scholarly journals Administrative and syndromic surveillance data can enhance public health surveillance

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Tara C. Anderson ◽  
Hussain Yusuf ◽  
Amanda McCarthy ◽  
Katrina Trivers ◽  
Peter Hicks ◽  
...  
Keyword(s):  
Public Health ◽  
Administrative Data ◽  
Syndromic Surveillance ◽  
Health Surveillance ◽  
Local State ◽  
Surveillance Data ◽  
Data Sources ◽  
Urgent Care ◽  
American Hospital ◽  
State Regional

ObjectiveThis roundtable will address how multiple data sources, includingadministrative and syndromic surveillance data, can enhance publichealth surveillance activities at the local, state, regional, and nationallevels. Provisional findings from three studies will be presented topromote discussion about the complementary uses, strengths andlimitations, and value of these data sources to address public healthpriorities and surveillance strategies.IntroductionHealthcare data, including emergency department (ED) andoutpatient health visit data, are potentially useful to the publichealth community for multiple purposes, including programmaticand surveillance activities. These data are collected through severalmechanisms, including administrative data sources [e.g., MarketScanclaims data1; American Hospital Association (AHA) data2] andpublic health surveillance programs [e.g., the National SyndromicSurveillance Program (NSSP)3]. Administrative data typically becomeavailable months to years after healthcare encounters; however, datacollected through NSSP provide near real time information nototherwise available to public health. To date, 46 state and 16 localhealth departments participate in NSSP, and the estimated nationalpercentage of ED visits covered by the NSSP BioSense platform is54%. NSSP’s new data visualization tool, ESSENCE, also includesadditional types of healthcare visit (e.g., urgent care) data. AlthoughNSSP is designed to support situational awareness and emergencyresponse, potential expanded use of data collected through NSSP(i.e., by additional public health programs) would promote the utility,value, and long-term sustainability of NSSP and enhance surveillanceat the local, state, regional, and national levels. On the other hand,studies using administrative data may help public health programsbetter understand how NSSP data could enhance their surveillanceactivities. Such studies could also inform the collection and utilizationof data reported to NSSP.

scholarly journals Approach to Onboarding Emergency Medical Services (EMS) Data Into a Syndromic Surveillance System

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Samurl P. Prahlow ◽  
David Atrubin ◽  
Allison Culpepper ◽  
Janet J. Hamilton ◽  
Joshua Sturms ◽  
...  
Keyword(s):  
Public Health ◽  
Emergency Medical Services ◽  
Surveillance System ◽  
Syndromic Surveillance ◽  
Health Surveillance ◽  
Use Cases ◽  
Data Sources ◽  
Medical Services ◽  
Emergency Medical ◽  
Data Elements

ObjectiveTo describe the strategy and process used by the Florida Department of Health (FDOH) Bureau of Epidemiology to onboard emergency medical services (EMS) data into FDOH’s syndromic surveillance system, the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE-FL).IntroductionSyndromic surveillance has become an integral component of public health surveillance efforts within the state of Florida. The near real-time nature of these data are critical during events such as the Zika virus outbreak in Florida in 2016 and in the aftermath of Hurricane Irma in 2017. Additionally, syndromic surveillance data are utilized to support daily reportable disease detection and other surveillance efforts. Although syndromic systems typically utilize emergency department (ED) visit data, ESSENCE-FL also includes data from non-traditional sources: urgent care center visit data, mortality data, reportable disease data, and Florida Poison Information Center Network (FPICN) data. Inclusion of these data sources within the same system enables the broad accessibility of the data to more than 400 users statewide, and allows for rapid visualization of multiple data sources in order to address public health needs. Currently, the ESSENCE-FL team is actively working to incorporate EMS data into ESSENCE-FL to further increase public health surveillance capacity and data visualization.MethodsThe ESSENCE-FL team worked collaboratively with various public health program stakeholders to bring EMS data, aggregated by the FDOH Bureau of Emergency Medical Oversight Emergency Medical Services Tracking and Reporting System (EMSTARS) team, into ESSENCE-FL. The ESSENCE-FL team met with the EMSTARS team to discuss use cases, demonstrate both systems, and to obtain project buy-in and support. Initial project meetings included review of ESSENCE-FL system support, user types (roles and access), as well as data security and compliance. An overall project timeline was established, and deliverables were added into system support contracts. Multiple stakeholders, across disciplines representing each key use case, reviewed the Florida version of the National Emergency Medical Services Information System (NEMSIS) version 3.4 data dictionary to identify program-specific data element needs. An element scoring spreadsheet was returned to the ESSENCE-FL team. These scores were aggregated and discordant scores were reviewed by the ESSENCE-FL team. A one-month extract of EMS data was reviewed to assess variable completeness and relevance. Monthly team meetings facilitated the final decisions on the data elements by leveraging lessons learned through onboarding other data sources, findings from the analysis of the one-month extract, stakeholder comments, and advice from other states known to be leveraging EMS data for public health surveillance.ResultsThrough a collaborative and broad approach with partners, the ESSENCE-FL team attained stakeholder buy-in and identified 81 data elements to be included in the EMS feed to ESSENCE-FL. The final list of data elements was determined to best support health surveillance of this population prior to presenting to the ED. The inclusion of the EMS data in ESSENCE-FL will increase the epidemiologic characterization and analysis of the opioid epidemic in Florida. Additional key use cases identified during this project included enhanced injury surveillance, enhanced occupational health surveillance, and characterization of potential differences between EMS and ED visits.ConclusionsThis comprehensive approach can be used by other jurisdictions considering adding EMS data to their syndromic surveillance systems. When considering onboarding a new data source into a surveillance system, it is important to work closely with stakeholders from disciplines representing each of the key use cases to broaden buy-in and support for the project. Through employing this comprehensive approach, syndromic surveillance systems can be better developed to include data that are widely utilizable to many different stakeholders in the public health community.

scholarly journals Using Syndromic Data for Opioid Overdose Surveillance in Utah

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Wei Hou ◽  
Elizabeth Brutsch ◽  
Angela C Dunn ◽  
Cindy L Burnett ◽  
Melissa P Dimond ◽  
...  
Keyword(s):  
Public Health ◽  
Emergency Department ◽  
Real Time ◽  
Emergency Department Visit ◽  
Syndromic Surveillance ◽  
Chief Complaint ◽  
Surveillance Data ◽  
Urgent Care ◽  
Mortality Data ◽  
Opioid Overdose

Objective: To monitor opioid-related overdose in real-time using emergency department visit data and to develop an opioid overdose surveillance report for Utah Department of Health (UDOH) and its public health partners.Introduction: The current surveillance system for opioid-related overdoses at UDOH has been limited to mortality data provided by the Office of the Medical Examiner (OME). Timeliness is a major concern with OME data due to the considerable lag in its availability, often up to six months or more. To enhance opioid overdose surveillance, UDOH has implemented additional surveillance using timely syndromic data to monitor fatal and nonfatal opioid-related overdoses in Utah.Methods: As one of the agencies participating in the National Syndromic Surveillance Program (NSSP), UDOH submits de-identified data on emergency department visit from Utah’s hospitals and urgent care facilities in close to real-time to the NSSP platform. Emergency department visit data are available for analysis using the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE) system provided by NSSP. ESSENCE provides UDOH with patient-level syndromic data for analysis and early detection of abnormal patterns in emergency visits. A total of 38 out of 48 acute care hospitals and multiple urgent care facilities are enrolled in the system in Utah. More than 90% of these hospitals report chief complaint data, and discharge data are available from about 15% of the facilities. Data were analyzed by querying key terms in the chief complaint field including: any entry of: ‘overdose’, drug and brand names for opioids, street names, ‘naloxone’, and miss-spellings. Exclusion terms included any mention of: ‘denies’, ‘quit’, ‘refill’, ‘withdraw’, ‘dependence’, etc. Data containing any ICD entry of: T40.0-T40.4, T40.60, and T40.69 were included in the analysis.Results: Between September 1, 2016 and August 31, 2017, Utah Department of Health identified 4,063 opioid-related overdose emergency department (ED) visits through the ESSENCE system using both chief complaint and discharge diagnosis queries. Of these visits, 3,865 (95%) were identified using chief complaints alone and 198 (5%) visits were added by searching the discharge diagnosis field. Opioid-related visits comprised approximately 0.3% of the total ED visits (1,267,244) reported during this time (Graph 1). More than half of the opioid-related emergency visits were reported from just five facilities. Rate of opioid-related visits ranging from 0 to 292 visits per 100,000 population per year (median: 108 visits per 100,000 population per year), with an overall rate for the state of 129 visits per100, 000 population per year. The highest rate of opioid-related visits occurred among patients aged 18 to 24 (219 visits per 100,000 population per year), and 59% of all opioid-related patients in Utah were female.Conclusions: The results presented are estimates of opioid-related overdoses reported using close to real-time data. These results would not include visits with incomplete or incorrectly coded chief complaints or discharge codes, or cases of opioid overdose who do not present to an emergency department or urgent care facility. The results from using syndromic data are consistent with existing surveillance findings using mortality data in Utah. This suggests that syndromic surveillance data are useful for rapidly capturing opioid events, which may allow for a timelier public health response. UDOH is currently evaluating syndromic surveillance data versus hospital discharge data for opioid-related emergency department visits, which may further optimize queries in ESSENCE, in order to provide improved opioid surveillance data to local public health partners. This analysis demonstrates that using syndromic surveillance data provides a more time-efficient alternative, enabling more rapid public health interventions, which improved opportunities to reduce opioid-related morbidity and mortality in Utah.

scholarly journals Towards an integrated animal health surveillance system in Tanzania: making better use of existing and potential data sources for early warning surveillance

2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Janeth George ◽  
Barbara Häsler ◽  
Erick Komba ◽  
Calvin Sindato ◽  
Mark Rweyemamu ◽  
...  
Keyword(s):  
Early Warning ◽  
Surveillance System ◽  
Animal Health ◽  
Health Surveillance ◽  
Surveillance Data ◽  
Data Sources ◽  
Surveillance Systems ◽  
Cross Sectional Survey ◽  
Traceability System ◽  
Spatial Coverage

Abstract Background Effective animal health surveillance systems require reliable, high-quality, and timely data for decision making. In Tanzania, the animal health surveillance system has been relying on a few data sources, which suffer from delays in reporting, underreporting, and high cost of data collection and transmission. The integration of data from multiple sources can enhance early detection and response to animal diseases and facilitate the early control of outbreaks. This study aimed to identify and assess existing and potential data sources for the animal health surveillance system in Tanzania and how they can be better used for early warning surveillance. The study used a mixed-method design to identify and assess data sources. Data were collected through document reviews, internet search, cross-sectional survey, key informant interviews, site visits, and non-participant observation. The assessment was done using pre-defined criteria. Results A total of 13 data sources were identified and assessed. Most surveillance data came from livestock farmers, slaughter facilities, and livestock markets; while animal dip sites were the least used sources. Commercial farms and veterinary shops, electronic surveillance tools like AfyaData and Event Mobile Application (EMA-i) and information systems such as the Tanzania National Livestock Identification and Traceability System (TANLITS) and Agricultural Routine Data System (ARDS) show potential to generate relevant data for the national animal health surveillance system. The common variables found across most sources were: the name of the place (12/13), animal type/species (12/13), syndromes (10/13) and number of affected animals (8/13). The majority of the sources had good surveillance data contents and were accessible with medium to maximum spatial coverage. However, there was significant variation in terms of data frequency, accuracy and cost. There were limited integration and coordination of data flow from the identified sources with minimum to non-existing automated data entry and transmission. Conclusion The study demonstrated how the available data sources have great potential for early warning surveillance in Tanzania. Both existing and potential data sources had complementary strengths and weaknesses; a multi-source surveillance system would be best placed to harness these different strengths.

scholarly journals Evaluation of Measles Surveillance Systems in Ginnir District, Bale Zone, Southeast Ethiopia: A Concurrent Embedded Mixed Quantitative/Qualitative Study 

2020 ◽  
Author(s):  
Falaho Sani ◽  
Mohammed Hasen ◽  
Mohammed Seid ◽  
Nuriya Umer
Keyword(s):  
Public Health ◽  
Qualitative Study ◽  
Surveillance System ◽  
Public Health Surveillance ◽  
Health Surveillance ◽  
Health Facilities ◽  
Surveillance Data ◽  
Surveillance Systems ◽  
Southeast Ethiopia ◽  
Bale Zone

Abstract Background: Public health surveillance systems should be evaluated periodically to ensure that the problems of public health importance are being monitored efficiently and effectively. Despite the widespread measles outbreak in Ginnir district of Bale zone in 2019, evaluation of measles surveillance system has not been conducted. Therefore, we evaluated the performance of measles surveillance system and its key attributes in Ginnir district, Southeast Ethiopia.Methods: We conducted a concurrent embedded mixed quantitative/qualitative study in August 2019 among 15 health facilities/study units in Ginnir district. Health facilities are selected using lottery method. The qualitative study involved purposively selected 15 key informants. Data were collected using semi-structured questionnaire adapted from Centers for Disease Control and Prevention guidelines for evaluating public health surveillance systems through face-to-face interview and record review. The quantitative findings were analyzed using Microsoft Excel 2016 and summarized by frequency and proportion. The qualitative findings were narrated and summarized based on thematic areas to supplement the quantitative findings.Results: The structure of surveillance data flow was from the community to the respective upper level. Emergency preparedness and response plan was available only at the district level. Completeness of weekly report was 95%, while timeliness was 87%. No regular analysis and interpretations of surveillance data, and the supportive supervision and feedback system was weak. The participation and willingness of surveillance stakeholders in implementation of the system was good. The surveillance system was found to be useful, easy to implement, representative and can accommodate and adapt to changing conditions. Report documentation and quality of data was poor at lower level health facilities. Stability of the system has been challenged by shortage of budget and logistics, staff turnover and lack of update trainings.Conclusions: The surveillance system was acceptable, useful, simple, flexible and representative. Data quality, timeliness and stability of the system were attributes that require improvement. The overall performance of measles surveillance system in the district was poor. Hence, regular analysis of data, preparation and dissemination of epidemiological bulletin, capacity building and regular supervision and feedback are recommended to enhance performance of the system.

Use of syndromic surveillance data to monitor poisonings and drug overdoses in state and local public health agencies

2016 ◽  
Vol 22 (Suppl 1) ◽  
pp. i43-i49 ◽  
Author(s):  
Amy Ising ◽  
Scott Proescholdbell ◽  
Katherine J Harmon ◽  
Nidhi Sachdeva ◽  
Stephen W Marshall ◽  
...  
Keyword(s):  
Public Health ◽  
Syndromic Surveillance ◽  
Surveillance Data ◽  
Local Public Health ◽  
Public Health Agencies ◽  
Health Agencies ◽  
Drug Overdoses ◽  
State And Local

scholarly journals Barriers to hospital electronic public health reporting and implications for the COVID-19 pandemic

2020 ◽  
Vol 27 (8) ◽  
pp. 1306-1309
Author(s):  
A Jay Holmgren ◽  
Nate C Apathy ◽  
Julia Adler-Milstein
Keyword(s):  
Public Health ◽  
Surveillance Data ◽  
Electronic Data ◽  
American Hospital ◽  
American Hospital Association ◽  
Public Health Agencies ◽  
Hospital Referral ◽  
Health Agencies ◽  
The Impact ◽  
To Receive

Abstract We sought to identify barriers to hospital reporting of electronic surveillance data to local, state, and federal public health agencies and the impact on areas projected to be overwhelmed by the COVID-19 pandemic. Using 2018 American Hospital Association data, we identified barriers to surveillance data reporting and combined this with data on the projected impact of the COVID-19 pandemic on hospital capacity at the hospital referral region level. Our results find the most common barrier was public health agencies lacked the capacity to electronically receive data, with 41.2% of all hospitals reporting it. We also identified 31 hospital referral regions in the top quartile of projected bed capacity needed for COVID-19 patients in which over half of hospitals in the area reported that the relevant public health agency was unable to receive electronic data. Public health agencies’ inability to receive electronic data is the most prominent hospital-reported barrier to effective syndromic surveillance. This reflects the policy commitment of investing in information technology for hospitals without a concomitant investment in IT infrastructure for state and local public health agencies.

scholarly journals A stastistical system for detecting Salmonella outbreaks in British livestock

2006 ◽  
Vol 134 (5) ◽  
pp. 952-960 ◽  
Author(s):  
R. KOSMIDER ◽  
L. KELLY ◽  
S. EVANS ◽  
G. GETTINBY
Keyword(s):  
Public Health ◽  
Early Detection ◽  
Detection System ◽  
Animal Health ◽  
Health Surveillance ◽  
Current Data ◽  
Surveillance Data ◽  
Data Types ◽  
Data Collection Process ◽  
Health Surveillance Data

Worldwide, early detection systems have been used in public health to aid the timely detection of increases in disease reporting that may be indicative of an outbreak. To date, their application to animal surveillance has been limited and statistical methods to analyse human health data have not been viewed as being applicable for animal health surveillance data. This issue was investigated by developing an early detection system for Salmonella disease in British livestock. We conclude that an early detection system, as for public health surveillance, can be an effective tool for enhanced surveillance. In order to implement this system in the future and extend it for other data types, we provide recommendations for improving the current data collection process. These recommendations will ensure that quality surveillance data are collected and used effectively to monitor disease in livestock populations.

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