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ISDS 2012 Conference Abstracts

Using Cultural Modeling to Inform a NEDSS-Compatible
System Functionality Evaluation
Olympia Anderson and Miguel Torres-Urquidy*

Centers for Disease Control and Prevention, Atlanta, GA, USA

Objective
The culture by which public health professionals work defines their

organizational objectives, expectations, policies, and values. These
aspects of culture are often intangible and difficult to qualify. The in-
troduction of an information system could further complicate the cul-
ture of a jurisdiction if the intangibles of a culture are not clearly
understood. This report describes how cultural modeling can be used
to capture intangible elements or factors that may affect NEDSS-
compatible (NC) system functionalities within the culture of public
health jurisdictions.

Introduction
The National Notifiable Disease Surveillance System (NNDSS)

comprises many activities including collaborations, processes, stan-
dards, and systems which support gathering data from US states and
territories. As part of NNDSS, the National Electronic Disease Sur-
veillance System (NEDSS) provides the standards, tools, and re-
sources to support reporting public health jurisdictions (jurisdictions).
The NEDSS Base System (NBS) is a CDC-developed, software ap-
plication available to jurisdictions to collect, manage, analyze and re-
port national notifiable disease (NND) data. An evaluation of NEDSS
with the objective of identifying the functionalities of NC systems
and the impact of these features on the user’s culture is underway.

Methods
We used cultural models to capture additional NC system func-

tionality gaps within the culture of the user. Cultural modeling is a
process of graphically depicting people and organizations referred to
as influencers and the intangible factors that affect the user’s opera-
tions or work as influences. Influencers are denoted as bubbles while
influences are depicted as arrows penetrating the bubbles. In the cul-
tural model, influence can be seen by the size and proximity (or lack
of) in the model. We restricted the models to secondary data sources
and interviews of CDC programs (data users) and public health ju-
risdictions (data reporters).

Results
Three cultural models were developed from the secondary infor-

mation sources; these models include the NBS vendor, public health
jurisdiction (jurisdiction) activities, and NEDSS technical consult-
ants. The vendor cultural model identified channels of communica-
tion about functionalities flowing from the vendor and the NBS users
with CDC as the approval mechanism. The jurisdiction activities
model highlighted perceived issues external to the organization that
had some impact in their organization. Key disconnecting issues in
the jurisdiction model included situational awareness, data compe-
tency, and bureaucracy. This model also identified poor coordination
as a major influencer of the jurisdiction’s activities. The NEDSS tech-
nical model identified major issues and disconnects among data ac-

cess, capture and reporting, processing, and ELR functionalities (Fig-
ure 1). The data processing functionality resulted in the largest neg-
ative influencer with issues that included: loss of data specificity,
lengthy submission strategies, and risk of data use. Collectively, the
models depict issues with the system functionality but mostly iden-
tify other factors that may influence how jurisdictions use the sys-
tem, moreover determining the functionalities to be included.

Conclusions
By using the cultural model as a guide, we are able to clarify com-

plex relationships using multiple data sources and improve our un-
derstanding of the impacts of the NC system functionalities on user’s
operations. Modeling the recipients of the data (e.g. CDC programs)
will provide insight on additional factors that may inform the NEDSS
evaluation.

Figure 1. Cultural model from a NEDSS technical consultation meeting.

Keywords
evaluation; cultural modeling; functionality; NEDSS

Acknowledgments

We acknowledge the leadership and staff of CDC’s stakeholders and the
Division of Notifiable Disease and Healthcare Information.

References

Beyer H, Holtzblatt K. Contextual Design: Defining Customer-Centered
Systems. San Diego (CA): Academic Press; 1998.

*Miguel Torres-Urquidy
E-mail: jvu5@cdc.gov

Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * 5(1):e84, 2013