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Automated Workflows and Data Integration: Enhancing Efficiency in Disease Reporting Systems with SSG's Casetivity Platform

Posted on February 24th, 2025   |   SSG
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As technology, data, and exchange standards continue to evolve, transitioning public health agencies from manual to automated workflows offers a transformative solution. This will enable health organizations to modernize and strengthen the infrastructures supporting their disease surveillance efforts. 

Below, we explore how SSG’s Casetivity platform and its cutting-edge tools modernize disease surveillance and reporting systems, helping public health agencies streamline operations and focus on impactful decision-making. 

The Challenges of Manual Disease Reporting Systems  

Traditional disease reporting systems rely heavily on manual processes, creating bottlenecks and hindrances to operational efficiency. Manual data entry is inherently slow and prone to errors. In addition to inaccurate or incomplete case surveillance data, this often results in reporting delays, which can have dire consequences during outbreaks when timely and accurate information is critical to formulating and implementing effective responses. 

Moreover, delayed follow-ups are commonplace, as manual systems lack the automation required to promptly notify health authorities and stakeholders about new cases or changes in disease status. This can lead to slower public health responses and reduced ability to control the spread of diseases. On top of these, manual reporting systems also struggle with inconsistent data quality and lack of standardization, making it difficult to compare and analyze data across different regions or timelines. These issues significantly compromise public health surveillance and response efforts.

How Automated Workflows Transform Disease Reporting  

The National Notifiable Diseases Surveillance System (NNDSS) is a nationwide collaboration that helps public health agencies at all levels to share health information. Each year, around 3,000 public health departments send disease data to 60 state, federal, and territorial departments, who then forward them to the Centers for Disease Control and Prevention (CDC, 2024). As you can imagine, this process can make disease data management and reporting a highly challenging proposition. 

Automated workflows can streamline the entire disease reporting process, expediting tasks and significantly reducing the likelihood of errors. To put this into perspective, Casetivity-DSS provides a unified disease surveillance platform for collecting, storing, and managing disease-related data from various sources. This allows it to automate the intake of data from labs, healthcare providers, and hospitals, reducing manual data entry, potential errors, and perhaps more importantly, data silos. 

Automated systems can quickly identify and notify relevant stakeholders about emerging disease trends, potential outbreaks, and individual case reports. This rapid dissemination of information allows for timely intervention and more efficient resource allocation. Moreover, automation facilitates consistent and standardized reporting, making it easier for public health officials to analyze and compare data across different regions and timeframes.

Ensuring Data Integration with HL7 Compliance  

HL7 (Health Level Seven) standards provide a common “language” and structure for healthcare data exchange, integration, and sharing between diverse software applications used by various healthcare providers. HL7 designs specific message types (e.g., for patient admission, lab results, etc.) and segments within those messages. These standards enable diverse systems to communicate effectively, enabling smooth and standardized data sharing across federal and state agencies (NIH, 2021).

By strictly adhering to these standards, Casetivity reduces the risk of errors and miscommunication, ensuring that data is consistently formatted and reliably transmitted between diverse information systems. This interoperability facilitates real-time data sharing and improves the accuracy and timeliness of health information, which is crucial for effective public health surveillance and response. 

Key Features of Casetivity for Disease Reporting  

SSG’s Casetivity-DSS is designed with public health agencies in mind, offering a suite of features that address common pain points in disease reporting.

Core Features:

  • Longitudinal Patient Views: Efficiently review a patient’s reportable disease history with an integrated, comprehensive timeline.
  • Automated Deduplication: Streamlined, automated deduplication processes reduce manual data handling and improve operational efficiency.
  • Automated Investigation Assignment: Automatically assign investigations for infectious diseases based on a patient’s residential address or healthcare provider location, eliminating manual steps for high-volume jurisdictions.
  • Disease-Specific Timeframes: Incorporate disease timeframes for automated decision support, reducing manual review by distinguishing between new and existing reportable events.
  • Real-Time ELR Ingestion: Ingest electronic laboratory reports in real-time rather than at scheduled intervals, ensuring up-to-date data availability.
  • Enhanced Laboratory Data Management:
    • Ingest susceptibility results with parent/child structuring.
    • Provide distinct laboratory result categories for investigations, such as current events, other events for the same patient, and unattached results.
    • Improved handling of negative results for diseases like Syphilis and COVID-19.

Advanced Automation:

  • Streamlined Lab and Code Mapping: Automatically create new lab facilities and map LOINC and SNOMED code combinations upon receipt of first reports.
  • Outbreak Linkage: Link investigations to outbreaks using local, state, and national identifiers like PNUSA#.
  • Enhanced Address Validation: Incorporate geocoding with longitude, latitude, census tract, and block data, along with standardized address formats.
  • Industry and Occupation Coding: Use the NIOSH API to normalize occupation data with industry and occupation codes.

Expanded Data Capabilities:

  • Enhanced Demographic Data: Support expanded race, ethnicity, sexual orientation, and gender identity (SOGI) data sets tailored to disease-specific requirements, including CDC variations.
  • Comprehensive Laboratory Information: Deliver complete lab result details, including ELR standards, local codes, and descriptions for epidemiologists.
  • CDC Disease Group Classification: Tag diseases with CDC group classifications to streamline reporting and generate ELR volume percentages by group.

Additional Functional Enhancements:

  • Decision Support Integration: Automate critical steps in creating or linking reportable events, improving accuracy and reducing labor.
  • Geospatial Insights: Enhanced geocoding supports geographic and census-based analysis for public health insights.
  • User-Friendly Interface for Investigators: Simplified workflows for epidemiologists and investigators enable rapid access to relevant data and decision-making tools.

Casetivity-DSS’s modular structure lets agencies customize the platform according to their unique requirements and only pay for the features they need. This flexibility makes Casetivity-DSS a scalable and cost-effective solution for enhancing disease surveillance in public health.

Why Choose Casetivity for Streamlined Disease Surveillance  

Casetivity Disease Surveillance System (DSS) is ideal for public health agencies that prioritize flexibility and adaptability. Its modular design allows organizations to build, reconfigure, and modify applications as needs change. The low-code architecture ensures quick implementation with minimal operational disruptions. Whether managing chronic disease data or responding to infectious disease outbreaks, Casetivity-DSS provides all the tools you need to deliver the benefits of disease surveillance to your communities. 

Contact us today to discuss your program requirements and discover how our solutions can modernize your operations. 

FAQs

  • What are the benefits of automating disease reporting workflows?

Automating disease reporting workflows offers numerous advantages, including:

  • Faster outbreak detection through real-time data analysis
  • Improved data quality by minimizing manual entry errors
  • Enhanced efficiency and collaboration through seamless data sharing between agencies
  • Quicker, more informed responses to public health threats

These benefits translate to cost savings, more accurate data for analysis, and a more proactive approach to disease control and prevention.

  • How does Casetivity ensure HL7 compliance for data integration?

Casetivity supports standardized data-sharing protocols, such as HL7 (Health Level Seven) and FHIR (Fast Healthcare Interoperability Resources), to ensure compatibility with various health systems. These protocols allow data to flow seamlessly between systems, reducing delays and improving response times. 

The platform also adopts industry-standard terminologies like SNOMED CT (Systematized Nomenclature of Medicine Clinical Terms) and ICD (International Classification of Diseases) codes to help ensure consistency in data reporting. Standardized formats help eliminate discrepancies, enabling health officials to compare and analyze data across regions.

  • What challenges do health agencies face in manual disease reporting?

Health agencies face several challenges with manual disease reporting. Chief among them are the following:

  • Data fragmentation: Scattered information across various systems and formats often leads to challenges with data sharing, integration, and analysis.  
  • Manual Processes: Manual data entry and paper-based systems can lead to inaccurate or incomplete information. These inherently slow processes delay the identification of disease trends and the implementation of effective control measures.
  • Limited Interoperability: Difficulty with sharing data between different health agencies and disparate systems impedes coordinated public health efforts.

These challenges compromise the overall effectiveness of disease control efforts.

  • How do e-signatures improve the efficiency of disease reporting?

E-signatures enhance the efficiency of disease reporting by streamlining the approval and verification processes. They allow healthcare professionals to quickly and securely sign documents and reports electronically, reducing the need for physical paperwork and manual handling. This speeds up the submission and processing of disease reports, ensuring timely updates and responses. 

E-signatures also provide a secure and verifiable way to authenticate documents, improving data integrity and compliance with regulatory standards. 

  • Why is automated follow-up important in a disease surveillance system?

Automating the follow-up process enables health agencies to quickly gather additional information, track disease progression, and ensure compliance with established treatment and preventive measures. These capabilities reduce the risk of missed or delayed follow-ups, which can hinder effective disease control and response. 

Automated follow-ups also free up valuable time for healthcare professionals, allowing them to focus on patient care and other critical tasks, ultimately enhancing the overall efficiency and effectiveness of the disease surveillance system.

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