Developing and validating a tool for assessing organizational resilience in healthcare organizations: a cross-sectional study

Introduction

The concept of organizational resilience has gained prominence in recent years as a means of understanding how organizations can withstand and adapt to unexpected disruptions. Originally used in fields like ecology and physics, resilience in the organizational context refers to a system's ability to absorb changes while maintaining core functionality (1). Despite its potential, the concept of organizational resilience remains somewhat unclear, particularly in terms of measurement. To address this, researchers suggest greater conceptual clarity and a more parsimonious approach to further develop the construct (2). This refinement could enhance the value of organizational resilience as a construct in disaster management research.

Resilience scholarship has roots in earlier work dating back to the 1970s; however, the conceptualization of organizational resilience as a distinct construct in organizational and management research evolved subsequently and expanded substantially in later decades, particularly as scholars began to frame resilience as an organizational capability for anticipating, absorbing, adapting to, and recovering from disruptions.

Research on organizational resilience has evolved through multiple conceptual streams, including early work on organizational responses to crises and uncertainty (3) and subsequent efforts to operationalize resilience as a managerial capability (4, 5). Later contributions further elaborated the notion of resilient organizations and firms, emphasizing adaptive capacity, learning, and systemic pre-paredness (6). In parallel, broader resilience frameworks developed at community and systems levels have provided important conceptual foundations for understanding resilience as a multi-level phenomenon (7). More recent scholarship has continued to refine theoretical models and empirical approaches to resilience, contributing to a more integrated understanding of how organizations anticipate, absorb, and adapt to disruptions. Collectively, this body of literature underscores the multidimensional nature of organizational resilience and informs the conceptual framework adopted in the present study.

Most researchers define organizational resilience as the ability of an entity to deal with internal and external changes, risks, or shocks (8). Fasey et al. (9) defined it as a dynamic capability to deal with significant change, emerging from multi-level interacting characteristics and processes. Ahmed et al. (10) conceptualized organizational resilience as both a process and an outcome, emphasizing strategic pre-paredness, adaptive responses to disruptive shocks, and the capacity for positive transformation. These definitions highlight the concept's complexity and multifaceted nature, emphasizing the need for a unified understanding to guide future research and practice in organizational resilience (11). The key features and components of a resilient organization include building situational awareness, managing vulnerabilities, investing resources, having the ability to improvise, having the capacity to anticipate events, learning ability, collaboration, resilience of individuals, flexibility, and redundancy (12).

In the present study, organizational resilience is conceptualized as a capability-oriented, process-based construct that reflects the organization's ongoing capacity to anticipate, adapt, respond to, and recover from disruption in the healthcare context.

In recent years, there has been growing recognition of the crucial need for early crisis and emergency pre-paredness, alongside efforts to enhance organizational resilience, particularly within healthcare organizations (13). This heightened focus can be largely attributed to the global COVID-19 pandemic. Furthermore, the terrorist attack in the State of Israel on October 7, 2023, underscored the essential nature of resilience in healthcare settings (14). These organizations were confronted with the daunting task of evacuating and treating thousands of casualties, each with varying degrees of injuries (15).

Research indicates that frequent exposure to emergency situations enhances resilience among emergency response organizations. This resilience develops through accumulated experience in managing challenging circumstances with limited resources, better preparing them for future crises (16).

While the concept of resilience and its practical applications have garnered increasing interest among researchers, policymakers, and healthcare managers, there remains a need for more studies that provide more detail on how to measure organizational resilience. This gap is particularly acute in the development of resilience measurement frameworks and indices specifically tailored for the healthcare sector. Despite growing recognition of its importance, the tools and methodologies for quantifying and assessing resilience in healthcare organizations remain underdeveloped. Several tools have been developed to measure organizational resilience, each with its own strengths and weaknesses. Lee et al. (17) created a survey tool to help organizations identify strengths and weaknesses of their resilience, while Stephenson et al. (18) developed a web-based survey focusing on social and cultural factors contributing to resilience. Sweya et al. (19) designed a tool specifically for water supply systems in Tanzania, emphasizing factors like environmental awareness and emergency response planning. proposed a more comprehensive measurement scale based on case studies of resilient companies, identifying five dimensions of organizational resilience that include capital, strategic, cultural, relationship, and learning resilience. These tools generally allow organizations to assess their resilience capabilities and guide improvement efforts. However, they vary in their focus, with some being industry-specific or emphasizing different aspects of resilience. The diversity of approaches highlights the complexity of measuring organizational resilience and the need for context-specific assessment tools. There is no consensus on the best methods for evaluating organizational resilience in healthcare settings, including which aspects should be measured, when assessments should be conducted, and which specific characteristics and indicators should be used. Approaches to measuring and assessing organizational resilience in this sector differ substantially in scope, format, content, and purpose. These methodologies vary between prospective assessments, which evaluate resilience before a crisis, and retrospective assessments, which analyze resilience during or after a crisis. Additionally, they differ in the degree to which they rely on pre-defined or shock-specific characteristics and indicators.

Understanding the diverse approaches to measuring organizational resilience lays the groundwork for identifying specific resilience-building components critical to healthcare settings. Such components, such as effective leadership and organizational culture (20), stand out as fundamental elements in nurturing and sustaining organizational resilience, particularly in response to crises.

As shown in Table 1 organizational resilience measurement approaches reported in the literature vary in their conceptual emphasis, scope, and sectoral applicability. The OR assessment tool used in the present study was developed as a healthcare-tailored, repeatable survey instrument, informed by prior scientific measurement frameworks and refined through expert validation, pilot testing, and an adapted Delphi process. Accordingly, the present study assesses perceived (self-reported) organizational resilience using a developed and validated anonymous Organizational Resilience Questionnaire, in which employees and managers provide subjective responses to resilience-related statements rather than completing an objective checklist of organizational features.

Table 1. Comparative summary of selected organizational resilience measurement tools and the present study's organizational resilience assessment tool.

Literature review

In the context of organizational resilience, seven fundamental factors have been identified. These include ethos, leadership and human capital, organizational culture, learning processes, situational awareness, organizational performance and adaptability capability.

The notion of ethos, encompassing an organization's mission, values, and principles, serves as a crucial cornerstone in building organizational resilience. It acts as the cultural and ethical backbone that guides decision-making, shapes behavior, and enhances adaptability in times of crisis (21).

Effective leadership is crucial for building organizational resilience in healthcare settings, particularly during crises like the COVID-19 pandemic (22). In resilient organizations, effective leadership involves developing self-awareness, practicing mindfulness, and maintaining a healthy work-life balance (23). Leaders can enhance their own resilience through optimism, empathy, gratitude, and self-care behaviors such as strategic resting and reflection (24). Nurse leaders are particularly obligated to cultivate resilience within themselves, their teams, and their entire organization. Resilient leadership contributes to reduced turnover, lower costs, and improved quality outcomes (25). By fostering resilience, healthcare leaders can better manage chronic stressors, inspire confidence, and navigate turbulent times (22, 24). Ultimately, resilient leadership is essential for sustaining performance improvement and quality in healthcare organizations (23).

Organizational culture plays a pivotal role in either preventing disasters or exacerbating crises (26). Building a resilient organizational culture is essential for effective crisis recovery, future success, and sustainability (27). Investing in human capital in healthcare organizations through continuous professional development and training is crucial for enhancing organizational resilience. Managers' attitudes toward risk, such as their level of crisis pre-paredness, shape the organizational ethos (28).

Fostering a culture of continuous learning and knowledge sharing is key to enhancing organizational resilience. Organizational learning capacity, leadership, and situational awareness are crucial for preparing healthcare organizations to effectively respond to disruptions and maintain the quality of healthcare services.

Situational awareness is vital for organizational resilience, enabling teams to accurately perceive and respond to internal and external changes (29, 30). Employee development through continuous training enhances skills, knowledge, confidence, and resilience within the organization.

Organizational performance is closely linked to organizational resilience, as an organization's capacity to function effectively in both routine conditions and disruptive events substantially contributes to its overall resilience. Research has also shown a positive and significant association between organizational resilience and organizational performance (31). In the present study, however, organizational performance is conceptualized as one of seven categories that jointly comprise the dependent variable, organizational resilience, and is therefore treated as an integral component of the construct rather than as a separate outcome. Accordingly, the intended outcome of strengthening organizational resilience is not organizational performance per se, but rather—ideally—the preservation of organizational functional continuity during emergencies, crises, and disasters.

Adaptability capability is essential for organizational resilience because it allows companies to manage uncertainty, recover from setbacks, and maintain performance over the long term. By promoting agility, learning, flexibility, and strategic resource management, organizations can create strong systems that not only endure challenges but also seize growth opportunities in ever-changing environments (32).

Understanding and fostering organizational resilience, effective leadership, situational awareness, and employee development are crucial for healthcare organizations to succeed in today's dynamic environment. These factors help organizations adapt to challenges and uncertainties, ensuring long-term effective function (33). The viability of an organization during varied crises is contingent on its resilience as opposed to its vulnerability (fragility). The concept of “anti-fragile” introduced by Taleb, (34) describes a system's ability to not only withstand challenges such as failures or volatility, but to improve in response to them. This concept explores how systems can enhance their performance and thrive during crises, suggesting that while systems may temporarily weaken or even collapse under stress, “anti-fragile” systems can effectively manage external pressures effectively, evolving beyond their previous state post-crisis. Organizational resilience aims to transition an organization from a fragile state–prone to dysfunction or collapse during a crisis-to a resilient and then “anti-fragile” state, where an organization not only copes successfully with a crisis but also flourishes, achieving what is termed “bouncing forward”. Strengthening resilience can help healthcare organizations transition from a fragility to anti-fragility, thus enabling them to not only withstand shocks but potentially emerge stronger from them (34).

Resilience in healthcare is essential for maintaining high-quality patient care during challenging circumstances. Enhancing organizational resilience in healthcare settings is expected to improve crisis management, enhance productivity, and ensure the continuity of operations. Understanding and prioritizing factors that contribute to resilience can strengthen organizations' ability to effectively navigate challenges and uncertainties.

The study aimed to develop and validate a tool for assessing organizational resilience in healthcare institutions (including the relative importance of each factor) and identify its predictive factors.

Methodology

Research design

The research methodology encompassed a series of carefully planned stages to develop and validate an assessment tool for measuring organizational resilience in healthcare settings. Initially, a comprehensive review of both scientific and gray literature on organizational resilience was conducted. This review helped to shape a clear definition of organizational resilience, tailored for both general and healthcare-specific organizations, and used as a basis for developing the assessment tool.

Following the literature review, an organizational resilience assessment tool was created. The development of this tool involved drafting 29 items that reflect various aspects of organizational resilience, which were then grouped into seven categories (factors) based on factor analysis.

These categories ranged from organizational culture to adaptability, with each category containing two to seven specific items. For instance, items included statements like, “Our organization has embraced a culture that values learning from mistakes and deriving lessons for ongoing improvement” (organizational culture factor) and “The internal communication within the organization is strong, efficient, and effective” (adaptability factor).

The content validity of the assessment tool was established by 12 content experts from both academia and practice. These experts reviewed and refined the tool to ensure it accurately measures the intended constructs. The tool was then pilot tested among 19 medical professionals from healthcare organizations not involved in the main study, to redefine the tool further. A modified Delphi process was conducted among content experts to determine the hierarchy of importance among the categories (factors) that compose the assessment tool. A consensus of at least 75% of the experts was defined as the minimum acceptable level of agreement. The Delphi process was conducted in two rounds. In the first round, 19 experts completed the questionnaire, followed by 16 experts in the second round. Organizational resilience items were rated independently by each expert across both rounds. Consensus was defined a priori as at least 75% of panel members. This threshold was based on recent Delphi methodological literature recommending 70–80% agreement as an acceptable standard for consensus (51). In the second round, consensus was achieved for all categories in the Organizational Resilience Questionnaire, ensuring both transparency and reproducibility of the process. Following this, the organizational resilience assessment tool was implemented across three distinct types of healthcare organizations to evaluate their levels of organizational resilience.

Data collection was conducted by distributing a URL link to medical personnel in the three participating healthcare organizations. Participants could access the tool via their computer or smartphone. The questionnaires were completed anonymously, after providing informed consent. Written research and ethical consent were obtained from the management of the participating organizations and the Tel Aviv University Ethics Committee (#0004464-5), ensuring compliance with ethical standards and securing the necessary authorizations to conduct the study responsibly and transparently. The period for completing the questionnaires in the three health organizations spanned from May 2022 to April 2023.

Sample selection

To ensure diverse representation across varied sectors within each organization, the assessment tool was distributed according to the calculated sample size requirements, except in the relatively small health bureau, where the tool was sent to all employees. To ensure diverse representation across professional sectors within each healthcare organization, the organizational resilience assessment tool was disseminated to all employees in the three participating institutions. The distribution was coordinated through each organization's administration, which emphasized the importance of participation.

G^*Power software was used to calculate the minimum sample size for effective statistical power employing a multivariate linear regression test with 10 independent variables. The parameters used for the calculation were an alpha size of 0.05 (type 1 error), power of 0.95 (type 2 error), and effect size of 0.15. The minimum sample size determined for each organization was 166 participants. The choice of f² = 0.15 aligns with Cohen's conventions for a small-to-moderate effect size in multiple regression analysis, reflecting realistic expectations for behavioral and organizational research.

Study population

The study was conducted across three distinct types of healthcare organizations to examine the applicability of the Organizational Resilience Questionnaire in different organizational contexts: a general hospital (acute-care medical center), an emergency medical services (EMS) organization, and a district health bureau (DHB). These organizations differed in core function (hospital-based, pre-hospital emergency care, and public/community health), workforce size (approximately 2,500 staff in the hospital, ~1,800 in EMS, and ~200 in the DHB), and site distribution (single-site vs. multi-site operations). All three organizations were selected from the same geographic region in southern Israel (peripheral region) to reduce the influence of environmental variation and contextual risk factors. The study population comprised active employees and managers from these three organizations, all of whom completed the Organizational Resilience Questionnaire. Respondents represented multiple professional disciplines, including physicians, paramedics, nursing staff, administrative personnel, logistics staff, and other relevant roles (see Table 2).

Table 2. Baseline characteristics of participating healthcare organizations and study population.

Data analysis

To minimize the risk of Type I errors associated with multiple comparisons, we predefined our statistical strategy for handling multiplicity. Specifically, adjustments for multiple hypothesis testing were planned a priori and applied where relevant, in accordance with guidelines aimed at ensuring the reproducibility and transparency of study results. This approach aligns with recommendations from leading medical journals to explicitly report methods for controlling the family-wise error rate or the false discovery rate in multivariate analyses.

Data analysis was performed using SPSS software (version 31). An Exploratory Factor Analysis test was initially performed to determine the number of factors examined in the organizational resilience assessment tool. The analysis was performed using the Varimax method. A Confirmatory Factor Analysis was then conducted on the composite Organizational Resilience assessment tool. Cronbach's alpha test was conducted to assess the reliability of the varied factors as well as the composite Organizational Resilience assessment tool. Pearson correlations were performed to identify associations, and repeated measures analysis of variance (ANOVA) was used to examine differences within and between the organizations. For each family of hypotheses tested jointly, a Bonferroni correction was applied to control the family-wise error rate of 0.05 in total. The significance alpha was adjusted according to the number of comparisons within each family, and confidence intervals were recalculated based on the corrected alpha level to ensure consistency with the adjusted significant criteria, and results were interpreted considering these corrections.

The widths of the 95% confidence intervals have not been adjusted for multiplicity, and the intervals should not be used in place of hypothesis testing.

The analysis also included Multivariate linear regression to identify predictors of organizational resilience, with significance set at p ≤ 0.05. The method we chose was Stepwise selection, which reduces the risk of overfitting by excluding irrelevant variables, and enhances interpretability by retaining only those predictors that contribute meaningfully to the model. Given the final regression model based on the minimum predictors correlated with Organization Resilience at level of 0.05, we applied further adjustments: all p-values were corrected to Bonferroni to control the FWER in the model, and all Confidence intervals were calculated at the level of 99.5% (95% adjusted to 10 predictors included in the model). Results were compared across organizations and aggregated to assess impacts on resilience within the broader healthcare system.

Results

Overall, 602 people participated in the study, amongst them 225 from the general hospital, 214 from the EMS, and 163 from the health bureau. A comparative descriptive analysis of respondents' baseline background characteristics was performed across the participating organizations. As expected, the samples differed in professional composition due to the distinct functions of each organization (e.g., physicians in the hospital, paramedics in the emergency medical services organization, and unique regulatory/public health roles in the district health office, such as food inspection and environmental health). These differences reflect the structural and operational diversity of the study settings and were considered when interpreting subsequent comparative and longitudinal results.

The organizational resilience assessment tool

The developed tool comprises 29 items (Table 9) separated into the following factors: ethos, organizational culture, leadership and human capital, situational awareness, adaptability, learning ability, and organizational performance. Table 3 shows the reliability of the overall assessment tool and the different factors that were found to be acceptable in all three health organizations. Table 4 shows the Confirmatory Factor Analysis of the composite Organizational Resilience assessment tool that yielded the following results: the Kaiser–Olkin Measure of sampling adequacy of the data is 0.924. The Bartlett's test of sphericity is Chi (d.f = 21) = 3,847.18, p < 0.001. The test results suggest that the assumption of equal variances among the seven categories defining the resilience variable has been rejected. This scenario is quite common in studies with five or more categories, where each category contains between two to seven statements. Consequently, the significance of this result does not hinder the progression of the study.

Table 3. Reliability (Cronbach-alpha values) of the composite organizational resilience assessment tool and its varied factors.

Table 4. Confirmatory factor analysis of the composite organizational resilience assessment tool.

^**p < 0.001.

Table 5 presents the results of the Exploratory Factor Analysis for the composite Organizational Resilience assessment tool, which showed a Kaiser–Meyer–Olkin value of 0.975 (406), with a significance level of p < 0.001. Prior to performing the factor analysis, a preliminary KMO test was administered to determine the suitability of the questionnaire statements for such analysis. The KMO value for the questionnaire was 0.924 on a scale from 0 to 1, signifying an “Excellent” level of fit. This indicates that the questionnaire statements are excellently suited for factor analysis using the Factor Analysis procedure. Achieving an excellent fit in the KMO test lends credibility to the results of the subsequent data analysis. Since we achieved an excellent KMO value, I proceeded with the factor analysis test to validate the questionnaire. The recommended distribution of items from the factor analysis aligns with the category grouping defined in the study. Consequently, seven categories were identified based on the item distribution presented in Table 5. This method provides statistical validation for the questionnaire, ensuring that items examining the same content area are placed within the same category according to the research questionnaire. Additionally, this complements the questionnaire validation through peer evaluation in a modified Delphi process, which achieved over 75% agreement after the second round. Therefore, the questionnaire is validated by both field experts and statistical methods, with a significance level of 0.05.

Table 5. Exploratory factor analysis of the organizational resilience assessment tool-item loadings for each variable.

Kaiser–Meyer–Olkim (406) = 0.975, p < 0.001.

Ranking the assessment tool

Table 6 presents the ranks (group average score) given by the content experts who participated in the modified Delphi process, to the respective factors of the organizational resilience assessment tool. The factor “leadership and human capital” received the highest average score (19% of the overall score), while “organization's performance” received the lowest average score (11% of the overall score).

Table 6. Ranks of the factors in the organizational resilience assessment tool based on a modified-Delphi process.

Levels of resilience

A relatively high level of organizational resilience was found in the three types of health entities, with an average score of 3.79 (out of 5) for the hospital, 3.91 for the EMS, and 3.73 for the district health bureau respectively. Table 7 presents the average scores of each health organization's resilience, broken down into the varied factors that compose organizational resilience. The level of organizational resilience among the EMS was found to be significantly higher in the factors of ethos, leadership and human capital, situational awareness, adaptability, and organizational performance. No significant differences were found in the level of organizational resilience between the three healthcare organizations in the factors of organizational culture and learning ability. The most significant effect size was in the situational awareness factors (0.319). According to the results of the multivariate linear regression test performed on the aggregated data of the three healthcare organizations, eight variables together explain 12% of the variation in organizational resilience [R (2) = 0.12]. The statistical F-value was F_{10, 530} = 7.17, p = 0.00. Table 8 shows the predictor variables, the standardized regression coefficients, significance of the results while adjusted to number of variables in the model, and the confidence interval calculated at level of 99.5%, according to Bonferroni correction. All regression model results shown in Table 8 are reported following a Bonferroni correction, applied to account for the inclusion of 10 predictors in the model. Accordingly, the original significance values were adjusted by multiplying them by ten, and the confidence intervals were recalculated at the 99.5% confidence level rather than the conventional 95%.

Table 7. Comparison of the factors of organizational resilience between the three health organizations.

Table 8. Multivariate linear regression-aggregated data (the three health organizations).

F_{(10, 530)} = 7.17, p < 0.001, R2 = 0.12.

Table 9. The organizational resilience questionnaire.

The multiple linear regression analysis model was statistically significant [F _{(10, 530)} = 7.17, p < 0.001] and accounted for approximately 12% of the variance in organizational resilience. This indicates the model provides a meaningful, albeit moderate, contribution to explaining the factors shaping organizational resilience across the three health systems.

Organizational context

The results demonstrate that employees in EMS organizations reported significantly higher levels of organizational resilience compared to hospital employees (β = 0.39, p = 0.02). In contrast, after correcting the p-value to Bonferroni's method, no significant difference was found between employees in Health Bureaus and those in hospitals (β = 0.397, p = 0.25). These findings highlight a relative advantage in EMS, possibly reflecting the nature of fieldwork, a strong sense of mission, and high team interdependence under emergency conditions.

Individual characteristics

Gender emerged as a significant predictor: men reported lower levels of organizational resilience than women (β = −0.169, p = 0.01). Educational background also played a significant role: employees with academic education reported lower level of resilience (β = −0.217, p < 0.001). This may be explained by higher expectations and a more critical perspective among those with a higher level of education. Age is positively associated with resilience (β = 0.32, p = 0.02), suggesting that older employees tend to report greater organizational resilience.

Additional variables

Managerial position did not emerge as a significant predictor (β = 0.104, p = 0.19). Similarly, being secular vs. religious (β = −0.106, p = 0.11), or organizational seniority (β = −0.11, p = 0.61), were not significantly associated with organizational resilience.

Age interactions

Although age was found as significantly positively associated with resilience (β = 0.32, p = 0.02), a significant negative interaction was found among EMS employees: higher age was associated with lower levels of organizational resilience (β = −0.358, p = 0.02). This pattern may reflect the physical and emotional toll of long-term fieldwork in emergency settings. A similar, though statistically non-significant, tendency was observed in Health Bureaus (β = −0.496, p = 0.07).

Discussion

Organizational resilience encompasses the ability to endure and recover from disruptions such as disasters due to natural hazards natural disasters, technological failures, or economic downturns (17). It involves adjusting, reacting, and recovering from challenges. This study contributes to the understanding of organizational resilience within healthcare settings, emphasizing the critical factors that enhance the ability to withstand and recover from adverse situations. Enhancing organizational resilience in healthcare institutions is essential to ensure operational continuity during emergencies. Strengthening resilience improves an organization's ability to respond to and manage crises effectively (35). In emergency situations, the capacity of healthcare institutions to maintain operations continuously and deliver medical services is critical for public wellbeing. Organizational resilience not only helps healthcare organizations to respond to crises but also supports swift and effective recovery in the aftermath of disasters (36).

The level of organizational resilience varies depending on an organization's role, responsibilities, and exposure to crises. Therefore, continuous assessment and improvement of resilience are vital for all organizations to prepare for unexpected disruptions (37).

This study identified leadership and human capital as significant pillars of organizational resilience. This finding is in line with previous studies, which posited that these elements foster cohesive, interdependent teams and thus enhance the resilience of organizations (38). Effective leadership and a strong organizational culture foster an environment conducive to resilience by nurturing robust team dynamics essential during crises. Other factors, such as ethos and organizational performance, were deemed less significant compared to leadership and human capital. Ethos reflects managers' perceptions of risk and their focus on crisis preparedness. This “ethos of resilience” shapes an organization's crisis management approach by embedding a culture of resilience across all levels (39). However, experts in the modified Delphi process may have found ethos difficult to quantify or measure due to its abstract nature (40). In terms of organizational performance, resilient organizations are often characterized by their adaptability and agility in adjusting profit-generation strategies (41).

Conversely, the study's findings suggest that in non-profit health organizations, performance metrics related to resilience may differ from those in profit-oriented organizations. Nonetheless, this contrasts with findings from Suryaningtyas et al., (42) which showed a positive relationship between resilience and organizational performance.

The differential levels of organizational resilience observed across healthcare organizations–general hospitals, EMS, and district health bureaus–highlight the impact of operational environments on resilience levels. EMS personnel exhibited greater perceived a higher level of organizational resilience than other organizations, possibly due to several reasons. One contributing factor is that emergency medical services often develop heightened resilience because they are routinely exposed to high-stress situations that necessitate swift decision-making under pressure (43). This exposure enables EMS teams to develop greater adaptability and lower stress levels compared to hospital workers (44). Hospitals typically handle a broader range of services—routine care, surgeries, rehabilitation—and, while they have emergency protocols in place, their pre-paredness may differ from that of EMS teams. Similarly, health bureau employees focus on policymaking and resource allocation rather than frontline emergency response. These roles require different levels of adaptability and response patterns.

While the nature of work influences organizational resilience, other factors-such as leadership quality, communication effectiveness, training programs, and resource allocation-also play a role. Evidence suggests that EMS teams' frequent exposure to life-threatening situations fosters higher resilience levels compared to hospital workers (45). This enhanced resilience helps EMS teams mitigate stress and adapt more effectively to challenges (46). However, building and maintaining resilience is an ongoing process that varies among individuals. Organizations must provide support systems such as stress management programs, psychological assistance, teamwork promotion, and open communication to help employees enhance their resilience skills (47).

In summary, while both EMS teams and hospital workers face stressful events in their roles, EMS teams' higher exposure intensity may contribute to their greater resilience. Supporting employees across all roles with resources and training is crucial for fostering organizational resilience across healthcare institutions (48). Programs like BRITE (Building Resilience within Institutions Together with Employees) aim to equip healthcare workers with resilience-fostering skills (49). Studies have shown that workplace resilience training programs can significantly improve employees' resilience, quality of life, and health behaviors (50).

The study underscores the importance of building and sustaining organizational resilience by developing key components such as organizational culture, leadership and human capital, situational awareness, adaptability, ethos, and learning capacity. These elements are vital for improving healthcare organizations' readiness to address both known and emerging challenges, including global health crises.

In the context of Israel's healthcare system, the findings emphasize the need for resilience-building efforts in light of ongoing crises such as the COVID-19 pandemic, the protracted war, and potential terror attacks following the events of October 7th.

Strengthening organizational resilience is particularly crucial for ensuring that healthcare institutions can respond effectively to such disruptions while safeguarding public health. Future research should explore these dimensions and extend the tool's applicability to a broader range of healthcare settings to generalize the findings more effectively.

This tool may also be useful in other local and international healthcare settings for baseline assessment, cross-organizational comparison, longitudinal monitoring, and evaluation of resilience-strengthening interventions. However, before broader implementation, its use in new contexts should be preceded by adaptation to the new context and renewed psychometric validation.

Limitations of the study

The collected sample size within the health bureau was slightly under the calculated needed sample size threshold (out of the total workforce of around 175 employees in the organization, 163 employees participated and provided their responses).

The study's R-squared value of 12% points to moderate explanatory power, suggesting that other unmeasured factors could significantly influence organizational resilience. This calls for further research to explore these dimensions comprehensively.

The importance of the factors within the organizational resilience questionnaire was validated through a modified Delphi process. This method was employed to mitigate potential biases among the participating experts, such as group thinking and the influence of specific teams that completed the questionnaires. As part of the tool validation, a high threshold of 75% agreement among the experts was set to address these potential biases.

A direct comparison between staff-reported organizational resilience and objectively measured organizational resilience across the three organizations was not conducted in the present study and should be considered a study limitation; future research should include triangulation with objective organizational assessment measures.

Conclusions

This study aimed to develop and validate a tool for assessing organizational resilience in healthcare settings, an increasingly critical area considering global health crises and local emergencies. The findings underscore the importance of various factors that contribute to an organization's resilience, including leadership and human capital, organizational culture, situational awareness, adaptability, and the ethos of resilience. The assessment tool has proven effective in identifying levels of resilience across diverse healthcare institutions. The tool's application in a general hospital, emergency medical services, and a district health bureau has provided valuable insights into the specific resilience capabilities of these organizations. This has highlighted the significance of tailored approaches to building resilience that consider each entity's unique operational and emergency response challenges. Leadership emerged as a critical factor in fostering a culture of resilience, particularly in high-pressure and crisis scenarios. The study also illuminated the vital roles of adaptability and situational awareness in maintaining operational effectiveness during disruptions. Importantly, the research identified areas for further enhancement, such as improving the understanding and measurement of organizational ethos and performance within the resilience framework. Further research is needed to explore the potential interaction effects among gender, age, and education, as these variables may jointly influence the observed outcomes. These analyses were beyond the scope of the present study and should be examined in future research with larger samples and more advanced modeling approaches. Although the study produced significant findings, its conclusions should be interpreted in light of certain limitations, including the modest predictive value of organizational resilience, which suggests that additional unmeasured factors may also play a role. Nevertheless, the study contributes to a clearer understanding of how organizational resilience can be systematically assessed and strengthened, and offers a useful foundation for healthcare leaders seeking to identify priorities and guide targeted interventions.

Correction note

A correction has been made to this article. Details can be found at: 10.3389/femer.2026.1789461.

Generative AI statement

The author(s) declared that generative AI was used in the creation of this manuscript. Generative AI was used solely for language editing and stylistic refinement (grammar, clarity, and readability). It was not used to generate scientific content, analyses, results, or references. The author(s) reviewed and approved all revisions and take full responsibility for the manuscript's content.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Footnotes

Edited by: Korakot Apiratwarakul, Khon Kaen University, Thailand

Reviewed by: Ihab H. Sawalha, American University of Madaba, Jordan

Dominicus Wahyu Pradana, Widya Mandala Catholic University Surabaya, Indonesia

Novil Wijesekara, Ministry of Health and Mass Media, Sri Lanka