Healthcare Case Study
Personalised Symptoms Management
Our client created an application helping people with certain disease to live their best lives through personalised symptom management.
It is possible thanks to personal data provided by users: symptoms, medication, hormonal cycle and events tracking.
See how we are helping them use patients’ data for science, while respecting their privacy.
Problem: Making use of Patients’ Data
Data Use Cases
- Provide pharmaceutical companies with anonymized longitudinal data on adverse events reported for their drugs
- Provide CROs with pre-screened patients that can be recruited for relevant clinical trials
- Use AI technology to provide guidance to the patients, based on their individual symptoms and situation, so that they can help themselves
- Run internal research to drive insights e.g. surveys on cohorts, data sets analysis to look for relevant events & symptom correlations
USER
| Name | Amanda Smith |
|---|---|
| Date of Birth | 12 Dec 1958 |
MEDICAL INFORMATION
| Diagnosis | Diabetes Type II (2011) |
|---|---|
| Medications | Kazano, Invokamet |
| Prescription Id | 1389239890090 Can be traced back to Amanda Smith |
PAYMENT INFORMATION
| Payment Method | Card 1234 **** **** **** 1234 |
|---|---|
| Billing Address | 4 Dominic st Drogheda, Louth, Ireland Can be traced back to Amanda Smith |
| Event | Hypoglycemia |
|---|---|
| Note | “Need to get Kazano from Cogaslann” Can be traced back to Location |
| Date and Time | 22 Sep 2022, 8:12AM |
Not compliant
to be used for anything else than personal symptom management
Not safe
to be stored at local devices
Not possible to be shared with researchers
Details can be traced back to the individual, even if the name is removed
Time-consuming
Requires repetitive manual operations to report compliance to authorities
With FileSafe
USER
| Name | Barbara Johnson [replaced] |
|---|---|
| Date of Birth | Dec 26, 1957 [randomized wihin range] |
MEDICAL INFORMATION
| Diagnosis | Diabetes Type II (2011) |
|---|---|
| Medications | Kazano, Invokamet |
| Prescription Id | 7281381293891 [randomized, format preserved] Can’t be traced back to the user |
PAYMENT INFORMATION
| Payment Method | Card 1234 **** **** **** 1234 |
|---|---|
| Billing Address | Village in Leinster province, Ireland [reduced to upper category] Can’t be traced back to the user |
| Event | Hypoglycemia |
|---|---|
| Note | [Removed] Can't be traced back to Location |
| Date and Time | 22 Sep 2022, 8:12AM |
Compliant
Can be used for Internal & External Research
Safe
Even if data sets are accessed by unauthorised individuals
Possible to be shared with researchers
Details can’t be traced back to the individual
Quick
No need to manually anonymize to prepare compliance reports
2
New Collaboration
Opportunities
Ready for internal and external research, while maintaining statistical relevance:
- Consistent data, everywhere
- Correct formats retention
- Data cleansing, basic data mining and outliers management
- Provide fit-for-use anonymized data
Ready for AI algorithms, to provide guidance based on patients’ individual situation
Increased
Customer
Trust
100% Irreversible
Personal information replaced with relevant equivalents
98%
Risk
Mitigated
Reliable anonymization in conformance to regulations
No transfer outside the source application or database
One-way data transformation