Streamlining Data Collection Through Enhanced Media Capture

Streamlining Data Collection Through Enhanced Media Capture

Patients often struggle to describe health concerns accurately to their doctors, creating a barrier to understanding at critical times. Traditional means of patient data collection have either been text-based, subjective, or solely reliant on healthcare professionals. Today, innovative new technologies are easing this struggle through enhanced media capture, where platforms have the functionality to help patients accurately capture their own health data through self-generated photos and videos. Patients can then upload this media directly into their electronic health records (EHRs).

This type of data is a growing trend in combination with other disparate data – through new platforms, all data can seamlessly integrate into one unified system to fuel research and assist with more accurate diagnoses. Incorporating media capture into regular clinical practice can optimize efficiency in care, enrich clinical records, and facilitate communication between healthcare professionals and their patients.1 

Patient Experience Data and RWE Research
Person-generated digital data is becoming increasingly important in healthcare. When patients upload their information as real-world data (RWD), the result is more accurate real-world experience (RWE) data packed with stronger insights.2 This symbiotic relationship between digital data and RWE is an innovative step toward closing the gaps in data generation for clinical research and other participant studies.

Patient-centered research is increasingly expected but often not collected or captured in traditional real-world databases. Researchers can use qualitative patient experience data (PED) to make informed study design decisions.3

Studies focused on RWE generation, like patient registries, HEOR studies, phase IV PMR studies, and post-market projects, are increasing the incorporation of patient-generated media capture. In these types of studies, enhanced media capture through patient-generated photos and video offers valuable insights into treatment progress, side effects, medication adherence, and overall health outcomes in a participant’s natural environment. This data, alongside traditional methods, can help paint a more comprehensive picture of a therapy’s effectiveness and safety in the real world.

Here are additional ways researchers facilitating these types of studies could leverage PED from photo uploads to guide RWE research design:

  • Visualizing disease progression: Photos can reveal physical changes, treatment side effects, and the everyday impact of illnesses, highlighting areas where traditional data might lack sufficient detail.
  • Capturing patient-centered outcomes: Photos can document aspects like mobility, fatigue, or medication adherence, providing insights into patient-reported outcomes not usually captured in routine data.
  • Uncovering hidden patterns: Analyzing trends in photo submissions across diverse patient populations can unveil previously unrecognized disease phenotypes or treatment responses.
  • Understanding participant needs: Examining photos can inform tailored recruitment messages and materials, resonating better with specific patient experiences and motivating participation.
  • Triangulating quantitative and qualitative data: Photos can serve as the visual context for RWD findings, enriching RWE, data interpretation, and facilitating a deeper understanding of patient experiences.

Challenges and Considerations
While patient-generated images hold immense potential in healthcare and research, some challenges can impede their effective use. These range from systemic limitations to implementation hurdles.

Technical issues are among the most common systemic limitations of this mode of data collection. Disparate EHR systems often strip out image attachments or display them inconsistently, hindering communication between providers and researchers using different platforms. Variable adoption of clinical photography services and transport standards can further complicate image sharing. During implementation, integration with existing workflows is another common challenge. Integrating patient-generated images seamlessly into existing workflows requires careful planning and consideration of data privacy and security concerns.

A recent Optum Digital Research Network study demonstrated the potential of integrated data capture for generating RWE. It highlighted the need for standardized practices and user-friendly tools to overcome the current hurdles of patient-generated images.4 A 2022 review on patient-generated health data also found photos and videos to be a powerful way to engage patients in health care, with potential transactional, functional, and emotional values.5

Moving forward, it will be critical for healthcare entities to provide infrastructure and support for patient-generated data. Today, advanced platforms can standardize enhanced media capture for more accurate digital data collection, and with the right tools, photo and video capture should continue to engage participants in meaningful ways across the healthcare spectrum, generating consistent value in research. 

EmpiraMed Solutions
EmpiraMed’s unique platform provides advanced image management and data collection features that enhance patient-reported and clinician-reported data into a single interoperable data set.  Participants can share pertinent media files they have captured about their experience or disease to be adjudicated by a clinician.

Contact us today to learn more about how EmpiraMed can become your digital data solution!

References

  1. Wongvibulsin S, Feterik K. Recommendations for Better Adoption of Medical Photography as a Clinical Tool. Interactive Journal of Medical Research. 2022;11(2):e36102. doi:https://doi.org/10.2196/36102
  2. Khosla S, Tepie MF, Nagy MJ, et al. The Alignment of Real-World Evidence and Digital Health: Realising the Opportunity. Therapeutic Innovation & Regulatory Science. Published online April 29, 2021. doi:https://doi.org/10.1007/s43441-021-00288-7
  3. Oehrlein EM, Burcu M, Schoch S, Gressler LE. Enhancing Patient Centricity of Real-World Data Research: An Exploratory Analysis Using the Patient Experience Mapping Toolbox. Value in Health. 2023;26(1):10-17. doi:https://doi.org/10.1016/j.jval.2022.10.002
  4. ‌Senerchia CM, Ohrt TL, Payne PN, et al. Using passive extraction of real-world data from eConsent, electronic patient reported outcomes (ePRO) and electronic health record (EHR) data loaded to an electronic data capture (EDC) system for a multi-center, prospective, observational study in diabetic patients. Contemporary Clinical Trials Communications. 2022;28:100920. doi:https://doi.org/10.1016/j.conctc.2022.100920
  5. Ploderer B, Rezaei Aghdam A, Burns K. Patient-Generated Health Photos and Videos Across Health and Well-being Contexts: Scoping Review. Journal of Medical Internet Research. 2022;24(4):e28867. doi:https://doi.org/10.2196/28867