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What Does Data Modernization Look Like?						Print
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										Click on the cards below to connect to related stories in the 2022 DMI Snapshot. You can also download a printable version of this page [PDF – 486 KB] or the full visual booklet [6 MB, 40 Pages].Data modernization looks like...An **epidemiologist** spending the day investigating COVID cases instead of entering them into a spreadsheettwo people discussing data posted on a digital wallA **community health worker** knowing precisely which neighborhood needs a pop-up vaccine cliniccommunity health worker using a device with a COVID-19 contact tracing appA **public health analyst** producing a report that used to take two days in just two clicks of a buttonwoman wearing a mask with a tracking app on deviceA **research team** analyzing more than 12 million health records to understand latent tuberculosis infectionteam working together to access dataA **responder** catching an uptick in overdose deaths and sending fentanyl test strips to the frontlineperson using laptop with data on screenA **data scientist** visualizing social media feeds to help monitor suicide trendswoman looking at data on screenA **multi-state healthcare network** saving 160,000 staff hours that would have been spent on paperworknetworkA **policymaker** using a real-time wastewater surveillance dashboard to send resources where they're needed mostperson using ipadMade possible through technologies like...Automated, **electronic reporting** that replaces paper and reduces the burden on health department staffA suite of **cloud-based tools** that saves time and costs while analyzing more kinds of data faster than ever beforeA **data catalog** where CDC’s experts can see which data exist in any part of the agency on any disease or conditionA **North Star Architecture** for data that can be used by every level of public health to collect, transform, and share informationOne **front door** for state and local partners to send data to all of CDC instead of sending to multiple programs in multiple ways**Common standards** that help different data systems across public health and healthcare speak the same languageDashboards that **visualize data** and make it available to the public, researchers, and policymakers in real timeNovel approaches like **artificial intelligence and machine learning** that can discover relationships in the data that are hard for traditional methods to findAnd by finding new ways to...Bring people from across public health, government, academia, and industry together to find **common solutions** to common data problemspeople reviewing data at a meetingOffer public health staff opportunities to **learn by doing** and to access the latest data science training anytime, anywherehands on work by doing**Open up the data** so that more people have access to the information they need for decisions, both in emergencies and every dayresearch teamModernize the **policies and agreements** that inform how data are exchanged so that we can get information where it needs to go to save liveswomen participating in meetingMake sure that **health equity** is "baked in" from the start on everything we dokids doing yoga**Use resources wisely** by making sure everything we invest in is connected, flexible, and sustainable for the futureman examining digital resourcesResulting in...
**Data increased**
**Data increased**
**20,000+**
healthcare facilities delivering automated, real-time case reports — up from just 187 before the pandemic
**20,000+**
healthcare facilities delivering automated, real-time case reports — up from just 187 before the pandemic
**91%**
complete race information in syndromic surveillance — up from 80% in 2019 — which is critical important for understanding health disparities
**91%**
complete race information in syndromic surveillance — up from 80% in 2019 — which is critical important for understanding health disparities
**~90%**
of death records coded automatically using natural language processing — up from 75% with the previous system – with data to jurisdictions in minutes
**~90%**
of death records coded automatically using natural language processing — up from 75% with the previous system – with data to jurisdictions in minutes
**Time saved**
**Time saved**
**~80%**
decrease in development time for CDC’s response and surveillance programs using new Cloud components
**~80%**
decrease in development time for CDC’s response and surveillance programs using new Cloud components
**1+**
year reduction in the time it takes to understand suicide death trends thanks to new “nowcasting” capabilities
**1+**
year reduction in the time it takes to understand suicide death trends thanks to new “nowcasting” capabilities
**~5.5**
days from sample collection to data available in CDC’s wastewater surveillance system — down from ~4 weeks
**~5.5**
days from sample collection to data available in CDC’s wastewater surveillance system — down from ~4 weeks
**People connected**
**People connected**
**3,700+**
training hours completed by CDC staff in the Data Academy — an 83% increase over the previous year
**3,700+**
training hours completed by CDC staff in the Data Academy — an 83% increase over the previous year
**18**
multi-sector meetings of the Consortium for Data Modernization, covering 24 high-priority topics
**18**
multi-sector meetings of the Consortium for Data Modernization, covering 24 high-priority topics
**200+**
CDC staff actively engaged in defining priorities and solving challenges through DMI Implementation Teams
**200+**
CDC staff actively engaged in defining priorities and solving challenges through DMI Implementation Teams
							
					
							Last Reviewed:  April 11, 2023						Source: 	Centers for Disease Control and Prevention, Office of Public Health Data, Surveillance, and Technology
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        Syndicate homeSurveillance and DataData Modernization Initiativeplus icon2022 DMI Snapshotplus iconWhat Does Data Modernization Look Like?Welcome to the 2022 DMI SnapshotHow the Snapshot WorksBasicsPrioritiesplus iconBuilding the Right FoundationAccelerating Data into ActionDeveloping a State-of-the-Art WorkforceSupporting and Extending PartnershipsManaging Change and GovernancePartnershipsplus iconConsortium for Data ModernizationFederal AgenciesOrganizationsState, Tribal, Local, and Territorial Health DepartmentsIndustry PartnershipsCDC and USDS: Innovation through PartnershipTechnologiesplus iconNorth Star ArchitectureArtificial Intelligence and Machine LearningCloud 101: Storing and Sharing InformationEnterprise Data, Analytics, and VisualizationCDC Front DoorImproving Public Health Data PipelinesDMI and COVID-19DMI and Health EquityWhy Sustainable Funding MattersMonitoring + EvaluationNotable Milestones: 2019-2023Data Policy and Standardsplus iconData AuthorityAdvancing InteroperabilityData Modernization and PoliciesBlogs and StoriesPublications and Resourcesplus iconModernizing for New and Complex Threats2021 DMI Snapshot To receive email updates about Public Health Surveillance and Data, enter your email address Email Address			What's this				Submit


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