Hospital triage system for adult patients using an influenza-like illness scoring system during the 2009 pandemic--Mexico

Emergency Triage of Highly Infectious Diseases and Bioterrorism

Emergency medical services are a key element in health systems for the evaluation and treatment of patients exposed to highly infectious diseases or bioterrorism agents. Triage and early identification at any point of care can have a significant impact on the prevention and management of these diseases. This chapter reviews triage practices, including early isolation and decontamination, of highly infectious diseases and bioterrorism agents at different health system levels.

Using machine-learning methods to support health-care professionals in making admission decisions

BACKGROUND

Large tertiary hospitals usually face long waiting lines; patients who want to receive hospitalization need to be screened in advance. The patient admission screening process involves a health-care professional ranking patients by analyzing registration information.

OBJECTIVE

The purpose of this study was to develop a machine-learning approach to screening, using historical data and the experience of health-care professionals to develop a set of screening rules to help health-care professionals prioritize patient needs automatically.

METHODS

We used five machine-learning methods to sequence and predict elective patients: logistic regression (LR), random forest (RF), gradient-boosting decision tree (GBDT), extreme gradient boosting (XGBoost), and an ensemble model of the four models.

RESULTS

The results indicate that all of the five models showed a good prioritization performance with high predictive values. In particular, XGBoost had the best predictive performance compared with others in terms of the area under the receiver operating characteristic curve (AUC), with the AUC values of LR, RF, GBDT, XGBoost, and the ensemble model being 0.881, 0.816, 0.820, 0.901, and 0.897, respectively.

CONCLUSION

The results reported here indicate that machine-learning techniques can be valuable for automating the screening process. Our model can assist health-care professionals in automatically evaluating less complex cases by identifying important factors affecting patient admission.

The Utility of Preliminary Patient Evaluation in a Febrile Respiratory Infectious Disease Unit outside the Emergency Department

A febrile respiratory infectious disease unit (FRIDU) with a negative pressure ventilation system was constructed outside the emergency department (ED) of the Samsung Medical Center in 2015, to screen for patients with contagious diseases requiring isolation. We evaluated the utility of the FRIDU during 1 year of operation. We analyzed 1,562 patients who were hospitalized after FRIDU screening between August 2015 and July 2016. The level of isolation recommended during their screening at the FRIDU was compared with the level deemed appropriate given their final diagnosis. Of the 1,562 patients screened at the FRIDU, 198 (13%) were isolated, 194 (12%) were reverse isolated, and 1,170 (75%) were not isolated. While hospitalized, 97 patients (6%) were confirmed to have a contagious disease requiring isolation, such as tuberculosis; 207 patients (13%) were confirmed to be immunocompromised and to require reverse isolation, mainly due to neutropenia; and the remaining 1,258 patients (81%) did not require isolation. The correlation coefficient for isolation consistency was 0.565 (P < 0.001). The sensitivity and negative predictive value of FRIDU screening for diagnosing contagious disease requiring isolation are 76% and 98%, respectively. No serious nosocomial outbreaks of contagious diseases occurred. During FRIDU screening, 114 patients were admitted to the resuscitation zone due to clinical instability, and three of these patients died. The initial isolation levels resulting from FRIDU screening were moderately well correlated with the isolation levels required by the final diagnosis, demonstrating the utility of pre-hospitalization screening units. However, the risks of deterioration during the screening process remain challenges.

The presence of fever in adults with influenza and other viral respiratory infections

We compared the rates of fever in adult subjects with laboratory-confirmed influenza and other respiratory viruses and examined the factors that predict fever in adults. Symptom data on 158 healthcare workers (HCWs) with a laboratory-confirmed respiratory virus infection were collected using standardized data collection forms from three separate studies. Overall, the rate of fever in confirmed viral respiratory infections in adult HCWs was 23·4% (37/158). Rates varied by virus: human rhinovirus (25·3%, 19/75), influenza A virus (30%, 3/10), coronavirus (28·6%, 2/7), human metapneumovirus (28·6%, 2/7), respiratory syncytial virus (14·3%, 4/28) and parainfluenza virus (8·3%, 1/12). Smoking [relative risk (RR) 4·65, 95% confidence interval (CI) 1·33-16·25] and co-infection with two or more viruses (RR 4·19, 95% CI 1·21-14·52) were significant predictors of fever. Fever is less common in adults with confirmed viral respiratory infections, including influenza, than described in children. More than 75% of adults with a viral respiratory infection do not have fever, which is an important finding for clinical triage of adult patients with respiratory infections. The accepted definition of 'influenza-like illness' includes fever and may be insensitive for surveillance when high case-finding is required. A more sensitive case definition could be used to identify adult cases, particularly in event of an emerging viral infection.

Surge capacity principles: care of the critically ill and injured during pandemics and disasters: CHEST consensus statement

BACKGROUND

This article provides consensus suggestions for expanding critical care surge capacity and extension of critical care service capabilities in disasters or pandemics. It focuses on the principles and frameworks for expansion of intensive care services in hospitals in the developed world. A companion article addresses surge logistics, those elements that provide the capability to deliver mass critical care in disaster events. The suggestions in this article are important for all who are involved in large-scale disasters or pandemics with injured or critically ill multiple patients, including front-line clinicians, hospital administrators, and public health or government officials.

METHODS

The Surge Capacity topic panel developed 23 key questions focused on the following domains: systems issues; equipment, supplies, and pharmaceuticals; staffing; and informatics. Literature searches were conducted to identify evidence on which to base key suggestions. Most reports were small scale, were observational, or used flawed modeling; hence, the level of evidence on which to base recommendations was poor and did not permit the development of evidence-based recommendations. Therefore, the panel developed expert opinion-based suggestions using a modified Delphi process. Suggestions from the previous task force were also included for validation by the expert panel.

RESULTS

This article presents 10 suggestions pertaining to the principles that should guide surge capacity and capability planning for mass critical care, including the role of critical care in disaster planning; the surge continuum; targets of surge response; situational awareness and information sharing; mitigating the impact on critical care; planning for the care of special populations; and service deescalation/cessation (also considered as engineered failure).

CONCLUSIONS

Future reports on critical care surge should emphasize population-based outcomes as well as logistical details. Planning should be based on the projected number of critically ill or injured patients resulting from specific scenarios. This should include a consideration of ICU patient care requirements over time and must factor in resource constraints that may limit the ability to provide care. Standard ICU management forms and patient data forms to assess ICU surge capacity impacts should be created and used in disaster events.

Introduction and executive summary: care of the critically ill and injured during pandemics and disasters: CHEST consensus statement

Natural disasters, industrial accidents, terrorism attacks, and pandemics all have the capacity to result in large numbers of critically ill or injured patients. This supplement provides suggestions for all of those involved in a disaster or pandemic with multiple critically ill patients, including front-line clinicians, hospital administrators, professional societies, and public health or government officials. The current Task Force included a total of 100 participants from nine countries, comprised of clinicians and experts from a wide variety of disciplines. Comprehensive literature searches were conducted to identify studies upon which evidence-based recommendations could be made. No studies of sufficient quality were identified. Therefore, the panel developed expert-opinion-based suggestions that are presented in this supplement using a modified Delphi process. The ultimate aim of the supplement is to expand the focus beyond the walls of ICUs to provide recommendations for the management of all critically ill or injured adults and children resulting from a pandemic or disaster wherever that care may be provided. Considerations for the management of critically ill patients include clinical priorities and logistics (supplies, evacuation, and triage) as well as the key enablers (systems planning, business continuity, legal framework, and ethical considerations) that facilitate the provision of this care. The supplement also aims to illustrate how the concepts of mass critical care are integrated across the spectrum of surge events from conventional through contingency to crisis standards of care.

Antiviral strategies for emerging influenza viruses in remote communities

BACKGROUND

Due to the lack of timely access to resources for critical care, strategic use of antiviral drugs is crucial for mitigating the impact of novel influenza viruses with pandemic potential in remote and isolated communities. We sought to evaluate the effect of antiviral treatment and prophylaxis of close contacts in a Canadian remote northern community.

METHODS

We used an agent-based, discrete-time simulation model for disease spread in a remote community, which was developed as an in-silico population using population census data. Relative and cumulative age-specific attack rates, and the total number of infections in simulated model scenarios were obtained.

RESULTS

We found that early initiation of antiviral treatment is more critical for lowering attack rates in a remote setting with a low population-average age compared to an urban population. Our results show that a significant reduction in the relative, age-specific attack rates due to increasing treatment coverage does not necessarily translate to a significant reduction in the overall arrack rate. When treatment coverage varies from low to moderate, targeted prophylaxis has a very limited impact in reducing attack rates and should be offered at a low level (below 10%) to avoid excessive waste of drugs.

CONCLUSIONS

In contrast to previous work, for conservative treatment coverages, our results do not provide any convincing evidence for the implementation of targeted prophylaxis. The findings suggest that public health strategies in remote communities should focus on the wider availability (higher coverage) and timely distribution of antiviral drugs for treatment of clinically ill individuals.

Systematic review of strategies to manage and allocate scarce resources during mass casualty events

STUDY OBJECTIVE

Efficient management and allocation of scarce medical resources can improve outcomes for victims of mass casualty events. However, the effectiveness of specific strategies has never been systematically reviewed. We analyze published evidence on strategies to optimize the management and allocation of scarce resources across a wide range of mass casualty event contexts and study designs.

METHODS

Our literature search included MEDLINE, Scopus, EMBASE, Cumulative Index to Nursing and Allied Health Literature, Global Health, Web of Science, and the Cochrane Database of Systematic Reviews, from 1990 through late 2011. We also searched the gray literature, using the New York Academy of Medicine's Grey Literature Report and key Web sites. We included both English- and foreign-language articles. We included studies that evaluated strategies used in actual mass casualty events or tested through drills, exercises, or computer simulations. We excluded studies that lacked a comparison group or did not report quantitative outcomes. Data extraction, quality assessment, and strength of evidence ratings were conducted by a single researcher and reviewed by a second; discrepancies were reconciled by the 2 reviewers. Because of heterogeneity in outcome measures, we qualitatively synthesized findings within categories of strategies.

RESULTS

From 5,716 potentially relevant citations, 74 studies met inclusion criteria. Strategies included reducing demand for health care services (18 studies), optimizing use of existing resources (50), augmenting existing resources (5), implementing crisis standards of care (5), and multiple categories (4). The evidence was sufficient to form conclusions on 2 strategies, although the strength of evidence was rated as low. First, as a strategy to reduce demand for health care services, points of dispensing can be used to efficiently distribute biological countermeasures after a bioterrorism attack or influenza pandemic, and their organization influences speed of distribution. Second, as a strategy to optimize use of existing resources, commonly used field triage systems do not perform consistently during actual mass casualty events. The number of high-quality studies addressing other strategies was insufficient to support conclusions about their effectiveness because of differences in study context, comparison groups, and outcome measures. Our literature search may have missed key resource management and allocation strategies because of their extreme heterogeneity. Interrater reliability was not assessed for quality assessments or strength of evidence ratings. Publication bias is likely, given the large number of studies reporting positive findings.

CONCLUSION

The current evidence base is inadequate to inform providers and policymakers about the most effective strategies for managing or allocating scarce resources during mass casualty events. Consensus on methodological standards that encompass a range of study designs is needed to guide future research and strengthen the evidence base. Evidentiary standards should be developed to promote consensus interpretations of the evidence supporting individual strategies.

Diagnosing swine flu: the inaccuracy of case definitions during the 2009 pandemic, an attempt at refinement, and the implications for future planning

Background  At the onset of the pandemic H1N1/09 influenza A outbreak in Australia, health authorities devised official clinical case definitions to guide testing and access to antiviral therapy.

Objectives  To assess the diagnostic accuracy of these case definitions and to attempt to improve on them using a scoring system based on clinical findings at presentation.

Patients/Methods  This study is a retrospective case–control study across three metropolitan Melbourne hospitals and one associated community‐based clinic during the influenza season, 2009. Patients presenting with influenza‐like illness who were tested for H1N1/09 influenza A were administered a standard questionnaire of symptomatology, comorbidities, and risk factors. Patients with a positive test were compared to those with a negative test. Logistic regression was performed to examine for correlation of clinical features with disease. A scoring system was devised and compared with case definitions used during the pandemic. The main outcome measures were the positive and negative predictive values of our scoring system, based on real‐life data, versus the mandated case definitions’.

Results  Both the devised scoring system and the case definitions gave similar positive predictive values (38–58% using ascending score groups, against 39–44% using the various case definitions). Negative predictive values were also closely matched (ranging from 94% to 73% in the respective score groups against 83–84% for the case definitions).

Conclusions  Accurate clinical diagnosis of H1N1/09 influenza A was difficult and not improved significantly by a structured scoring system. Investment in more widespread availability of rapid and sensitive diagnostic tests should be considered in future pandemic planning.

Early detection of pandemic (H1N1) 2009, Bangladesh

To explore Bangladesh’s ability to detect novel influenza, we examined a series of laboratory-confirmed pandemic (H1N1) 2009 cases. During June–July 2009, event-based surveillance identified 30 case-patients (57% travelers); starting July 29, sentinel sites identified 252 case-patients (1% travelers). Surveillance facilitated response weeks before the spread of pandemic (H1N1) 2009 infection to the general population.

An analysis of 332 fatalities infected with pandemic 2009 influenza A (H1N1) in Argentina

BACKGROUND

The apparent high number of deaths in Argentina during the 2009 pandemic led to concern that the influenza A H1N1pdm disease was different there. We report the characteristics and risk factors for influenza A H1N1pdm fatalities.

METHODS

We identified laboratory-confirmed influenza A H1N1pdm fatalities occurring during June-July 2009. Physicians abstracted data on age, sex, time of onset of illness, medical history, clinical presentation at admission, laboratory, treatment, and outcomes using standardize questionnaires. We explored the characteristics of fatalities according to their age and risk group.

RESULTS

Of 332 influenza A H1N1pdm fatalities, 226 (68%) were among persons aged <50 years. Acute respiratory failure was the leading cause of death. Of all cases, 249 (75%) had at least one comorbidity as defined by Advisory Committee on Immunization Practices. Obesity was reported in 32% with data and chronic pulmonary disease in 28%. Among the 40 deaths in children aged <5 years, chronic pulmonary disease (42%) and neonatal pathologies (35%) were the most common co-morbidities. Twenty (6%) fatalities were among pregnant or postpartum women of which only 47% had diagnosed co-morbidities. Only 13% of patients received antiviral treatment within 48 hours of symptom onset. None of children aged <5 years or the pregnant women received antivirals within 48 h of symptom onset. As the pandemic progressed, the time from symptom-onset to medical care and to antiviral treatment decreased significantly among case-patients who subsequently died (p<0.001).

CONCLUSION

Persons with co-morbidities, pregnant and who received antivirals late were over-represented among influenza A H1N1pdm deaths in Argentina, though timeliness of antiviral treatment improved during the pandemic.

Infection control management of patients with suspected highly infectious diseases in emergency departments: data from a survey in 41 facilities in 14 European countries

BACKGROUND

In Emergency and Medical Admission Departments (EDs and MADs), prompt recognition and appropriate infection control management of patients with Highly Infectious Diseases (HIDs, e.g. Viral Hemorrhagic Fevers and SARS) are fundamental for avoiding nosocomial outbreaks.

METHODS

The EuroNHID (European Network for Highly Infectious Diseases) project collected data from 41 EDs and MADs in 14 European countries, located in the same facility as a national/regional referral centre for HIDs, using specifically developed checklists, during on-site visits from February to November 2009.

RESULTS

Isolation rooms were available in 34 facilities (82,9%): these rooms had anteroom in 19, dedicated entrance in 15, negative pressure in 17, and HEPA filtration of exhausting air in 12. Only 6 centres (14,6%) had isolation rooms with all characteristics. Personnel trained for the recognition of HIDs was available in 24 facilities; management protocols for HIDs were available in 35.

CONCLUSIONS

Preparedness level for the safe and appropriate management of HIDs is partially adequate in the surveyed EDs and MADs.

Google Flu Trends: correlation with emergency department influenza rates and crowding metrics

BACKGROUND

 Google Flu Trends (GFT) is a novel Internet-based influenza surveillance system that uses search engine query data to estimate influenza activity and is available in near real time. This study assesses the temporal correlation of city GFT data to cases of influenza and standard crowding indices from an inner-city emergency department (ED).

METHODS

 This study was performed during a 21-month period (from January 2009 through October 2010) at an urban academic hospital with physically and administratively separate adult and pediatric EDs. We collected weekly data from GFT for Baltimore, Maryland; ED Centers for Disease Control and Prevention-reported standardized influenzalike illness (ILI) data; laboratory-confirmed influenza data; and ED crowding indices (patient volume, number of patients who left without being seen, waiting room time, and length of stay for admitted and discharged patients). Pediatric and adult data were analyzed separately using cross-correlation with GFT.

RESULTS

 GFT correlated with both number of positive influenza test results (adult ED, r = 0.876; pediatric ED, r = 0.718) and number of ED patients presenting with ILI (adult ED, r = 0.885; pediatric ED, r = 0.652). Pediatric but not adult crowding measures, such as total ED volume (r = 0.649) and leaving without being seen (r = 0.641), also had good correlation with GFT. Adult crowding measures for low-acuity patients, such as waiting room time (r = 0.421) and length of stay for discharged patients (r = 0.548), had moderate correlation with GFT.

CONCLUSIONS

 City-level GFT shows strong correlation with influenza cases and ED ILI visits, validating its use as an ED surveillance tool. GFT correlated with several pediatric ED crowding measures and those for low-acuity adult patients.

Etiology and clinical characteristics of influenza-like illness (ILI) in outpatients in Beijing, June 2010 to May 2011

Background

Since May 2009, exposure of the population of Beijing, China to pH1N1 has resulted in an increase in respiratory illnesses. Limited information is available on the etiology and clinical characteristics of the influenza-like illness (ILI) that ensued in adults following the pH1N1 pandemic.

Methods

Clinical and epidemiological data of ILI in adults was collected. A total of 279 throat swabs were tested for twelve respiratory viruses using multiplex RT-PCR. Clinical characteristics of influenza A in outpatients versus test-negative patients were compared using Pearson's χ2 and the Mann-Whitney U test. 190 swabs were tested for pH1N1 by virus isolation. Consultation rates for ILI were compared between 2009 and 2010.

Results

One or two virus were detected in 29% of the samples. Influenza A virus (FLU-A) accounted for 22.9% (64/279). Other viruses were present at a frequency less than 3.0%. Cough was significantly associated with Influenza A virus infection (χ2, p<0.001). The positive rate of FLU-A was consistent with changes in the ILI rate during the same period and there was a significant reduction in the incidence of ILI in 2010 when compared to 2009. During the 2010–2011 influenza season, the incidence peaked in January 2011 in Beijing and north China.

Conclusions

Exposure to pH1N1 had no impact on typical influenza seasonal peaks, although FLU-A remained the predominant virus for 2010 in Beijing. Symptomatically, cough was associated with FLU-A infection. The positive rate of influenza virus was consistent with changes in the ILI rate during the same period and there was a significant reduction in the incidence of ILI in 2010 when compared to that of 2009.