Taylor Christopher

Under the Electronic Health Record Incentive Program Rule, hospitals are eligible to receive incentive payments from the Centers of Medicare and Medicaid Services provided they meet certain requirements including Meaningful Use (MU). Demonstrating MU requires meeting a core and menu set of objectives including the capability to submit electronic syndromic surveillance, Electronic Lab Reporting (ELR), and immunization data in accordance with state law and practice. NH is building a NH Heath Information Exchange to serve all NH's MU needs including those of public health. This represents a huge opportunity for public health to collect more data to enhance disease detection and control, improve safety, and reduce health disparities, but also presents an integration challenge.

Objective

To describe steps used to build the required infrastructure to meet Public Health MU reporting requirements for electronic syndromic surveillance, ELR, and immunization data in NH Division of Public Health Services.

In response to the terrorist attack of September 11, 2001, the NH Department of Health and Human Services (NH DHHS) engaged state and external partners in the design of an early warning surveillance system to support bioterrorism and emergency preparedness. Initially, NH DHHS began collecting four syndrome counts from thirteen hospital Emergency Departments (ED) by fax. Automation began in 2002, when an over the counter (OTC) syndromic surveillance pilot system was implemented by Scientific Technologies Corporation (STC). In 2003-2004 this system, the Syndromic Tracking and Encounter Management System (STEMS), was expanded to include school absentee and occupational health reports. Over time, an internal Death Data application was automated to query vital record deaths, and in 2005 a real-time ED surveillance pilot, the Automated Hospital ED Data System (AHEDD), was developed by STC to replace manual ED surveillance. Over the past decade NH continued to expand the original concept with innovative approaches to identify undetected or under reported disease outbreaks.

Objective

To illustrate development of syndromic surveillance in NH, share innovation experience with the public health community, and contribute to the syndromic surveillance body of knowledge in the new public health Information Technology landscape.

In April 2009, a novel strain of influenza A was detected in Mexico, which quickly spread to the United States and the rest of the world. In response to the pandemic, the New Hampshire Department of Health and Human Services (NH DHHS) developed a web-based school absenteeism reporting system to track and record overall absenteeism and influenza-like-illness (ILI) related absenteeism in New Hampshire schools.

Objective

To monitor community illness and detect outbreaks during the 2009 influenza A/H1N1 pandemic using a newly developed surveillance system for monitoring school absenteeism.

The Automated Hospital Emergency Department Data System is designed to detect early indicators of bioterrorism events and naturally occurring public health threats. Four investigatory tools have been developed with drill-down detail reporting: 1. Syndromic Alerting, 2. Chief Complaint Data Mining, 3. ICD9 Code Disease, and 4. Influenza-Like-Illness Tracking.

All analysis processing runs on the server in seconds using ORACLE PL/SQL stored procedures and arrays.

Objective

This paper details the development of electronic surveillance tools by Communicable Disease Surveillance, which have increased detection and investigation capabilities.

Syndromic surveillance is focused upon organizing data into categories to detect medium to large scale clusters of illness. Detection often requires that a critical threshold be surpassed. Data mining searches through data to identify records containing keywords. New Hampshire has combined data mining with syndromic surveillance since January 2003 to improve detection capacity.

Objective

1. Understand the principles behind the use of syndromic surveillance and data mining. 2. Understand how New Hampshire's unique approach combining data mining with syndromic surveillance has enhanced disease surveillance efforts. 3. Describe the steps and code necessary to implement and enhance data mining.

The Death Certificate Surveillance was implemented in October 2001 to enhance New Hampshire's ability to monitor for bioterrorism and other public health threats, such as communicable diseases and chemical exposures. In 2003, this surveillance system was automated. Death certificates become available for review by disease surveillance staff within 24 hours of filing. Learning objectives: 1. Discuss the value of death certificate surveillance in detecting communicable disease 2. Explain the death certificate review process 3. Describe how death certificate surveillance can be automated.