A Brief History of Public Health Informatics—Lessons for Leaders and a Look Into the Future

Ross, David A.; Baker, Edward L.

doi:10.1097/phh.0000000000001672

Cited by 5 publications

(3 citation statements)

References 11 publications

(20 reference statements)

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“…Public health data dashboards are a critical communication tool for governments, health organizations, and academic research teams to bring rapidly emerging health surveillance information to a broader audience [ 1 , 2 ]. The rise of data dashboards in the United States during the COVID-19 pandemic resulted in a rapid proliferation of interactive maps, charts, and graphs and the wide dissemination of disease surveillance data by governmental organizations and research teams [ 3 , 4 ].…”

Section: Introductionmentioning

confidence: 99%

Public Health Dashboards in Overdose Prevention: The Rhode Island Approach to Public Health Data Literacy, Partnerships, and Action

Yedinak,

Krieger,

Joseph

et al. 2024

J Med Internet Res

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As the field of public health rises to the demands of real-time surveillance and rapid data-sharing needs in a postpandemic world, it is time to examine our approaches to the dissemination and accessibility of such data. Distinct challenges exist when working to develop a shared public health language and narratives based on data. It requires that we assess our understanding of public health data literacy, revisit our approach to communication and engagement, and continuously evaluate our impact and relevance. Key stakeholders and cocreators are critical to this process and include people with lived experience, community organizations, governmental partners, and research institutions. In this viewpoint paper, we offer an instructive approach to the tools we used, assessed, and adapted across 3 unique overdose data dashboard projects in Rhode Island, United States. We are calling this model the “Rhode Island Approach to Public Health Data Literacy, Partnerships, and Action.” This approach reflects the iterative lessons learned about the improvement of data dashboards through collaboration and strong partnerships across community members, state agencies, and an academic research team. We will highlight key tools and approaches that are accessible and engaging and allow developers and stakeholders to self-assess their goals for their data dashboards and evaluate engagement with these tools by their desired audiences and users.

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Section: Introductionmentioning

confidence: 99%

Public Health Dashboards in Overdose Prevention: The Rhode Island Approach to Public Health Data Literacy, Partnerships, and Action

Yedinak,

Krieger,

Joseph

et al. 2024

J Med Internet Res

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show abstract

“…Quickly expanding these networks to a national scale that reaches a wide range of populations and settings has significant technical and sustainability challenges. 6 , 7 Similarly, chronic disease surveillance registries need timely access to linked clinical, administrative, and social determinants of health data across diverse healthcare settings. 8 Chronic disease surveillance must address additional challenges, given the need for diagnostic, therapeutic, and observational longitudinal data over many years.…”

Section: Introductionmentioning

confidence: 99%

MENDS-on-FHIR: leveraging the OMOP common data model and FHIR standards for national chronic disease surveillance

Essaid,

Andre,

Brooks

et al. 2024

JAMIA Open

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Objectives The Multi-State EHR-Based Network for Disease Surveillance (MENDS) is a population-based chronic disease surveillance distributed data network that uses institution-specific extraction-transformation-load (ETL) routines. MENDS-on-FHIR examined using Health Language Seven’s Fast Healthcare Interoperability Resources (HL7® FHIR®) and US Core Implementation Guide (US Core IG) compliant resources derived from the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) to create a standards-based ETL pipeline. Materials and Methods The input data source was a research data warehouse containing clinical and administrative data in OMOP CDM Version 5.3 format. OMOP-to-FHIR transformations, using a unique JavaScript Object Notation (JSON)-to-JSON transformation language called Whistle, created FHIR R4 V4.0.1/US Core IG V4.0.0 conformant resources that were stored in a local FHIR server. A REST-based Bulk FHIR $export request extracted FHIR resources to populate a local MENDS database. Results Eleven OMOP tables were used to create 10 FHIR/US Core compliant resource types. A total of 1.13 trillion resources were extracted and inserted into the MENDS repository. A very low rate of non-compliant resources was observed. Discussion OMOP-to-FHIR transformation results passed validation with less than a 1% non-compliance rate. These standards-compliant FHIR resources provided standardized data elements required by the MENDS surveillance use case. The Bulk FHIR application programming interface (API) enabled population-level data exchange using interoperable FHIR resources. The OMOP-to-FHIR transformation pipeline creates a FHIR interface for accessing OMOP data. Conclusion MENDS-on-FHIR successfully replaced custom ETL with standards-based interoperable FHIR resources using Bulk FHIR. The OMOP-to-FHIR transformations provide an alternative mechanism for sharing OMOP data.

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“…Public health networks that collect, harmonize, and report on acute diseases have traditionally relied on manual health surveys and local data collection methods. Quickly expanding these networks to a national scale that reaches a wide range of populations and settings has significant technical and sustainability challenges [6,7]. Similarly, chronic disease surveillance registries need timely access to linked clinical, administrative, and social determinants of health data across diverse healthcare settings [8].…”

Section: Introductionmentioning

confidence: 99%

MENDS-on-FHIR: Leveraging the OMOP common data model and FHIR standards for national chronic disease surveillance

Essaid,

Andre,

Brooks

et al. 2023

Preprint

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Objective The Multi-State EHR-Based Network for Disease Surveillance (MENDS) is a population-based chronic disease surveillance distributed data network. Current data partners create institution-specific extraction-transformation-load (ETL) routines. MENDS-on-FHIR provides a standards-based ETL approach using Health Language Seven's Fast Healthcare Interoperability Resources (HL7® FHIR®) and US Core Implementation Guide (US Core IG) compliant resources derived from the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). Materials and Methods The input data source was a research data warehouse (RDW) containing clinical and administrative data in OMOP CDM Version 5.3 format. OMOP-to-FHIR transformations, using a unique JavaScript Object Notation (JSON)-to-JSON language called Whistle, created FHIR R4.0.1/US Core IG V4.0.0 conformant resources that were stored in a local FHIR server. A REST-based Bulk FHIR $export request extracted FHIR resources to populate a local MENDS database. Results Eleven OMOP tables were used to create 10 FHIR/US Core compliant resource types. A total of 1.13 trillion resources were extracted and inserted into the MENDS repository. A very low rate of non-compliant resources was observed. Discussion OMOP-to-FHIR transformations passed validation with only minimal non-compliance issues. These resources provided the clinical and administrative data elements required by the MENDS surveillance use case. The Bulk FHIR application programming interface (API) enabled population-level data exchange using interoperable FHIR resources. The OMOP-to-FHIR transformation pipeline creates a FHIR "facade" for accessing OMOP data. Conclusion MENDS-on-FHIR successfully replaced custom ETL with standards-based interoperable FHIR resources using Bulk FHIR. The OMOP-on-FHIR transformations provide an alternative mechanism for sharing OMOP data.

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A Brief History of Public Health Informatics—Lessons for Leaders and a Look Into the Future

Cited by 5 publications

References 11 publications

Public Health Dashboards in Overdose Prevention: The Rhode Island Approach to Public Health Data Literacy, Partnerships, and Action

Public Health Dashboards in Overdose Prevention: The Rhode Island Approach to Public Health Data Literacy, Partnerships, and Action

MENDS-on-FHIR: leveraging the OMOP common data model and FHIR standards for national chronic disease surveillance

MENDS-on-FHIR: Leveraging the OMOP common data model and FHIR standards for national chronic disease surveillance

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