---
id: "coronavirus-smarter-crowdsourcing:strategies/Develop-standard-definitions,structures,and-variab"
type: "GovLab policy strategy"
title: "Develop standard definitions,structures,and variables for key public health monitoring and surveillance…"
url: "https://coronavirus.smartercrowdsourcing.org/strategies/develop-standard-definitions,structures,and-variab"
summary: "Develop standard definitions,structures,and variables for key public health monitoring and surveillance health data."
source: "The GovLab (coronavirus.smartercrowdsourcing.org)"
licence: "Creative Commons Attribution-ShareAlike 4.0 International License (https://creativecommons.org/licenses/by-sa/4.0/)"
---

# Develop standard definitions,structures,and variables for key public health monitoring and surveillance…

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
- Recommendation: [Improve Information Infrastructure](https://coronavirus.smartercrowdsourcing.org/recommendations/improve-information-infrastructure)
- Part of: [Smarter Crowdsourcing in the Age of Coronavirus](https://coronavirus.smartercrowdsourcing.org/)

## Actions governments should take

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

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.