Public Health Data Management & Health Information Exchange Solutions

To support disease surveillance and outbreak mitigation, public health organizations are burdened with collecting and processing high volumes of non-standardized data, and are often spending valuable time doing so manually. Reconciling and harmonizing data feeds is an urgent need to enable timely analytics and surveillance. Solutions that automate data cleansing, validation and workflow processes are necessary to free valuable public health resources and improve outcomes.

Download Solution Guide

The Public Health Data Management Solution (DMS) enables Public Health jurisdictions to:

  • Accelerate and streamline the handling, administration and communication of a variety of public health information.
  • Shift workloads from reconciling data issues to addressing care related activities to make our communities safer and achieve public health transformation.
  • Automate rejection of incomplete or substandard data sets. Auto-notify providers or labs with data issues.
  • Ensure incoming data sets are complete while still allowing critical data to pass through.
  • Standardize different formats and normalize outcomes to state reporting and FHIR standards.
  • Improve data quality with features like zip code to city validation.
  • Increase timeliness of reporting result.
  • Allow public health departments to manage and notify labs that stop sending data to disease surveillance systems.
  • Provide full HIPAA compliant security and auditing with the ability to automatically purge any data that is no longer needed.
  • Highly configurable workflow engine to meet your specific needs.
  • Quickly assign and approve priority tasks.
  • Fully compliant with HIPAA, FERPA, and other public sector regulations and security standards.
  • HL7 Compliant for full data integration and exchange.

SSG DMS Benefit Summary

Successfully deployed in multiple states

Successfully deployed in multiple states

Customizable government process engine

Customizable government process engine

Aggregates diverse lab data at scale into single repository

Aggregates diverse lab data at scale into single repository

Standardizes formats, normalizes outcomes to local reporting standards

Standardizes formats, normalizes outcomes to local reporting standards

Create customized dashboards for business intelligence and workflow distribution

Create customized dashboards for business intelligence and workflow distribution

Saves team resource time with automated data processing, cleansing, validation

Saves team resource time with automated data processing, cleansing, validation

Watch the DMS Video

Key Features

  • Easy to deploy. Rapidly go-live with Public Health DMS in days
  • Provides information validation
  • Support diverse data formats including but not limited to XLS, XLSX, CSV, TSV, JSON, XML
  • Leading, industry standard platform.
  • Privacy & Security
  • HL7 Compliant
  • Configurable / Customizable
  • Actionable Intelligence
  • Full Warranty

Accelerate Value from Diverse Public Health Data

Request A Demo

FAQs

  1. How do modern platforms handle HL7 integration and real-time data exchange? 

Modern platforms use sophisticated orchestration engines to ingest, transform, and route HL7 and FHIR messages in real-time. These systems automate the validation and normalization of incoming data, ensuring it is immediately usable by downstream disease surveillance or immunization modules.

For example, they can receive raw data from a source system (like a lab), translate it into a standard HL7 format, and route it to multiple destinations (like an EHR or billing system) simultaneously. Meanwhile, specific clinical events, such as a patient being admitted (ADT message) or a lab result being verified (ORU message), can trigger real-time data exchange. 

  1. What should agencies look for in health information exchange software? 

Agencies should look for software that can handle diverse data formats, including unstructured flat files and non-standard messages, beyond basic HL7. The ideal solution provides automated data cleansing, deduplication, and robust security auditing to maintain the integrity and privacy of sensitive health information.

  1. How can public health systems extract clean, analysis-ready data across programs?

Public health systems can achieve clean, analysis-ready data by using platforms with built-in data normalization, validation, and deduplication tools. Platforms like Casetivity, for example, can reconcile multiple data feeds and correct errors in real time, providing a single source of truth to business intelligence tools for cross-program analysis and reporting.