Five worthy reads is a regular column on five noteworthy items we have discovered while researching trending and timeless topics. This week, we explore the use of synthetic data in healthcare.

Synthetic data in healthcare

Designed by Dhanwant Kumar

Healthcare generates data at an astonishing rate, with a single patient contributing about 80 megabytes annually through imaging and electronic medical records. Back in 2017, industry insiders projected a staggering compound annual growth rate of 36% for healthcare data by 2025. That’s a pace that surpasses even the most ambitious forecasts for other colossal sectors, such as manufacturing, financial services, and media and entertainment. However, this digital treasure trove comes with its fair share of complexities.

Healthcare data is undoubtedly a goldmine of information, but it’s also a sensitive one. Authentic patient data often harbors personally identifiable information, sparking legitimate concerns about privacy. It can also carry biases, reflecting the demographics and experiences of the patients behind the numbers.

This is where the magic of synthetic data unfolds. Synthetic data is like a digital chameleon, expertly mimicking real data without a trace of PII. Patient privacy remains sacrosanct. What’s more, this data can be crafted to eliminate bias, painting a more inclusive picture of the patient population than what’s typically seen in genuine patient data.

Synthetic data’s potential is transformative. It serves as a vital resource for training machine learning (ML) models, conducting safe clinical trials, and advancing medical innovations. For example, it enables the training of ML models to detect diseases like cancer and facilitates ethical clinical trials without exposing patients to real drug risks. This is the transformative power of synthetic data in healthcare—an exciting journey into the future of medicine.

Let’s take a look at the five interesting reads across the internet that sheds light on synthetic data’s potential and of course, with a dash of caution.

1. Synthetic Data is Enabling Better Healthcare Tools: Here’s How

Particle Health’s article explains the burgeoning role of synthetic data in healthcare. It delves into how synthetic data addresses privacy concerns and biases while revolutionizing healthcare practices. The article highlights its potential applications, including ML training and ethical clinical trials, underscoring the transformative impact of synthetic data in the healthcare landscape.

2. How healthcare enterprises can benefit from synthetic health data, including 3 practical use-cases

The article explores three compelling use cases for synthetic health data in the healthcare industry, highlighting its potential to drive innovation and address privacy concerns. It discusses applications in ML model training, clinical trials, and improving patient outcomes while emphasizing the ethical advantages of synthetic data in safeguarding patient privacy. This article underscores how synthetic health data is poised to revolutionize healthcare practices.

3. Synthetic patient data in healthcare: a widening legal loophole

The authors discuss the emergence of generative adversarial networks in artificial intelligence (AI) for healthcare, which create high-fidelity synthetic data resembling real data while protecting patient privacy. While synthetic data holds promise in diversifying datasets and enhancing research, it lacks clear legislation, raising concerns about potential misuse by companies and implications for consumer privacy. As financial investment in synthetic data grows, both benefits and risks remain uncertain, urging awareness amongst consumers and policymakers.

4. MITRE-Created Synthea™ Designated a “Digital Public Good”  

MITRE’s creation of Synthea, designated as a digital public good, revolutionizes healthcare by generating synthetic patient data. This innovative tool addresses privacy concerns and biases while advancing medical research, clinical trials, and AI training. Synthea stands as a powerful resource for a data-driven future in healthcare.

5. The Dangers Of Using Synthetic Patient Data To Build Healthcare AI Models

This insightful piece delves into the multifaceted ethical and operational dilemmas that arise, shedding light on the nuanced interplay between innovation and the safeguarding of patient privacy. It offers a comprehensive exploration of the evolving terrain of AI-driven healthcare solutions, providing readers with a deeper understanding of the challenges and opportunities at hand.

The landscape of synthetic data in healthcare is evolving rapidly, and it’s crucial to stay informed. As we navigate this exciting journey into the future of medicine, it’s imperative to strike a balance between harnessing the potential of synthetic data for healthcare advancement and ensuring the highest standards of ethics and patient privacy. Synthetic data is a powerful tool, but its responsible and ethical utilization is paramount for shaping the healthcare landscape.