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  • May 11, 2017

Big cities continue to be centers for innovative solutions and services.

Legacy systems that are not interoperable, and numerous silo information technology systems pose budgetary, operational, and workforce challenges for health departments.
Governments are quickly identifying opportunities to take advantage of this energy and revolutionize the means by which they deliver services to the public. The governmental public health sector is rapidly evolving in this respect, and Chicago is an emerging example of some of the changes to come. Governments are gradually adopting innovative informatics and big data tools and strategies, led by pioneering jurisdictions that are piecing together the standards, policy frameworks, and leadership structures fundamental to effective analytics use. They give an enticing glimpse of the technology’s potential and a sense of the challenges that stand in the way. This is a rapidly evolving environment, and cities can work with partners to capitalize on the innovative energies of civic tech communities, health care systems, and emerging markets to introduce new methods to solve old problems.

Over the last 2 years, WRC has been working internally and with partners to build new technologies that help local government offices collaborate with local residents to identify and address health problems that impact the public at large. Because these technologies are digital and utilize Web-based platforms, they have the potential to extend information to wider, more diverse audiences than some traditional public health interventions.

Public health departments are facing extraordinary challenges that include the prospect of future budgetary challenges, the uncertainty of a future public health workforce, and the emergence of informatics and big data, as well as the questions surrounding integration with health systems that have new emerging payment and delivery models.

The Department of Public Health, like other government entities, is following the lead of the business sector, which for decades has used data to drive decision making and strategy. Government, like business, is beginning to use data to test new ideas and to measure and respond quickly to what works, as well as to develop ways to revise and improve interventions that are less effective. Like businesses, governments are starting to engage customers through social networks, Web sites, and blogs and are learning to use technology to function more effectively. Because of its potential to reach larger swaths of the public with fewer resources, digital strategies have shown to support government in becoming lean, advancing priorities, and engaging residents. That—in a time of shrinking resources—delivers better services, faster.

Liberating data is an important component of WRC innovation strategy. Liberating data is making data accessible, discoverable, and usable by the public so that it can spur entrepreneurship, innovation, and discovery. For several years, the federal government has issued calls for increased transparency of operations. As a result, government agencies are releasing data that the public can access to generate awareness that can foster more ideas for potential solutions and efficiencies. In May 2013, President Obama established a historic executive order that outlines steps to make government-held data more accessible to the public and to entrepreneurs and others as fuel for innovation and economic growth. The goal of open data is to make data underutilized in government available and placed in the hands of people who can unlock its potential value.

Since then, thousands of data sets have been released in usable format, giving all types of organizations the tools to develop new products and services to help millions of Americans, and creating jobs of the future in the process. “Open data” has increased the flow of information, and in doing so, it has created an opportunity for government leaders and their teams to analyze it to improve outcomes, look for inefficiencies, and communicate better with their constituents. The City of Chicago, for instance, is using its open data platform to collect, measure, visualize, and communicate performance data to its residents.

WRC innovation framework is supported by 3 pillars: informatics, application development, and predictive analytics (PA), each of which is anchored in the unique use of data. Data liberation spurs innovation by allowing developers the flexibility to freely utilize the open data in application development, analysis, data visualization, and so forth, to serve the residents of Chicago. Applications are often adopted by the City or by civic communities that share their knowledge to develop open-source projects for the city. Predictive analytics uses many variables that are often derived from open data sources, such as weather, 311 complaints, business licenses, and so forth.

Our goals include improving the use of scarce resources, being smarter with data, fostering engaged citizenship, spurring economic development, leveraging nontraditional partners, and evolving departmental culture. To achieve these goals, we use informatics, application development, and PA.


Public health informatics, defined as the systematic application of information and computer science and technology to public health practice, research, and learning.4 In its infancy in 2001, public health informatics focused primarily on better disease surveillance and outbreak detection systems. Public health informatics then evolved to ensure that there was a connection between public health systems and clinical systems. Now the impetus is to identify ways to leverage informatics to merge structured and unstructured data to generate valuable insights to advance health.

A major driver of the informatics revolution is certainly the 2009 Health Information Technology for Economic and Clinical Health (HITECH) Act (Title XIII of Pub. L. 111-5), which has led to incentive payments tied to meaningful use requirements. Much has been written about meaningful use implications for public health because of the requirements supporting modifiable electronic laboratory reporting, syndromic surveillance, and reporting to immunization registries. The commentary has been positive and negative. There are potential consequences for population health if the proposal of removing public health measures in stage III proceeds as proposed. Public health measures provide an additional profile for health departments about communities that guide interventions and education campaigns. Beyond the public health reporting requirements, population health stands to gain considerable advantages by establishing chronic disease surveillance systems.

Currently at WRC, we are working to create an informatics data tool that enables providers to generate community-profiles public health data to understand the social, environmental, and economic context of their patients, and to support clinical decision making in real time. This coupled with geographic information systems provides a map of the community ecosystem visually. The Institute of Medicine has recently argued for embedding social determinants of health data into the electronic health records (EHRs), a move we believe aligns with the larger goals of improving patient care, advancing population health, and reducing health care costs.

Big data has been leveraged extensively in commercial industries and by companies such as Amazon to generate insights that can lead to more informed, targeted, and successful marketing efforts. Health care “big data” is a branch of health care informatics that pools large and disparate data sets and applies a suite of mathematical approaches that derives associations, facilitates comparisons, and generates insights that are not otherwise possible using standard analytics. “Big data” is a term used to describe a collection of data sets with the following 3 characteristics: volume — large amounts of data generated; velocity — frequency and speed of which data are generated, captured, and shared; and variety — diversity of data types and formats from various sources. The public health community is just starting to emerge as a user of data in unique ways, taking a page from the commercial playbook. As the focus on innovative uses of data in health strengthens, there will be an increasing need for cross-sector relationships anchored by local and state health departments to maximize the benefits achieved from appropriately using these data. Neither health departments nor health systems can navigate this terrain alone — nor should they. Working together — governments, health plans, academic delivery systems, community-based organizations, and the private sector — these organizations have the potential to leverage data and technology to transform public health. To evaluate the success of open data, a city can be accountable for the number of data sets, the number of applications developed, and the economic multiplier effect of small businesses created as a result of open data. Increased economic development through civic innovation is most often viewed through the lens of open data.