Data Driven Decisions

Stacey Flanagan, Director of Jersey City’s Health and Human Services Department

Stacey Flanagan, Director of Jersey City’s Health and Human Services Department

Harnessing data to drive decision-making seems obvious. Yet, when access to real-time information is disrupted, challenges arise in aligning initiatives with goals and objectives. The COVID epidemic demonstrated that even in the face of sufficient available data, real-time access is critical and strategic decision-makers are only as successful as the timely access to reliable data. During the pandemic, obtaining up-to-date data was difficult as state and federal agencies did not universally provide it to municipalities to improve their decision-making. In short, data collected at daily intervals became central to public health.

The most common public health process for reducing the spread of COVID is Test - Trace – Treat, the execution of which proved difficult throughout the pandemic. Access to and use of timely data and information technology were the greatest allies during Covid. Without innovative and programmatic support, we would not be on the other side of this pandemic.

For example, testing was difficult from the very onset and only limited to symptomatic individuals. Engaging with residents required an online tracking tool. Immediately, we saw government agencies lean on Microsoft Teams as a tool to allow many to work simultaneously from different locations. Utilizing shareable programs involving multiple individuals allowed operational continuity in providing access to testing.

Once residents were set up for testing, it was important to have real-time information regarding results. While labs were starting to get backed up, new systems needed to be put in place to allow agencies to see test results and provide information in a timely manner to newly infected individuals. Plus, it was essential to understand the percentage of positive cases in a community. Sharing this information with the public, which the City of Jersey City did through an online portal called Tableau, allowed the public to access information that was not traditionally available.

With increased numbers of residents becoming infected, Health Departments had to pivot from testing to contact tracing. Tracing required staff to call and ask people, who were often still sick, questions about their symptoms and recent visits with friends and family. This may seem intrusive, but it is a standard in combatting communicable diseases. Across the country, public health databases could not handle the volume of cases. In order to contact trace in a timely manner, health departments needed HIPPA Compliant tools to track COVID-positive residents. These tools needed to mirror the systems that health agencies already have in place to ensure the same data is being collected across the community. The City of Jersey City designed a tracing form on Cognito to allow many staff to collect data as quickly as possible.

The importance of collecting demographics during contract tracing is so that health leadership can see trends and concerns and plan a treatment strategy, in this case, target demographics most impacted by the virus. Whether it be by age, race, and/or gender, the more data health leadership had, the more they could design successful interventions. For example, after reviewing data collected through the Department of Health & Human Services in Jersey City, age was the primary factor in fatalities. Over 75% of all fatalities in Jersey City were individuals over the age of 60. Additionally, race proved to be a factor in fatalities. Of the fatalities in Jersey City, only 26% were white. Death in males was over 15% more than in females. Having this knowledge, or any daily information, allowed health agencies to pivot and provide more targeted education and intervention strategies.

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Information Technology

real-time access

Microsoft