Transforming Public Health with Data Analysis and Visualization

You can’t address public health challenges without data collection and analysis. Every year, the healthcare industry creates enormous amounts of data from many sources in many different formats. Adding to this complexity is data from government sources. This includes census data, demographics, economic data, crime data, and more.

To be of value, this data needs to be collected, collated, analyzed, and communicated. That’s where modern data analytics and visualization becomes critical with helping healthcare and public health organizations turn their data into actionable insights.

When challenges arise, data analytics and visualization can help determine not just what happened, but potentially why, and more importantly, suggest solutions for improvement. Without it, we’ll see duplicative efforts, inefficiency, and wasted resources. Through data analytics and cross-collaboration within the healthcare landscape, we can create tailored solutions that enhance healthcare quality, access, and outcomes for the people who need it most.

Healthcare Data: Challenges and Opportunities

The two biggest hurdles to effective healthcare data utilization are the bottlenecks of data collection and data analysis. The healthcare system collects data from many sources. These include electronic medical records, claims, and research studies.

Each of these sources generates different pieces of information that need to be cleaned, combined, and analyzed to create a complete picture of the care delivered to patients. Furthermore, each of these data sources has advantages and limitations from an analysis perspective.

Generally speaking, most organizations generate healthcare data for purposes other than improving individual and public health. For example, claims data has the specific information needed for processors. This helps them decide if a medical service is necessary and whether to pay or deny a claim.

Claims data alone can overlook important details. These details help us understand a person’s overall health.

They also show health-related social needs. These needs include living conditions, safety, access to healthy food, and income.

What Data Analytics and Visualization Can Do

Public health and healthcare delivery systems have different goals. However, data solutions can help meet both sets of needs.

Using science and analytics can help healthcare systems in many ways. It can improve efficiency, boost revenues, and enhance care delivery. This also leads to better patient outcomes.

Pandemic and Public Health Crises Response

On the population level, unstructured data, commonly known as “big data,” and machine learning are enabling new insights. Big data involves the analysis of large datasets, potentially from thousands or tens of thousands of patients and individuals. When we look at big data, we can find groups and trends within various populations. This helps us understand the past and predict the future to improve outcomes.

We often see predictive analysis and data visualizations have their greatest public health impact in pandemic response and prevention. During the COVID-19 pandemic, health organizations played a key role. Both government and non-government groups used data analysis. They showed how data visualization can aid public health decisions.

For example, the Centers for Disease Control and Prevention (CDC) utilized wastewater to track and predict hotspots and new outbreaks of COVID-19. By analyzing the presence of the virus in wastewater it was possible to detect the presence of the disease before patients began to show symptoms.

This information helped improve healthcare delivery by directing resources to prepare for outbreaks. It also alerted healthcare providers to expect more patients and reduce the impact of disease. In this way, data analytics and visualization are the foundation of planning, budgeting, and preparing for public health crises.

We can see another example of predictive data analysis with recent findings related to H5 avian flu. The CDC is actively tracking cases across the United States, looking at exposure location and source. As of early January 2025, there are 66 confirmed human cases of H5 in the U.S.

Out of these cases, 40 are linked to contact with dairy herds (cattle), not poultry. These data collection and analytical efforts shape public policy responses, inform decision-makers, and drive resource allocation.

Environmental Factors and Social Drivers of Health – Uncovering Impact Beyond Individual Patients

More and more, it is recognized that environmental factors significantly influence health outcomes. These concerns go beyond pollution and bad air quality. They include simple things like grocery store access, safe places to play, and living costs.

By examining social drivers of health and environmental hazards, healthcare organizations can identify individuals who are at risk for various chronic health conditions earlier. Then, healthcare providers can deliver targeted care to prevent severe complications further down the line and improve overall outcomes.

Using the interdisciplinary approach of data science, we can uncover new insights that show how healthcare impacts whole communities, not just individual patients. By applying economic and actuarial methods, it is possible to determine deeper impacts.

For example, a specific public health initiative may increase the rate of diabetes screenings conducted in a population. As a result of this increase in screenings, the number of cases detected early enough for treatment increases. This increase in treatment then leads to a decrease in the number of amputations or other severe complications of diabetes within that population.

Using effective data analysis, can help practitioners and decision-makers use resources wisely, set priorities, and tackle complex challenges.

Even with the best data collection and analysis, one more step is needed to make data meaningful: communication. If you cannot communicate the value and purpose of the data presented, then the data is functionally useless.

Data visualization allows clear, effective, and immediate communication of information. For example, in the case of the CDC’s COVID-19 wastewater tracking, they utilize a visual display on the map. This lets you immediately identify where potential outbreaks are geographically. By clear and effective communication, data visualization prevents misconceptions and errors.

Ready to Make an Impact? Explore our Data Analytics and Visualization Solutions

Excellent data analytics and visualization allow us to understand the challenges and opportunities facing healthcare and public health organizations at all levels. They are key tools in advancing improvements in healthcare quality, access, and outcomes and are essential to solving the public health challenges of today and the future.

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