Standard of care (SoC) plays a critical role in healthcare and research, acting as a benchmark for what is widely accepted as appropriate medical treatment or practice in a given context. It is shaped by clinical guidelines, expert consensus, and evidence-based practices. However, its application is not static; it evolves based on emerging evidence, technological advances, and local factors such as resource availability. SoC is the foundation of medical practice, representing the treatments and procedures generally recognized as appropriate and effective in routine clinical settings.
In Real-World Evidence (RWE) research, SoC data provides a clear picture of how healthcare is delivered and experienced outside the controlled environment of clinical trials. This real-world perspective makes it invaluable for understanding treatment patterns, effectiveness, and outcomes across diverse patient populations.
SoC data is particularly important in RWE research because it reflects actual clinical practices rather than idealized experimental conditions. It offers insights into how treatments are prescribed, administered, and adjusted based on individual patient needs. It also enables researchers to evaluate the comparative effectiveness of different treatments, shedding light on how existing therapies perform in real-world settings compared to new interventions or alternatives. Furthermore, SoC data highlights adherence to clinical guidelines, identifying gaps between recommended practices and actual implementation, which can inform updates to guidelines or targeted educational initiatives.
Diverse sources contribute to SoC data in RWE, including electronic health records (EHRs), claims databases, patient registries, and observational studies. Each of these data sources captures critical elements of routine care, from treatment administration to long-term outcomes. This allows researchers to analyze healthcare delivery comprehensively, offering a more nuanced understanding of patient experiences and population-level trends.
SoC data plays a vital role in various applications of RWE research. For instance, it supports regulatory decision-making by providing evidence for drug approvals or label expansions based on real-world outcomes. Health technology assessments (HTAs) use SoC data to compare the cost-effectiveness of interventions, while post-market surveillance relies on it to monitor long-term safety and effectiveness. Moreover, it helps optimize clinical pathways by identifying successful treatment protocols and areas for improvement.
Comparison of SoC Data Collected via EDC and EHR
There are specific circumstances where it could be debated whether SoC data can be considered RWD. It might be the case only under certain circumstances, and this would depends on how the data is generated, collected, and used.
The way SoC data is collected—whether via electronic data capture (EDC) systems or EHR—can influence its classification, usability, and alignment with RWD standards.
1. EDC Systems
- What is EDC? EDC systems are primarily used in clinical trials to collect data entered manually by investigators and clinical staff. These systems are designed for structured, protocol-driven data collection within controlled settings.
- SoC Data in EDC: Data about treatments and outcomes consistent with the SoC may be collected in clinical trials when participants are assigned to a SoC arm or when SoC forms the baseline comparator. However, this data is collected under controlled conditions and often tailored to trial protocols, making it less reflective of routine practice.
- Characteristics:
- Controlled Environment: Data is collected per a predefined protocol, limiting variability.
- Structured Entry: Data fields are standardized and specific to the trial.
- Verification: Often monitored and audited for regulatory compliance.
- Not Fully Real-World: Reflects SoC in an idealized or monitored environment.
2. EHR Systems
- What is EHR? EHR systems store patients' medical records as part of routine healthcare delivery. These records include information on diagnoses, treatments (including SoC), outcomes, and other clinical details.
- SoC Data in EHR: SoC data captured in EHR represents treatments administered as part of usual clinical practice, outside of controlled trial environments. It includes real-world variations in patient management, adherence, and provider decisions.
- Characteristics:
- Unstructured and Diverse: Data may include free text (e.g., clinical notes) or structured fields, leading to variability.
- Reflective of Routine Practice: Captures the heterogeneity of real-world patient care.
- Data Quality Issues: May include missing data, inconsistent coding, or errors.
- Real-World Data: Aligns with FDA’s definition of RWD when collected systematically.
Key Differences Between EDC and EHR for SoC Data
| Feature | EDC (Clinical Trials) | EHR (Routine Practice) |
| Purpose | Research-focused, aligned with trial protocols. | Patient care-focused, integrated into clinical workflows. |
| Environment | Controlled, with limited variability. | Real-world, reflecting variability in care delivery. |
| Data Entry | Manual, often by trained staff, adhering to protocols. | Automated or semi-automated from care processes. |
| Structure | Highly structured and standardized. | Variable; may include unstructured data (e.g., notes). |
| Data Quality | High quality, monitored and audited. | Variable, with potential inconsistencies. |
| Real-World Relevance | Limited (trial-specific environment). | High (routine care environment). |
Regulatory Perspective
- EDC Data:
- More often to be classified as part of clinical trial data, not RWD, unless explicitly designed to mirror real-world conditions or the need for data handling.
- EHR Data:
- Directly aligns with RWD criteria when captured systematically and used to inform decisions outside the trial setting.
In conclusion, the standard of care forms the backbone of clinical practice, ensuring that patients receive treatments grounded in evidence and professional consensus. When documented systematically, it transitions into RWD, offering critical insights that can drive improvements in healthcare delivery, policy, and innovation.