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Data Processing Steps of Public Health Surveillance

Posted on September 11th, 2023   |   SSG

Public health surveillance systems process patient data at the state and local levels. Once the information is collected, it must be validated and cleansed before being included in the final report. The findings will shape public health policy with the goal of preventing the spread of disease. 

Public health surveillance runs on data collection and analysis. Patient outcomes are monitored at the state and local levels to help public health officials track emerging trends and implement policies that protect the public from the spread of disease. Departments collect, process, and aggregate large quantities of patient data in real-time to respond to trends. Several steps must be taken to enter the data into the public health surveillance system.

The way this information is processed can affect the department’s ability to interpret it. Officials need to quickly identify the trends once they receive the data while analyzing various social and environmental factors that can affect the agency’s response. The data collection and aggregation process must also comply with the latest federal reporting requirements while cleansing and validating the responses to improve the accuracy of the report.

Learn about the four steps of public health surveillance data processing to find out how this information is used to limit the spread of disease. 

What is public health surveillance? 

Public health surveillance is the systematic collection, analysis, and interpretation of patient data as it is used to address and improve specific health outcomes. It is conducted at the state or local level to track and monitor health trends within the community, including the spread of infectious diseases and environmental hazards that can lead to illness and disability. 

Data is stored in public health surveillance systems that compare patient outcomes over time. The information in the system is used to identify and track emerging health trends. The findings will influence the government’s response to the trend as officials coordinate with the public and community leaders. For additional analysis, the information may also be passed onto the federal government, such as the Centers for Disease Control and Prevention (CDC). 

Why is data processing important in public health surveillance? 

Data processing is the muscle behind the public health surveillance system. It allows the department to collect and analyze patient data from hundreds, if not thousands, of individual healthcare providers and institutions who interact with the public daily. 

The data contains valuable insights into the health of everyone who interacts with the local healthcare system, including whether they have tested positive for a disease/condition, the severity of their symptoms, any treatments they have received, and their vaccination status, as well as contextual information such as the person’s age, race/ethnicity, gender, sexual orientation, religious affiliation, occupation, address, and other factors that can affect the department’s analysis of the underlying trend. 

The process allows department members to access patient information as soon as it’s entered into the system. Automated data processing tools aggregate the data to highlight changes and new results, so the agency can begin mounting a response if additional action is needed. 

What are the key steps in data processing for public health surveillance? 

Public health surveillance data must be processed before the department can use it as part of its analysis. The processing steps and requirements vary based on the department’s software program, but the principles remain the same.

  • Patient Identification

The first step is to identify the patient or groups of patients who make up the data. Patient identification is the correct matching of an individual or group of individuals to an intervention or communication system that collects the data. If the patient already exists in the system, the provider must find their existing electronic healthcare record or create a new record if the patient is new to the system. To protect patient privacy, the system assigns each person a unique patient identifier (UPI) instead of using their name or social security number. 

  • Data Collection

The second step is to collect information from the patient and enter it into the software system, which creates new data. Providers may ask the patient questions about their health while adding it to their electronic health record. Patients may also self-report information when filling out a form online. The collection process can also be automated through remote sensors that send clinical information to the records system. 

  • Data Transmission

Once the data has been collected, it needs to be transmitted to the state or local health department. The data is securely transmitted to the disease surveillance system for follow up, review, and analysis. Some entries and information may need to be reformatted during the exchange. Users must identify and remove duplicate records to improve accuracy.  

  • Data Use

The final step is to use the aggregated data to satisfy the health objective. The public health department uses its findings to evaluate and improve healthcare practices. It may invest in a public awareness campaign to disseminate the information among those most likely to be affected by the trend. The data may also be used to advocate for changing state and local health guidelines and requirements to limit activities and practices that can increase the spread of disease. 

What technologies are used for data processing in surveillance?

Technology facilitates public health surveillance data collection, exchange, and analysis. 

It starts with the public health surveillance software system administered by the department. Participating healthcare providers and institutions can transmit data to the public health surveillance software system using various methods, including file upload, HL7 messages, and more. This data will be deduplicated and cleansed before it is accepted into the surveillance system for analysis.

Consumer tablets, computers, and smartphones are also used to collect data. Providers typically enter information into these devices while consulting with patients before transmitting the data to the disease surveillance system for analysis. 

Patients may also use public health apps on their personal devices to document symptoms and other important health information. 

Smart sensors and automated patient monitoring tools can be used to continuously record clinical information, such as patient blood sugar, blood pressure, heart rate, and falls.

Public health surveillance may also use information generated by private businesses and other public institutions as part of its analysis, such as over-the-counter pharmacy retail sales, school and work absences, and public events like concerts and sports that tend to draw large crowds. This information may be collected through ticket sales, customer and employer surveys, and internal reporting systems that are then shared with the public health department.

Data processing helps public health departments make the most of the information they collect from various stakeholders in the community. Every entry needs to be validated and cleansed before making its way into the final system. Contact SSG to learn more about data processing for public health software.