In today’s complex healthcare landscape, real-world data (RWD) is increasingly valued for its information regarding diverse patient populations. Clinical research sites are an essential part of the RWD collection process, which increasingly leverages advanced technologies that enhance data collection, analysis and informed decision-making.
RWD can accelerate development timelines and augment clinical trial insights with key observational results from a wider and more diverse range of patients. However, clinical research sites face numerous challenges beyond the collection of RWD, such as managing overburdened staff, constrained budgets and the imperative to maintain high-quality patient care.
Diversity adds tangible value
Diversifying RWD in terms of population and data sources is crucial for generating real-world evidence (RWE) with far-reaching implications. RWD includes information from electronic health records (EHRs), claims data and patient-reported outcomes (PROs), which can provide a more complete picture of patient’s medical histories, healthcare usage and treatment experiences. The value of RWD resides in its many applications, such as treatment strategy documentation, individualized treatment planning and treatment efficacy and safety assessment in real-world populations.
Integrated technology solutions can augment the potential of clinical trial sites to realize the benefits of RWD collection. For example, technology can enable the extraction and curation of unstructured relevant data from patient records. These can provide additional and valuable insights into treatment rationale or assist in more precise in-patient identification for clinical trial participation. This data can also be used to study the differences in patient journeys for a given disease to advise quicker, more informed decisions and assess therapies for broader patient populations. This inclusivity extends to assessing treatments for different socioeconomic groups, gender-based variations and age-specific considerations. It also permits the evaluation of treatment effects in populations frequently excluded from traditional clinical trials, such as pregnant women.
Together, sites and technology facilitate swift advancements in research and the development of life-saving therapies.
Challenges in collecting real-world data
Collecting RWD for clinical research presents several challenges in several areas. For example, there are budget constraints that often limit the time allocated for research, meaning that staff can be overburdened as HCPs must prioritize patient care. When resources are available for research, the collection of observational data tends to be deprioritized in favor of clinical trials for novel therapies.
Moreover, there can be concerns relating to data completeness. Often, a patient’s data is siloed across various providers, which hinders the ability to create a comprehensive and coherent picture of a patient’s healthcare record.
Another challenge includes data integration and linkage. Integrating RWD from disparate sources requires robust data linkage methods to ensure patient identifiers are accurate and consistent across datasets. This is crucial for identifying and tracking individuals throughout their patient care journey. As RWD is often collected from diverse sources, such as EHRs, claims data, patient-reported outcomes and wearable devices, this heterogeneity can lead to inconsistencies in data formats, coding practices and missing values, which can complicate data analysis and interpretation. A lack of standardization in data collection and coding practices can hinder data comparability and analysis.
Patient diversity in data availability is another challenge. Clinical trials have traditionally been out of reach for many, particularly those in rural areas and low-income communities, which may be due to transportation hurdles, language barriers and site research capabilities. Even awareness of clinical trials can be a challenge, especially for underserved populations, which may not have equal access to information.
Technology fatigue is an increasing issue for clinical sites. Individual technological solutions are not always integrated with each other, resulting in increased site burden for technology training, excessive log-in requirements and handling updates. These challenges highlight the necessity for advanced integrated technological solutions to streamline processes and enhance the quality of data collected and analyzed in clinical research and open clinical trials to more representative populations and democratize clinical trial access.
Advanced technologies mitigate challenges
Technology is already being leveraged in several beneficial ways. For example, EMR data can be fed directly into an Electronic Data Capture (EDC) system. This means that when running a clinical trial or study requiring case report forms, technology can automatically pre-populate fields within those forms using relevant data from the EMR. All that remains for the site is to confirm the accuracy of the data and fill in any missing information. This streamlines the process by leveraging secondary data, ultimately alleviating site burden in observational studies.
Increasingly, the role of modern clinical technologies, like artificial intelligence (AI), in overcoming RWD collection challenges, enhancing patient and disease diversity in clinical research and improving patient care is becoming pivotal in several important ways:
Enabling interoperability: A lack of interoperability between health information systems reduces the quality of care provided to patients and wastes resources. Technology, including AI, may be able to support healthcare interoperability by addressing the challenges of fragmented data and disparate systems, such as data standardization and harmonization, data matching and linking and real-time data sharing and access. Addressing data fragmentation and data exchange can empower healthcare providers to deliver more coordinated, efficient and patient-centered care.
Enhanced patient recruitment for diverse populations: AI-embedded digital platforms are helping sites identify patient populations through optimal channels, such as social media and telehealth, enhancing patient recruitment for clinical studies and helping them reach broader, more diverse patient populations.
Expanding scope to encompass underdiagnosed diseases: By collecting and analyzing large RWD sets, AI can pinpoint diseases that are underdiagnosed, like non-alcoholic steatohepatitis and idiopathic pulmonary fibrosis. It can also help rare disease sites recruit patients by identifying those at risk or who should be screened but have not been diagnosed, thus enhancing recruitment.
Streamlining patient experiences: Smart technologies are simplifying patient experiences and improving clinical research involvement by enabling remote participation and minimizing the need for physical presence at research sites. It is also enabling the prediction of personalized therapies and diagnostics through large dataset analysis, leading to more effective, individualized treatments. Wearable devices, such as Fitbits and glucose monitoring devices, can, for example, collect real-time patient data, making clinical research more accessible and easier for patients. Furthermore, telemedicine visits allow those with limited mobility or living in rural areas to take part, supporting increased patient diversity.
Deeper insights into advancing patient therapies: Modern AI technologies enable deeper insights into the effectiveness of potential therapies across diverse patient populations by collecting and analyzing large datasets.
The future of technology in real world data collection
Diversifying available data hubs has a pivotal role in unlocking the full potential of RWD and generating impactful RWE that benefits a diverse range of patient groups. Developing standardized data collection practices, harmonizing data elements and implementing robust data governance frameworks can ensure the quality, reliability and validity of RWD for clinical trials, leading to more informed treatment decisions and improved patient outcomes.
Various technologies can streamline RWD collection and analysis, reduce costs, enhance patient recruitment and enable deeper insights into advancing patient therapies. These capabilities must be integrated to minimize site fatigue from technology overload. However, by embracing the transformative power of technology, organizations can revolutionize clinical research and usher in a new era of personalized and equitable healthcare.
About James Coutcher
James Coutcher is a seasoned industry expert and currently serves as the Senior Director and Global Head of Emerging Methods and Solutions, Real World Solutions at IQVIA. Prior to his role at IQVIA, James held executive positions including Vice President, Commercial Solutions at CorEvitas, LLC (formerly Corrona), and Global Head of Healthcare at GlobalData. James earned his Bachelor of Arts in Chemistry from Boston University, further complementing his expertise with an MBA from Quantic School of Business and Technology.