31,771 research outputs found
Controlling nosocomial infection based on structure of hospital social networks
Nosocomial infection raises a serious public health problem, as implied by
the existence of pathogens characteristic to healthcare and hospital-mediated
outbreaks of influenza and SARS. We simulate stochastic SIR dynamics on social
networks, which are based on observations in a hospital in Tokyo, to explore
effective containment strategies against nosocomial infection. The observed
networks have hierarchical and modular structure. We show that healthcare
workers, particularly medical doctors, are main vectors of diseases on these
networks. Intervention methods that restrict interaction between medical
doctors and their visits to different wards shrink the final epidemic size more
than intervention methods that directly protect patients, such as isolating
patients in single rooms. By the same token, vaccinating doctors with priority
rather than patients or nurses is more effective. Finally, vaccinating
individuals with large betweenness centrality is superior to vaccinating ones
with large connectedness to others or randomly chosen individuals, as suggested
by previous model studies. [The abstract of the manuscript has more
information.]Comment: 12 figures, 2 table
Wearable proximity sensors for monitoring a mass casualty incident exercise: a feasibility study
Over the past several decades, naturally occurring and man-made mass casualty
incidents (MCI) have increased in frequency and number, worldwide. To test the
impact of such event on medical resources, simulations can provide a safe,
controlled setting while replicating the chaotic environment typical of an
actual disaster. A standardised method to collect and analyse data from mass
casualty exercises is needed, in order to assess preparedness and performance
of the healthcare staff involved. We report on the use of wearable proximity
sensors to measure proximity events during a MCI simulation. We investigated
the interactions between medical staff and patients, to evaluate the time
dedicated by the medical staff with respect to the severity of the injury of
the victims depending on the roles. We estimated the presence of the patients
in the different spaces of the field hospital, in order to study the patients'
flow. Data were obtained and collected through the deployment of wearable
proximity sensors during a mass casualty incident functional exercise. The
scenario included two areas: the accident site and the Advanced Medical Post
(AMP), and the exercise lasted 3 hours. A total of 238 participants simulating
medical staff and victims were involved. Each participant wore a proximity
sensor and 30 fixed devices were placed in the field hospital. The contact
networks show a heterogeneous distribution of the cumulative time spent in
proximity by participants. We obtained contact matrices based on cumulative
time spent in proximity between victims and the rescuers. Our results showed
that the time spent in proximity by the healthcare teams with the victims is
related to the severity of the patient's injury. The analysis of patients' flow
showed that the presence of patients in the rooms of the hospital is consistent
with triage code and diagnosis, and no obvious bottlenecks were found
Approach to Assessing the Preparedness of Hospitals to Power Outages
Within the secondary impacts of electricity blackouts, it is necessary to pay attention
to facilities providing medical care for the population, namely the hospitals. Hospitals
represent a key position in the provision of health care also in times of crisis. These
facilities must provide constant care; it is therefore essential that the preparedness of such
facilities is kept at a high level. The basic aim of this article is to analyse the preparedness
of hospitals to power outages (power failures, blackouts) within a pilot study. On that
basis, a SWOT analysis is used to determine strengths and weaknesses of the system of
preparedness of hospitals to power outages and solutions for better security of hospitals
are defined. The sample investigated consists of four hospitals founded by the Regional
Authority (hospitals Nos. 1-4) and one hospital founded by the Ministry of Health of the
Czech Republic (hospital No. 5). The results of the study shows that most weaknesses of
the preparedness of hospitals are represented by inadequately addressed reserves of fuel
for the main backup power supply, poor knowledge of employees who are insufficiently
retrained, and old backup power supplies (even 35 years in some cases)
Estimating Potential Infection Transmission Routes in Hospital Wards Using Wearable Proximity Sensors
Contacts between patients, patients and health care workers (HCWs) and among
HCWs represent one of the important routes of transmission of hospital-acquired
infections (HAI). A detailed description and quantification of contacts in
hospitals provides key information for HAIs epidemiology and for the design and
validation of control measures. We used wearable sensors to detect close-range
interactions ("contacts") between individuals in the geriatric unit of a
university hospital. Contact events were measured with a spatial resolution of
about 1.5 meters and a temporal resolution of 20 seconds. The study included 46
HCWs and 29 patients and lasted for 4 days and 4 nights. 14037 contacts were
recorded. The number and duration of contacts varied between mornings,
afternoons and nights, and contact matrices describing the mixing patterns
between HCW and patients were built for each time period. Contact patterns were
qualitatively similar from one day to the next. 38% of the contacts occurred
between pairs of HCWs and 6 HCWs accounted for 42% of all the contacts
including at least one patient, suggesting a population of individuals who
could potentially act as super-spreaders. Wearable sensors represent a novel
tool for the measurement of contact patterns in hospitals. The collected data
provides information on important aspects that impact the spreading patterns of
infectious diseases, such as the strong heterogeneity of contact numbers and
durations across individuals, the variability in the number of contacts during
a day, and the fraction of repeated contacts across days. This variability is
associated with a marked statistical stability of contact and mixing patterns
across days. Our results highlight the need for such measurement efforts in
order to correctly inform mathematical models of HAIs and use them to inform
the design and evaluation of prevention strategies
Ambulance Emergency Response Optimization in Developing Countries
The lack of emergency medical transportation is viewed as the main barrier to
the access of emergency medical care in low and middle-income countries
(LMICs). In this paper, we present a robust optimization approach to optimize
both the location and routing of emergency response vehicles, accounting for
uncertainty in travel times and spatial demand characteristic of LMICs. We
traveled to Dhaka, Bangladesh, the sixth largest and third most densely
populated city in the world, to conduct field research resulting in the
collection of two unique datasets that inform our approach. This data is
leveraged to develop machine learning methodologies to estimate demand for
emergency medical services in a LMIC setting and to predict the travel time
between any two locations in the road network for different times of day and
days of the week. We combine our robust optimization and machine learning
frameworks with real data to provide an in-depth investigation into three
policy-related questions. First, we demonstrate that outpost locations
optimized for weekday rush hour lead to good performance for all times of day
and days of the week. Second, we find that significant improvements in
emergency response times can be achieved by re-locating a small number of
outposts and that the performance of the current system could be replicated
using only 30% of the resources. Lastly, we show that a fleet of small
motorcycle-based ambulances has the potential to significantly outperform
traditional ambulance vans. In particular, they are able to capture three times
more demand while reducing the median response time by 42% due to increased
routing flexibility offered by nimble vehicles on a larger road network. Our
results provide practical insights for emergency response optimization that can
be leveraged by hospital-based and private ambulance providers in Dhaka and
other urban centers in LMICs
The Relationship between Therapeutic Alliance and Service User Satisfaction in Mental Health Inpatient Wards and Crisis House Alternatives: A Cross-Sectional Study
Background
Poor service user experiences are often reported on mental health inpatient wards. Crisis houses are an alternative, but evidence is limited. This paper investigates therapeutic alliances in acute wards and crisis houses, exploring how far stronger therapeutic alliance may underlie greater client satisfaction in crisis houses.
Methods and Findings
Mixed methods were used. In the quantitative component, 108 crisis house and 247 acute ward service users responded to measures of satisfaction, therapeutic relationships, informal peer support, recovery and negative events experienced during the admission. Linear regressions were conducted to estimate the association between service setting and measures, and to model the factors associated with satisfaction. Qualitative interviews exploring therapeutic alliances were conducted with service users and staff in each setting and analysed thematically.
Results
We found that therapeutic alliances, service user satisfaction and informal peer support were greater in crisis houses than on acute wards, whilst self-rated recovery and numbers of negative events were lower. Adjusted multivariable analyses suggest that therapeutic relationships, informal peer support and negative experiences related to staff may be important factors in accounting for greater satisfaction in crisis houses. Qualitative results suggest factors that influence therapeutic alliances include service user perceptions of basic human qualities such as kindness and empathy in staff and, at service level, the extent of loss of liberty and autonomy.
Conclusions and Implications
We found that service users experience better therapeutic relationships and higher satisfaction in crisis houses compared to acute wards, although we cannot exclude the possibility that differences in service user characteristics contribute to this. This finding provides some support for the expansion of crisis house provision. Further research is needed to investigate why acute ward service users experience a lack of compassion and humanity from ward staff and how this could be changed
CAMMD: Context Aware Mobile Medical Devices
Telemedicine applications on a medical practitioners mobile device should be context-aware. This can vastly improve the effectiveness of mobile applications and is a step towards realising the vision of a ubiquitous telemedicine environment. The nomadic nature of a medical practitioner emphasises location, activity and time as key context-aware elements. An intelligent middleware is needed to effectively interpret and exploit these contextual elements. This paper proposes an agent-based architectural solution called Context-Aware Mobile Medical Devices (CAMMD). This framework can proactively communicate patient records to a portable device based upon the active context of its medical practitioner. An expert system is utilised to cross-reference the context-aware data of location and time against a practitioners work schedule. This proactive distribution of medical data enhances the usability and portability of mobile medical devices. The proposed methodology alleviates constraints on memory storage and enhances user interaction with the handheld device. The framework also improves utilisation of network bandwidth resources. An experimental prototype is presented highlighting the potential of this approach
The Potential Trajectory of Carbapenem-Resistant Enterobacteriaceae, an Emerging Threat to Health-Care Facilities, and the Impact of the Centers for Disease Control and Prevention Toolkit.
Carbapenem-resistant Enterobacteriaceae (CRE), a group of pathogens resistant to most antibiotics and associated with high mortality, are a rising emerging public health threat. Current approaches to infection control and prevention have not been adequate to prevent spread. An important but unproven approach is to have hospitals in a region coordinate surveillance and infection control measures. Using our Regional Healthcare Ecosystem Analyst (RHEA) simulation model and detailed Orange County, California, patient-level data on adult inpatient hospital and nursing home admissions (2011-2012), we simulated the spread of CRE throughout Orange County health-care facilities under 3 scenarios: no specific control measures, facility-level infection control efforts (uncoordinated control measures), and a coordinated regional effort. Aggressive uncoordinated and coordinated approaches were highly similar, averting 2,976 and 2,789 CRE transmission events, respectively (72.2% and 77.0% of transmission events), by year 5. With moderate control measures, coordinated regional control resulted in 21.3% more averted cases (n = 408) than did uncoordinated control at year 5. Our model suggests that without increased infection control approaches, CRE would become endemic in nearly all Orange County health-care facilities within 10 years. While implementing the interventions in the Centers for Disease Control and Prevention's CRE toolkit would not completely stop the spread of CRE, it would cut its spread substantially, by half
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