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@#The neonatal mortality rate in Papua New Guinea is high, estimated at 24 per 1000 live births. The neonatal case fatality rate in newborns in provincial and referral hospitals was 5.9% in 2021. Deteriorating newborns can be difficult to identify. This observational study investigated the feasibility of using a neonatal colour coded observation and response chart to identify neonates at risk of deterioration and to promptly escalate care in the Special Care Nursery of Port Moresby General Hospital. The chart was adapted from the Plymouth Hospital Neonatal Early Warning System chart, and was used to collect data over 8 weeks between 1st May and 30th June 2022. One hundred and fifty seven (157) neonates were observed over the 72 hours following admission to the Special Care Nursery. Neonates were grouped into those that had triggers (vital signs that fell in the red zone) and a stable group (who had no observations in the red zone). Of the 157 patients recruited 72 (45.9%) were stable, and 85 (54.1%) had triggers that should prompt a response. Forty seven (55.3%) of the neonates in the trigger group had appropriate interventions. Neonates with observations in the red zone (triggers) were more likely to die in the first 72 hours compared with those with no triggers. Most of the nurse responded positively to the introduction of the chart. Whilst the Neonatal Early warning System is a tool that can be used to identify neonates at risk of clinical deterioration, proper training of its use and knowledge of and appropriate escalation of care are necessary to ensure its benefit
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@#The coronavirus disease 2019 (COVID-19) pandemic has uncovered the need for health systems to be strengthened in order to be able to respond quickly to any potential future outbreaks. In response, the Pacific Syndromic Surveillance System (PSSS) is currently being used by many countries within the Pacific Islands for tracking and addressing infectious disease outbreaks, including COVID-19. To maximise its usefulness as an early warning system, investments must be made in strengthening data quality, data sharing, health facility capacity, technology, and ongoing evaluation of surveillance systems. Doing so will ensure that the PSSS and other surveillance systems can remain effective tools for monitoring and respond to infectious disease outbreaks in the Pacific Islands
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Objective:To comprehensively evaluate and compare the early warning system's ability to predict the risk of maternal disease in China, such as the British National Intensive Care Audit and Research Center (ICNARC)-Obstetric Early Warning Score (OEWS) system, the National Maternal Safety Early Warning Standard (MEWC) recommended by the National Coalition for Maternal Safety, the Irish Maternity Early Warning System (IMEWS) proposed in the clinical practice guidelines issued by the head of health services at the Royal Medical College of Ireland.Methods:A total of 872 pregnant women who were admitted to the Women′s Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital were prospectively observed from January 2019 to December 2019. The data during hospitalization were collected to calculate the scores of the three obstetric early warning scoring systems, to compare and evaluate the prediction and identification ability of three early warning systems for critically ill pregnant women.Results:A total of 872 cases were included in this study, of which 167 were critically ill, accounting for 19.2%, and 705 were non-critically ill, accounting for 80.8%. The three obstetric early warning systems (OEWS,MEWC,IMEWS) in critical group scored 4(2, 6),3(0, 6),5(3, 6), and non-critical group scored 1(0, 1), 0(0, 0), 2(0, 3), respectively. The critical group scored significantly higher than the non-critical group ( P<0.001). The AUC of OEWS was 0.961 (95% CI 0.948-0.975, P<0.001) and that of MEWC was 0.803 (95% CI 0.757 - 0.850, P<0.001). The AUC of IMEWS was 0.853 (95% CI 0.817-0.888, P<0.001). No obstetric critical illness occurred when OEWS was 0. The positive likelihood ratio was 8.208 6 when OEWS≥6. Conclusions:Three kinds of early warning systems have good predictive ability for the occurrence of critical obstetric diseases in China. Among the three warning systems, OEWS has better predictive ability than the other two, and has better hierarchical ability. However, due to the differences in population, environment and conditions in different regions, each obstetric medical unit can improve OEWS according to its own conditions and design an obstetric early warning system that meets its own clinical needs.
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【Objective】 To conduct accurate analysis of blood inventory, so as to provide basis for taking targeted measures. 【Methods】 Taking the suspended red blood cells(RBCs) as an example, mathematical formulas were set by online Excel table, and the inventory of each blood group of RBCs in a certain day can be predicted accurately by inputting daily inventory and units distributed, and estimated daily units collected.Preventive measures such as enhancing recruitment or limiting collection could be taken as soon as possible to keep the blood inventory at a reasonable level. 【Results】 Blood inventory had been moderate during the six months of practice, and neither blood shortage nor collected blood expiring occurred. 【Conclusion】 The early warning system based on the online form, which is highly practical and easy to operate, is suitable for inventory management of blood components.
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Objective: To establish an early warning system for cutaneous leishmaniasis in Fars province, Iran in 2016. Methods: Time-series data were recorded from 29201 cutaneous leishmaniasis cases in 25 cities of Fars province from 2010 to 2015 and were used to fit and predict the cases using time-series models. Different models were compared via Akaike information criterion/Bayesian information criterion statistics, residual analysis, autocorrelation function, and partial autocorrelation function sample/model. To decide on an outbreak, four endemic scores were evaluated including mean, median, mean + 2 standard deviations, and median + interquartile range of the past five years. Patients whose symptoms of cutaneous leishmaniasis began from 1 January 2010 to 31 December 2015 were included, and there were no exclusion criteria. Results: Regarding four statistically significant endemic values, four different cutaneous leishmaniasis space-time outbreaks were detected in 2016. The accuracy of all four endemic values was statistically significant (P<0.05). Conclusions: This study presents a protocol to set early warning systems regarding time and space features of cutaneous leishmaniasis in four steps: (i) to define endemic values based on which we could verify if there is an outbreak, (ii) to set different time-series models to forecast cutaneous leishmaniasis in future, (iii) to compare the forecasts with endemic values and decide on space-time outbreaks, and (iv) to set an alarm to health managers.
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Objective: To establish an early warning system for cutaneous leishmaniasis in Fars province, Iran in 2016. Methods: Time-series data were recorded from 29 201 cutaneous leishmaniasis cases in 25 cities of Fars province from 2010 to 2015 and were used to fit and predict the cases using time-series models. Different models were compared via Akaike information criterion/Bayesian information criterion statistics, residual analysis, autocorrelation function, and partial autocorrelation function sample/model. To decide on an outbreak, four endemic scores were evaluated including mean, median, mean + 2 standard deviations, and median + interquartile range of the past five years. Patients whose symptoms of cutaneous leishmaniasis began from 1 January 2010 to 31 December 2015 were included, and there were no exclusion criteria. Results: Regarding four statistically significant endemic values, four different cutaneous leishmaniasis space-time outbreaks were detected in 2016. The accuracy of all four endemic values was statistically significant (P<0.05). Conclusions: This study presents a protocol to set early warning systems regarding time and space features of cutaneous leishmaniasis in four steps: (i) to define endemic values based on which we could verify if there is an outbreak, (ii) to set different time-series models to forecast cutaneous leishmaniasis in future, (iii) to compare the forecasts with endemic values and decide on space-time outbreaks, and (iv) to set an alarm to health managers.
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Objective@#To analyze the effectiveness and response status of China Infectious Disease Automated Alert and Response System (CIDARS) in Hunan province from 2012 to 2016 for improving the system.@*Methods@#To collect the early warning signals, the number of suspected events, the result of on-site investigation, the signal response time and the result of public health emergencies, and the χ2 test, correlation analysis and non-parametric test were used to analyze the information on CIDARS in Hunan Province during the period from 2012 to 2016.@*Results@#A total of 108 188 signals were generated by the CIDARS in Hunan Province; The warning involved 30 kinds of infectious diseases and 138 counties (districts), and each county (district) received 3.00 weekly warning messages on average; 100% early warning signal was responded, 2 h response rate was 92.43%; The median response time (P25-P75) was 0.28 (0.11-0.77) h in the single case warning, and the five-year timely response rate showed an upward trend year by year (trend χ2=58.89, P<0.05); the median response time (P25-P75) was 0.56 (0.28~1.06) h in the time series warning, and the five-year timely response rate showed no trend (trend χ2=2.43, P>0.05); the time series warning response was more timely than the single case warning, and the difference between the two timely response rates was statistically significant(χ2=5156.60, P<0.05). The studies showed that the sensitivity, specificity, and detection timeliness of the system were 84.80%, 69.53%, and 2.80 d, respectively; There was no significant difference in the infectious diseases detecting timeliness of CIDARS(H=8.75, P>0.05); the system had the best effect in rubella, and the positive likelihood ratio of rubella is 4.36.@*Conclusions@#CIDARS in Hunan province runs well overall with high sensitivity and timely response to the early warning signals, but the specificity of the early warning system needs to be improved. The quality of the epidemic report of infectious diseases needs to be further improved, and the early warning parameters and warning method should be adjusted according to the characteristics of different diseases and the differences among different regions.
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Objective@#To analyze the effectiveness and response status of China Infectious Disease Automated Alert and Response System (CIDARS) in Hunan province from 2012 to 2016 for improving the system.@*Methods@#To collect the early warning signals, the number of suspected events, the result of on-site investigation, the signal response time and the result of public health emergencies, and the χ2 test, correlation analysis and non-parametric test were used to analyze the information on CIDARS in Hunan Province during the period from 2012 to 2016.@*Results@#A total of 108 188 signals were generated by the CIDARS in Hunan Province; The warning involved 30 kinds of infectious diseases and 138 counties (districts), and each county (district) received 3.00 weekly warning messages on average; 100% early warning signal was responded, 2 h response rate was 92.43%; The median response time (P25-P75) was 0.28 (0.11-0.77) h in the single case warning, and the five-year timely response rate showed an upward trend year by year (trend χ2=58.89, P<0.05); the median response time (P25-P75) was 0.56 (0.28~1.06) h in the time series warning, and the five-year timely response rate showed no trend (trend χ2=2.43, P>0.05); the time series warning response was more timely than the single case warning, and the difference between the two timely response rates was statistically significant(χ2=5156.60, P<0.05). The studies showed that the sensitivity, specificity, and detection timeliness of the system were 84.80%, 69.53%, and 2.80 d, respectively; There was no significant difference in the infectious diseases detecting timeliness of CIDARS(H=8.75, P>0.05); the system had the best effect in rubella, and the positive likelihood ratio of rubella is 4.36.@*Conclusions@#CIDARS in Hunan province runs well overall with high sensitivity and timely response to the early warning signals, but the specificity of the early warning system needs to be improved. The quality of the epidemic report of infectious diseases needs to be further improved, and the early warning parameters and warning method should be adjusted according to the characteristics of different diseases and the differences among different regions.
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Studies have shown that pregnant women due to their specificity and social factors during pregnancy, maternal mortality and postpartum serious complications were significantly higher. Taking effective measures to control maternal mortality and ensuring the safety of pregnant women is an urgent problem to be solved.The first measure to ensure the safety of pregnant women is to use appropriate assessment tools, accurate, dynamic and comprehensive risk assessment of pregnant women. At present, with the start of a comprehensive two-child policy,research related to obstetric early warning scores has become the focus of research in the field of obstetric care.Therefore,this article through the"obstetrics","maternal","risk warning","risk score"as the key word,search Wanfang database,Chinese Journal full-text database(CNKI),Chinese biomedical literature database(CBM);foreign language literature,such as PubMed,Web of Science,Springer,EBSCO and other databases,with"early warning score","risk score","risk score system","Obstetric","Obstetric care"Word for retrieval.So that to provide a comprehensive analysis of the status quo of the use of early risk assessment tools at home and abroad,and to summarize the contents of the assessment tools,and further point out the problems in the current research.
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OBJECTIVE:To improve the level of rational drug use,and to reduce the workload of clinical pharmacists. METH-ODS:Established“Intelligent Management and Solution for Clinical Rational Drug Use”of our hospital was introduced,including post-prescription review(all prescriptions review)system, self-maintenance system for rational drug use knowledge base,pre-pre-scription review (rational drug use real-time review) early warning system. The effects of intelligent system were evaluated. RE-SULTS & CONCLUSIONS:After the application of the system,the following aspects could be achieved,including“all prescrip-tions review”,“multi-prescriptions/longitudinal review”,system knowledge base real-time update and autonomous definition of re-view rules,effective communication and intervention between physicians and pharmacists before printing prescription by Yaozhidao instant messaging system. Through related trial evaluation,the proportion of false positive prescriptions decreased by 17.65% after 4 months of the application of the system;drug consultation prescriptions review average score of outpatient pharmacists increased from 81 to 94.85;the time of prescription review decreased by 4.72-5.46 times. Through mandatory interception of unqualified pre-scriptions,severe warning,timely prompt and pharmacists’intervention,the rate of unqualified prescriptions pre-reviewed by the system in respiration department decreased from 32% in Jan. 2015 and 21% in May to 4.62% in Dec. So,the application of the system promotes rational drug use in outpatient department,reduces the workload of pharmacists and ensures the safety of drug use comprehensively.
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Mass gatherings pose public health challenges to host countries, as they can cause or exacerbate disease outbreaks within the host location or elsewhere. In July 2012, the 11th Festival of Pacific Arts (FOPA), a mass gathering event involving 22 Pacific island states and territories, was hosted by Solomon Islands. An enhanced syndromic surveillance (ESS) system was implemented for the event. Throughout the capital city, Honiara, 15 sentinel sites were established and successfully took part in the ESS system, which commenced one week before the FOPA (25 June) and concluded eight days after the event (22 July). The ESS involved expanding on the existing syndromic surveillance parameters: from one to 15 sentinel sites, from four to eight syndromes, from aggregated to case-based reporting and from weekly to daily reporting. A web-based system was developed to enable data entry, data storage and data analysis. Towards the end of the ESS period, a focus group discussion and series of key informant interviews were conducted. The ESS was considered a success and played an important role in the early detection of possible outbreaks. For the period of the ESS, 1668 patients with syndrome presentations were received across the 15 sentinel sites. There were no major events of public health significance. Several lessons were learnt that are relevant to ESS in mass gathering scenarios, including the importance of having adequate lead in time for engagement and preparation to ensure appropriate policy and institutional frameworks are put in place.
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Chinese materia medica (CMM) and pieces of Chinese medicine are important composition of National Essential Drugs List, which also embodys the characteristics of traditional Chinese medicine (TCM). National Essential Drugs List is well known for its "safe, necessary, effective, inexpensive", but some chemicals in the list are often short of supply because of their low cost. Usually, Chinese patent medicine composes of more ingredients in prescription, among which there is a complementary price and the price fluctuation is in the normal range. But in recent years, some CMM prices experience massive run-ups followed by precipitous falls, which results in medicine manufacturers stopping production. The effect of short-term rising on feed quality can not be ignored. This article discusses the necessity and feasibility of early warning methods for the essential Chinese medicine supply based on National Census of CMM Resource Survey, and this method is explained and demonstrated with Compound Danshen Tablets as example.
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Objective To evaluate the effect of automatic early warning information system on the response of malaria elimi-nation in Jiangsu Province through the operation of the national automatic early warning system of infectious diseases. Methods The malaria early warning information was collected from the automatic early warning information subsystem in the national infor-mation system for diseases control and prevention. Malaria early warning signals were analyzed from September 1 to December 31, 2012. The statistical analysis was conducted for the completion rates of case investigation within 3 days before and after the applica-tion of malaria early warning information system. Results Jiangsu Province received 85 mobile phone short messages(SMS)of malaria case from early warning system from September 1 to December 31,2012. After judgments,23 cases were deleted includ-ing 8 repeated cases and 15 cases that were excluded through the microscopy examination and epidemiological investigation by the confirmation of county CDC. From July to December in 2012,the monthly completion rates of case investigation within 3 days were 55.56%,78.57%,90.00%,100%,100%and 100%,respectively. The completion rates of case investigation within 3 days in Ju-ly,August,September and October were significantly different by χ2 test(χ2=10.66,P<0.05). The completion rates of foci in-vestigation and action within 7 days in Jiangsu Province were all 100%from July to December in 2012. Conclusions The comple-tion rates of case investigation within 3 days are associated with SMS from the early warning system. The malaria warning system from the national infectious diseases can effectively improve the response to malaria cases for primary CDC. It also plays an impor-tant role for the timely confirmation and diagnosis of malaria cases.
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Objective To analyze the results of application on China Infectious Diseases Automated-alert and Response System(CIDARS)and for further improving the system. Methods Amount of signal, proportion of signal responded, time to signal response, manner of signal verification and the outcome of each signal in CIDARS were descriptively analyzed from July 1,2008to June 30, 2010. Results A total of 533 829 signals were generated nationwide on 28 kinds of infectious diseases in the system. 97.13% of the signals had been responded and the median time to response was 1.1 hours. Among them, 2472 signals were generated by the fixed-value detection method which involved 9 kinds of diseases after the preliminary verification, field investigation and laboratory tests. 2202 signals were excluded, and finally 246 cholera cases, 15 plague cases and 9H5N1 cases as well as 39 outbreaks of cholera were confirmed. 531 357 signals were generated by the other method - the 'moving percentile method' which involved 19 kinds of diseases. The average amount of signal per county per week was 1.65, with 6603 signals(1.24%)preliminarily verified as suspected outbreaks and 1594 outbreaks were finally confirmed by further field investigation. For diseases in CIDARS, the proportion of signals related to suspected outbreaks to all triggered signals showed a positive correlation with the proportion of cases related to outbreaks of all the reported cases (r=0.963, P＜0.01). Conclusion The signals of CIDARS were responded timely, and the signal could act as a clue for potential outbreaks, which helped enhancing the ability on outbreaks detection for local public health departments.
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Objective To evaluate the performance of China Infectious Disease Automatedalert and Response System(CIDARS). Methods A retrospective analysis was conducted on data related to the warning signals, the outcome of signal verification, the field investigation of CIDARS,and the emergent events reported through Public Health Emergency Events Surveillance System from July 1,2008 to June 30, 2010 in Zhejiang province. The performance of CIDARS was qualitatively evaluated by indicators on its sensitivity and rote of false alarm. Results In total, 26 446 signals were generated by the system which involving 17 diseases, with an average of 2.83 signals per country per week. Among all the signals, 99.95% of them were responded. 0.90% of the signals were judged as suspected events via the preliminary verification, and 30 outbreaks were finally confirmed by field investigation. The sensitivity of the system was 69.77% with the false alarm rate as 1.39%. Conclusion The system seemed to have worked on the outbreak early warning of infectious diseases and could directly reflect the anomaly event emerged from the infectious disease reporting system.However, more efforts should be paid to the following areas as how to decrease the false positive signals, select suitable thresholds and increase the quality of data in order to enhance the accuracy of the system.
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Objective To understand the effectiveness of China Infectious Disease Automated-alert and Response System(CIDARS)for outbreak detection at the regional level.Methods Two counties in Hunan province(Yuelu and Shuangfeng county)and two counties in Yunnan province(Xishan and Gejiu county)were chosen as the study areas. Data from CIDARS were analyzed on the following items: reported cases, warning signals, the time interval of signal response feedback, way of signal verification, outcome of signal verification and field investigation, from July 1,2008 to June 30,2010. Results In total, 12 346 cases from 28 kinds of diseases were reported,and 2096 signals of 19 diseases were generated by the system, with an average of 4.94 signals per county per week. The median of time interval on signal verification feedback was 0.70 hours(P25-P75:0.06-1.29 h)and the main way of signal preliminary verification was through the review of surveillance data(account for 63.07%). Among all the signals, 34 of them(1.62%)were considered to be related to suspected events via the preliminary verification at the local level. Big differences were found to have existed on the proportion of signals related to the suspected events of the total signals among the four counties, with Shuangfeng county as 4.71%, Yuelu county as 1.88%, Gejiu county as 0.95% and Xishan county as 0.58%. After an indepth study on the fields of suspected events, 12outbreaks were finally confirmed, including 5 on rubella, 4 on mumps, 2 on influenza and 1 on typhoid fever. Conclusion CIDARS could be used to assist the local public health institutions on early detection of possible outbreaks at the early stage. However, the effectiveness was different depending on the regions and diseases.
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Objective Weifang is a pilot of the health system reform, the research aims to investigate the present situation of turnover intention within the medical staff in Weifang's public hospitals, seeking main influencing factors, while exploratory research about how to bulid a three-stage early-warning system also included. Methods Chooseing 29 public hospitals with stratified random sampling method, questionare investigation for 933 qualified samples,and spss 16. 0 was also used as an analysis method. Results About 49% of the respondents have turnover intention, those working years less than 10 have the strongest turnover intention, individual work-emotional exhaustionsocial support from family members or friends, and restriction of personal development are three main causes from Logistic analysis. Conclusion According to the stage characteristic of turnover intention, building an early-warning system could play an important role in controlling brain-drain.
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In line with the hospital development practice in recent years,this paper discussed the early-warning system for hospital talents drainage.First of all,it points out that early-warning indicators,early-warning analysis and early-control measures are key elements of such a system.On this basis,it pinpoints key points in building this system,including organizational assurance,by-level management,dynamic tracking,fairness,bettering of HR mechanism,and reservation of potential HR resources.Therefore,this will be highly useful and practical for studying how to minimize talents drainage and maintain competitive advantages of hospitals.
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Regular surveillance of malaria epidemics is fundamenta l f or malaria epidemiology.Malaria early warning system(MEWS)based on malaria sur veillance is a systematic framework for the prediction of malaria epidemics.The surveillance included environmental factors,transmission potential,risk factors ,morbidity and mortality,and weather condition.The MEWS will enable the authorit ies to make early and correct forecast of malaria and take proper preventive mea sures.