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Validation of a framework for measuring hospital disaster resilience using factor analysis.

ABSTRACT: Hospital disaster resilience can be defined as "the ability of hospitals to resist, absorb, and respond to the shock of disasters while maintaining and surging essential health services, and then to recover to its original state or adapt to a new one." This article aims to provide a framework which can be used to comprehensively measure hospital disaster resilience. An evaluation framework for assessing hospital resilience was initially proposed through a systematic literature review and Modified-Delphi consultation. Eight key domains were identified: hospital safety, command, communication and cooperation system, disaster plan, resource stockpile, staff capability, disaster training and drills, emergency services and surge capability, and recovery and adaptation. The data for this study were collected from 41 tertiary hospitals in Shandong Province in China, using a specially designed questionnaire. Factor analysis was conducted to determine the underpinning structure of the framework. It identified a four-factor structure of hospital resilience, namely, emergency medical response capability (F1), disaster management mechanisms (F2), hospital infrastructural safety (F3), and disaster resources (F4). These factors displayed good internal consistency. The overall level of hospital disaster resilience (F) was calculated using the scoring model: F = 0.615F1 + 0.202F2 + 0.103F3 + 0.080F4. This validated framework provides a new way to operationalise the concept of hospital resilience, and it is also a foundation for the further development of the measurement instrument in future studies.

SUBMITTER: Zhong S

PROVIDER: S-EPMC4078582 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature

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Validation of a framework for measuring hospital disaster resilience using factor analysis.

Zhong Shuang S Clark Michele M Hou Xiang-Yu XY Zang Yuli Y FitzGerald Gerard G

International journal of environmental research and public health 20140618 6

Hospital disaster resilience can be defined as "the ability of hospitals to resist, absorb, and respond to the shock of disasters while maintaining and surging essential health services, and then to recover to its original state or adapt to a new one." This article aims to provide a framework which can be used to comprehensively measure hospital disaster resilience. An evaluation framework for assessing hospital resilience was initially proposed through a systematic literature review and Modifie ...[more]

PMID: 24945190

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Project description:Disasters are a recurring fact of life, and major incidents can have both immediate and long-lasting negative effects on the health and well-being of people, communities, and economies. A primary goal of many disaster preparedness, response, and recovery plans is to reduce the likelihood and severity of disaster impacts through increased resilience of individuals and communities. Unfortunately, most plans do not address directly major drivers of long-term disaster impacts on humans-that is, acute, chronic, and cumulative stress-and therefore do less to enhance resilience than they could. Stress has been shown to lead to or exacerbate ailments ranging from mental illness, domestic violence, substance abuse, post-traumatic stress disorders, and suicide to cardiovascular disease, respiratory problems, and other infirmities. Individuals, groups, communities, organizations, and social ties are all vulnerable to stress. Based on a targeted review of what we considered to be key literature about disasters, resilience, and disaster-associated stress effects, we recommend eight actions to improve resiliency through inclusion of stress alleviation in disaster planning: (1) Improve existing disaster behavioral and physical health programs to better address, leverage, and coordinate resources for stress reduction, relief, and treatment in disaster planning and response. (2) Emphasize pre- and post-disaster collection of relevant biomarker and other health-related data to provide a baseline of health status against which disaster impacts could be assessed, and continued monitoring of these indicators to evaluate recovery. (3) Enhance capacity of science and public health early-responders. (4) Use natural infrastructure to minimize disaster damage. (5) Expand the geography of disaster response and relief to better incorporate the displacement of affected people. (6) Utilize nature-based treatment to alleviate pre- and post-disaster stress effects on health. (7) Review disaster laws, policies, and regulations to identify opportunities to strengthen public health preparedness and responses including for stress-related impacts, better engage affected communities, and enhance provision of health services. (8) With community participation, develop and institute equitable processes pre-disaster for dealing with damage assessments, litigation, payments, and housing.

Project description:BackgroundThe exposure of people and infrastructure to flood and storm related disasters across the world is increasing faster than vulnerability is decreasing. For people with non-communicable diseases this presents a significant risk as traditionally the focus of disaster management systems has been on immediate trauma and communicable diseases. This focus must now be expanded to include the management of non-communicable diseases because these conditions are generating the bulk of ill health, disability and premature death around the globe. When public health service infrastructure is destroyed or damaged access to treatment and care is severely jeopardised, resulting in an increased risk of non-communicable disease exacerbation or even death. This research proposes disaster responders, coordinators and government officials are vital assets to mitigate and eventually prevent these problems from being exacerbated during a disaster. This is due to their role in supporting the public health service infrastructure required to maximise treatment and care for people with non-communicable diseases. By focusing on the disaster cycle as a template, and on mitigation and prevention phases in particular, these actions and activities performed by disaster service responders will lead to overall improved preparedness, response, recovery and rehabilitation phases.MethodsData were collected via 32 interviews and one focus group (eight participants) between March 2014 and August 2015 (total of 40 participants). The research was conducted in the State of Queensland, Australia, with disaster service providers. The analysis included the phases of: organizing data; data description; data classification; and interpretation.ResultsThe research found a relationship between the impact of a disaster on public health service infrastructure, and increased health risks for people with non-communicable diseases. Mitigation strategies were described for all phases of the disaster cycle impacting public health service infrastructure. Specific measures include: increasing the use of telemedicine; preplanning with medical suppliers; effective town planning; health professionals visiting evacuation centers; evacuation centers having power for medical equipment; hubs for treatment and care after a disaster; evacuation of high risk people prior to disaster; mapping people at risk by non-communicable disease; and a mechanism for sharing information between agencies. A common theme from the participants was that having accurate and easily accessible data on people with non-communicable diseases would allow disaster service providers to adequately prepare for and respond to a disaster.ConclusionsDisaster service providers can play a vital role in reducing the risk of disaster exacerbated non-communicable diseases through public health service infrastructure resilience. They are often employed in communities where disasters occur and are therefore best-placed to lead implementation of the mitigation strategies identified in this research. To sustainably implement the mitigation strategies they will need to become integrated into effective performance and monitoring of the disaster response and health sector during non-disaster periods. For this to occur, the strategies should be integrated into business and strategic plans. Achieving this will help implement the Sendia Framework for Disaster Risk Reduction 2015-2030 and, most importantly, help protect the health of people with non-communicable diseases before, during and after a disaster.

Project description:BackgroundThe performance of routine and supplemental immunization activities is usually measured by the administrative method: dividing the number of doses distributed by the size of the target population. This method leads to coverage estimates that are sometimes impossible (e.g., vaccination of 102% of the target population), and are generally inconsistent with the proportion found to be vaccinated in Demographic and Health Surveys (DHS). We describe a method that estimates the fraction of the population accessible to vaccination activities, as well as within-campaign inefficiencies, thus providing a consistent estimate of vaccination coverage.Methods and findingsWe developed a likelihood framework for estimating the effective coverage of vaccination programs using cross-sectional surveys of vaccine coverage combined with administrative data. We applied our method to measles vaccination in three African countries: Ghana, Madagascar, and Sierra Leone, using data from each country's most recent DHS survey and administrative coverage data reported to the World Health Organization. We estimate that 93% (95% CI: 91, 94) of the population in Ghana was ever covered by any measles vaccination activity, 77% (95% CI: 78, 81) in Madagascar, and 69% (95% CI: 67, 70) in Sierra Leone. "Within-activity" inefficiencies were estimated to be low in Ghana, and higher in Sierra Leone and Madagascar. Our model successfully fits age-specific vaccination coverage levels seen in DHS data, which differ markedly from those predicted by naïve extrapolation from country-reported and World Health Organization-adjusted vaccination coverage.ConclusionsCombining administrative data with survey data substantially improves estimates of vaccination coverage. Estimates of the inefficiency of past vaccination activities and the proportion not covered by any activity allow us to more accurately predict the results of future activities and provide insight into the ways in which vaccination programs are failing to meet their goals. Please see later in the article for the Editors' Summary.

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Validation of a framework for measuring hospital disaster resilience using factor analysis.

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Validation of a framework for measuring hospital disaster resilience using factor analysis.

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