In the context of health research, both observational studies and clinical trials are crucial for understanding disease processes, patient outcomes, and the safety and efficacy of treatments. However, due to varying regulatory requirements and standards, the archiving requirements for these types of studies are distinct. Here are some of the key differences:
[1] Regulations and Guidelines: Clinical trials as governed by a global set of ethical and scientific standards, such as ICH GCP. These standards are then adopted into law in different regions, say for instance, through the Regulation EU/536/2014, and 21 CFR 312 in the US. These rules are clear about how to manage, store, and archive data and require specific documents to prove the integrity of the trial data. They also set out how long these crucial documents should be kept (e.g., at least 25 years).
On the flip side, observational studies aren’t governed by such unified requirements when it comes to document retention and archiving. They still follow ethical guidelines and good practice principles like the Declaration of Helsinki, ISPE GPP, and STROBE guidelines, but these may not give you exact retention times or archiving mechanisms.
[2] Data Collection and Confidentiality: Clinical trials are data-rich; they collect a large amount of confidential and sensitive patient data. Regular sponsor audits and regulatory inspections mean they need to keep robust records. Observational studies, while they also handle sensitive data, usually don’t interact with patients as much and don’t face as many regulatory inspections. So, they’ve traditionally not had to maintain as meticulous records.
[3] Data Accessibility: Clinical trial data is often more restricted in terms of who can access it and how it can be shared. This is due to both regulatory needs and commercial interests. Observational data, though, is often used for big-picture disease studies, and it’s usually designed to be more shareable – as long as it’s anonymized and ethical procedures are followed.
It’s important to remember that what I’ve explained are general patterns. The exact requirements can change based on region, the type of data you’re dealing with, and even who’s funding your work. If you need specific guidance, don’t hesitate to reach out to an expert or regulatory authority in your area.
Share this story...
Real World Evidence (RWE) 101 – Parkinson’s Disease
RWE 101 - Parkinson’s Disease Real-world evidence (RWE) refers to clinical evidence regarding the usage and potential benefits or risks of a treatment derived from analysis of real-world data [...]
Real World Evidence (RWE) 101 – Benefits of RWE in the Context of Rare Diseases
RWE 101 - Benefits of RWE in the Context of Rare Diseases Real-world evidence (RWE) refers to information on health care that comes from real-world settings, such as electronic [...]
Real World Evidence (RWE) 101 – Disease Prevalence vs Incidence
RWE 101 - Disease Prevalence vs Incidence Real-world evidence (RWE), derived from real-world data (RWD), allows us to gain insights into disease prevalence and incidence outside of controlled clinical [...]
Real World Evidence (RWE) 101 – Principles for Ensuring that Research Results are Reliable, Valid, and Objective
RWE 101 - Principles for Ensuring that Research Results are Reliable, Valid, and Objective Ensuring that research results are reliable, valid, and objective requires careful planning, execution, and evaluation. [...]
Real World Evidence (RWE) 101 – Why Should Non-Interventional Studies NOT be Promotional?
RWE 101 - Why Should Non-Interventional Studies NOT be Promotional? Non-interventional studies (NIS) are designed to observe and analyze data from real-world clinical settings without intervening or manipulating any [...]
Real World Evidence (RWE) 101 – Seeding Studies
RWE 101 - Seeding Studies Seeding studies, in the context of real-world evidence (RWE), refer to studies that were conducted by pharmaceutical or medical device companies after a product's [...]







