IOM issues 4 recommendations for clinical data sharing

Laura Pedulli | | Health Exec | Quality

The Institute of Medicine has released four recommendations urging significant changes in how clinical trial data are shared, reports Modern Healthcare. 

IOM's recommendations are as follows:

1. Data sharing should be the expectation and the norm.

2. A fully analyzable set of data should be available no later than 18 months after a study's completion.

3. Strategies should be implemented to encourage data sharing, including the creation of technological platforms, boosting financial support and creating incentives.

4. The fourth recommendation calls ons sponsors of a study to take the lead on making the recommendations happen.

Read more below:

IOM urges vast changes in clinical trial data sharing

Laura Pedulli

Related Content

The top 25 children's heart hospitals in the US
Study ranks US health system dead last among wealthy nations
The 25 top US hospitals for diabetes care
The 25 best heart hospitals in the United States
Medical staff must have a say in what AI is adopted for patient care, says AMA
Cardiology salaries keep rising, outpacing consumer prices—interventional cardiologists see biggest jump

Around the web

Cardiovascular Business
Q&A: MedAxiom CEO explores key trends in cardiologist, cardiovascular surgeon compensation

Compensation for heart specialists continues to climb. What does this say about cardiology as a whole? Could private equity's rising influence bring about change? We spoke to MedAxiom CEO Jerry Blackwell, MD, MBA, a veteran cardiologist himself, to learn more.

Cardiovascular Business
Payment cuts and beyond: Key takeaways for cardiologists from the 2025 Medicare Physician Fee Schedule

The American College of Cardiology has shared its perspective on new CMS payment policies, highlighting revenue concerns while providing key details for cardiologists and other cardiology professionals. 

AI in Healthcare
A modest proposal to rally AI regulators around a simple game plan

As debate simmers over how best to regulate AI, experts continue to offer guidance on where to start, how to proceed and what to emphasize. A new resource models its recommendations on what its authors call the “SETO Loop.”