How to Monetize Healthcare Data in Snowflake

The healthcare data market is thriving and is estimated to exceed $43 billion. The rising demand for data insights within the healthcare sector primarily fuels this growth. As a result, healthcare companies possess a valuable data treasure that can be used as a separate income stream.

The Snowflake AI Data Cloud is a leading cloud-based data platform that provides a powerful and secure environment for storing, analyzing, and sharing healthcare data. Snowflake has created a marketplace to share data between organizations for free or profit.

In this blog, we’ll walk you through how the Snowflake Marketplace works, the different pricing models available for selling your data, and strategies you can employ to monetize your healthcare data.

What is the Snowflake Marketplace and How Does it Work?

The Snowflake Marketplace platform within the Snowflake Data Cloud allows users to discover, try, buy, and integrate third-party data and solutions directly into their Snowflake environment.

Users can explore a variety of data sets, connectors, and applications within the marketplace, acquire them seamlessly through Data Shares, and incorporate them into their Snowflake data workflows. This marketplace makes it easy to find and integrate external data sources, enhancing Snowflake’s versatility and capabilities and, ultimately, helping businesses get more value from their Snowflake investment.

There are two types of listings in the marketplace: public and private.

Private allows you to create a share that is only seen by specific customers you designate. Private listings let you take advantage of the capabilities of listings to share data and other information directly with other Snowflake accounts in any Snowflake region. Conversely, public listings are visible to any Snowflake account in the Marketplace.

Pricing Models for Healthcare Data in Snowflake Marketplace

In the Snowflake Marketplace, data providers can leverage two flexible pricing models to monetize their offerings: usage-based and subscription-based.

Usage-based

This pricing allows providers to charge consumers based on their actual data usage. This can be implemented in three ways:

Monthly Base Fee

Charges a fixed price per calendar month in which at least one query that accesses paid data is run. The fixed price is not charged if no query is run against data in the listing. The monthly fee is not prorated. For example, here’s clinical trial data being sold on the Marketplace for $2084 per month:

Per Query

Charges a fixed fee for each query executed against the data. This can be implemented with or without a monthly fixed fee.

Billable Events

Only listings that share an application can use Custom Event Billing, which charges based on billable events. With Custom Event Billing, you can charge a price for specific types of usage of your application. For example, you can charge:

Per row of data modified by the application
Per procedure call made by the application
Per row of data used by the application
Per unique row of data updated in a month by your application (monthly active rows)

You can also charge for other events defined in your application code. This feature is currently in public preview.

Subscription-Based

For this pricing plan, consumers are charged upfront for access to the data product for a specified term. You can offer the listing with recurring billing for a subscription that auto-renews (preview) or non-recurring billing for access for a fixed term. The provider determines the term, which can be between 1 and 36 months.

The choice between these models depends on the specific data product and target audience. Usage-based pricing offers flexibility for consumers and can benefit providers with unpredictable usage patterns. Subscription-based pricing provides predictable revenue streams and can be attractive for consumers needing consistent data access.

Strategies for Monetizing Healthcare Data with Snowflake

Raw Data

The first and most straightforward strategy to monetize your business’s healthcare data is simply making raw data (stripped of Personally Identifiable Information (PII)) available in the Marketplace. This allows other organizations to use the data to create insights.

Some examples of in-demand healthcare data include:

Electronic Health Records (EHRs): Patient information, medical history, diagnoses, treatments, and prescriptions are stored digitally.
Clinical Trial Data: Information generated during the testing of new drugs and medical treatments.
Genomic Data: DNA sequences and genetic information for personalized medicine and research.
Health Monitoring Devices Data: Data was collected from wearable devices and health apps to monitor activities, vital signs, and overall well-being.
Health Insurance Claims Data: Information related to medical services, procedures, and costs submitted for insurance reimbursement.
Telehealth and Telemedicine Data: Patient consultations, remote monitoring, and virtual care interactions.
Public Health Databases: Aggregated data on diseases, outbreaks, and population health for epidemiological research.
Medical Imaging Data: X-rays, MRIs, CT scans, and other diagnostic imaging results.
Pharmaceutical Research Data: Data from drug discovery, development, and clinical trials.
Remote Patient Monitoring Data: Continuous monitoring of patients outside of traditional healthcare settings, often for chronic conditions.

Here’s an actual example of health-related characteristics aggregated to given locations being sold on the Marketplace:

Enriched Data for Business Intelligence

The second strategy is to enrich your raw data by deriving your insights and selling that data on the Marketplace. This can be even more enticing to potential data consumers as they won’t have to employ their own data analysts.

Several key steps are involved in enhancing your raw healthcare data:

Data Cleaning: Identify and rectify the raw data’s inaccuracies, inconsistencies, and missing values to ensure its quality.
Normalization: Standardize data formats, units, and terminology to create a consistent dataset for analysis.
Integration: Combine data from different sources to create a comprehensive dataset that provides a holistic view of healthcare information.
De-identification: Ensure compliance with privacy regulations by removing or anonymizing personally identifiable information (PII) to protect patient privacy.
Data Transformation: Convert raw data into a format suitable for analysis, such as aggregating data over specific periods or creating relevant metrics.
Data Enhancement: To provide a more comprehensive context, raw data should be augmented with additional information, such as demographic data, socioeconomic factors, or external data sources.

Here’s an actual example of Centers for Medicare & Medicaid Services (CMS) data that has been combined into separate views for even further analysis being sold on the Marketplace:

Data Clean Rooms

The Marketplace can also market your data for use in a data clean room. A data clean room is a secure and controlled environment that allows multiple companies or divisions to bring data together for joint analysis while adhering to certain guidelines and regulations.

Data clean rooms control what data comes in, how the data in the clean room can be joined to other data in the clean room, what types of analytics each party can perform on the data, and what data (if any) can leave.

Any PII data loaded into the clean room is secured and encrypted. The data owner has full control over the clean room, while approved partners can get a feed with anonymized data.

Utilizing private listings in the Marketplace, data providers and consumers can share data to combine it and provide an enriched outcome for all parties.

Legal and Ethical Considerations for Selling Data

Selling healthcare data (or any type of data) raises several legal and ethical concerns that businesses must navigate to ensure compliance and maintain public trust. From a legal standpoint, data privacy regulations such as the General Data Protection Regulation (GDPR) in the European Union and the California Consumer Privacy Act (CCPA) in the United States impose strict requirements on collecting, processing, and transferring personal data.

Businesses must obtain informed consent from individuals before selling their data, provide transparency about how the data will be used, and implement robust security measures to safeguard against data breaches. Failure to comply with these regulations can result in significant fines and legal consequences.

Ethically, selling data introduces considerations related to user consent, fairness, and the responsible use of information. Businesses must be transparent about their data practices and ensure that individuals know how their data will be used.

Additionally, there is a responsibility to avoid discriminatory practices or the exploitation of vulnerable populations by selling sensitive information. Striking a balance between business interests and ethical considerations is crucial for maintaining a positive reputation and establishing customer trust.

To navigate these complexities, companies should adopt ethical data practices, prioritize transparency, and stay informed about evolving legal frameworks surrounding data protection and privacy.

Suppose the data you plan to sell on the Marketplace contains Personally Identifiable Information (PII). In that case, Snowflake has many features to mask or omit that information before it gets to the Marketplace. This is essential to ensure your customer’s information is not compromised.

Closing

The healthcare industry’s impressive $43 billion valuation highlights the increasing importance of using data-driven insights in the sector. Companies in this industry are realizing the immense value of their data, and that’s where platforms like Snowflake step in to play a crucial role in securely storing, analyzing, and sharing this valuable data.

The introduction of the Snowflake Marketplace is another sign of how data monetization is evolving. It provides a dedicated platform where organizations can share healthcare data, whether for free or for profit, marking a significant shift in how data is exchanged within the industry.

If your organization wants to monetize your healthcare data in the Marketplace, the Snowflake experts at phData can help! Contact us today for advice, best practices, actionable strategies, and more!

FAQs

How do I become a seller on the Snowflake Marketplace?

Within your Snowflake account, navigate to the Marketplace and click the Become a Provider button at the bottom of the page. Users with the CREATE DATA EXCHANGE LISTING privilege can create a listing for data they’d like to sell within their Snowflake account.

Can I update or modify my retail datasets after they are listed on the Snowflake Marketplace?

You can modify, unpublish, or delete a listing from Provider Studio in Snowsight. When you unpublish a listing, existing consumers can still access the associated data product unless you remove them from the share. To remove a listing and access to the listing for all consumers using the listing, delete the listing.