Table 1 Measurement and assessment approaches of organizational resilience
Author/s, year | Format of the approach | Type of shock/challenge | Stage of resilience | Nature of output | Purpose |
|---|---|---|---|---|---|
Adini et al. 2012 [37] | Structured evaluation tool | Various types of emergencies (mass casualty events, toxicological and chemical events, and biological events such as pandemics and bio-terror agents) | Pre-shock | Overall preparedness for emergencies score for each hospital | Formative, diagnostic |
Awad and Cocchio, 2015 [38] | An electronic cross-sectional survey | Mass casualty events | Pre-shock | Percentages and frequencies describing preparedness level of hospital pharmacy for each survey question | Formative |
Bin Shalhoub et al. 2017 [39] | Questionnaire based on the WHO toolkit for assessing health-system capacity for crisis management and WHO hospital emergency response checklist | Mass casualty events | Pre-shock | Percentages and frequencies describing preparedness level of hospitals for each question or area of the questionnaire | Formative, diagnostic |
Higgins et al. 2004 [40]Â | A survey instrument based on the Mass Casualty Disaster Plan Checklist and a brief supplemental bioterrorism preparedness survey based on a checklist developed for the Agency for Healthcare Research and Quality | Mass casualty events | Pre-shock | Percentages and frequencies describing preparedness level of hospitals | Formative, diagnostic |
Traub et al. 2007 [41] | Hospital surge capacity survey | Mass casualties as a result of terrorism or natural disasters | Pre-shock | Numbers of operating theatres, ICU beds and x-ray machines required according to the predictor of numbers of mass casualties | Formative, summative |
Aladhrai et al. 2015 [42] | WHO Hospital emergency response checklist | Man-made conflicts (2011 Yemeni revolution) | Pre- and post-shock (comparing the level of preparedness in 2011 with that in 2013) | Overall preparedness score for each hospital Hospitals categorised as unacceptable, insufficient or effective, based on the overall score | Formative, diagnostic |
Ardalan et al. 2016 [43] | Farsi version of the WHO Hospital Safety Index (FHSI) | Disasters | Pre-shock | Overall score of hospital safety Hospitals categorised to three safety classes: low, average, and high based on the total score | Formative, diagnostic |
Djalali et al. 2013 [44] | The Functional Capacity module of the WHO Hospital Safety Index (HSI) | Disasters | Pre- and during the shock | Functional capacity score for each hospital Hospitals categorised as: (1) will function during a disaster; (2) at risk, interventional measures are needed; (3) inadequate, urgent intervention is needed | Formative, diagnostic |
Zhong et al. 2014 [45] | A framework and derived questionnaire for measuring hospital disaster resilience | Disasters | Pre-, during and after | Overall hospital resilience score, hospitals classified as extremely resilient to disasters; extremely impacted upon in a disaster; or have greater difficulty in recovering based on the overall score | Formative, diagnostic |
Janati et al. 2017 [46] | WHO hospital emergency response checklist | Disasters | Pre-shock | Percentages and frequencies describing preparedness level of hospitals | Formative, diagnostic |
Naser et al. 2018 [47] | WO Hospital Emergency Response Checklist | Disasters | Pre-shock | Overall emergency preparedness and response score for each hospital Hospitals categorised as unacceptable, insufficient, or effective | Formative, diagnostic |
Hosseini et al. 2019 [48] | Questionnaire based on the WHO Hospital Safety Index (HSI) and the assessment of vulnerability elements at hospitals developed by Mulyasari et al. (2013) Data analysed using TOPSIS technique | Unexpected disasters and events | Pre-shock | Hospitals ranked based on disaster preparedness scores | Formative, diagnostic |
Khazaei Monfared et al. 2017 [49] | WHO Hospital Safety Index translated to Farsi and adapted to Iran’s context by Ardalan et al. (2016) | Unexpected disasters (floods, earthquakes, severe weather changes, bioterrorism, and epidemics) | Pre-shock | Hospital safety score for each hospital Hospitals categorised as low safety, medium safety and high safety based on the safety score | Formative, diagnostic |
Cimellaro et al. 2017 [50] | Discrete event simulation (DES) models | Disasters and other emergencies | During-shock | Model of an emergency department’s performance based on different parameters | Formative |
Shirali et al. 2016 [51] | Questionnaire based on the seven dimensions of resilience engineering | Natural and man-made disasters | Pre-, during and post-shock | Average scores for each indicator related to the hospital in different crisis management phases | Formative, summative and diagnostic |
Ul-Haq et al. 2019 [52] | WHO Toolkit for assessing health system capacity for crisis management (user manual and assessment form) | Natural or manmade, predictable or unpredictable disasters | Pre-shock | Percentages and frequencies describing preparedness level of hospitals for different indicators Healthcare facilities categorised as acceptable, partial or inadequate | Formative, diagnostic |
Sobhani et al. 2014 [53] | A standard checklist | Natural disasters | Pre-shock | Overall level of preparedness against disasters for each hospital Hospitals categorised into very poor; poor; moderate; good; and very good | Formative, diagnostic |
Brevard et al. 2008 [54] | Direct observation and recording of events from within the hospital before, during, and after the storm; retrospective review of the hospital master disaster plan and a survey of key staff present during and post-storm | Hurricanes | Pre-, during- and post-shock | Percentages and frequencies describing preparedness level; qualitative description of events from before, during, and after the storm; survey responses rated on a scale of three: completely inadequate, partially adequate, completely adequate | Formative, diagnostic and summative |
Rios et al. 2021 [55] | Interviews with healthcare professionals Data analysed using Kruk et al.’s resilience framework | Hurricanes | Post-shock | Qualitative description of the key factors that led to a poorly resilient hospital and health system | Formative, summative |
Cimellaro et al. 2010 [56] | A comprehensive model to quantify disaster resilience | Earthquakes | Pre-, during and post-shock | Loss estimation models and recovery models that can be applied to complex systems of structures and infrastructure networks | Formative |
Jacques et al. 2014 [57] | Damage and loss-of-function survey tool Data analysed using fault-tree method | Earthquakes | Pre-, during and post-disaster | Descriptions of the loss of functionality of physical systems, the impact to healthcare services and support services, and the sharing of resources and transfer of patients in a hospital system; Variation in hospital functionality over time | Formative |
Miniati and Iasio, 2012 [58] | The theory of complex systems analysis with the use of an input–output inoperability (Leontief) model and a rapid seismic vulnerability assessment with the field data collection using the WHO evaluation forms | Earthquakes | During-shock | Description of the hospital response evaluation with a focus on capacity to cope during an earthquake disaster based on different scenarios | Formative, diagnostic |
Mulyasari et al. 2013 [59] | Questionnaire based on the WHO Hospital Safety Index (HSI) and the assessment of vulnerability elements at hospitals | Earthquakes | Pre-shock | Description of responses of the hospitals concerning the different preparedness indicators and past disaster experiences | Formative, diagnostic |
Yavari et al. 2010 [60] | Predictive model for estimating the post-disaster ability to provide services | Earthquakes | Post-shock | A practical model for estimating the functionality of hospitals after an earthquake | Formative |
Paterson et al. 2014 [61] | A climate change resiliency assessment toolkit (checklist, a facilitator’s guide for administering the checklist, and a resource guidebook to inform adaptation) | Climate change impact (extreme weather events) | Pre-shock | The degree to which healthcare facility is resilient to current climate variability and future climate change based upon included indicators | Formative, diagnostic |
Ten Eyck, 2008 [62] | Standardized data form evaluating surge response plans The surge in demand was calculated using the FluAid and FluSurge tools | Hospital surge capacity as a result of avian flu pandemic | Pre- and during-shock | Cumulative surge capacity for the region Percentages and frequencies for each of the six categories of resources | Formative |
Sharma and Sharma 2020 [63] | A semi-structured online questionnaire and available published and unpublished data for situation analysis | Pandemics (Covid-19 pandemic) | Pre-shock | Percentages and frequencies describing preparedness level of hospitals for each question or area of the questionnaire | Formative, diagnostic |
Prateepko and Chongsuvivatwong, 2012 [64] | A checklist for health care facilities based on the WHO checklist for influenza pandemic preparedness planning, the preparedness checklist for long-term care facilities, other international infection control and preparedness checklists | Influenza pandemic | Pre-shock | Description of responses of the healthcare facilities concerning the different preparedness areas | Formative, diagnostic |
Dewar et al. 2014 [65] | Questionnaire and semi-structured interviews | Pandemic influenza | Pre-shock | Percentages and frequencies describing preparedness level of hospitals and common themes emerging from interviews | Formative |
Ambat and Vyas, 2020 [66] | Semi-structured questionnaire | Emerging infectious disease | Pre-shock | Percentages and frequencies describing preparedness level of hospitals | Formative |
Gilson et al. 2017Â [67] | Document reviews, in-depth interviews, group discussions and observations | Routine challenges | Pre-, during- and post-challenge | Qualitative description of different types of strategies and organizational capacities in nurturing everyday resilience | Formative, summative and diagnostic |
Gilson et al. 2020 [68] | Observations, in-depth interviews, analysis of meeting minutes and secondary data Analysis of data based on the everyday health system resilience (EHSR) framework | Chronic stress of large-scale organizational change | Pre-, during- and post-challenge | Qualitative description of different types of strategies and organizational capacities in nurturing everyday resilience | Formative, summative and diagnostic |
Kagwanja et al. 2020 [69] | Observations, reflective meetings and in-depth interviews with middle-level managers and peripheral facility managers Data were analysed considering each element of the everyday health system resilience (EHSR) framework | Chronic stressors | Pre-, during-and post-challenge | Qualitative description of different types of absorptive, adaptive and transformative strategies and organizational capacities in nurturing everyday resilience adopted | Formative, summative and diagnostic |
Crowe et al. 2014 [70] | A model and prototype software tool | Disruptions due to service reconfigurations | During-and after challenge | Model of the impact of different patterns of disruption to healthcare resources and infrastructure on health services | Formative |
Davis et al. 2020 [71] | Modelling framework | Hospital overcrowding | During-shock | Model quantifying the impact of each contributing component on hospitals | Formative |