Electronic Case Reporting Development, Implementation, and Expansion in the United States.

INTRODUCTION: The COVID-19 pandemic highlighted the need for a nationwide health information technology solution that could improve upon manual case reporting and decrease the clinical and administrative burden on the US health care system. We describe the development, implementation, and nationwide expansion of electronic case reporting (eCR), including its effect on public health surveillance and pandemic readiness. METHODS: Multidisciplinary teams developed and implemented a standards-based, shared, scalable, and interoperable eCR infrastructure during 2014-2020. From January 27, 2020, to January 7, 2023, the team conducted a nationwide scale-up effort and determined the number of eCR-capable electronic health record (EHR) products, the number of reportable conditions available within the infrastructure, and technical connections of health care organizations (HCOs) and jurisdictional public health agencies (PHAs) to the eCR infrastructure. The team also conducted data quality studies to determine whether HCOs were discontinuing manual case reporting and early results of eCR timeliness. RESULTS: During the study period, the number of eCR-capable EHR products developed or in development increased 11-fold (from 3 to 33), the number of reportable conditions available increased 28-fold (from 6 to 173), the number of HCOs connected to the eCR infrastructure increased 143-fold (from 153 to 22 000), and the number of jurisdictional PHAs connected to the eCR infrastructure increased 2.75-fold (from 24 to 66). Data quality reviews with PHAs resulted in select HCOs discontinuing manual case reporting and using eCR-exclusive case reporting in 13 PHA jurisdictions. The timeliness of eCR was <1 minute. PRACTICE IMPLICATIONS: The growth of eCR can revolutionize public health case surveillance by producing data that are more timely and complete than manual case reporting while reducing reporting burden.

The Public Health Information Network (PHIN) Preparedness initiative.

The Public Health Information Network (PHIN) Preparedness initiative strives to implement, on an accelerated pace, a consistent national network of information systems that will support public health in being prepared for public health emergencies. Using the principles and practices of the broader PHIN initiative, PHIN Preparedness concentrates in the short term on ensuring that all public health jurisdictions have, or have access to, systems to accomplish known preparedness functions. The PHIN Preparedness initiative defines functional requirements, technical standards and specifications, and a process to achieve consistency and interconnectedness of preparedness systems across public health.

BioSense--a national initiative for early detection and quantification of public health emergencies.

BioSense is a national initiative to enhance the nation's capability to rapidly detect, quantify, and localize public health emergencies, particularly biologic terrorism, by accessing and analyzing diagnostic and prediagnostic health data. BioSense will establish near real-time electronic transmission of data to local, state, and federal public health agencies from national, regional, and local health data sources (e.g., clinical laboratories, hospital systems, ambulatory care sites, health plans, U.S. Department of Defense and Veterans Administration medical treatment facilities, and pharmacy chains).

Introduction of a hierarchy to LOINC to facilitate public health reporting.

Public health reporting of laboratory results requires unambiguous identification of the test performed and the result observed. Some laboratories are currently using Logical Observation Identifier Names and Codes (LOINC) for the electronic reporting of laboratory tests and their results to public health departments. Initial use revealed inconsistent identification and use of LOINC concepts by laboratories and public health agencies and an inability to systematically extend, for public health use, the tables when adding new concepts. We applied simple, logical rules to existing LOINC concepts to facilitate the creation of a hierarchy of concepts and to allow the identification and specification of appropriate terms for public health reporting and subsequent data aggregation. The hierarchy also allows the systematic addition of new concepts further supporting public health reporting. Application of the hierarchy is illustrated by using all laboratory LOINC concepts assigned to the subset of microbiology test types (CLASS MICRO).