Deidentified Patient Data to Speed up Digital Health Development

Researchers and public health services need access to patient data. They might use this data to identify trends in public health, or learn more about new diseases. One of the most recent examples of the use of public health research is during the COVID pandemic. 

Deidentified patient data helped to identify common symptoms, and the appearance of the virus as it progressed. This meant that the spread of the virus could be understood and managed. 

Deidentified patient data has similar benefits in health tech development, too. These data sets can be used to emulate users of digital health solutions. Development can move quickly as the patient data isn’t bound by compliance regulations. 

Anonymized data sets protect patient privacy in digital health development. Avoiding compliance violations is key to the success of the digital health project.

What does HIPAA say?

The Health Insurance Portability and Accountability Act (HIPAA) outlines the necessary compliance regulations to protect patient data. Anyone that handles patient data is bound under HIPAA. This includes healthcare providers, insurers, and those business associates. Typically, a digital health development company would be classed as a “business associate”. 

HIPAA states that identifiable patient data is covered by the regulations. This includes information like names, addresses, treatments, photographs and more. Therefore, this information needs to be safeguarded against inappropriate storage or disclosure. 

However, there are a very specific set of guidelines for the use of unidentifiable information. Completely anonymized data can be used without adhering to HIPAA guidelines. HIPAA specifies what is considered deidentified patient data, and what sets of information are still covered by HIPAA. 

According to HIPAA, deidentified patient data is sets of patient data that have had all identifying factors removed. There must be no identifying factors within the set of data. There is an extensive list of factors that must be removed from the information, including the following:

• Names

• Geographical identifiers, other than state

• Dates

• Telephone numbers

• Health record or identifying numbers

• Photographs

• And more

The information must not be identifiable to a single person in any instance. Anonymized data can then be used without adherence to HIPAA regulations. HIPAA does not deem that there is a risk to patient privacy, as they cannot be identified. 

These sets of data can be utilized within research, digital health developments, public health assessments and more. 

Therefore, anonymized patient data can speed up the development process within digital health. The information is not protected by HIPAA. This means that there is no need to carry out risk assessments, implement HIPAA safeguards, and address breaches of data. Anonymized data sets can protect the digital health development, as well as the privacy of the patients. The development process is also much quicker, as a result.

Benefits and Uses of Deidentified Patient Data

The most common use for anonymized patient data is within the research sector. Patient data on specific diseases or illnesses, and the applied treatments, can be particularly useful in disease research. 

Information on how the disease progresses, and noticeable symptoms can help to spot the presence of the disease even earlier. Researchers can also monitor what treatments are used, and how effective each one is.

Information like this can help researchers to further understand the disease or virus. This allows researchers to develop new treatments, and improve public advice. 

Similarly, deidentified patient data can help to manage public health. The spread of new diseases and viruses can be monitored using these data sets. As a result, vaccine effectiveness can be measured, and any new symptoms are spotted quickly. The COVID pandemic highlighted the importance of anonymized data. 

Deidentified patient data doesn’t just benefit the healthcare industry, exclusively.  Protected health information (PHI) can be found in many industries, and anonymized patient information has other benefits. The digital health and health technology industry can utilize anonymized patient information within the build process of their solutions. 

Machine learning is a fast-growing and innovative area in the digital healthcare industry. Artificial intelligence has proved its capability to identify diseases and suitable treatments. In fact, the latest innovations have been said to diagnose illnesses as quick, if not quicker, than human physicians. 

Anonymized data sets are to thank for the power of this innovative technology. The AI models have trawled hoards of healthcare data, to learn more about the appearance of illnesses and disease. With thousands of use cases available, they can match the given case study to the closest match within the databases. 

In this case, as with any other digital health development, anonymized patient data has facilitated the speed of development, too. However, digital healthcare does face a difficult challenge in compliance. Needless to say, patient privacy is the priority. However, it can slow the build process down for health tech solutions. 

Effective compliance requires a risk assessment procedure, regular audits, and processes for handling breaches or violations. For tech developments that utilize anonymized data, this isn’t necessary. Therefore, the overall time frame for a project can be reduced.

Limited Data Sets 

Deidentified patient data must not be confused with limited data sets, or vice versa. This could have a detrimental effect on a digital health development project. Limited data sets are still protected by HIPAA, whereas deidentified patient data is not. 

Misunderstanding anonymized data, or mistaking data sets, could lead to a HIPAA breach or violation. The primary difference between the two types of anonymized data is the level of anonymity. Limited data sets are stripped of some, but not all, identifying factors. Whereas, deidentified patient data must have all identifying factors removed.

For example, deidentified patient data requires that all address details are removed from the set. The state may be included, depending on the size of the area. However, limited data sets permit the recording of city, town, state or full zip code. 

Similarly, limited data sets may include a patients’ date of birth, although only the year is advised. Completely anonymized data sets must have this information removed.

For this reason, limited data sets must be securely stored or disclosed, under HIPAA. They follow the same regulatory requirements as all other PHI. The only difference is that limited data sets are not subject to HIPAA tracking or accounting requirements.

Limited data sets may be used in a very similar manner as deidentified data. However, HIPAA regulations and appropriate safeguards are required. Therefore, handling limited data sets is much more time consuming than fully anonymized data. Depending on the purpose of the data set, deidentified patient data is much easier to handle.

At Vertrical, we understand how to handle personal health information. We have teams of compliance experts, ready to assess your digital health projects. We also have engineers, project managers and business analysts available to build your next health tech solution. Get in touch today to discuss your requirements.