the spiritual rehabilitation of affected people after natural disasters. CONCLUSIONS: Both systematic review as well as qualitative study are essential in order to explore spiritual rehabilitation of affected people after natural disasters, while the current study was employed systematic review. It is expected that planners and policy-makers can use the extracted factors for improving the spiritual rehabilitation of people affected by natural disasters.

Emergency department-based injury surveillance information system: a conceptual model.

BACKGROUND: Injury data play a pivotal role in monitoring public health issues and Injury Surveillance Information Systems (ISIS) are useful for continuous data collection and analysis purposes. Since emergency department (ED) is usually the first place of referral for the injured people, the aim of this study was to develop a conceptual model for an ED-based ISIS. METHODS: This study was completed in 2020 and the Delphi technique (three rounds) was used to determine the main components of an ED-based ISIS. The participants were selected using the purposive sampling method. A 5-point Likert scale questionnaire was used for data collection and data were analyzed using descriptive statistics. RESULTS: In the first, second, and third rounds of the Delphi study, 60, 44, and 28 experts participated, respectively. In the first and second rounds, most of the items including the personal data, clinical data, data sources, and system functions were found important. In the third round of the Delphi study, 13 items which did not reach a consensus in the previous rounds were questioned again and five items were removed from the final model. CONCLUSION: According to the findings, various data elements and functions could be considered for designing an ED-based ISIS and a number of data sources should be taken into count to be integrated with this system. Although the conceptual model presented in the present study can facilitate designing the actual system, the final system needs to be implemented and used in practice to determine how it can meet users' requirements.

Development and Psychometric Properties of Decision-Making Scale for Emergency Hospital Evacuation in Disasters.

BACKGROUND: The evidence shows that the need for emergency evacuation in hospitals has arisen. Designing an emergency evacuation decision making tool increases the confidence of hospital managers in the decision made. Therefore, this study was aimed at the development, and the psychometric properties, of the decision-making scale for emergency hospital evacuation in disasters. METHODS: This study was done in 2 phases of qualitative study and literature review and designing and psychometric properties of the instrument. After development of the primary item pool, the psychometric properties of the questionnaire were evaluated. In this regard, face and content validity, internal consistency (Alpha's Cronbach), reliability (ICC), and stability were assessed. RESULTS: In the validity stage of the instrument, 4 items were removed. Also, 4 items were modified and 2 items were merged. The number of items was thus decreased to 64. After CVI calculation, 5 items were removed, 4 items were modified, and 2 items were merged. As a result of this, the number of items decreased to 58 items. The scale has good reliability and stability. CONCLUSION: It seems that the instrument could be useful in decision-making for emergency hospital evacuation in disasters.

A qualitative evaluation of the challenges in management for patients with chronic diseases during disasters in Iran.

BACKGROUND: Iran's health care system faces significant challenges in managing the growing burden of non-communicable diseases, and these are exacerbated during the frequent natural disasters. The current study was designed to understand challenges in providing healthcare services to patients with diabetes and chronic respiratory diseases during such crisis periods. METHODS: The conventional content analysis was used in this qualitative study. Participants included 46 patients with diabetes and chronic respiratory diseases, and 36 stakeholders with knowledge and experience in disasters. Data collection was carried out employing semi-structured interviews. Data analysis was performed using Graneheim and Lundman method. RESULTS: Four major challenges in providing care to patients with diabetes and chronic respiratory diseases during natural disasters include integrated management, physical, psychosocial health, health literacy and the behavior and barriers to healthcare delivery. CONCLUSIONS: Developing countermeasures against medical monitoring system shutdown in order to detect medical needs and problems faced by chronic disease patients including those with diabetes and chronic obstructive pulmonary disease (COPD), is essential in preparedness for future disasters. Developing effective solutions may result in improved preparedness and better planning of diabetic and COPD patients for disasters.

Data quality assessment in emergency medical services: an objective approach.

BACKGROUND: In emergency medical services, high quality data are of great importance for patient care. Due to the unique nature of this type of services, the purpose of this study was to assess data quality in emergency medical services using an objective approach. METHODS: This was a retrospective quantitative study conducted in 2019. The research sample included the emergency medical records of patients who referred to three emergency departments by the pre-hospital emergency care services (n = 384). Initially a checklist was designed based on the data elements of the triage form, pre-hospital emergency care form, and emergency medical records. Then, data completeness, accuracy and timeliness were assessed. RESULTS: Data completeness in the triage form, pre-hospital emergency care form, and emergency medical records was 52.3%, 70% and 57.3%, respectively. Regarding data accuracy, most of the data elements were consistent. Measuring data timeliness showed that in some cases, paper-based ordering and computer-based data entry was not sequential. CONCLUSION: Data quality in emergency medical services was not satisfactory and there were some weaknesses in the documentation processes. The results of this study can inform the clinical and administrative staff to pay more attentions to these weaknesses and plan for data quality improvement.

Data Quality in Health Care: Main Concepts and Assessment Methodologies.

INTRODUCTION: In the health care environment, a huge volume of data is produced on a daily basis. However, the processes of collecting, storing, sharing, analyzing, and reporting health data usually face with numerous challenges that lead to producing incomplete, inaccurate, and untimely data. As a result, data quality issues have received more attention than before. OBJECTIVE: The purpose of this article is to provide an insight into the data quality definitions, dimensions, and assessment methodologies. METHODS: In this article, a scoping literature review approach was used to describe and summarize the main concepts related to data quality and data quality assessment methodologies. Search terms were selected to find the relevant articles published between January 1, 2012 and September 31, 2022. The retrieved articles were then reviewed and the results were reported narratively. RESULTS: In total, 23 papers were included in the study. According to the results, data quality dimensions were various and different methodologies were used to assess them. Most studies used quantitative methods to measure data quality dimensions either in paper-based or computer-based medical records. Only two studies investigated respondents' opinions about data quality. CONCLUSION: In health care, high-quality data not only are important for patient care, but also are vital for improving quality of health care services and better decision making. Therefore, using technical and nontechnical solutions as well as constant assessment and supervision is suggested to improve data quality.

Using Artificial Intelligence for Predicting the Duration of Emergency Evacuation During Hospital Fire.

OBJECTIVE: A danger threatening hospitals is fire. The most important action following a fire is to urgently evacuate the hospital during the shortest time possible. The aim of this study was to predict the duration of emergency evacuation following hospital fire using machine-learning algorithms. METHODS: In this study, the real emergency evacuation duration of 190 patients admitted to a hospital was predicted in a simulation based on the following 8 factors: the number of hospital floors, patient preparation and transfer time, distance to the safe location, as well as patient's weight, age, sex, and movement capability. To design and validate the model, we used statistical models of machine learning, including Support Vector Machines Random Forest, Naive Bayes Classifier, and Artificial Neural Network. RESULTS: Data analysis showed that based on the Area Under the Curve, precision, and sensitivity values of 99.5%, 92.4%, and 92.1%, respectively, the Random Forest model showed a better performance compared to other models for predicting the duration of hospital emergency evacuation during fire. CONCLUSION: Predicting evacuation duration can provide managers with accurate information and true analyses of these events. Therefore, health policy makers and managers can promote preparedness and responsiveness during fire by predicting evacuation duration and developing appropriate plans using machine learning models.

Building Resilience in Firefighters: A Systematic Review.

Background: We aimed to identify indicators affecting firefighters' resilience through a systematic review. Methods: International electronic databases, including Web of Science, Medline through PubMed, Scopus, Cochrane Library, and Google Scholar, were searched on Dec 23, 2018. The search strategy was developed using main words, including firefighter, resilience, and indicators. Then, the indicators related to firefighters' resilience were extracted and analyzed using a qualitative synthesis method. Results: Overall, 7178 unique documents were identified by searching different databases. Then, by screening the title and abstract, 7104 articles were excluded, and only 74 full text papers were critically studied. Finally, 31 full text articles were selected for the analysis. Quality appraisal of included studies done by modified STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) tool. Moreover, 186 indicators and criteria were extracted from the included studies and classified into 6 domains and 15 categories. Conclusion: This study suggests six main domains, including physical health, physical fitness, mental health, life style, job-related competencies, and demographic status, to categorize different indicators of firefighters' resilience. Building resilience in firefighters requires all these domains to be considered in the assessment, planning, and evaluation processes.

A Systematic Literature Review of Driver's Sociocultural Factors Predisposing to Road Traffic Crashes.

Background: Various factors are involved in the occurrence and prediction of road traffic crashes (RTCs). The most important of these are human factors that can be influenced by the sociocultural characteristics of the drivers. This research aimed at identifying the socio-cultural factors (SCFs) in car drivers affecting the RTCs. Methods: In the present study, Web of Science, PubMed, Scopus, ProQuest, Google Scholar, Cochran Library, Magiran, Irandoc, Noor magas, Islamic World Science Citation Center, and Scientific Information Database were searched from 1990 to August 20th, 2021; key journals, the reference lists of the included studies, gray literature, websites of relevant organizations were manually reviewed. Studies that reviewed the effect of SCFs related to car drivers in the incidence or prediction of road traffic crashes were included and analyzed using thematic content analysis. Results were expressed based on the PRISMA guideline. The quality of the included studies was assessed using related checklists. Results: Eighty-four eligible studies were determined from a systematic search and entered into the analysis process. Studies are presented that SCFs affecting the occurrence of RTCs fall into four categories, including (1) sociodemographic characteristics, (2) personality traits, (3) driver behavior (driving style), (4) driver performance (driving skills). Conclusion: In most studies, SCFs have been examined in frames of social-demographic characteristics and risky driving behaviors. While, the impact of personality traits and driver performance, which are very important factors on RTCs, has not been addressed. Therefore, investigating the impact of these factors in occurring RTCs is crucial.

Designing a conceptual model for the formation of unsafe antisocial behaviors in motor vehicle drivers: a grounded theory study.

BACKGROUND: Many accidents caused by vehicles are the result of improper driving behavior. Use the vehicle in an antisocial form has led to a phenomenon called driving violence. Antisocial behavior while driving has a potential risk to other road users. This study aims to explain the conceptual framework of the formation of unsafe antisocial behaviors in the road traffic field. METHODS: This qualitative grounded theory study was conducted with exploratory methods. 31 participants were included in this study. Purposeful and theoretical sampling was used in this study. The data collection process was semi-structured interviews. Codes, subcategories, and categories were extracted by the inductive process and analyzed by Corbin and Strauss approach. Trustworthiness criteria were used to assure the quality of the results. The data analysis process continued until there were no new concepts. RESULTS: A conceptual model was developed to explain the different relationships between the main categories extracted from the study. 10 main categories with 44 subcategories were extracted. Categories include cultural factors, educational factors, rules, economic factors, psychological factors, infrastructure weakness, poor socialization of individuals, violent driving, reduced social welfare and reduced traffic safety. CONCLUSIONS: The people's socialization weakness in society was considered as the core concept in the process of formation of these behaviors. The conceptual model obtained from this study can be used in developing prevention programs and identifying the required interventions Considering the negative consequences caused by this type of behavior, its prevention should be the focus of road traffic policy makers.

Factors Challenging the Spiritual Rehabilitation of Iranian Men Affected by Natural Disasters: A Qualitative Study.

Spiritual health is one important dimension of human health. Natural disasters, however, can adversely affect human spiritual health. One of the undeniable requirements of disaster management is the spiritual rehabilitation of victims to help them recover to their pre-disaster health conditions. This study aimed to explore the factors challenging the spiritual rehabilitation of Iranian men suffering from natural disasters based on the experiences of key informants. The participants were 19 spiritual health experts in post-disaster spiritual rehabilitation. Participants were selected using a purposive sampling method until data saturation was reached. The data were collected through semi-structured interviews and analyzed using Granheim and Lundman (2004) content analysis method. The factors challenging men's spiritual rehabilitation were classified into 6 main categories and 16 subcategories. The extracted categories included (i) correcting victims' perspectives, (ii) describing God's characteristics, (iii) seeking help from God, (iv) strengthening spiritual beliefs, (v) psychological factors, and (vi) tranquility factors. Our findings identified the important factors challenging the spiritual rehabilitation of the men victimized by natural disasters, which needed to be considered by responsible organizations and health sectors. Particularly, the organizations in charge of disaster management should take necessary measures and plans during the post-disaster phase to restore people's spiritual health. Spiritual health, currently a neglected dimension of health, should be considered people's in parallel with physical, psychological, and social health dimensions. Our results can be helpful in developing action plans for delivering a comprehensive spiritual rehabilitation service, which would help to lead to the full rehabilitation of victims after natural disasters.

The Policy Gap and Inefficiency in Public Volunteers' Response to Assist the Hospitals After Natural Disasters in Iran: A Grounded Theory Methodology.

OBJECTIVE: This study aims to explore a public volunteer's hospital response model in natural disasters in Iran. METHODS: This study employed grounded theory using the Strauss and Corbin 2008 method and data analysis was carried out in three steps, namely open, axial, and selective coding. The present qualitative study was done using semi-structured interviews with 36 participants who were on two levels and with different experiences in responding to emergencies and disasters as "public volunteers" and "experts". National and local experts were comprised of professors in the field of disaster management, hospital managers, Red Crescent experts, staff and managers of Iran Ministry of Health and Medical Education. RESULTS: The main concept of the paradigm model was "policy gap and inefficiency" in the management of public volunteers, which was rooted in political factions, ethnicity, regulations, and elites. The policy gap and inefficiency led to chaos and "crises over crises." Overcoming the policy gap will result in hospital disaster resilience. Meanwhile, the model covered the causal, contextual, and intervening conditions, strategies, and consequences in relation to the public volunteers' hospital response phase. CONCLUSIONS: The current public volunteers' hospital in Iran suffered from the lack of a coherent, comprehensive, and forward-looking plan for their response. The most important beneficiaries of this paradigm model will be for health policy-makers, to clarify the main culprits of creating policy gap and inefficiency in Iran and other countries with a similar context. It can guide the decision-makings in upstream documents on the public volunteers. Further research should carried out to improve the understanding of the supportive legal framework, building the culture of volunteering, and enhancing volunteers' retention rate.

The effects of Pre-hospital Trauma Life Support (PHTLS) training program on the on-scene time interval.

BACKGROUND: Recent studies have shown that reducing pre-hospital time could improve the outcomes of trauma victims. Due to the importance of pre-hospital time management, this study aims to determine the effects of the Pre-hospital Trauma Life Support (PHTLS) training program on the on-scene time interval reduction. METHODS: The PHTLS training program was implemented based on global standards for pre-hospital emergency technicians. The research tool was a questionnaire designed by the Ministry of Health and Medical Education in Iran. The mean on-scene time interval was calculated before, after and one month after the intervention in the control (n = 32) and experimental group (n = 32). The data were analyzed using SPSS. RESULTS: The mean on-scene time interval in the target group (one month after intervention) has been significantly lower than that of the control group. Moreover, the mean and standard deviation from the on-scene time interval in the target group has been reduced from 17.6 ± 5.5 (before intervention) to 12 ± 3.8 min (one month after intervention) which was statistically significant. CONCLUSION: The implementation of the PHTLS training program can lead to the reduction of on-scene time interval. Therefore, considering the role of reducing on-scene time intervals on victims' survival, the integration of the PHTLS training programs with pre-hospital emergency medical service systems seems inevitable.

Design and psychometric evaluation of sociocultural scale predicting the incidence of road traffic crashes in drivers.

BACKGROUND: Various factors are involved in the occurrence of Road Traffic Crashes (RTCs), one of the most important of these are human factors that can be greatly influenced by the specific sociocultural bases of the drivers. So far, there has not been a scale for measuring Sociocultural Factors (SCFs) predicting the occurrence of RTCs in Iranian drivers. Therefore, the present study was conducted to design and to do psychometric evaluation of a scale for measuring SCFs predicting the occurrence of RTCs in drivers. METHODS: This exploratory sequential mixed method was carried out in three phases. In phases 1 and 2, an initial items pool was created based on systematic literature review (phase1), and semi structured interviews (phase 2). In phase 3, the initial scales were validated using face and content validities. Then, principal component analysis and confirmatory factor analysis were performed to assess the construct validity. Finally, the reliability of the scale was evaluated by examining internal consistency and stability. RESULTS: The scale content validity index was 0.92. Principal component analysis showed seven factors with 27 items, which explain 55.56% of the total variance. In confirmatory factor analysis, model fit indices were satisfactory. Discriminant analysis was also able to distinguish between two groups of accident-involved drivers and accident-free drivers (P less than 0.0001). The reliability of the scale by Cronbach's alpha, Theta, Omega and intra-class correlation coefficients was 0.82, 0.96, 3.07, and 0.80, respectively. CONCLUSIONS: This scale can be used as a valid and reliable scale to evaluate the SCFs predicting the occurrence of RTCs in drivers. Furthermore, the findings of this study will be useful in identifying and planning to reduce RTCs, especially in accident-prone drivers.

A model to explain the challenges of emergency medical technicians' decision making process in emergency situations: a grounded theory.

BACKGROUND: To manage life-threatening conditions and reduce morbidity and mortality, pre-hospital's on-scene decision making is an influential factor. Since pre-hospital's decision making is a challenging process, it is necessary to be identified this process. This study was conducted to explore the model of Iranian emergency medical technicians' decision making in emergency situations. METHODS: This study was applied through grounded theory method using direct field observations and semi-structured interviews. Purposeful sampling with 26 participants including 17 emergency medical technicians including dispatchers, physicians of medical directions, managers and 1 representative for court affairs was performed. Interviews were lasted from October 2018 to July 2019. Corbin and Strauss approach, 2015 (open, axial and selective coding) were used to analyze data. RESULTS: A paradigm model was developed to explain the relationships among the main categories. Decision making in the context of fear and concern was emerged as the core category. Unclear duties, insufficient authorities and competencies as well as lack of enough decision making's protocols and guidelines were categorized as casual conditions. Other important categories linked to the core category were interactions, feelings and "customer focus approach". Action-interaction strategies were taken by Emergency Medical technicians lead to some negative consequences that can threaten clinical outcome and patient safety. CONCLUSIONS: Based on the finding of this study, Emergency Medical technicians' decision making in the context of fear and concern, as the core concept of this model, lead to decrease in quality of the pre-hospital services, stakeholders' dissatisfaction, hospital emergency units' overload, decrease in reputation of the Emergency Medical Technicians, threat to patient clinical outcome and patient safety. To prevent of these negative consequences, facilitation of the Emergency Medical Technicians' on-scene decision making is recommended.

A model for Vision Zero implementation in Iran: a grounded theory study.

BACKGROUND: Road Traffic injuries (RTIs) are major global health issues, but they have been neglected. RTIs are multi-faceted in nature and, like many injuries, are costly but preventable. Iran has one of the highest rates of deaths due to traffic accidents among middle-income countries. Hence, there is a need for effective and preventive approaches in road safety management. One of the new approaches to road safety is the Vision Zero. The aim of this study was to design a Vision Zero implementation model in Iran. METHODS: This present study was conducted using the qualitative grounded theory approach. Purposive, snowball and maximum variety sampling were used to select participants. In-depth interviews were used to collect data. Grounded theory method was used to analyze the data using Corbin and Strauss method. RESULTS: In this study, 19 interviews were conducted with 17 participants. Based on data analysis, a total of 4 main categories and 13 subcategories were obtained. According to the participants, the lead agency was recognized as the core category. Other concepts were categorized as causal conditions, intervening conditions, contextual conditions, action/interaction strategies, and consequences. CONCLUSIONS: Establishing a lead agency with inter-organizational coordination through political support and legislation and changing the approach of road safety can be effective in implementing a Vision Zero. Also, improving the safety attitude of the stakeholders and changing their approach through training and advocacy from various organizations related to road safety is effective in creating a lead agency and implementing a vision zero. In addition, in order to implementation of the model, it is very important to pay attention to the economic, political and ethical underlying factors towards human beings.

Exploring the criteria and factors affecting firefighters' resilience: A qualitative study.

PURPOSE: Firefighters are exposed to high levels of occupational risk factors, such as safety risks, chemical, ergonomic, and physical hazards that may jeopardize their lives. To overcome these hazards, firefighters must be physically, mentally, and personally fit to work. This study aimed to explore the criteria and factors affecting firefighters' resilience based on stakeholders' experiences. METHODS: This qualitative study was carried out using conventional content analysis. In total, 21 face-to-face interviews were conducted by firefighters who were experienced in the field. The interviews were carried out from July 2019 to January 2020. The data were collected using 3 unstructured interviews and then resumed by 18 semi-structured interviews. Data analysis was done using Graneheim method. RESULTS: The participants had more than 5 years of experience in the field of search and rescue. The extracted codes through data analysis were classified into 3 main categories (individual, organizational, and social factors), 9 sub-categories (mental, physical, occupational, managerial, colleagues-related, equipment-related, environmental, community-related, and family-related factors), as well as 19 sub-sub-categories and 570 codes. CONCLUSION: Firefighters' personality, physical condition, behavior and psychological characteristics can affect their resilience along with organizational and management factors that play significant role in people's safety. Developing a tool for assessing resilience can help decision makers to have a real depict of firefighters' job qualifications.

Establishing the Status of Patients With Non-Communicable Diseases in Disaster: A Systematic Review.

OBJECTIVE: People with NCDs are particularly vulnerable to disasters. This research systematically reviewed reports describing studies on the status of patients with NCDs before, during and after disasters. METHOD: Relevant articles published from 1997 to 2019 were collected by searching the Scopus, PubMed, and Science Direct databases. We specifically examined reports describing NCDs and including the key words 'Non-Communicable Disease and Disasters.' NCDs include cardiovascular, respiratory, diabetes and cancer diseases. RESULTS: The review identified 42 relevant articles. Most of the included studies were found to have described the conditions of patients with NCDs after disasters - 14 (13.3%), during disasters - 11 (26.2%), before disasters - 6 (14.3%), within all stages of disasters: before, during and after - 6 (14.3%), only during and after disasters - 4 (9.5%), and includes before and during disasters - 1 (2.4%). CONCLUSION: NCDs pose major health issues in disasters. Development of strong counter measures against the interruption of treatment, as well as surveillance systems to ascertain medical needs for NCDs are necessary as preparation for future disasters.