Healthcare is a deeply personal concern. But, that sense of privacy needs to be balanced with the need to provide data so that patients can make informed decisions. And where does this health data come from? It has to come from the market at large.

The Health Insurance Portability and Protection Act (HIPPA) regulates the transmission of personal health data. But it only applies to certain organizations.These entities include “…health information from health care providers, health plans, and healthcare clearinghouses (HIPAA “covered entities”) and their business associates.” The preceding statement is an excerpt from a legal brief covering health data analytics.

Ethical Sources of Medical Data

Bearing this in mind, we have to be careful to source data from outside of the supply-chain regulated by HIPPA. One of the shortcuts to finding this information is through de-identification. By removing protected healthcare information (PHI) from medical data sets, we can be reasonably confident that personally identifiable medical data is not present.

PHI includes a person’s name, address, social security number and any other corresponding information that could be reverse engineered to identify the individual behind the data being provided. Compromising a person’s right to medical privacy is not only unethical, but can lead to significant fines and possible imprisonment.

Voluntary Collection of Medical Data for Better Care

One of the easiest ways around the complex requirements for sourcing large batches of medical data is through voluntary submission. By informing patients of the benefits of submitting their medical information, many individuals will voluntarily provide their medical data.

An international example of this is how patients find an appropriate health fund in Australia. Companies create online portals for patients to enter their healthcare information. In return for their voluntary submission, they receive different rate plans available to them. And based on their specific needs for coverage, they can opt-into the best plan for them.

In the United States, we’re seeing an increasing trend towards employers opting to self-insure their employees. This means that, instead of shopping around for policies on the open market, they create a fund that is specifically earmarked for paying the medical bills of their employees.

When an employee joins the company, they are offered the opportunity to voluntarily join the company’s healthcare plan. They also have the option to opt-out and still gain employment. The information that is provided helps companies forecast their need to set aside funds to cover future medical obligations.

Life Science Innovations Thanks to Medical Data

There are multiple sources of medical data, beyond voluntarily submitted information. For example, administrative data can be provided to help life science researchers identify trends. While this type of data is easily accessible electronically, it lacks clinical data – the kind of data that helps spur the most medical innovation in life sciences.

We’re going to see an increase in medical treatment systems – large hospital chains and insurance companies – leveraging big data in the medical space to find ways to optimize patient care. A recent survey found that 95% of CEOs in the healthcare industry expected to increase their investment in big data solutions.

This will likely bleed into the world of AI – leveraging advanced algorithms to parse data and gain insights into the patient treatment cycle.

For life science innovators, this data will be too valuable to ignore – especially if it’s already been curated by industry experts. Therefore, many healthcare companies will enter into business associate relationships, as defined by HIPPA, in order to gain access to the innovative information they need.

In conclusion, when medical data is made more accessible, patients win. They receive smarter care, based on important insights that are only possible with the aggregation of large data sets. And as patient care becomes smarter, we’ll see faster innovation cycles. All of this leads to better treatment, as long as we can maintain proper data security and anonymization.