Conventional cancer clinical trials can be slow and costly, often produce results with limited external validity, and are difficult for patients to participate in. Recent technological advances and a dynamic policy landscape in the United States have created a fertile ground for the use of real-world data (RWD) to improve current methods of clinical evidence generation. Sources of RWD include electronic health records, insurance claims, patient registries, and digital health solutions outside of conventional clinical trials. A definition focused on the original intent of data collected at the point of care can distinguish RWD from conventional clinical trial data. When the intent of data collection at the point of care is research, RWD can be generated using experimental designs similar to those employed in conventional clinical trials, but with several advantages that include gains in efficient execution of studies with an appropriate balance between internal and external validity. RWD can support active pharmacovigilance, insights into the natural history of disease, and the development of external control arms. Prospective collection of RWD can enable evidence generation based on pragmatic clinical trials (PCTs) that support randomized study designs and expand clinical research to the point of care. PCTs may help address the growing demands for access to experimental therapies while increasing patient participation in cancer clinical trials. Conducting valid real-world studies requires data quality assurance through auditable data abstraction methods and new incentives to drive electronic capture of clinically relevant data at the point of care.
Rates of PD-L1 Expression Testing in US Community-Based Oncology Practices for Patients with Metastatic Non-Small Cell Lung Cancer (mNSCLC) Receiving Nivolumab or Pembrolizumab
Sean Khozin, MD, MPH; Amy P. Abernethy, MD, PhD; Nathan C. Nussbaum, MD; Jizu Zhi, PhD; Melissa D. Curtis; Melisa Tucker; Shannon E. Lee; David E. Light; Gideon Michael Blumenthal, MD; Richard Pazdur, MD.
Machine vision and AI
Data Sharing and Blockchain
The data-sharing community is undergoing rapid development, with several potential models and approaches (Table 1). Multiple models should coexist, either as a single platform with tiered access or as discrete platforms with the potential for cross-communication that includes truly open platforms. As the community sees the benefits of sharing trial data, more will be shared. NEJM, 2017
Investigating the utility of blockchain as a decentralized network for owner-mediated exchange of health data at scale. In collaboration with IBM Watson Health.
Digital Health and Health Information Technology
A sensor-based study to capture the experience of patients with advanced malignancy undergoing active treatment*
*More information coming soon
Health Delivery Redesign
If you were to start from scratch and design a medical practice that helped patients and physicians collaborate, reduced the inefficiencies inherent in traditional clinical encounters, improved patient access, and reinforced quality care–what would that look like?
Over the past several years, the health care industry has focused on a variety of strategies and models to address these issues, including electronic medical records (EMRs), clinical groupware, personal health records, patient registries, and medical homes. All of these are viewed as important pieces of the puzzle for creating integrated, high-quality health care delivery networks. Physician practices have started to more widely adopt electronic systems to track patient care, particularly around health maintenance and chronic conditions such as diabetes and heart disease. In 2010, data from Centers for Disease Control (CDC) and the National Ambulatory Medical Care Survey (NAMCS) found that 50% of office-based physicians in the US use some kind of an EMR system, up from 18% in 2001. In some respects, the trends are encouraging.
The problem is that most of these solutions must be embedded or retrofitted into existing practices that have workflows and processes that do not easily lend themselves to participatory medicine. Furthermore, the process of adopting an EMR system is an expensive commitment for most medical practices, with costs as high as $120,000 per physician in the first year of implementation. An even bigger impediment is the reimbursement structure of health care, which rewards volume over quality and leaves little room for physicians to explore innovative modalities that focus on enhancing the patient-doctor therapeutic relationship. Only a few physician practices have had the luxury of undertaking the necessary retooling of their practices to enhance clinical interactions, patient participation, patient access, and continuity of care, ingredients that are essential to increasing the quality of care in a patient-centric environment. It should, therefore, come as no surprise that the 2010 CDC/NAMCS report found that despite the increase in the use of electronic systems, only 10% of physicians have a “fully functional” EMR system that may enable them to meet the meaningful use criteria as defined by the US Department of Health and Human Services (DHHS).
For the past several years, coauthor Khozin has explored new approaches to addressing these challenges by developing a system that was designed from scratch to fully integrate office and online systems. His efforts were based on the hypothesis that improving health outcomes requires redesigning the care delivery paradigm so that it empowers both patients and physicians. This article describes the strategies he chose, practical experiences, challenges faced, and implications for future efforts.