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0401 1 Denis Costello - Patient Generated Data

  1. Patient Generated Data The patient organisation experience of using technology Denis Costello, Snr. Manager Patient Engagement in Digital Technologies EURORDIS – Rare Diseases Europe (Barcelona)
  2. What is Patient Generated Data (PGD) Patient-generated data are health-related data created, recorded, or gathered by or from patients (or family members or other caregivers) to help support and manage disease state.  Patient generated data include, but are not limited to: • health related events / symptoms • medication adherence • biometric data (wearable devices) • Patient Reported Outcomes (PROs) 12/07/2019 2 Patient-generated data are distinct from data generated in clinical settings and through encounters with health care providers in two important ways:  Patients, not providers, are responsible for capturing or recording these data.  Patients decide what data to share, and with which health care providers / researcher to do so. Examples include physical activity using wearable devices, and medication adherence and ePRO using a mobile app. Courtesy of Dr. Elin Haf Davies
  3. What the Doctor sees… 12/07/2019 3 Courtesy of Dr. Elin Haf Davies
  4. What the Patient experiences… 12/07/2019 4 Courtesy of Dr. Elin Haf Davies "99 percent of patient activity happens outside of the hospital or clinic, beyond the scope of the [electronic health record] EHR"
  5. Why do we need technology to foster Patient Generated Data ? Increasing the probability of success and lowering costs  Improve remote patient monitoring, and natural history understanding  Drive value from Patient Generated Data – demonstrate what’s important to patients  Reduce the amount of monitoring intervention that contributes to a lower quality of data captured.  Conduct studies anywhere in the world where there’s an Internet or 3G connection.  Conduct studies in geographies without having to be too concerned about the costs or practicalities of that locations infrastructure.  For selected studies / diseases / drug type - reduce the number of patient visits and reduce the overall cost of running a study.  Bring objective, outcome based data to Drug Application and increase the probability of success. 12/07/2019 5
  6. Growing interest in Patient Generated Data 12/07/2019 6
  7. Patient Generated Data using 12/07/2019 7
  8. Patient Generated Data via wearables 12/07/2019 8
  9. Patient Generated Data via wearables 12/07/2019 9
  10. Social Q&A PROMs Genotype Phenotype Patient Generated Data via Health29 ( “Health29 is a platform with patient health data, by and for people” Source:
  11. PROMs • Full set of clinical data • Customized by patient organization • Standardized and with quality controls • Easy to fill by users • API for interoperability
  12. Phenotype • Deep phenotyping using CNLP • Standard HPO • Based on AI for symptoms identification • Phenotype can be initiated by patients
  13. Genotype • Full genetic information • Standard HGVS nomenclature • Clustering patients according genetic variations + phenotype
  14. Patient group N Patient group 2 Patient group 1 Public data Health providers Academia Data Sources High Quality Data Platform Services Experiences Patient data locker 1 Diagnosis Data insights, standarization, sharing, portability… Patient data locker N Patients driving research
  15. Patients driving research 12/07/2019 15
  16. 17
  17. My StudiesSocial 18
  18. Patients & Caregivers https://mystudies.rareconnect.org Researchers Clinicians ( De-identified data ) Advocacy Organizations 19
  19. Designed to provide researchers with a customizable survey and questionnaire system that they can push to their study participants to complete. Patient Reported Outcomes (PROs) 20
  20. In addition to surveys, participants can also track medical events, tests, and medications as longitudinal data. Future versions of My Studies will enable participants to share their outcome measures with their clinicians. Patient Reported Outcomes (PROs) 21
  21. Participant registration 22
  22. Data is stored on an instance of HPC4Health owned by CHEO. HPC4Health is a secure facility that has undergone external Privacy Impact Assessment (PIA) and Threat Risk Assessment (TRA). My Studies Social Private Cloud Environment My Studies Administrators Participant HPC4Health Support Team RareConnect Administrators User Research data 23
  23. Conclusions Some final thoughts:  Consider which data is most important and impactful for your patient group/community to generate  Don’t be afraid to work with experts to develop new data instruments which can determine unmet medical need or clinical added value for example  Where possible do not build from scratch but make use of existing, compliant, affordable, reliable and well supported platforms (e.g. Health29 or others)  Learn from what other patient groups are doing, via webinars, conferences, newsletters etc  Develop a data plan which encompasses governance, access, sustainability, compliance (GDPR, Privacy Impact Assesment)  Consider how much resources you will need. Can’t give you a figure as each case is different! 12/07/2019 24
  24. Thank you!  Email:  Twitter: @rarecare  LinkedIn: 12/07/2019 25

Editor's Notes

  1. To achieve all of I’ve said before we have created Health29. Our main lines are social q&a, proms, genotype and phenotype.
  2. Other of the objectives that we pursue with Health29 is to support the development of new drugs, making standardized and quality data available to the research. We develop tools to capture Patient Reported Outcome Measurements in a way that is easy to fill by the patient or caregiver.
  3. 11. PHENOTYPE Having a good description of the phenotype for a patient can be one of the most difficult things to get. With our ‘deep phenotyping’ tool we make it this process easier and standard. It can be done by patient or clinician in several ways (we will have a look at it later, at the demo) Joining phenotype and genotype, and extract insights from this information will be a powerful feature that represents a next step to precision medicine.
  4. We store genotype information too. The patient uploads the genetic variant file and we translate it to standard HGVS nomenclature. (Human Genome Variation Society) We use Microsoft Genomics to get the variant file from the whole genetic information file.