Epidemiology and RWE of Medical Devices, Diagnostics, and MedTech

1. Course Aim

Medical devices, diagnostics, and medtech are used extensively across healthcare. In surgery, devices are used as instruments (e.g., cutters, staplers, catheters, and sutures) or implants (e.g., cardiovascular stents, hip or knee replacements). Increasingly, surgeries also use digital tools to guide, plan and navigate procedures. Both traditional laboratory diagnostics (e.g., lateral flow assays) and artificial intelligence-enhanced imaging are all becoming more complex and may both generate and utilize substantial clinical data. Wearable products may be used alone or in conjunction with other health interventions to improve outcomes, reduce healthcare utilization, or even to generally promote increased physical activity. Use of real world data (RWD) and epidemiologic methods to study utilization, safety, and effectiveness across the medtech spectrum is a rapidly expanding and developing field. Thus, studies of medical devices using RWD are gaining visibility outside of ISPE.

Epidemiology and real-world evidence (RWE) generation for medical devices, diagnostics, and medtech uses methodologies similar to those for medicines. However, alternative strategies are often implemented due to the nature of the products, data sources, and situational use. With the changing regulatory and reimbursement environments, it is more important than ever for pharmacoepidemiologists to better understand the design and analytic methods applicable for studies of these products using RWD. Additionally, to enhance the utility of RWE for clinical practice, researchers should appreciate the unique needs when evaluating combinations of these products with medicines and the incorporation of medtech-generated RWD into pharmacoepidemiologic studies.

This course highlights generation of RWE in four common types of medical devices. Current issues in study design and analysis will be addressed via case studies. At the end of the course, break-out discussions will be available for a deeper dive into one type of device or method with the instructors who have extensive experience in medical device epidemiology, including work in regulatory, industry and in academic sectors.

2. Requisites Statement

Information in this introductory course spans entry, intermediate, and advanced-level topics. Methods discussed will be applicable across therapeutic areas and provide understanding of the current regulatory and clinical context of epidemiology and RWE for medical devices, diagnostics, and medtech.

While a general understanding of observational study design is recommended, there are no specific materials to be reviewed before the course.

3. Course Objectives

• Critically examine the unique challenges and considerations for generating RWE for four device types: therapeutic, diagnostic, monitoring, and combination devices.
• Apply RWE study design principles to each device type through case studies.
• Identify relevant data sources and statistical methods for analysing RWD specific to these device types.
• Discuss the impact of RWE on improving safety, effectiveness, and patient outcomes for each device type.
• Understand trends underlying advances in medical devices, diagnostics, and medtech, and the needs for robust RWE methods

4. Syllabus Outline

1. Overview of course, objectives, aspects of device RWE generation, and types of medical devices
Students will be introduced to the language of medical devices, diagnostics, medtech, and combination products. Discussion will include identification of exposures, with a focus on four types of devices: therapeutic, diagnostic, monitoring, and combination products.
2. Therapeutic Devices
Students will learn the crucial role of RWE in evaluating safety and effectiveness of therapeutic devices. Two case studies will focus on harnessing data captured by a cardiac ablation device to assess safety/effectiveness and on incorporating facility and provider into confounding adjustment.
3. Diagnostic Devices
Students will be introduced to relevant data sources for RWE generation when evaluating the performance of diagnostic devices. An exemplar will focus on use of electronic medical records to generate performance metrics for AI-enhanced disease detection.
4. Monitoring Devices
Students will learn the importance of RWE generated from devices in understanding patient outcomes and healthcare utilization. The case study will describe data collection from wearable tracking devices to monitor physical activity.
5. Combination Products
Students will hear about the complexities of generating RWE for combination products and differences in RWE needs for delivery devices based on whether the device or medicine component is the primary focus. A comparison of RWE needs for two drug delivery systems, one implanted and one external, will be provided.
6. Current state & future of epidemiology and RWE of medical device, diagnostic, and medtech
Students will learn of ways to get involved in conducting studies and developing methodologies for RWE generation of medical devices, diagnostics, and medtech at ISPE and beyond.