Navigating the Landscape of Real World Evidence Studies in Healthcare
05/01/2024Madalena Plácido, a dedicated outcomes research manager at Promptly Health and a PhD candidate in Epidemiology and Public Health at NOVA National School of Public Health, fervently explores health outcomes analytics, patient-reported outcome measures (PROMs), and and the transformative landscape of value-based healthcare.
She has eight years of experience working in outcomes research and epidemiology, addressing the needs of national and international pharmaceutical and medtech industries. She has further enriched her expertise in epidemiology, pharmacoepidemiology, and Patient-Reported Outcome Measures (PROMs) by participating in specialized training courses at prestigious European universities.
As the current president of MiGRA Portugal, a Portuguese Migraine and Headache Patients’ Association co-founded by her, Madalena champions patient advocacy and empowers communities.
With over 20 abstract publications in global and local congresses and three peer-reviewed journal papers, she contributes significantly to healthcare advancements.
Could you elaborate on your experience in real world evidence studies and what motivated your entry into this particular field?
I have eight years of experience working in outcomes research and epidemiology, addressing the needs of national and international pharmaceutical and medtech industries.
The intersection of cutting-edge data analytics and healthcare has ushered in a transformative phase in evidence collection, poised to redefine decision-making within the healthcare landscape. Real world evidence (RWE) studies serve as a gateway to enhancing patient well-being, refining healthcare delivery, and ensuring its long-term viability.
They provide invaluable insights into the efficacy and safety of medical interventions, resource utilization, and the characterization of patients, surpassing the constraints of controlled clinical trials by encompassing the diverse and intricate scenarios encountered in routine clinical settings.
Real World Evidence Studies in Healthcare
Data Sources and Collection
What real world data sources does Promptly utilize for its real world evidence studies?
The challenge of sourcing data from clinical practice and amalgamating diverse data streams remains a significant constraint in RWE studies. This arduous and costly process often involves only a subset of patients and lacks reproducibility for future investigations.
Our RWE studies capitalize on a vast pool of information drawn from routinely gathered Real World Data obtained through partnerships with various data sources, including data collected directly by Promptly.
We primarily rely on the Observational Medical Outcomes Partnership (OMOP) data structure. Leveraging federated data from hospitals that adhere to the standardized OMOP data model grants us access to a diverse and extensive patient cohort, mirroring the complexities of real-world healthcare scenarios.
Employing technology to align existing hospital data sources with OMOP standards enables us to streamline data collection, enhancing reproducibility and scalability. Collaborative agreements with our data partners also facilitate the execution of multicenter and international RWE studies.
What measures are taken to guarantee the quality and dependability of gathered data?
Our approach involves utilizing OHDSI tools to maintain the data quality, aligning it with the OMOP data model. Additionally, we adhere to the EU Data Quality Framework set forth by the European Medicines Agency (EMA), aligning with the guidance of the HMA-EMA Joint Big Data Task Force to ensure data reliability.
Furthermore, we employ a Software Testing Life Cycle process, aligned with agile development methodologies, encompassing planning, design, development, rigorous testing, and deployment phases to uphold code quality.
Methodologies and Analysis
What study types does Promptly conduct, and what influence do they have on clinical practice?
At Promptly, we engage in a diverse range of study types designed to significantly impact clinical practice. Our extensive presence spans across 10 countries, with a dedicated focus on enhancing patient outcomes. With over 20,000 patients under our care and real-world evidence studies conducted in more than 10 therapeutic areas, we are committed to shaping the future of healthcare.
Our studies fall into three distinct categories: off-the-shelf, complex, and highly complex. Off-the-shelf studies delve into patient characterization, patient-level drug utilization, population-level drug utilization, and population-level descriptive epidemiology. These foundational studies provide essential insights into patient behaviors and treatment patterns.
Moving up the complexity ladder, our complex studies encompass prevalent user active comparator cohorts, new user active comparator cohorts, self-controlled case risk interval, self-controlled case series, time-series, and intricate drug utilization studies. These studies are strategically designed to provide nuanced perspectives, aiding in risk minimization strategies and optimizing patient care.
We are not just conducting research; we are actively shaping the landscape of clinical practice. Our commitment to innovation and comprehensive data analysis ensures that our studies have a tangible influence on healthcare decisions, ultimately benefiting both patients and healthcare professionals worldwide.
Which methodologies or approaches are employed for analyzing real world evidence?
In order to optimize study efficiency and value, while upholding rigorous standards of quality, reproducibility, transparency, and regulatory acceptance, our research follows the DARWIN EU Standardised Analytics. Utilizing the OMOP Common Data Model (OMOP CDM) enables the effective implementation of Standardised Analytics.
Collaboration Framework
What is the role and contribution of each healthcare partner during studies?
Becoming a Data Partner allows healthcare organizations to join a global network of Health Systems, Payers, and diagnostics service providers, and participate in sponsored data collaborations, without compromising on privacy and security. The network operates under a common data model (OMOP-CDM) and federated infrastructure, ensuring that data is consistent, interoperable with other datasets, and remains protected in its original location.
How is the collaboration structured to ensure effective communication, data sharing, and compliance with privacy regulations (e.g., GDPR, HIPAA)?
The network operating model focuses on data access over data sharing — data is securely analyzed where it sits as opposed to shared in bulk exports. Instead of storing data centrally, federated learning distributes the question/query to individual devices or servers, where the computations occur. These locally computed results are then aggregated, to create global insights. Through this process, Data Partners remain in full control of their assets, having all sensitive data protected in their servers while also being able to capture its full value through internal and external collaborations.
Future Directions
What is your vision for the future development of Real-World Evidence (RWE) studies within the healthcare domain?
Within the dynamic healthcare landscape, I anticipate a pivotal role for RWE studies in shaping evidence-driven decision-making. The convergence of diverse data streams, sophisticated analytics, and collaborative partnerships is poised to inaugurate an era where RWE studies not only complement conventional clinical trials but also spearhead transformative advancements in healthcare delivery.
To sum up, the domain of RWE studies, particularly within the OMOP data structure utilizing federated hospital data, represents an exciting expedition at the crossroads of healthcare and technology. It is through this multifaceted exploration that we endeavor to contribute to a healthcare realm that not only relies on robust evidence but also addresses the intricacies of real-world situations.
Learn mode about our Real World Evidence Studies
