In the previous blog, we discussed the various ways of monetizing HealthTech apps. In this blog, we take a closer look at how to monetize digital health data.
The healthcare industry is generating more data than ever before. It is among the leading industries across the globe when it comes to data generation.
Whether it is accelerating medical innovation or augmenting the health outcomes of patients, data is the cornerstone of all advancement. This explosive growth in healthcare data is causing new opportunities to mushroom across the globe.
Companies like IQVIA, Embleema, and Prognos Health are making the most of this opportunity by creating robust, compliant, and scalable solutions to mobilize and monetize healthcare datasets.
In this blog, we take a holistic look at how digital health data can be monetized by product owners. Data monetization is much more than just “selling data”. It requires a nuanced understanding of the various revenue-making strategies for healthcare data, which is the aim of this blog.
Let’s hit the ground running!
When to Consider Monetizing Digital Health Data
Data monetization in healthcare is almost like a jigsaw puzzle. Several pieces of this puzzle need to fall into place before a sustainable revenue model can be established. Here are a few questions to ask yourself that can help identify if you are ready to take the plunge into monetizing digital health data.
1. Do you have access to significantly large digital health datasets?
Selling healthcare data profitably requires you to have access to a continuous stream of massive, aggregated, and purposeful datasets. Make sure that you have a large enough dataset in hand before considering healthcare data monetization.
2. What is the quality of the datasets that you wish to monetize?
If the data you are trying to monetize is of good quality, free from statistical noise, and de-duplicated (i.e. free from duplications and redundancies), you will have a clear advantage in the market.
3. How rich and useful is the information generated by your dataset?
Data that offers insights into something new, or provides incrementally better information about a problem usually have a premium price tag attached to it. Hence, such data will generate better returns for you.
To understand the factors affecting data monetization better, let’s take the case of Fractal Analytics, for example.
The key is to ask yourself this: what problem is my data solving? The usefulness of your data in the buyer’s decision-making process along with specific use cases of the data will make it much easier to monetize at scale.
Key Steps to Monetize Digital Health Data from Scratch
Having discussed the ‘when’ part of healthcare data monetization, we now move to the ‘how’ part of it. Below are the key steps to follow.
1. Start by identifying the right paying users for your data.
The best place to begin is to identify the right “customers” or “paying users” for your data. Understanding how they interact with the data as well as with other data stakeholders is key.
2. Map their unique data requirements and information needs.
Dive deeper into the specific data needs of your users. Identifying their purpose behind obtaining the data will help you to address their unique data requirements and information needs.
3. Research competitors who are providing similar data.
Assess the value propositions that your competitors bring to the table. Understand what they are doing well, and where their weaknesses lie. Your data offerings will be shaped significantly by such competitor analysis.
4. Identify the compliance and regulatory requirements.
Ensure that the data collection happens in adherence to the existing compliance requirements like the Health Insurance Portability and Accountability Act of 1996 (HIPAA) in the U.S. and the General Data Protection Regulation (GDPR) in the EU.
5. Determine the data pricing and the revenue model.
Identify how similar datasets are priced in the market. Select the right revenue model from a wide variety of options, like the subscription model, the one-time payment model, the volume-based pricing model, the user-based pricing model, and so on.
6. Run a pilot/test campaign with early adopters.
Conduct a pilot or a test campaign with a handful of early adopters or “first customers.” Experiment with everything–starting with the core data offerings, the data delivery mechanisms, the pricing and revenue models, as well as any additional data services you might be offering.
7. Keep looking for opportunities for data innovation.
Congratulations! You are now ready to take your digital health data solution to the market and scale up your monetization model accordingly. Don’t forget to keep an eye out for timely opportunities in data innovation.
Let’s consider another example to understand healthcare data monetization better.
A Few Do’s and Don’ts
|Ask your users to provide their consent in writing before collecting the data. Users may choose to opt in or opt out of sharing their healthcare data, as applicable.||When generating first-party data, it is important to ensure that data collection does not hamper the user experience of your app.|
|Anonymization and de-identification of health data are a must.||Never compromise your data integrity, no matter how complicated the data journey gets. Remember, once your customers lose trust in your data, it will be hard to win them back.|
At present, the environment is ripe for digital health data to be harnessed and monetized. Healthcare data is sought by a wide range of public and private organizations. These include pharmaceutical companies, wellness and fitness brands, life science research hubs, hospitals and diagnostic centers, community health organizations, govt. healthcare organizations, medical device manufacturers, clinical experts and innovators, and so on. Hence, monetizing your digital health data is the right step forward to generate lucrative returns through the right revenue model and carefully crafted go-to-market strategies.
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