The 6-step guide to extract value from open data

The healthcare use case with Tekkare, an expert in public official healthcare sources.

If data is the 21st century’s fuel, open data is its largest oil field.

Ever heard of #opendata? This promise of accessing nearly unlimited raw data from governments in all sectors: Education, Urbanism, Environment, Public policies, Healthcare?

Democracies strive to provide as much data available as possible, to build trust and empower citizens and organizations.

For the past decade, open data has exploded. The European Data Portal had 400,000 available datasets in 2016, it now has 1.5 million. a nearly 4x in 8 years.

This is all very appealing.

Yet, if 1.5 million raw datasets are not analyzed and contextualized, they will remain largely untapped.

(Unsplash credits: Daniil Silantev)

Extracting value from open data

Here is a 6-step guide to extract value from official public data, with the healthcare industry. This is how Tekkare, a world leader in healthcare official public data management does it:

Identify and collect 

First identify and collect the most valuable official healthcare public data sources all around the world. It is an expertise our team has built over the 8 years of existence of @Tekkare, and also our founder’s 30 years of experience in life sciences knowledge.

Two ways to identify the data: our team analyses the countries open data policies and look after new releases, or our partners identify relevant datasets for their use. 

We clean, enrich, optimize and normalize all collected data

Clean: we control the quality of the variables, and we keep essential variables for the analysis

Enrich: link a data set with an other data set in order to add information on the original data set. For example: a prescribed drug database can be linked with a price database to match a drug and its price. 

Optimize: organize data tables to allow efficient data management, to rapidly access to all data, which is key when managing billions of data points.

Normalize: healthcare data is complex. From one source to another, from one country to another, it needs standardized terms and nomenclatures/coding to make databases more readable and accessible.

Repeat: build the largest data warehouse dedicated to official healthcare public data

Today we regularly collect over 200 sources across the world, from global organizations such as WHO, EU Clinical Trials or OECD, to national governmental agencies, such as the FDA, NHS, CNAM (French Social Security), Ministério da Saude - Datasus Brazil, the Ministry Of Health, Labour And Welfare of Japan, BfArM etc.

As of February 2024 we manage over 1500 datasets from these sources, and counting. 

All these datasets are available through our datawarehouse, for data scientists who wish to build applications, enriched with their own proprietary data. 

Develop business analytics applications with the user experience in mind to facilitate the use of this data 

For our no-code users, from business insights, market access, marketing, clinical and medical affairs or salesforce effectiveness departments, we built a (really) user-friendly and modern platform, allowing easy navigation across all our available data and analysis. 

Access in 5 clicks the monthly sell-out for Rx drugs in France, 2 clicks to scout for all FDA approvals on a given indication, 1 click to see our Global Oncology data coverage in 30 countries…

Keep the data updated on a regular basis

A data platform is good, but you know what’s better? An up-to-date data platform. We constantly update all data sets we show on the platform, adapting to the frequency of each data set’s lifecycle. 

Hence, the French RPPS file (Healthcare Professional Directory file) is updated daily, while FDA Approvals’ data is updated weekly, Transparency data annually, and so on. 

We run approximately 10,000 data sets updates per year. 

Provide a digital ecosystem for partners :

Our partners can access our ecosystem in various ways: 

 - a web platform, with all our enriched analyses, built over 8 years on all our partner’s use cases

 - a data warehouse, for data science team to feed internal applications, with the goal of enriching their internal data with external reliable sources

 - a data catalog, containing all our data sets, to identify potential analyses of interest.

@Tekkare has mastered this process for 8 years, building the most sophisticated datawarehouse of public official healthcare sources.