SSG Blog

Public Health Data Management Trends for 2023

Posted on February 27th, 2023   |   SSG

The art of collecting and analyzing public health data continues to evolve. New trends and gaps in the existing public health data infrastructure are pushing public health officials to embrace new collection and analysis methods. Data analytics are playing an increasingly important role in public health administration. Officials are starting to collect new types of data on specific populations to create more informed policies. They are also trying to figure out how they can better use the technology they have to protect the public from infectious and noninfectious diseases. Learn about the latest trends in public health data management and how they will shape the future of public health in 2023 and beyond. 

What data management trends are projected for 2023?

The COVID-19 pandemic accelerated the healthcare industry’s push toward digitization. Public health agencies are now tasked with collecting and analyzing large volumes of data related to various diseases and conditions to organize the information into a standardized format. Officials extract meaningful insights about the disease, which then informs the policymaking process. They use the collected data to communicate important health-related information to the community at large, including individuals, healthcare providers, and organizations.

To organize and analyze this data, the agency must quickly incorporate data from a wide range of sources so it can then be organized into a single interface. Providers, labs, and facilities often use different reporting methods and file types, which can make it difficult for public health workers to collect the required data. Agencies are continuously refining the public health data management process to save time and improve the accuracy of their findings. Workers should be able to read and upload any file type regardless of the type of electronic surveillance system they are using to analyze the trends. The system should also flag the incoming data for missing fields, duplicate entries, and other common mistakes that can reduce the quality of the findings. Workers only have so much time in the day. The uploading process should be automated whenever possible to free up additional resources. 

But many agencies are only starting to scratch the surface in terms of what this technology can achieve. The push towards automated, seamless data entry is only the beginning. 

  • Using Analytics to Reduce Health Inequalities

Public health officials are responsible for addressing health inequalities that prevent underrepresented communities from accessing the care and information they need to protect themselves from disease. 

It all starts with improving the quality of the data these agencies receive. Various factors can affect a person’s chances of becoming infected or getting diagnosed with a disease. Agencies are starting to collect additional information about the population, including the individual’s race or ethnicity, how much they make, where they work/live, and whether they engage in healthy behaviors. 

More departments are incorporating the social determinants of health into their analyses to better understand how certain groups are likely to be affected by the latest health trends. This only increases the amount of information that needs to be processed and analyzed. Having a scalable, automated public health software system will help these departments meet the challenges of the day as the volume of data continues to increase. 

Officials should consider including additional determinants by requesting this information from providers and making space for it in the data management program interface. Once the data has been incorporated, the agency can use prediction models based on historical analysis to better serve communities and individuals with poor social determinants of health.

  • Increasing Interoperability for Shorter Response Times

Responding quickly to the changing public health landscape is crucial to preventing the spread of disease. Public health agencies need to collect and analyze the information they receive as soon as it comes in to help officials respond to the latest events as quickly as possible while preventing errors that can affect the accuracy of their findings. The public health agency’s guidance is only as good as the information the agency receives. Any delay or error in the collection process could inhibit the agency’s ability to keep the public safe. 

The situation on the ground is also likely to change at a moment’s notice, especially when the agency is dealing with a novel virus like COVID-19 that continues to mutate, so the official guidance must be ready to change as well.

This shows the importance of automating the data collection process. Public health workers can quickly ingest large volumes of data from a wide range of sources without having to enter this information by hand. The interface should also be easy to use and highly configurable to accommodate the different types of data being collected.

Data analytics and predictive modeling can also be used to assess the future impact of various public health guidelines and policies using machine learning (ML), so officials can understand how the population will be affected before the policies are implemented. 

  • Data Management at Scale for an Aging Population 

The U.S. population is getting older with people living longer than ever before even as the average life expectancy goes down. Many older Americans are now living with more than one chronic condition, which increases the amount of data that needs to be collected. These individuals will also use more health services over their lifetimes as the healthcare industry gets better at treating these conditions. 

Public health departments need to scale up their operations as these changes take effect. Workers must also be sensitive to the patient’s underlying conditions when collecting health-related information on the population. These conditions can make individuals more susceptible to infectious disease, which can complicate the department’s ability to respond to a public health emergency. Officials and managers can use public health software to expedite the data collection process without losing important information about a patient’s condition. 

Are there negative and positive trends in public health data management?

These trends aim to improve the quality of the data health agencies collect, but the push towards interoperability may exacerbate existing health inequalities if some departments and agencies struggle to keep up with the flow of information being generated. The increase in data will put additional pressure on agencies that may already be experiencing operational challenges due to budget cuts and staffing shortages. If these agencies struggle to implement the latest trends, the local population will only suffer as a result.

Automating the data collection process will help agencies save time and money even when working with limited resources. Workers won’t have to spend as much time entering information into the system, which leaves more time for analysis. The system should also automatically flag duplicate or inaccurate inputs as these agencies and their network of providers adjust to the latest trends. 

The amount of data needed to keep the public safe will only increase in the years to come. The system should also be scalable, so the department can increase its reach and include new types of data without having to hire additional staff. 

What data management trends should I follow in 2023?

Regardless of the challenges your public health department faces, you should focus on simplifying and automating the data collection process in 2023 and the years to come. Workers should be able to interface with any type of data that comes their way using a single interface that can be adjusted as the situation evolves. 

Adding data related to the social determinants of health will help you better serve the local community. Consider including additional data types in the reporting process to enhance the quality of the guidelines you put in place. As telemedicine adoption rates increase, you will also need to adjust the collection and analysis process. 

Use these emerging health data management trends to improve your public health agency, and contact SSG for more information about our software solutions for public health agencies.

As we explore the evolving landscape of public health data management in 2023, it’s clear that innovative strategies and technologies are pivotal in shaping the future of health equity. One of the most crucial goals in harnessing these advancements is to reduce health disparities across communities. Effective data management plays a fundamental role in identifying and addressing these disparities, offering insights that can lead to targeted interventions and improved health outcomes for underserved populations. By focusing on the strategic collection, analysis, and application of public health data, we can uncover patterns and trends that are essential for making informed decisions. Learn more about how effective data management is key to reducing health disparities and promoting equality in healthcare access and outcomes.