How can synthetic data improve telehealth?

Post COVID-19 pandemic has brought many changes to the world, among which, the development of telehealth cannot be ignored. According to McKinsey & Company, telehealth use has increased 38x from the pre-COVID-19 baseline. In addition, AI has played a more and more important role in the healthcare industry. It is said that AI in the healthcare market is projected to grow from USD 6.9 billion in 2021 to USD 67.4 billion by 2027. The rapid development of the telehealth industry is accompanied by a large amount of personal information including age, gender, and electronic health records. To further boost the development of telehealth as well as to preserve personal information, synthetic data generated by Betterdata’s AI engine plays a critical role.

Synthetic data is generated based on real-world data. Using a combination of data processing pipelines and AI deep generative models such as Generative Adversarial Networks (GANs) and autoencoders, betterdata can generate thousands of “fake” electronic health records which share the same characteristics and structure as the original data. These electronic health records didn’t contain any of the real personal information and are completely compliant with data privacy laws such as PDPA. Besides preserving privacy, synthetic data can boost the development of telehealth or medtech in the following ways.

Leveraging synthetic data, electronic health records can be shared across different clinics, telehealth vendors, hospitals, and other relevant stakeholders such as retail pharmacies. Since synthetic data doesn't contain any personally identifiable information (PII), relevant stakeholders such as hospitals within the same country, and hospitals in different countries can share the electronic health records to build a more comprehensive medical case database while preserving patients’ privacy. In addition, such large dataset could be fed to improve the diagnostic accuracy of telehealth’s machine learning (ML) model and can help with more accurate prescriptions. Besides, synthetic data generated by betterdata’s AI engine could be more balanced, including patients of all ages. This could help the telehealth company to better train their ML/AI model to improve the accuracy of diagnosis when patients seek help from their mobile application.

Synthetic data could be used to build prototypes to demonstrate the benefits of the medtech products. With the development of digitalization, more and more hospitals and clinics tend to move their patients’ health records online. With synthetic tabular data generated by betterdata’s AI engine, medtech vendors could use the synthetic data to demonstrate how their products could help to manage large amount of health records.

In a nutshell, telehealth and medtech are still growing at a fast pace under the pandemic. It is assumed that more and more people will seek medical advices via mobile applications. Synthetic data generated through Betterdata’s AI engine can facilitate sharing of patients’ records while preserving patients’ privacy, which will further improve the accuracy of ML/AI prescription. Besides, medtech which is dedicated to developing management tools for hospitals could also use synthetic data to demonstrate their capability to deal with large amount of patients’ health records.

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