This presentation will focus on health managment information systems (HMIS) and surveillance activities in resource limited settings. The presenters will discuss how systems could be enhanced using smart phones or other innovative technologies and provide examples of ongoing applications in the field.
Panelists
Marion McNabb, MPH, DrPh Candidate, Program Manager, DGAP, Center for Global Health and Development, Boston University School of Public Health
Join ISDS for a presentation on public health quality measures in the context of surveillance activities by Peggy Honoré from the US Department of Health and Human Services. Quality in healthcare and public health must serve as a catalyst for improving the health of the nation. While organized efforts to address healthcare quality have advanced rigorously in recent years, progress in public health quality is beginning to emerge as well. Contributing to this effort is a framework for public health quality released by the US Department of Health and Human Services.
BioSense 2.0 has become a platform for technical receipt and analysis of syndromic surveillance data for many jurisdictions nationwide, as well as a collaborative effort that has engaged a larger community of syndromic surveillance practitioners, Governance Group, and federal agencies and organizations. The potential longterm benefits of BioSense 2.0 for resource and data sharing have at times been overshadowed by the short-term limitations of the system and disconnected efforts among the CoP. In May 2014, representatives from 41 jurisdictions attended a 2-day, in-person meeting where four workgroups were formed to address on-boarding, data quality, data sharing and syndrome definition in an effort to advance changes that resonate with actual surveillance practice.
Objective
This roundtable will provide a forum for the syndromic surveillance Community of Practice (CoP) to learn about activities of the BioSense 2.0 User Group (BUG) workgroups that address priority issues in syndromic surveillance. It will be an opportunity to discuss key challenges faced by public health jurisdictions in the era of Meaningful Use and identify further needs and best practices in the areas of data quality, data sharing, onboarding, and developing syndrome definitions.
Current local, state, and national initiatives related to meaningful use and the modernization of electronic health records, and the growing availability of electronic information exchanges, have become important drivers to establishing syndromic surveillance systems. Effective implementation of electronic syndromic surveillance interfaces requires approaches that ensure the receipt of quality, timely, and reliable information.
While there are published specifications for the HL7 ADT message and National Institute of Standards and Technology (NIST) validation tools, there has been little documentation about the necessary steps for a local public health department to validate and confirm that an interface that is producing consistent and quality information. The lack of effective validation efforts has led to incomplete or inconsistent data utilized by syndromic systems and their intended audiences.
The County of San Diego has developed and utilized a framework for validating new syndromic interfaces. This presentation will highlight several pragmatic methods to validate the HL7 message content, provide specific examples of validation, and describe the pitfalls that could result from a poorly validated syndromic interface.
Real-time emergency department (ED) data are currently received from 78 of 80 New Jersey acute care and satellite EDs by Health Monitoring Systems Inc.’s (HMS) EpiCenter system. EpiCenter collects, manages and analyzes ED registration data for syndromic surveillance, and provides alerts to state and local health departments for surveillance anomalies. After the 2012 Superstorm Sandy devastated parts of New Jersey, NJDOH initiated a plan to develop severe weather surveillance using EpiCenter to provide the Department with the ability to track both health and mental health concerns during adverse weather conditions to alert the public about emerging health hazards.
Objective
To describe the development and validation of a mental health classification to track emergency department visits for potential needed public health response during severe weather events.
Since its inception in 2008, PHO has grown through new funding to establish the agency, as well as a series of program transfers from the Government of Ontario, including ID surveillance. PHO’s current role in ID surveillance in Ontario is to support the public health and health care systems with surveillance information, tools, and resources for the prevention and control of IDs. PHO also provides scientific and technical expertise for IDs, including different aspects of surveillance (e.g., data entry requirements, statistical algorithms, provincial surveillance reports).
The overarching aim of the framework is to establish PHO’s key priorities, strategies, and actions to guide ID surveillance over the next five years and will help advance ID surveillance across Ontario. This is PHO’s first step towards a strategic and coordinated approach to ID surveillance.
Objective
This presentation will outline the development process for Public Health Ontario’s (PHO’s) first Infectious Disease Surveillance Framework (the framework), highlight key elements of the framework, and identify examples of infectious disease (ID) surveillance activities and projects that align with the framework.
Before the launch of standard National Health Information System (NMHIS) in 2000, there had been acute paucity of reliable and timely health information in Pakistan. Health Departments had no choice than to resort to estimates or carry expensive community based surveys to determine the disease incidence. After the development and deployment of NHMIS, overall Health System is reshaping itself based upon the regular and frequent information now available on a good number number of priority health problems. This is system is now offering tremendous opportunities for promoting the cause of evidence based decision making and monitoring of its expanded health care structure. This effort had led to putting in place a standard system of data collection and transmission from roughly 13000 public health services (both urban and rural ). The new system is now able to promptly locate pockets of vulnerable communities reporting high disease incidence.
Objective
Purpose of this abstract is to show how launch of a standard National Health Information System is has become the main national data source, and is, playing a pivotal role in facilitating decision making in health care system in Pakistan.
ILINet is used nationwide by sentinel healthcare providers for reporting weekly outpatient visit numbers for influenza-like illness to CDC. The Florida Department of Health receives urgent care center (UCC) data through ESSENCE from participating facilities. Seminole County is unique in that its four sentinel providers located in separate UCCs report into both systems, and all their discharge diagnoses are available through ESSENCE. However, the reported number of patients being discharged from those providers with diagnoses of influenza is not equivalent to the number of cases reported into ILINet. Data from the two systems were therefore compared both among and between the individual sentinel providers in order to determine the extent of the variation over four influenza seasons.
Objective
To compare influenza-like illness (ILI) data reported to the Centers for Disease Control and Prevention (CDC) U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet) with discharge diagnosis data for influenza from the same reporting source obtained through the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE) in Seminole County, Florida.
Data from the Emergency Departments (EDs) of 49 hospitals in New York City (NYC) is sent to the Department of Health and Mental Hygiene (DOHMH) daily as part of the syndromic surveillance system. Currently, thirty-four of the EDs transmit data as flat files. As part of the Center for Medicare and Medicaid Services Electronic Health Record Incentive Program, otherwise known as Meaningful Use, many EDs in our system have switched or are in the process of switching to HL7 Messaging Standard Version 2.5.1. Given there may be differences in data completeness, quality, and content between the new HL7 data and legacy data, we evaluated data sent in both formats in parallel by several EDs.
Objective
To evaluate potential changes in emergency department (ED) syndromic surveillance data quality, as hospitals shift from sending data as flat file format (Legacy Data) to real-time/batch HL7 Messaging Standard Version 2.5.1, in compliance with Meaningful Use requirements.
Per a frequently asked questions document on the ISDS website, approximately two thirds of HL7 records received in BioSense do not provide a Visit ID. As a result, BioSense data processing rules use the patient ID, facility ID and earliest date in the record to identify a unique visit. If the earliest dates in records with the same patient ID and facility ID occur within the same 24-hour time frame, those two visits are combined into one visit and the earliest date will be stored. The ED data sent by hospitals to NC DETECT include unique visit IDs and these are used to identify unique visits in NC DETECT. These data are also sent twice daily to BioSense. In order to assess the potential differences between the NC DETECT ED data in NC DETECT and the NC DETECT ED data in BioSense, an initial analysis of the 24-hour rule was performed.
Objective
NC DETECT emergency department (ED) data were analyzed to assess the impact of applying the BioSense “24-hour rule” that combines ED visits into a single visit if the patient ID and facility ID are the same and the earliest recorded dates occur within the same 24-hour time frame.