How Casetivity Drives Seamless Interoperability of Disease Surveillance Systems
Fast-moving infectious diseases can quickly escalate into public health crises that threaten the well-being of entire populations. While technological advancements have revolutionized how we share information, many public health organizations still struggle with fragmented data sources, incompatible formats, and outdated collection processes, hindering their ability to respond effectively to health crises.
Below, we explore the critical importance of interoperability in disease surveillance systems, identify current gaps in electronic disease surveillance, and highlight how Casetivity addresses these challenges with practical, targeted solutions.
The Importance of Interoperability in Disease Surveillance Systems
Public health agencies rely on diverse data sources, from hospitals and laboratories to electronic health records (EHRs) and community health programs. Maintaining data accuracy is the foundation of evidence-based decision-making in disease surveillance. Without interoperability, these data systems remain siloed and limited, hindering their ability to share accurate and timely information.
Seamless data exchange across different systems and health departments allows public health professionals to identify outbreaks, track disease progression, and coordinate targeted responses across populations. During the COVID-19 pandemic, jurisdictions with integrated disease surveillance systems were better equipped to manage case data, allocate resources, and communicate risks to the public.
Beyond outbreak response, data interoperability also supports routine public health efforts like immunization tracking, chronic disease management, and policy development. It reduces redundancies, improves data accuracy, and facilitates informed decision-making – all critical areas in today’s complex public health landscape.
Current Gaps in Electronic Disease Surveillance Interoperability
Technology has made sharing information faster and more accessible than ever before. However, the seamless sharing of public health data continues to face several challenges. According to the Centers for Disease Control and Prevention (CDC), many public health data systems rely on outdated technologies that don’t work well with other systems. This challenge is further compounded by the lack of organized and standardized data and inflexible data sharing policies and agreements (CDC, n.d.).
Here’s a closer look at these interoperability gaps:
- Fragmented Data Sources: Disease surveillance data comes from various sources. In addition to labs, physician notes, and disease registries, these include input from manual records searches, interviews with staff, and even door-to-door canvassing. These fragmented data sources make it inherently challenging to seamlessly access and exchange information between systems.
- Lack of Standardization: Achieving seamless data exchange is challenging enough. However, enabling systems to interpret and understand it in the same way is equally (if not more) critical to effective disease surveillance. Without standardized data formats, terminologies, and coding practices, data integration can result in mismatched or misinterpreted information.
- Data Security Concerns: Balancing access to critical health information with stringent privacy and security standards poses a significant challenge to achieving interoperability. Information systems must comply with Health Insurance Portability and Accountability Act (HIPAA) regulations. While these controls were designed to protect sensitive patient data, these requirements often conflict with the urgency of real-time data sharing.
These multi-layered challenges restrict disease surveillance programs and the necessary response efforts to improve public health outcomes. Fortunately, SSG offers a disease surveillance platform designed to address these persistent challenges.
Casetivity’s Approach to Enhancing Data Integration in DSS
SSG uses a holistic and innovative approach to tackling interoperability challenges. Designed with public health goals in mind, Casetivity systematically bridges data silos to enhance the overall functionality of disease surveillance systems (DSS).
Here’s an overview of how Casetivity addresses interoperability issues:
- Data Integration and Cleansing: Casetivity utilizes industry standards-based Application Programming Interfaces (APIs) to integrate into public health information systems. Its advanced algorithms automate the ingestion and standardization of diverse data feeds to harmonize data and ensure semantic interoperability. Moreover, Casetivity supports any data model and architecture, making legacy data migrations quick and seamless.
- Configurable Records Management: Casetivity’s records management module collates all your data in a centralized repository to ensure data security and consistency. This highly configurable module enables organizations to collect and manage diverse types of information, including outbreak detection, case management, and contact tracing data. By centralizing data from various sources and structures, Casetivity enhances team communication and streamlines workflows, enabling seamless collaboration across public health efforts.
- Secure User Portals: Casetivity allows organizations to create portals tailored to specific roles and end users. This Portal Module appropriately partitions access to features and data in the DSS. This means that sensitive information is accessible only to authorized personnel, reducing the risk of data breaches while ensuring that users have the tools and information they need to perform their tasks efficiently.
By providing role-specific access, Casetivity streamlines workflows while maintaining data security, enabling public health agencies to maintain confidence in their data integrity and compliance with privacy regulations.
Core Interoperability Topics in Disease Surveillance: Data Sharing, Standardization, and Security
Achieving true interoperability requires addressing three core areas:
- Data Sharing Protocols: Effective disease surveillance relies on timely data exchange. 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 (National Institutes of Health, 2020).
- Standardized Formats: Casetivity 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.
- Secure Information Exchanges: Casetivity protects sensitive health information by employing advanced encryption methods, role-based access controls, and compliance with all relevant regulations. By prioritizing security, Casetivity fosters trust among stakeholders while facilitating data accessibility.
These foundational principles help ensure that disease surveillance systems supported by Casetivity are robust, reliable, and ready to meet the evolving challenges of modern public health.
Getting Started with Casetivity: Achieving Seamless DSS Interoperability
Modernizing your workflows with Casetivity is a straightforward process designed to minimize disruption and shorten the time to solution. Start by engaging stakeholders, including healthcare providers, IT staff, and public health officials, to identify their pain points and align goals and objectives. Our team can collaborate with different health department teams to assess existing systems and identify interoperability gaps.
From there, we will assist you with configuring Casetivity to fit your organization’s workflows and processes. This includes integrating the platform with existing systems and configuring dashboards, reports, and alerts to meet your specific needs.
Contact us today to schedule a demo and revolutionize how you manage and execute your disease surveillance program.
References:
- Centers for Disease Control and Prevention (CDC) (n.d.). About Public Health Data Interoperability. Retrieved from https://www.cdc.gov/data-interoperability/php/about/index.html
- National Institutes of Health (NIH) (May 29, 2020). Public health reporting and outbreak response: synergies with evolving clinical standards for interoperability. Retrieved from https://pmc.ncbi.nlm.nih.gov/articles/PMC7647366/