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Exploration of Ontological Management of Reportable Events to Facilitate Surveillance

Project Name: Exploration of Ontological Management of Reportable Events to Facilitate Surveillance

Project Status: Proposed

Point of Contact  Laura Conn

Center: Center for Surveillance, Epidemiology, and Laboratory Services

Keywords: Reportable event, ontology, data integration, national surveillance

Project Description: In 2013 the CDC piloted the Reportable Conditions Knowledge Management System (RCKMS), to nationally consolidate the different facets of reporting. As part of this effort the knowledge management working group convened public health experts to assess the potential for ontological representation of concepts in this domain. The workgroup identified concepts that can be represented using coded values from existing external resources, and identified gaps where current resources are not sufficient. This work was presented at the biomedical informatics conference, AMIA 2014 (3). Work by Panhuis et. al. (4) in 2013 highlights the need for computable and publically available data related to public health reporting, to allow analysis of long term disease patterns. In their study, they mobilized historical data to observe contagious disease changes over time. They noted that a total of 56 notifable diseases were reportable, but none continuously over the 1888 and 2013 period. The changes they observed reflect the shifting public health priorities and challenges. In this preliminary study, we aim to facilitate the unification and consolidation of reporting terminology to enable such studies.

Potential impact: Once conditions are reported to a state or other jurisdictional public health agency, case definitions are used to determine which reports should be forwarded from the ‘local’ public health agency to the CDC for national surveillance. The logic for defining a confirmed or probable case (i.e. case definitions) for each condition tracked on a national level is available in HTML on the CDC website (1). In addition, the coded concepts for these nationally notifiable events and other selected relevant value sets of coded concepts are available on the PHIN VADS website managed by the CDC (2). While the nationally notifiable conditions are similar to reportable events, they do not include all conditions and criteria for reporting in a given jurisdiction. In addition, the conditions change over time, but the reasons for change and relationship between current and previous conditions are not captured.

Applicability for reuse within other public health programs: The workgroup reviewed user stories provided by the following stakeholders groups: epidemiologist working at a state or local health department, CDC epidemiologist, knowledge curator/terminologist, reporter, researcher, EHR vendor, laboratorian, and public health official. The following user stories reflect some of the areas impacted by the inconsistencies in reportable event description and management. Each set of stories includes a variety of stakeholders but similar data structure needs, and demonstrates the need to align reportable events to enable integrated surveillance across jurisdictions.

  1. User stories addressing relationships between reportable events by jurisdiction: Story example: “I am the epidemiologist for the communicable diseases branch of my health department and I would like to see the reporting specifications for all conditions in our neighboring jurisdictions to compare against ours. In order to compare the criteria for a given reportable topic, there needs to be a way to link similar reportable events with different names or different criteria for the topic.” Resource example: Show the criteria for reporting pertussis-related events from a lab or clinical setting for the following spatial contexts: Utah and Colorado. The system would need to know that pertussis and whooping cough were the same.
  2. User stories that require understanding about the relationship between semantic changes in reportable events. Story example: “I am an epidemiologist defining a new or updating a reportable event and need to decide which subset of a condition should be made reportable. To improve consistency across jurisdictions, I want to find related conditions from other jurisdictions and be able to view hierarchical relationships across related conditions.” Resource example: In Utah, the condition ‘Hantavirus infection and pulmonary syndrome’ was retired and replaced by ‘Hantavirus pulmonary syndrome’. In Colorado however, the change has yet to be made. What is the relationship between the two terms and the nationally notifiable condition used for national surveillance?
  3. User stories related to linking national surveillance to reportable events. Story example: “I am the CDC epidemiologist with the National Notifiable Disease Surveillance System (NNDSS) and I need to know if states are collecting information, in other words does the state include relevant reportable events in their jurisdiction to assert that a given state is reporting Nationally Notifiable Conditions (NNCs) for their jurisdiction. Currently, this knowledge is manually derived from CSTE’s State Reportable Condition Assessment (SRCA), which is retrospective and difficult to interpret.” Resource example: Each year, CDC’s NNDSS needs to know if each nationally notifiable condition is or is not reportable in each jurisdiction. This requires knowledge of each reportable condition in each jurisdiction and to understand whether or not it should map to a specific nationally notifiable condition for the surveillance year.
  4. User story that combines semantic changes over time and national surveillance. Story example: I am a researcher reviewing notifiable condition reports for Shiga toxin-producing Escherichia coli over the last 10 years. I want to take into account changes in naming and classification at the national level as well as differences in how jurisdictions report the disease so my data is inclusive of all the reports that are applicable. Resource example: Three notifiable conditions (Enterohemorrhagic Escherichia coli (EHEC) shiga toxin+ (serogroup non-O157), Enterohemorrhagic Escherichia coli (EHEC) O157:H7, and Enterohemorrhagic Escherichia coli (EHEC) shiga toxin+ (not serogrouped)) were retired in 2006 and replaced by the supertype Shiga toxin-producing Escherichia coli (STEC).

Methodology: The RCKMS knowledge working group provided recommendations for domains of knowledge to be managed using ontologies. An ontology of reportable events would allow this project to meet the surveillance and querying requirements defined by the user stories. The concepts to be managed by this ontology are the events, the relationships between active and retired events, the relationship between national and state-defined events and the criteria associated with given events. A reportable event ontology is a complex undertaking that involves management of concepts from the national and jurisdictional level. This is of high priority. The surveillance use cases require epidemiologists to be able to track conditions over time, but the events that capture the conditions change. The querying-based use cases need to be able to evaluate what is currently reported, with what was previously reported, and to do so across changes at the state/local jurisdiction level, as well as at the national level. Therefore, the ontology would need to relate the reportable events to their criteria, and how they relate to each other. A key component of this reportable event ontology will be defining the relationships that exist between events that are currently used, such as replaced_by. This will allow us to understand the evolution of the usage of a condition.

Expected results: In the course of collecting the artifacts and developing an ontology we expect to uncover patterns and inconsistencies in the current management of the life cycle of reportable events. We will present this back to the CDC/NNDSS as a set of observations and recommendations. We will develop an ontology and corresponding data relating the time periods of usage to the condition names. We will link the jurisdiction level events to the national level events for 3 states. We expect to find both overlapping and unique events. We have at least two time points capturing reportable conditions for these states. We expect to uncover the processes needed to map and manage local and national events.

For more information about this project, please contact the CHIIC at chiic@cdc.gov or Brian Lee at brian.lee@cdc.hhs.gov.

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