Reduce Health Disparities with Effective Data Management in Public Health
The goal of public health is to provide the local population with the resources and information it needs to live a long, productive life, but the quality of care each person receives often depends on the quality of the data the state uses to monitor important health trends.
Collecting data on the entire population and making room for supplemental information beyond a person’s health status can improve public health by identifying disparities among certain groups, some of which may be more at risk for developing life-threatening conditions and diseases due to various social and environmental factors that effective data management can address.
Public health data management can transform how public health agencies approach this problem by freeing up additional resources, improving outreach and patient communication, and identifying the root causes of inequality. Learn how data management in public health is changing the healthcare system for the better.
Automating Routine Processes
The rapid increase in the amount of healthcare data being created presents public health departments with an opportunity. This data can contain insights into the health of the population, including which factors increase a person’s risk of developing certain conditions and diseases. But collecting and analyzing patient data can be costly for health departments, many of which are already dealing with budget constraints. The only way to effectively act on this data is to send it to a centralized repository for analysis, so administrators can quickly look at the emerging trends when implementing various policies at the local level.
Effective data management shouldn’t be overly complicated or time-consuming. The data collection process can be automated using the latest technology, so public health agencies don’t have to waste time entering data manually. Systems should automatically populate data fields based on what information needs to be collected to address the underlying issue using medical records, test results, vaccination forms and other important healthcare data. Systems should also have the ability to alert users to possible duplicate entries to increase reporting accuracy.
Automating this process can free up additional department resources that can help resolve health inequalities in the community, such as outreach and community engagement or the creation of new healthcare policies.
Scaling Data Collection
To address health disparities, providers and officials must first identify what’s known as the social determinants of health (SDOH), nonmedical factors that can affect a person’s physical and mental health. Financial hardship, environmental hazards such as toxic materials and pollution, lack of access to healthcare, educational inequalities, and lack of access to nutritious foods can all impact a person’s ability to lead a healthy lifestyle.
Public health departments must make room for the social determinants of health in their records systems by asking providers to collect this information. However, this means scaling up the department’s data collection efforts. The department should be able to easily adjust data management systems to make room for supplementary information, such as where the patient works and lives, exposure to environmental hazards, level of education, and how likely they are to engage in healthy behaviors. Modifying the data input fields as new data becomes available without revamping the entire records system is critical for success.
Addressing the Social Determinants of Health
Identifying the underlying causes of health disparities is necessary to address them. Once the department has collected data on the SDOH, it should use a tailored approach to help the local population overcome these challenges. Officials can use this information to create a public relations campaign targeting those most likely to be affected, so these individuals can take steps to reduce their risk of developing various conditions and diseases. The campaign can also target healthcare providers, government officials, and community leaders who have clout with the community in question.
The department should be sensitive to the needs and customs of the people it is trying to reach. The information may need to be translated into different languages or put into terms the population can easily understand. The campaign also needs to be shared where these individuals are most likely to spend their time, such as community centers, places of worship, and workplaces.
In other cases, the department can take steps to reduce the presence of hazardous materials, such as lead, asbestos, and environmental pollutants, to protect the local population from exposure. Officials can focus on educating individuals on how to protect themselves based on who is most likely to be affected by these hazards.
What are some challenges associated with reducing health disparities using data management?
Effective data management is the best way to address health disparities, but issues can still arise. Public health departments need a data collection system that’s easy to use and compatible with existing digital infrastructure to make the transition as smooth as possible. The input forms should be configurable based on what information needs to be collected. Many officials are drowning in too much public health data, which is just as detrimental to efficiency as collecting too little data.
The system needs to convey the findings using an actionable report that can easily be shared with all parties involved. The data must also be limited to what’s needed to address the underlying health concern without violating patient privacy laws.
What are health disparities?
Health disparities are related to the current and historically unequal distribution of social, political, economic, and environmental resources that can affect a person’s quality of life. Everyone needs the same basic components to lead a healthy lifestyle, including sustainable housing, a balanced diet, regular exercise, and access to healthcare services. But money, geography, education, and historical biases can prevent some people from attaining these essentials.
How can data management help reduce health disparities?
Data management can reduce health disparities by identifying the root causes of these inequalities. Diverging patient outcomes is often caused by environmental, economic, and social factors that can be addressed at the local level. The data management system will identify the factors that can lead to health disparities, so officials can take steps to remedy them.
What types of health data are used to address health disparities?
Health officials typically focus on the social determinants of health when addressing health disparities. Data can include a wide range of information regarding how people live, work, and develop over time. Social, economic, cultural, and political factors can all play a role. The department will need to tailor its collection efforts based on which factors are most likely to make a difference in terms of the health of the community.
Data management will play a significant role in the ongoing effort to reduce health inequalities across the U.S. Having the right information at the right time and acting on it in a meaningful way is vital. SSG is a leader in public health software. Contact us today to learn more about our data management solutions and request a free demo.