No. 1, January 2006
TOOLS & TECHNIQUES
Development of the Diabetes Indicators and Data
Sources Internet Tool (DIDIT)
Qaiser Mukhtar, PhD, Prachi Mehta, DrPH, Erica R. Brody, MPH, Jenny Camponeschi, MS, Michael Friedrichs, MS, Angela M. Kemple, MS, Brenda Ralls,
Suggested citation for this article: Mukhtar Q, Mehta P, Brody ER, Camponeschi J, Friedrichs M, Kemple AM, et al. Development of the Diabetes Indicators and Data Sources Internet Tool (DIDIT). Prev Chronic Dis [serial online] 2006 Jan [date cited].
Available from: URL: http://www.cdc.gov/pcd/issues/2006/
Developing a Web-based tool that involves the input, buy-in, and
collaboration of multiple stakeholders and contractors is a complex process.
Several elements facilitated the development of the Web-based
Diabetes Indicators and Data Sources Internet Tool (DIDIT). The DIDIT is
designed to enhance the ability of staff within the state-based
Diabetes Prevention and Control Programs (DPCPs) and the Centers for Disease
Control and Prevention (CDC) to perform diabetes surveillance. It contains
information on 38 diabetes indicators (measures of health or factors
associated with health) and 12 national- and state-level data sources. Developing the DIDIT
required one contractor to conduct research on content for diabetes indicators
and data sources and another contractor to develop the Web-based application
to house and manage the information. During 3 years, a work group composed of
representatives from the DPCPs and the Division of Diabetes Translation (DDT)
at the CDC guided the development process by 1) gathering information on and
communicating the needs of users and their vision for the DIDIT, 2) reviewing
and approving content, and 3) providing input into the design and system
functions. Strong leadership and vision of the project lead,
clear communication and collaboration among all team members, and a
commitment from the management of the DDT were essential elements in
developing and implementing the DIDIT. Expertise in diabetes surveillance
and software development, enthusiasm, and dedication were also instrumental in
developing the DIDIT.
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The Diabetes Indicators and Data Sources Internet Tool (DIDIT) is a
Web-based resource designed to strengthen the capacity of the staff and
partners of state-based Diabetes Prevention and Control Programs (DPCPs) and
staff of the Centers for Disease Control and Prevention (CDC) to conduct
diabetes surveillance and program evaluation. The tool contains detailed
information on 38 diabetes indicators (measures of health or factors
associated with health) and their associated data sources (e.g., Behavioral
Risk Factor Surveillance System [BRFSS]). The content, design, and function of the DIDIT have been described elsewhere (1). This article
describes the process of developing the DIDIT, beginning with the conceptual
phase and proceeding through the content and systems phases
(Table 1). In so
doing, we provide an example for other agencies and organizations as well as
other entities within the CDC that are interested in developing a similar tool.
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Developing the Concept and Content
The DIDIT was developed in response to a request from the DPCPs for
technical assistance in surveillance and program evaluation (2). In August
2001, a work group comprised of representatives from the CDC’s Division of
Diabetes Translation (DDT) and eight DPCPs (representing Alabama, Minnesota,
Montana, New Mexico, New York, Oregon, Utah, and Wisconsin) was convened to
develop a tool that would provide comprehensive information about 1) diabetes
indicators (e.g., foot examinations, diabetes-related hospitalizations) and 2) their associated data sources (e.g., BRFSS, Medicare) in one
centralized place. The work group generated a list of 55 indicators (later
reduced to 38) and developed an outline describing the desired contents and
format of a tool called the diabetes indicator tool.
In October 2001, an overview and vision of the DIDIT was presented to six
focus groups at the annual meeting of DPCP directors. Three key themes
- The DIDIT should be a Web-based application to allow for content updates and easy accessibility (in contrast to a CD-ROM).
- The DIDIT should be a reference tool that promotes consistency and
standardization of data analysis required for diabetes surveillance.
- The tool’s development should continue to be informed by DPCP
representatives (the intended user group) to ensure that it meets the
needs of program staff involved in diabetes surveillance.
Input from these initial focus groups and subsequent feedback from the DPCPs
served as the basis for developing the concept, content, and Web application
for the DIDIT.
Development of content
Content development took place in two stages. During the first stage, the
work group selected 10 of the originally identified 55 indicators to develop a
prototype. The 10 indicators were as follows: 1) diabetes prevalence, 2)
annual hemoglobin A1c test, 3) annual influenza vaccination, 4) pneumococcal
vaccination, 5) level of diabetes education, 6) diabetes-related
hospitalizations, 7) prevalence of end-stage renal disease, 8) hospitalization
for lower extremity amputations, 9) physical inactivity, and 10) overweight.
Because members of the work group lived in
different states, discussions were conducted through a series of telephone
conferences and two in-person meetings.
During the second stage, the work group selected an additional 28
indicators from the original 55 through a two-round modified Delphi process.
Indicators were ranked in priority according to the following four criteria:
- Relationship to a national policy objective (such as the DDT’s national
diabetes objectives  or Healthy People 2010 objectives
- Alignment with current practice guidelines, such as those from the
American Diabetes Association (4)
- Responsiveness to efforts of the DPCPs
- Measurability through public data sources, particularly state-level
data such as the BRFSS (5)
The typical reason for excluding an indicator was that no state-level data
source could be identified to measure it. A list of indicators that were
excluded and the rationale for excluding them can be found on the DIDIT
(available from www.cdc.gov/diabetes/statistics/index.htm). All 10 indicators
used to develop the prototype as well as all 28 selected during the second
stage were retained, with a total of 38 indicators selected for inclusion. At
this stage, the selection of fields to
describe each indicator (e.g., definitions of indicators) and data source (e.g., its methodology for data
collection, data access) was also finalized with input from the DIDIT work
After selecting indicators, associated data sources, and their related
fields of information, the DIDIT team, including work group members,
contractors for both content and Web site development, and DDT leaders, met in
January 2003 (Table 1). The major focus of the meeting was to develop a
process to ensure that the information included in the DIDIT was accurate and
complete. The work group viewed the Web-based prototype with 10 indicators and
eight associated data sources. Each work group member was assigned a set of
indicators from the group of 38 to review and revise.
During content development, a contractor researched information on selected
indicators and their associated data sources,
and the work group provided feedback on its accuracy and completeness.
Comments and suggestions on content were discussed during monthly conference
calls, and the content was approved by all work group members before it was
finalized. A second in-person meeting was held to review and refine content
and to ensure that the process of reviewing content was efficient and
effective. The protocol for developing and refining content resulted in
valuable end-user feedback. Development of the Web-based application took place at the same time as
development of content.
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Developing the Web-based Application
The parallel development of the application and its content relied on the
software development life cycle (Table 2). This process included the
following four major phases: 1) planning, 2) analysis, 3)
design, and 4) implementation (6). We adopted an iterative and
incremental approach, with overlap between analysis, design, and
Phase 1: planning
The primary purpose of project planning was to articulate the
objectives and scope of the DIDIT and ensure the technical feasibility
of the system.
We noted previously that the purpose and vision for the DIDIT were defined early
during the concept development phase. During the project planning phase, the
work group articulated the purpose and vision to the technical contractors,
and they produced a document that outlined the definition and scope of the
project; this document served as a blueprint for system development efforts.
Additional activities in this phase included confirming the project’s
operational and organizational feasibility, developing a schedule, estimating
costs, and allocating resources. The project planning phase culminated in the
development of a final project plan, which was reviewed by the project lead
and management staff. After the plan was approved, technical development
efforts, or systems analysis, for the DIDIT were initiated.
Phase 2: analysis
The analysis phase defined in detail what the information system
needed to accomplish to provide users with the benefits they desired. Several
storyboards were created to display preliminary design options for Web page
content and format. The storyboards were uploaded onto a secure Internet site
to allow sharing among and feedback from a geographically dispersed user
group. As design options were presented, users were quickly able to provide
comments. An iterative feedback process allowed further revisions to DIDIT
storyboards. System requirements were prioritized as they were identified.
The analysis phase culminated with the development of model diagrams, which
were used to drive the next phase, system design.
Phase 3: design
While the analysis phase focused on what the system should do, the design
phase focused on how the system should function. Information from the analysis
phase was used to design the application, the database, the user interface,
and the operating environment. The application and database were designed in
parallel with the user interface. The user interface is a critical component because
it ensures ease of use. It was designed with stakeholder input to ensure that
the final product would reflect stakeholder needs.
Phase 4: implementation
During the implementation phase, a demonstration model was built,
tested, and released with information on the 10 pilot indicators and
associated data sources. The model included core functionalities such as the
ability to browse, sort, and search, and it was demonstrated at the first
in-person work group meeting in early 2003. Input was solicited on additional
features, including the addition of DPCP-specific data sources,
system-searching functions, and report formats.
Phase 4a: Merging the content and the Web system
After the demonstration model was developed, the development of the content
and the Web system converged. The work group began using the DIDIT to review
and refine the content of indicators and data sources. The contractor
responsible for researching and developing the content delivered a data set on
indicators and data sources to the systems developers for upload into the
DIDIT. Once uploaded, the content was reviewed by the work group, and
appropriate modifications were made. This process took place iteratively
between February and April 2003, with a total of three uploads, until all 38
indicators and 12 data sources had been uploaded, reviewed, and finalized. An
unexpected positive outcome from this process was that as the work group
reviewed DIDIT content, it also tested and evaluated system functionality and
design, leading to several important changes.
Rationale for Conducting Pilot Tests of the Diabetes
Indicators and Data Sources Internet Tool (DIDIT)
1. Provides validation that system function, design, and content are
consistent with the responses elicited from users during the processes
of requirements gathering and usability testing. This validation closes
the information loop and confirms earlier assumptions.
2. Enables exploration of requirements or
ideas suggested by users after the processes of requirements gathering
and usability testing are complete. Although it might be too late to
include these features in the first release, they can be incorporated
into later phases.
3. Allows users to work with a real-life model, permitting
them to visualize and respond to more advanced requirements they may
find difficult to comprehend without such a model. Users also understand
more advanced requirements when they can work with a system designed for
fundamental needs and functions. In addition, requirements often build
on one another.
4. Permits testing among a small subset of a large population of
users, preferably subsets that differ from those selected in earlier
development phases. This ensures a more representative sampling
throughout the development process, and it ensures that feedback is
well-rounded and unbiased. Although not all
suggestions made during the pilot-testing phase are ultimately
incorporated, the process often sparks ideas for future enhancements and
provides insights for training and user support.
Before the DIDIT was formally implemented in September 2003, both usability
testing and pilot testing were conducted to obtain user feedback about system
design and usage to further refine the new tool. Usability testing was
conducted in April 2003 at the DDT national conference, with pilot testing in
July and August 2003 through conference calls and NetMeeting (Microsoft Corp,
Redmond, Wash). NetMeeting allowed participants throughout the nation to
view the DIDIT as it was being demonstrated at the CDC in Atlanta, Ga. Pilot
testing is a critical and often overlooked component of the software life
cycle, and there are important reasons for conducting it (Sidebar). The objective of usability testing and pilot testing was to
formally validate that system function, design, and content were consistent
with the needs of users as determined during earlier phases. Feedback from
these processes was evaluated and used to make further refinements to the
system before its final release in September 2003.
Phase 4b: System maintenance and training
Shortly after the release of the DIDIT, the project lead conducted a national
training session for DPCPs and CDC staff using NetMeeting. A team of DDT
professionals was then assigned the responsibility of providing ongoing user
support and training for technical and functional aspects of the DIDIT. The
project lead’s responsibilities included providing support on questions and
issues related to the content and application of the DIDIT in the context of DPCP programs.
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Elements That Facilitated the Development of the DIDIT
Several factors were critical to successfully developing and implementing
the DIDIT. The factors have practical implications for other agencies that
want to undertake a similar effort.
The work group members had extensive knowledge and experience in diabetes
surveillance and epidemiology, which proved essential in guiding the content
and technical contractors during the development process. DIDIT team members
were a motivated, dedicated, enthusiastic, and knowledgeable group of DPCP
representatives and DDT staff. In addition, the knowledge and skills of the
contractor were critical to researching and developing content on indicators
and data sources.
Buy-in of management
The project lead effectively solicited the interest and support of DDT management
to ensure that financial and staff resources were available to develop the new
tool. To sustain interest and support of management, the project lead
presented draft content and DIDIT prototypes at various CDC and national
public health meetings throughout the development process (Table 1). These
presentations allowed management to realize the high level of interest among
prospective users and the potential for the DIDIT as an important tool for
diabetes surveillance. Updates were also shared with DDT
management on an ongoing basis.
Commitment of time and resources
Development of a comprehensive reference tool such as the DIDIT requires a
commitment of time and resources. The management of the DDT supported allocation
of resources and time needed to create the DIDIT.
Strong leadership and clear vision
The DIDIT project lead had a clear vision of the type of tool that would
fulfill the surveillance needs of the DPCP and the DDT. A strength of the
project lead was her ability to communicate the vision of the DIDIT to the
project team and stakeholders throughout the development process.
Collaboration among stakeholders and contractors
Development of the DIDIT involved input from stakeholders across the country.
Clear and ongoing communication among stakeholders was essential to the
development process. During the first in-person work group meeting, we learned
that face-to-face interactions were highly appreciated by work group members
and that these interactions helped build rapport among members. In-person
meetings were arranged at national conferences to avoid issues of travel
approval and costs. Timelines and other defined plans facilitated
collaboration. A contractor who was skillful at organizing materials,
facilitating meetings, motivating work group members, and responding to the
needs of work group members was also essential. Because the work group
volunteered its time to create the DIDIT, efforts were made to minimize the
burden placed on its members. Minimizing this burden helped to maintain a core group
of members who have actively participated for more than 3 years.
Iterative development process
Development of both content and Web application took place incrementally
and iteratively. Members of the work group reviewed the content in phases,
allowing the content contractor to apply feedback to subsequent phases.
Similarly, because an incremental process was conducted that involved
analysis, design, and implementation at the same time, the contractors were
able to make a demonstration model of the DIDIT during the early phases of
development, which facilitated refinements to its content and design. Working
with an actual tool triggered ideas among users for additional functions and
alternative designs that may have been overlooked at the prototyping stage. A
model also allowed us to obtain user input on database-driven features such as
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Implications for Public Health Practice
The ability to assess the status of the public’s health in a timely,
consistent, and accurate manner satisfies the first two of the 10 essential
public health services as defined by the Institute of Medicine: 1) “monitor health status to identify community
health problems” and 2) “diagnose and investigate health problems and
health hazards in the community” (7).
The DIDIT represents an innovative approach to enhancing the capacity of
state and federal agencies to perform public health surveillance. As one user
has described, “The DIDIT offers a one-stop shop that is available 24
hours a day.” It empowers users by providing them easy access to information
that has been reviewed by DIDIT work group members for accuracy and content.
In addition to providing a road map for development, this article highlights
components that were critical to the successful development of the DIDIT. These
components synergistically influenced the development process. Having adequate
time, expertise, and commitment of resources, for example, would not have been
sufficient for success without the clear communication and rapport among the
project team members or buy-in and involvement of all stakeholders. Because
these critical factors enhance one another, it is difficult to prioritize them.
Other entities that wish to undertake a similar effort of systems development
can use these requirements as guiding principles and customize them for their
own needs and circumstances.
A major benefit of sharing these elements is to prevent other agencies from
having to “reinvent the wheel” when they can draw directly on the
experiences of the DIDIT team. While the technology is available to develop
information technology solutions for addressing public health problems, it is
vital to have effective processes and methods in place to successfully
identify the needs of users and harness and customize appropriate technology
to meet those needs.
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We thank the following individuals at the DDT: Stephanie Benjamin,
Surveillance Coordinator; Rich Gerber, Deputy Branch Chief; and Ed Gregg,
Epidemiologist. In addition, we thank Tom Chapel, the CDC, and all DPCPs that
participated in DIDIT usability and pilot testing.
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Corresponding Author: Qaiser Mukhtar, PhD, Division of Diabetes
Translation, Centers for Disease Control and Prevention, 4770 Buford Hwy,
Mail Stop K-10, Atlanta, GA 30341. Telephone: 770-488-5505. E-mail: email@example.com.
Author Affiliations: Prachi Mehta, DrPH, Northrop Grumman Mission Systems,
Atlanta, Ga; Erica R. Brody, MPH, RTI International, Research Triangle Park, NC; Jenny Camponeschi, MS,
Wisconsin Department of Health and Family Services, Division of Public Health
Diabetes Prevention and Control Program, Madison, Wis; Michael Friedrichs,
MS, Brenda Ralls, PhD, Diabetes
Prevention and Control Program, Utah Bureau of Health Promotion, Utah
Department of Health, Salt Lake City, Utah; Angela M. Kemple, MS, Oregon
Department of Human Services, Diabetes Prevention and Control Program,
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- Mukhtar Q, Brody ER, Mehta P, Camponeschi J, Clark CK, Desai J, et al.
An innovative approach to enhancing the surveillance capacity of
state-based diabetes prevention and control programs: the Diabetes
Indicators and Data Sources Internet Tool (DIDIT). Prev Chronic Dis
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Implementing program evaluation and
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Standards of medical care in diabetes.
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Public health surveillance of diabetes in the United States. J Public
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In: Burd JS. Systems analysis and design in a changing world. 2nd
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Washington (DC): National Academies Press; 2002.
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