NEWS & BLOGS

Your Health Data is the New Prescription: Why the FDA is Looking Beyond Trials to 'Real-World' Information

Provision Consulting Group
1 minute ago
3 min read

The way we live today is intrinsically tied to data. From the prescriptions we receive at the hospital and the glucose meters we use at home to the ECG features on our smartwatches and the records in our health apps—we are constantly generating a stream of "real-world data."

Crucially, this data is now moving beyond simple record-keeping. Recent news indicates that this real-world data can serve as compelling evidence to support new product approvals (or regulatory reviews).

The FDA, in its announcement on December 15, 2025, significantly lowered a major barrier by stating it will not always require patient-level, personally identifiable data when submitting Real-World Evidence (RWE). This signals a pivotal shift toward:

Lowering the burden of personal information disclosure.
Placing greater emphasis on 'results from the real world.'

From Controlled Trials to Real-World Results: RWE and RWD

Traditionally, the safety and efficacy of new products (drugs, medical devices, etc.) are confirmed through highly controlled clinical trials. However, clinical trials are often time-consuming, expensive, and face difficulties in participant recruitment.

This is driving a global trend: a call to look beyond clinical trials and incorporate the actual results seen when products are used in real-world settings.

The FDA refers to the evidence generated from this real-world data as Real-World Evidence (RWE), and the data itself as Real-World Data (RWD). RWD encompasses diverse sources such as: Electronic Health Records (EHR/EMR), Insurance claims data, Patient registries, Data from wearables (smartwatches, etc.)

The biggest change in this recent update is the "personal data barrier." The FDA has officially confirmed that applicants are not obligated to submit all 'individual patient-level, personally identifiable data' every time RWE is presented, though it may still be required in specific circumstances.

What Does This Announcement Change?

1. Potential Reduction in the "Waiting Time"

Conducting large, lengthy clinical trials is particularly challenging in areas with small patient populations (like rare diseases) or in rapidly evolving fields (such as Digital Health, AI, and Wearables).

By enabling the better use of RWD/RWE, the speed at which valuable evidence can be gathered and submitted is likely to accelerate. It is important to note, however, that this does not eliminate the need for clinical trials.

2. Better Visibility into "Real-World Performance"

Clinical trials operate under pristine, controlled conditions. The real world, however, is far more complex, encompassing variations in age, lifestyle, co-morbidities, concomitant medications, and diverse usage environments.

RWD captures this reality, offering a clearer picture of 'what results occur when the product is used in practice.'

3. Easing the Burden of Personal Data Issues

The core message of this announcement is clear: Data utilization previously hampered by personal information concerns can now be discussed on a more practical, realistic basis.

Crucially, submitting less personal data does not mean the review process will be looser. On the contrary, the focus on the quality, reliability, and fairness of the data will become even more stringent.

A Clear Signal for the Future

The FDA's announcement is, in short, a clear signal that the agency is moving decisively away from a reliance solely on clinical trials and toward a model that integrates real-world data.

With the FDA opening the door further, the "method of health data collection and generation" becomes the key differentiator for companies. While this is primarily an issue for the pharmaceutical and medical device sectors, it offers a wider implication for all industries: we are entering an era where real-world outcomes must be explained through data.

In the future, a simple statement like "we tested it" may be less important than the quality of the data, the criteria used, and the consistency of the verification methods.