At a recent webinar with Sepanta Fazaeli, Clinical Systems & Medical Systems Lead at Stryker and Rajpal Singh, Associate Director at IQVIA, moderated by Mark Priatel, VP of Software Development at DistillerSR, we explored the benefits of centralizing literature management, which enhances accessibility and organization-wide visibility while also significantly reducing the time and resources required to complete literature reviews.
Q: Why is the management and reuse of literature critical in healthcare research and development?
A: In the ever-changing landscape of healthcare research and development, managing and reusing literature have always been critical pillars that support innovation and efficient decision-making. Centralizing literature management significantly enhances accessibility, visibility across the organization, and reduces the resources and time required for comprehensive literature reviews. Overall, effective management and reuse of literature are fundamental to the successful development of medical devices and pharmaceutical products, helping companies innovate responsibly while ensuring safety and compliance with regulatory standards.
Q: Rajpal, can you tell us about your journey implementing automation inside your organization and how data reuse plays into that strategy?
A: The industry has undergone significant evolution in its approach to conduct systematic literature reviews (SLRs), particularly in response to changing requirements and the need for greater efficiency and flexibility. Traditionally, SLRs were conducted to answer specific questions or address particular aspects of a topic, leading to separate reviews for clinical, economic, and other domains. However, the trend has shifted towards conducting more comprehensive reviews that capture multiple insights within a single SLR. This approach not only saves time and resources but also allows for a more holistic understanding of the evidence. Updating these systematic literature reviews more frequently ensures that the analysis remains current and relevant. We conduct SLRs by adhering to global standards and ensuring consistency and efficiency, allowing regional teams to adapt these SLRs to meet local compliance and regulatory requirements related to their diverse markets. By facilitating the reuse of systematic reviews across different geographies and teams, the industry has promoted collaboration and knowledge sharing, maximizing the utility of existing resources and fostering a culture of continuous learning and development. We are saving up to 40% in terms of time and resources since implementing DistillerSR.
Q: Sepanta, can you share the background and context of your organization and how you’ve approached automation and data reuse?
A: I started working at Stryker not long after the new wave of MDR regulation came in, which pushed us away from traditional Excel files and clinical evaluation in silos. We adopted the reuse mindset very early on. The rapid transformation of AI tools and models also kicked in, especially from 2022, reinforcing this transition and pushing us further towards adopting new data management practices across different departments and enhancing the organization’s overall data handling capabilities. This includes standardizing forms and using APIs to automate report generation, significantly reducing manual input time and enhancing efficiency across various documentation processes. We also enabled the reuse of extracted data across similar product lines, further streamlining our operations.
Q: Sepanta, how has data reuse transformed your workflow and how much time have you saved?
A: Data reuse has significantly transformed our workflow by using standardized forms and questions across our entire product CRs in DistillerSR. The use of APIs for data collection has allowed us to automate report generation and share these reports with the appropriate stakeholders. This approach has drastically cut down on the time we would have otherwise spent on manual inputs. Additionally, by identifying families of devices that share similar labeling, we enable the reuse of extracted data for clinical evaluations, further enhancing our efficiency.
Looking to the future, Sepanta and Rajpal will be focused on enhancing collaboration across different geographies and teams, addressing the challenges of data standardization and quality, and further integrating AI tools to support data reuse and management efforts effectively. These examples emphasize the importance of managing evidence gathering, collection, and curation strategically and leveraging data reuse to transform workflows, improve efficiencies, and foster innovation in healthcare.
