Sep 2, 2020

Health history platform launches to trace genetic conditions

patient family history
genetic conditions
famhis
hereditary diseases
Leila Hawkins
2 min
Health history platform launches to trace genetic conditions
The mobile app lets patients control their health history data...

A new platform that can help identify individuals who are at high risk of hereditary diseases has launched. 

Developed by FamHis Inc, FamGenix is a free patient mobile app that is being released worldwide, following a soft launch last November for patients, and the release of the provider portal for clinicians last month. Servers have so far been launched in the US and Europe, and are planned for Canada and Australia in October. 

The platform facilitates a telemedicine-based approach to gathering family health histories, aiming to save time and improving accuracy. The concept behind FamGenix is that patients are in control of their own data. They are able to communicate with family members through a feature called FamShare, allowing a secure exchange of data to provide an accurate family history.

Each family member can control their own health record and privacy settings. Important health information, like genetic test results, can be easily shared with other family members via the app, facilitating the process of family tracing for genetic conditions. 

“With 25 years in the industry, I’ve seen firsthand the benefits of an accurate family health history and the effect it has on decision making for healthcare providers and their patients,” said Michael Brammer, Founder and CEO of FamHis, Inc.

“But the idea that it’s something to address only when patients are facing a health crisis, is short-sighted. FamGenix is much more than a simple screening tool and is the first of its kind to empower patients to own and maintain their own family health history, indefinitely. Preventative healthcare is the future of medicine and it begins with family history.” 

Healthcare providers can review the patient data, and the system screens patients to identify those who are high-risk - in other words, who meet criteria for further genetic counseling or testing. 

Standard or custom questionnaires help to identify any condition (not just cancer) or other data needed for clinical or research purposes. There is also a white-label option for healthcare providers who want to brand the app as their own in the app stores. FamHis has signed their first white-label license with a prestigious cancer center and has pilots planned in several countries.

The app is available for download from the App Store and Google Play, while healthcare professionals can access a free trial. 

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Jun 24, 2021

Data de-identification - why it matters in healthcare

dataprivacy
patientdata
electronicmedicalrecords
datadeidentification
3 min
Riddhiman Das, co-founder and CEO of data privacy startup TripleBlind tells us why data de-identification is important in the healthcare sector

Large amounts of healthcare data is generated yet goes unused due to privacy concerns. To address this, data privacy firm TripleBlind has created Blind De-identification, a new approach that allows healthcare organisations to use patient data while eliminating the possibility of the user learning anything about the patient’s identity. 

We asked Riddhiman Das, co-founder and CEO to tell us more about data de-identification. 

Why is data de-identification important in healthcare? 
Blind De-identification allows every attribute of any given dataset to be used, even at an individual level, while being compliant to privacy laws, rules, and regulations by default.

Governments around the world are adopting global data privacy and residency laws like GDPR, which prohibit citizens’ personally identifiable information data from leaving the borders of the country. While great for data protection, data residency laws result in global silos of inaccessible data. TripleBlind allows computations to be done on enterprise-wise global data, while enforcing data residency regulations. 

In the US, HIPAA compliance has relied on what is called the Safe Harbor method, which requires removing 18 types of personal patient identifiers like names, email addresses, and medical record numbers. The Safe Harbor method can be too restrictive with the data or can leave too many indirect identifiers, which puts the patient data security at risk. Getting de-identification wrong could make an organisation liable for a costly mistake.

What does TripleBlind's solution do? 
With TripleBlind, data is legally de-identified in real time with practically 0% probability of re-identification. Our solution allows analytics on data containing personally identifiable information and protected health information  with zero possibility of re-identifying an individual from the dataset. This allows healthcare organisations to access more meaningful data, creating more accurate and less biased results.

For example, a healthcare drug researcher in a rural, predominantly white area, would only have patient data that would reflect their local population. With TripleBlind’s de-identification, they could more easily leverage third-party data from another healthcare facility in a more diverse region, creating a more complete data set that more accurately reflects the larger population. This has the possibility to create more accurate diagnoses and better drug results for more diverse populations.

How can healthcare organisations use this in practice? 
TripleBlind is blind to all data and algorithms. That means we never take possession of customer data. We only route traffic between entities, enforce permissions, and provide audit trails. The enterprise’s data remains under their control. TripleBlind does not host, copy or control their data, algorithms or other information assets, ever. 

We facilitate a connection to an encrypted version of their information assets. Our technology allows the algorithms and data to interact in an encrypted space that only exists for the duration of the operation. Organisations use their existing infrastructure, so it’s not hardware dependent.

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