National Electronic Disease Surveillance System (NEDSS): A Standards-Based Approach To Connect Public Health and Clinical Medicine

2001 ◽  
Vol 7 (6) ◽  
pp. 43-50 ◽  
Author(s):  
&NA;
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Clinical Medicine ◽  
Disease Surveillance System

scholarly journals Potential Early Identification of a Large Campylobacter Outbreak Using Alternative Surveillance Data Sources: Autoregressive Modelling and Spatiotemporal Clustering (Preprint)

2020 ◽  
Author(s):  
Mehnaz Adnan ◽  
Xiaoying Gao ◽  
Xiaohan Bai ◽  
Elizabeth Newbern ◽  
Jill Sherwood ◽  
...  
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Case Reports ◽  
Surveillance Data ◽  
Data Sources ◽  
Google Trends ◽  
School Absenteeism ◽  
Disease Surveillance System ◽  
Spatiotemporal Clustering

BACKGROUND Over one-third of the population of Havelock North, New Zealand, approximately 5500 people, were estimated to have been affected by campylobacteriosis in a large waterborne outbreak. Cases reported through the notifiable disease surveillance system (notified case reports) are inevitably delayed by several days, resulting in slowed outbreak recognition and delayed control measures. Early outbreak detection and magnitude prediction are critical to outbreak control. It is therefore important to consider alternative surveillance data sources and evaluate their potential for recognizing outbreaks at the earliest possible time. OBJECTIVE The first objective of this study is to compare and validate the selection of alternative data sources (general practice consultations, consumer helpline, Google Trends, Twitter microblogs, and school absenteeism) for their temporal predictive strength for Campylobacter cases during the Havelock North outbreak. The second objective is to examine spatiotemporal clustering of data from alternative sources to assess the size and geographic extent of the outbreak and to support efforts to attribute its source. METHODS We combined measures derived from alternative data sources during the 2016 Havelock North campylobacteriosis outbreak with notified case report counts to predict suspected daily Campylobacter case counts up to 5 days before cases reported in the disease surveillance system. Spatiotemporal clustering of the data was analyzed using Local Moran’s I statistics to investigate the extent of the outbreak in both space and time within the affected area. RESULTS Models that combined consumer helpline data with autoregressive notified case counts had the best out-of-sample predictive accuracy for 1 and 2 days ahead of notified case reports. Models using Google Trends and Twitter typically performed the best 3 and 4 days before case notifications. Spatiotemporal clusters showed spikes in school absenteeism and consumer helpline inquiries that preceded the notified cases in the city primarily affected by the outbreak. CONCLUSIONS Alternative data sources can provide earlier indications of a large gastroenteritis outbreak compared with conventional case notifications. Spatiotemporal analysis can assist in refining the geographical focus of an outbreak and can potentially support public health source attribution efforts. Further work is required to assess the location of such surveillance data sources and methods in routine public health practice.

scholarly journals Infectious Disease Reporting and Outbreak Management Improvement Project

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Donald E. Brannen ◽  
Melissa Branum ◽  
Amy Schmitt
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Reporting System ◽  
Median Number ◽  
Clinical Services ◽  
Disease Reporting ◽  
E Coli ◽  
Disease Surveillance System ◽  
The Impact

ObjectiveImprove disease reporting and outbreak mangement.IntroductionSpecific communicable diseases have to be reported by law withina specific time period. In Ohio, prior to 2001, most of these diseasereports were on paper reports that were reported from providers tolocal health departments. In turn the Communicable Disease Nursemailed the hardcopies to the Ohio Department of Health (ODH).In 2001 the Ohio Disease Reporting System (ODRS) was rolled out toall local public health agencies in Ohio.1ODRS is Ohio’s portion ofthe National Electronic Disease Surveillance System. ODRS shouldnot be confused with syndromic surveillance systems that are fordetecting a disease outbreak before the disease itself is detected.2Chronic disease surveillance system data has been evaluated forlong term trends and potential enhancements.3However, the use ofcommunicable disease reports vary greatly.4 However, the exportdata has not routinely been used for quality improvement purposesof the disease reporting process itself. In December 2014, GreeneCounty Public Health (GCPH) begain a project to improve reportingof communicable diseases and the response to disease outbreaks.MethodsInitial efforts were to understand the current disease reportingprocess: Quantitative management techniques including creating alogic model and process map of the existing process, brainstormingand ranking of issues. The diseases selected to study included:Campylobacteriosis, Cryptosporidiosis, E. coli O157:H7 &shiga toxin-producing E. coli, Giardiasis, Influenza-associatedhospitalization, Legionnaires’ disease, Pertussis, Salmonellosis,and Shigellosis. The next steps included creating a data collectionand analysis plan. An updated process map was created and thepre- and post-process maps were compared to identify areas toimprove. The median number of days were compared before andafter improvements were implemented. Modeling of the impact ofthe process improvements on the median number of days reportedwas conducted. Estimation of the impact in healthy number of daysderived from the reduction in days to report (if any) were calculated.ResultsProcess improvements identified: Ensure all disease reportersuse digital reporting methods preferably starting with electroniclaboratory reporting directly to the online disease reporting system,with other methods such as direct web data entry into system, faxinglab reports, orsecure emailing reports, with no or little hard copy mailing;Centralize incoming email and fax reports (eliminating process steps);Standardize backup staffing procedures for disease reporting staff;Formalize incident command procedures under the authorized personin charge for every incident rather than distribute command betweenenvironmental and clinical services; and place communicable diseasereporting under that single authority rather than clinical services. Thedays to report diseases were reduced from a median of 2 to .5 days(p<.001). All the diseases were improved except for crytosporodiumdue to an outlier report two months late. The estimated societalhealthy days saved were valued at $52,779 in the first eight monthsafter implementation of the improvements.ConclusionsImprovements in disease reporting decreased the reporting timefrom over 2 days to less than 1 day on average. Estimated societalhealthy days saved by this project during the first 9 months was$52,779. Management of early command and control for outbreakresponse was improved.

scholarly journals Potential Early Identification of a Large Campylobacter Outbreak Using Alternative Surveillance Data Sources: Autoregressive Modelling and Spatiotemporal Clustering

10.2196/18281 ◽  
2020 ◽  
Vol 6 (3) ◽  
pp. e18281
Author(s):  
Mehnaz Adnan ◽  
Xiaoying Gao ◽  
Xiaohan Bai ◽  
Elizabeth Newbern ◽  
Jill Sherwood ◽  
...  
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Case Reports ◽  
Surveillance Data ◽  
Data Sources ◽  
Google Trends ◽  
School Absenteeism ◽  
Disease Surveillance System ◽  
Spatiotemporal Clustering

Background Over one-third of the population of Havelock North, New Zealand, approximately 5500 people, were estimated to have been affected by campylobacteriosis in a large waterborne outbreak. Cases reported through the notifiable disease surveillance system (notified case reports) are inevitably delayed by several days, resulting in slowed outbreak recognition and delayed control measures. Early outbreak detection and magnitude prediction are critical to outbreak control. It is therefore important to consider alternative surveillance data sources and evaluate their potential for recognizing outbreaks at the earliest possible time. Objective The first objective of this study is to compare and validate the selection of alternative data sources (general practice consultations, consumer helpline, Google Trends, Twitter microblogs, and school absenteeism) for their temporal predictive strength for Campylobacter cases during the Havelock North outbreak. The second objective is to examine spatiotemporal clustering of data from alternative sources to assess the size and geographic extent of the outbreak and to support efforts to attribute its source. Methods We combined measures derived from alternative data sources during the 2016 Havelock North campylobacteriosis outbreak with notified case report counts to predict suspected daily Campylobacter case counts up to 5 days before cases reported in the disease surveillance system. Spatiotemporal clustering of the data was analyzed using Local Moran’s I statistics to investigate the extent of the outbreak in both space and time within the affected area. Results Models that combined consumer helpline data with autoregressive notified case counts had the best out-of-sample predictive accuracy for 1 and 2 days ahead of notified case reports. Models using Google Trends and Twitter typically performed the best 3 and 4 days before case notifications. Spatiotemporal clusters showed spikes in school absenteeism and consumer helpline inquiries that preceded the notified cases in the city primarily affected by the outbreak. Conclusions Alternative data sources can provide earlier indications of a large gastroenteritis outbreak compared with conventional case notifications. Spatiotemporal analysis can assist in refining the geographical focus of an outbreak and can potentially support public health source attribution efforts. Further work is required to assess the location of such surveillance data sources and methods in routine public health practice.

scholarly journals Status report - Individual, programmatic and systemic indicators of the quality of mental health care using a large health administrative database: an avenue for preventing suicide mortality

2018 ◽  
Vol 38 (7/8) ◽  
pp. 295-304
Author(s):  
Lise Thibodeau ◽  
Elham Rahme ◽  
James Lachaud ◽  
Éric Pelletier ◽  
Louis Rochette ◽  
...  
Keyword(s):  
Public Health ◽  
Mental Health ◽  
Health Care ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Health Care Services ◽  
Status Report ◽  
Care Services ◽  
Disease Surveillance System

Suicide is a major public health issue in Canada. The quality of health care services, in addition to other individual and population factors, has been shown to affect suicide rates. In publicly managed care systems, such as systems in Canada and the United Kingdom, the quality of health care is manifested at the individual, program and system levels. Suicide audits are used to assess health care services in relation to the deaths by suicide at individual level and when aggregated at the program and system levels. Large health administrative databases comprise another data source used to inform population- based decisions at the system, program and individual levels regarding mental health services that may affect the risk of suicide. This status report paper describes a project we are conducting at the Institut national de santé publique du Québec (INSPQ) with the Quebec Integrated Chronic Disease Surveillance System (QICDSS) in collaboration with colleagues from Wales (United Kingdom) and the Norwegian Institute of Public Health. This study describes the development of quality of care indicators at three levels and the corresponding statistical analysis strategies designed. We propose 13 quality of care indicators, including system-level and several population-level determinants, primary care treatment, specialist care, the balance between care sectors, emergency room utilization, and mental health and addiction budgets, that may be drawn from a chronic disease surveillance system.

scholarly journals Enhancing Disease Surveillance Event Communication among Jurisdictions

2009 ◽  
Vol 2 ◽  
pp. BII.S3523
Author(s):  
Nathaniel R. Tabernero ◽  
Wayne A. Loschen ◽  
Joel Jorgensen ◽  
Joshua Suereth ◽  
Jacqueline S. Coberly ◽  
...  
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Common Ground ◽  
Software Tool ◽  
Surveillance Systems ◽  
Communication Tool ◽  
Web Based ◽  
Disease Surveillance System ◽  
Public Health Officials

Automated disease surveillance systems are becoming widely used by the public health community. However, communication among non-collocated and widely dispersed users still needs improvement. A web-based software tool for enhancing user communications was completely integrated into an existing automated disease surveillance system and was tested during two simulated exercises and operational use involving multiple jurisdictions. Evaluation of this tool was conducted by user meetings, anonymous surveys, and web logs. Public health officials found this tool to be useful, and the tool has been modified further to incorporate features suggested by user responses. Features of the automated disease surveillance system, such as alerts and time series plots, can be specifically referenced by user comments. The user may also indicate the alert response being considered by adding a color indicator to their comment. The web-based event communication tool described in this article provides a common ground for collaboration and communication among public health officials at different locations.

scholarly journals Disease Surveillance System of Bangladesh: Combating Public Health Emergencies

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Mohammed Husain ◽  
Mahmudur Rahman ◽  
Asm Alamgir ◽  
M. Salim Uzzaman ◽  
Meerjady Sabrina Flora
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Communicable Disease ◽  
Control Unit ◽  
Communicable Diseases ◽  
Health Facilities ◽  
Surveillance Data ◽  
Public Health Emergencies ◽  
Disease Surveillance System

Objectivea) To observe trends and patterns of diseases of public health importance and responseb) To predict, prevent, detect, control and minimize the harm caused by public health emergenciesc) To develop evidence for managing any future outbreaks, epidemic and pandemicIntroductionDisease surveillance is an integral part of public health system. It is an epidemiological method for monitoring disease patterns and trends. International Health Regulation (IHR) 2005 obligates WHO member countries to develop an effective disease surveillance system. Bangladesh is a signatory to IHR 2005. Institute of Epidemiology, Disease Control and Research (IEDCR <www.iedcr.gov.bd>) is the mandated institute for surveillance and outbreak response on behalf of Government of the People’s Republic of Bangladesh. The IEDCR has a good surveillance system including event-based surveillance system, which proved effective to manage public health emergencies. Routine disease profile is collected by Management Information System (MIS) of Directorate General of Health Services (DGHS). Expanded Program of Immunization (EPI) of DGHS collect surveillance data on EPI-related diseases. Disease Control unit, DGHS is responsible for implementing operational plan of disease surveillance system of IEDCR. The surveillance system maintain strategic collaboration with icddrr,b.MethodsThe IEDCR is conducting disease surveillance in several methods and following several systems. Surveillance data of priority communicable disease are collected by web based integrated disease surveillance. It is based on weekly data received from upazilla (sub-district) health complex on communicable disease marked as priority. They are: acute watery diarrhea, bloody dysentery, malaria, kala-azar, tuberculosis, leprosy, encephalitis, any unknown disease. Government health facilities at upazilla (sub-district) send the data using DHIS2. During outbreak, daily, even hourly reporting is sought from the concerned unit.Moreover, IEDCR conducts disease specific specialized surveillance systems. Data from community as well as from health facilities are collected for Influenza, nipah, dengue, HIV, cholera, cutaneous anthrax, non-communicable diseases, food borne illness. Data from health facilities are collected for antimicrobial resistance, rotavirus and intussusception, reproductive health, child health and mortality, post MDA-surveillance for lymphatic filariasis transmission, molecular xenomonitoring for detection of residual Wucheria bancrofti, dengue (virological), emerging zoonotic disease threats in high-risk interfaces, leptospirosis, acute meningo-encephalitis syndrome (AMES) focused on Japanese encephalitis and nipah, unintentional acute pesticide poisoning among young children. Data for event based surveillance are collected from usual surveillance system as well as from dedicated hotlines (24/7) of IEDCR, media monitoring, and any informal reporting.Case detection is done by syndromic surveillance, laboratory diagnosed surveillance, media surveillance, hotline, cell phone-based surveillance. Dissemination of surveillance is done by website of IEDCR, periodic bulletins, seminar, conference etc. Line listing are done by rapid response teams working in the surveillance sites. Demographic information and short address are listed in the list along with clinical and epidemiological information. Initial cases are confirmed by laboratory test, if required from collaborative laboratory at US CDC (Atlanta). When the epidemiological trend is clear, then subsequent cases are detected by symptoms and rapid tests locally available.ResultsIn 2017, 26 incidents of disease outbreak were investigated by National Rapid Response Team (NRRT) of IEDCR. In the same year, 12 cases of outbreak of unknown disease was investigated by NRRT of IEDCR at different health facilities. Joint surveillance with animal health is being planned for detection and managing zoonotic disease outbreaks, following One Health principles. Department of Livestock, Ministry of Environment and icddrb are partners of the joint surveillance based on One Health principles.Disease Control unit of DGHS, district and upazilla health managers utilizes the disease surveillance data for public health management. They analyze also the surveillance data at their respective level to serve their purpose.ConclusionsA robust surveillance is necessary for assessing the public health situation and prompt notification of public health emergency. The system was introduced at IEDCR mainly for malaria and diarrhea control during establishment of this institute. Eventually the system was developed for communicable disease, and recently for non-communicable diseases. It is effectively used for managing public health emergencies. Notification and detection of public health emergency is mostly possible due to media surveillance.Data for syndromic surveillance for priority communicable diseases is often not sent timely and data quality is often compromised. Tertiary hospitals are yet to participate in the web based integrated disease surveillance system for priority communicable diseases. But they are part of specialized disease surveillances. Data from specialized surveillance with laboratory support is of high quality.Evaluation of the system by conducting research is recommended to improve the system. Specificity and sensitivity of case detection system should also be tested periodically.ReferencesCash, Richard A, Halder, Shantana R, Husain, Mushtuq, Islam, Md Sirajul, Mallick, Fuad H, May, Maria A, Rahman, Mahmudur, Rahman, M Aminur. Reducing the health effect of natural hazards in Bangladesh. Lancet, The, 2013, Volume 382, Issue 9910IEDCR. At the frontline of public health. updated 2013. www.iedcr.gov.bdAo TT, Rahman M et al. Low-Cost National Media-Based Surveillance System for Public Health Events, Bangladesh. Emerging Infectious Diseases. Vol 22, No 4. 2016.<www.iedcr.gov.bd> accessed on 1 Oct 2018. 

scholarly journals Evaluation of First Electronic Case Reports received in Illinois

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Stacey Hoferka
Keyword(s):  
Public Health ◽  
Case Report ◽  
Race And Ethnicity ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Communicable Disease ◽  
Case Reports ◽  
Production Environment ◽  
Provider Group ◽  
Disease Surveillance System

ObjectiveComparison of content in eCR and ELR cases reportingReview technical challenges and strategies for data managementIntroductionCommunicable disease reporting from providers can be a time-consuming process that results in delayed or incomplete reporting of infectious diseases, limiting public health's ability to respond quickly to prevent or control disease. The recent development of an HL7 standard for automated Electronic initial case reports (eICR) represents an important advancement for public health surveillance. The Illinois Department of Public Health (IDPH) participated in a pilot with the Public Health Informatics Institute and an Illinois-based provider group to accept eICR reports for Gonorrhea and Chlamydia.MethodsThe provider group working with their EHR vendor submitted a batch of CT and GC reports directly to IDPH in September 2017 according to the published eICR standard. A summary of the provider and PHII work has been presented previously in the STI eCR Learning Community. The eICR reports received from the provider were compared to case report data in the communicable disease surveillance system, I-NEDSS. Data was extracted from I-NEDSS that included race and ethnicity, timing of specimen collection, result, ELR submission surveillance action and treatment.ResultsIDPH received a batch of 89 files containing 77 unique persons, with 54 chlamydia (CT), 13 Gonorrhea (GC) and 10 co-infected case reports. The communicable disease surveillance system had captured 76 (98.7%) of the persons reported in the pilot. Among those, an Electronic Laboratory Report (ELR) was received for 72 (95%) cases, on average within 1 day of the lab report date. Data in I-NEDSS had a completion of 45% for race and ethnicity compared to 99% for race and 92% for ethnicity in the eICR files. Information on treatment in the surveillance system was reported for 18 (24%) cases compared to 67 (87%) cases.ConclusionsThis pilot was the first submission of real patient data submitted using the eICR standard to IDPH. Data was more complete from provider eICR reports for key demographic of race and ethnicity and treatment. A comparison with the current surveillance system showed near complete and timely case capture from ELR data. Integrated reporting of both ELR and eICR can produce a more complete case report through automated submissions and potentially reduce burden of data collection on health department communicable disease investigators. As public health reporting moves in this direction, public health agencies will have some substantial tasks to correctly ingest, map and interpret the increased amounts of information that are contained in the eICR. Further, the advantages of case reporting will be dependent on automated processes within the communicable disease system to merge data and apply business rules to automatically process completed case reports for high volume diseases, such as STIs. This work will continue as providers are ready to submit reports from different vendor products from a near real-time production environment.

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