---
id: "coronavirus-smarter-crowdsourcing:recommendations/improve-information-infrastructure"
type: "GovLab policy recommendation"
title: "Improve Information Infrastructure"
url: "https://coronavirus.smartercrowdsourcing.org/recommendations/improve-information-infrastructure"
summary: "Improve public health monitoring and surveillance information infrastructure by standardizing data formats and definitions, sharing data, and developing regulations and legislation that support public health monitoring and surveillance."
source: "The GovLab (coronavirus.smartercrowdsourcing.org)"
licence: "Creative Commons Attribution-ShareAlike 4.0 International License (https://creativecommons.org/licenses/by-sa/4.0/)"
---

# Improve Information Infrastructure

Improve public health monitoring and surveillance information infrastructure by standardizing data formats and definitions, sharing data, and developing regulations and legislation that support public health monitoring and surveillance.

- Part of: [Smarter Crowdsourcing in the Age of Coronavirus](https://coronavirus.smartercrowdsourcing.org/), [all recommendations](https://coronavirus.smartercrowdsourcing.org/recommendations)

## Strategy 1

Develop standard definitions,structures,and variables for key public health monitoring and surveillance health data.

- Timeframe: 3-6 Months (medium)
- Audience: Academia
- Type: Research, Policy/Legislative/Regulatory, Data, Partnerships, Capacity Building
- Strategy page: https://coronavirus.smartercrowdsourcing.org/strategies/develop-standard-definitions,structures,and-variab

### Actions governments should take (strategy 1)

1. Convene stakeholders who manage Electronic Health Record (EHR) systems and other epidemiological data systems across the country and encourage a crosswalk of the current system(s) to identify potentials for standardizations.
2. Identify specific opportunities to make immediate improvements to interoperability (such as standardizing similar fields across systems) and long-term improvements to interoperability (such as inter-system identifiers) .
3. Identify standardizable demographic data fields in existing systems such as phone numbers, email addresses, home addresses, social security numbers or voting IDs. Rely on existing data structures where possible, such as those maintained by telecom providers, voting registries, or social security administrators.
4. Develop guidance for laboratories, hospitals, and healthcare providers on how to more consistently capture these important fields.
5. Hold a workshop with key stakeholders to develop standard definitions, structures and variables.
6. Develop a parallel system to collect the data that fixes the data infrastructure issues and that is compatible with existing instruments of data collection. This system should be opt-in and voluntary but it can be promoted through incentives.
7. Incentivize adoption of standardized process and outcome measures within jurisdictions (vertical standardization) and across jurisdictions (horizontal standardization) through technical assistance and cost reimbursements or cost sharing.

### Examples from around the world (strategy 1)

1. Estonia has one of the most [highly-developed national ID-card systems](https://e-estonia.com/solutions/e-identity/id-card/) in the world. Every citizen in Estonia has an online e-health record that can be tracked, and linked to a person’s electronic ID-card. The health records are secured with KSI Blockchain technology and are used to ensure data integrity. The information is only accessible to authorized health personnel. 99% of health data, prescription information and electronic billing in healthcare are digitized. The [Electronic Health Record](https://e-estonia.com/solutions/healthcare/) is a nationwide system that integrates data from diverse healthcare providers into a common record accessible to patients and doctors as a single electronic file. The system functions as a centralized, national database that retrieves data from various providers with different systems and presents the information into a standard format via the e-patient portal.

## Strategy 2

Promote and use open source and simple tools for data sharing between and among stakeholders.

- Timeframe: 3-6 Months (medium)
- Audience: Private Sector, Academia, Civil Society, Healthcare Providers, Government Workers, Organized Civil Society, Nonprofits
- Type: Policy/Legislative/Regulatory, Data, Technology/Innovation, Capacity Building
- Strategy page: https://coronavirus.smartercrowdsourcing.org/strategies/promote-and-use-open-source-and-simple-tools-for-d

### Actions governments should take (strategy 2)

1. Review policies that govern and restrict the storage and sharing of health information.
2. Set up an online, open repository for national surveillance data that provides timely reports in machine-readable format.
3. Offer informal peer learning opportunities where governments or representative associations coordinate informal forums or opportunities for individuals designing, implementing, and managing public health monitoring and surveillance programs to share ideas, challenges and best practices. These opportunities should be extended to include researchers, epidemiologists, or non-governmental actors.
4. Offer formal peer learning opportunities where governments or representative associations coordinate formal and structured forums or opportunities for those designing, implementing, and managing public health monitoring and surveillance programs to share ideas, challenges and best practices.
5. Publish open datasets to encourage participation of multiple research groups; use scientific peer-review as a system of checks and balances ensuring research quality.
6. Establish a code of conduct for research using public surveillance datasets.
7. Establish a single organization with the responsibility to oversee and advise on ways to improve data sharing and incorporate new technologies and approaches as they emerge.
8. Capitalize on existing databases or registers maintained by specific government agencies (such as social security, post service, or census data) to bolster existing public health monitoring and surveillance data systems.
9. Integrate these databases into the public health monitoring and surveillance data systems or contact tracing platform to increase ability for contact tracers to reach individuals confirmed as COVID-19 positive or identified as contacts of COVID-19 positive cases.
10. [Develop and use a data governance playbook for epidemic response and building broad commitment to it (see GovLab Zika/MBD Report)](https://zika.smartercrowdsourcing.org/en/files/smarter-crowdsouring-for-zika-and-other-mosquito-borne-diseases.pdf)

### Examples from around the world (strategy 2)

1. The European Bioinformatics Institute launched the [Covid-19 Data Portal](https://www.covid19dataportal.org/) in collaboration with multiple European partners. The portal is funded by the European Union to allow researchers and healthcare professionals to [submit, share, and access publicly available data on COVID-19](https://coronavirusexplained.ukri.org/en/article/vdt0011/) in order to assist in developing diagnostic tools, treatment and a vaccine.

## Strategy 3

Develop and advocate for a legislative framework for public health monitoring and surveillance health data.

- Timeframe: 6-12 Months (long)
- Audience: Government Workers
- Type: Policy/Legislative/Regulatory, Data
- Strategy page: https://coronavirus.smartercrowdsourcing.org/strategies/develop-and-advocate-for-a-legislative-framework-f

### Actions governments should take (strategy 3)

1. Conduct an analysis of existing regulatory and legislative mechanisms that may hinder or inhibit collecting, standardizing or sharing data.
2. Issue temporary executive orders to enable data sharing while working toward a more durable and long-term regulatory and legislative solution. Use executive orders or other regulatory or legislative authorities to incentivize data sharing.
3. Advocate for and develop new or replacement legislation and regulations that codify processes and mechanisms for open data sharing and interoperability of data structures and systems.
4. Pass legislation or regulations that allows for controlled access to clinical data and the secondary use of that data.
5. Use an executive order to direct all agencies to open the data they have related to measuring the impact of COVID, including both public health and economic data and data relevant to measuring impact on minority and vulnerable populations.
6. issue a statistical policy directive establishing any needed public health data standards to improve national, local and non-governmental reporting of information necessary to respond to the coronavirus pandemic. Any new data standard or directive should apply consensus, voluntary standards to the extent practicable.
7. Adopt a standard that is used to transport the data when you don’t know who the recipient is. Examples of data sharing models include [HL7 - FHIR](https://www.hl7.org/) and [N3C](https://covid.cd2h.org/) (N3C Data Enclave is a secure platform through which the harmonized clinical data provided by our contributing members is stored).
8. For existing legislation, develop proposed replacement legislation and advocate for this legislation through the appropriate legislative processes and procedures.
9. Reduce the regulatory burdens that hinder or inhibit data sharing between jurisdictions.

### Examples from around the world (strategy 3)

1. [The Operational Framework for Mutual Aid Requests (OFMAR) is a mechanism that allows Provincial/Territorial (PT) governments to identify and share healthcare assets and professionals throughout jurisdictions. It has also established procedures to conduct emergency registration of healthcare professionals in other jurisdictions to ensure they are available to travel to the areas where they are most needed.](https://www.canada.ca/en/public-health/services/diseases/2019-novel-coronavirus-infection/health-professionals/covid-19-pandemic-guidance-health-care-sector.html)