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Real World Evidence (RWE) 101 – De-Identification versus Pseudo-Anonymisation

RWE 101 – Real World Evidence (RWE) 101 – De-Identification versus Pseudo-Anonymisation

De-identification and pseudo-anonymization are two commonly used techniques for protecting personal information in real world evidence (RWE) studies.

De-identification involves removing or obscuring any personal identifiers, such as names, addresses, and social security numbers, from a dataset. The goal is to make it impossible to identify individuals in the dataset. However, de-identified data can still potentially be re-identified if combined with other data sources or through statistical analysis.

Pseudo-anonymization involves replacing personal identifiers with a unique identifier, or code, that cannot be traced back to the individual without access to a separate database. This technique provides an additional layer of protection as the original personal identifiers are not included in the dataset. However, there is still a risk that individuals can be re-identified if the codes are compromised or if the separate database is breached.

In the context of RWE, both de-identification and pseudo-anonymization can be effective in protecting personal information. The choice of technique will depend on the level of risk associated with re-identification and the specific requirements of the study. For example, if the dataset contains sensitive information or the risk of re-identification is high, pseudo-anonymization may be preferred. If the risk of re-identification is low and the dataset does not contain sensitive information, de-identification may be sufficient.

It is important to note that neither de-identification nor pseudo-anonymization can guarantee complete protection of personal information. Additional measures, such as access controls and data use agreements, may be necessary to further reduce the risk of re-identification and protect the privacy of individuals in RWE studies.

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Real World Evidence (RWE) 101 – De-Identification versus Pseudo-Anonymisation2023-08-07T22:50:09+00:00

Real World Evidence (RWE) 101 – Data Tokenization

RWE 101 – 4 Potential Uses for Improving Drug Development

Real world evidence (RWE) refers to data collected outside the context of traditional clinical trials, such as observational studies, registries, and electronic health records. RWE can provide valuable insights into the safety, effectiveness, and real-world use of drugs, and has the potential to transform drug development.

Some of the opportunities of real world evidence in drug development include:

1. Improved patient recruitment: RWE can help identify patient populations that are typically underrepresented in clinical trials, such as elderly patients, patients with multiple comorbidities, and those with rare diseases. This can help improve patient recruitment and enable more representative clinical trials.
2. Enhance clinical trial design: RWE can help inform the design of clinical trials, for example, by identifying appropriate endpoints, understanding patient demographics, and identifying potential confounding factors that need to be accounted for.
Identify safety concerns: RWE can help identify safety concerns that may not have been detected in clinical trials, especially those related to long-term use or rare adverse events. This can help improve post-marketing surveillance and ensure that drugs are used safely in the real world.
3. Better understanding of effectiveness: RWE can provide insights into the effectiveness of drugs in the real world, including how drugs are used in combination with other treatments, and how patient outcomes vary across different subpopulations.
4. Accelerate drug development: By leveraging RWE, drug development timelines can be accelerated as fewer resources are required for clinical trials, making it easier to conduct larger and more complex studies. Additionally, RWE can help optimize the design of clinical trials, reducing the likelihood of failed trials and resulting in faster regulatory approvals.

In summary, real world evidence has the potential to improve drug development in a number of ways, including patient recruitment, clinical trial design, safety monitoring, and accelerating drug development timelines. By leveraging RWE, drug developers can gain a better understanding of how drugs work in the real world, which can ultimately improve patient outcomes.

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Real World Evidence (RWE) 101 – Data Tokenization2023-08-07T22:48:59+00:00

Real World Evidence (RWE) 101 – Primary Data versus Secondary Data

RWE 101 – Primary Data versus Secondary Data

Primary data and secondary data are two types of data used in research. The main difference between the two is that primary data is collected directly from the source, while secondary data is collected from sources that have already collected the data.

Primary data is original data that is collected for a specific research project. This type of data can be collected through various methods, including surveys, interviews, observations, and experiments. Primary data is collected with a specific research objective in mind, and the data is usually more focused and targeted than secondary data.

On the other hand, secondary data is data that has already been collected by someone else for a different purpose. This type of data can be collected from a wide variety of sources, including healthcare organisations, government agencies, academic institutions, and commercial organizations. Secondary data can be used to supplement primary data or to answer research questions that are not directly related to the original research objective.

There are advantages and disadvantages to both types of data. Primary data is more likely to be accurate and relevant to the specific research question being studied, but it can also be more time-consuming and expensive to collect. Secondary data is generally less expensive and easier to access, but it may not be as accurate or relevant to the specific research question being studied.

In general, researchers will use a combination of primary and secondary data to address their research questions and achieve their research objectives

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Real World Evidence (RWE) 101 – Primary Data versus Secondary Data2023-08-07T22:47:38+00:00

RWR Insights | Regulatory Considerations for Non-Interventional Study Protocols

RWR CONTEXT

Both RWE and clinical trials play critical roles in healthcare research. While clinical trials provide the highest level of evidence for determining a treatment’s efficacy, RWE studies complement this by providing evidence on real-world effectiveness and long-term safety.

Real-world evidence (RWE) study protocols and clinical trial protocols both outline the design and conduct of a study. However, they are distinctly different in several ways given the differences in objectives, methodologies, settings, and populations involved in clinical trials versus RWE studies.

The HARPER framework is a valuable resource for researchers and clinicians who are planning or conducting RWE studies. The framework can help to ensure that protocols are well-designed and will produce high-quality evidence.

Real-world evidence (RWE) study protocols and clinical trial protocols both outline the design and conduct of a study. However, they are distinctly different in several ways given the differences in objectives, methodologies, settings, and populations involved in clinical trials versus RWE studies.

[1] Objectives: The main objective of a clinical trial is to evaluate the efficacy and safety of a medical intervention in a controlled environment, usually by comparing it to a placebo or standard treatment. On the other hand, RWE studies typically aim to understand how an intervention works in routine clinical practice, often focusing on outcomes such as long-term effectiveness, side-effects, quality of life, and cost-effectiveness.

[2] Study Design and Methodology: Clinical trials, especially phase III, are predominantly randomized controlled trials (RCTs) where subjects are randomly assigned to the intervention or control group to minimise bias. They follow a pre-specified protocol and are conducted under tightly controlled conditions. RWE studies, on the other hand, are typically observational in nature and analyse data from sources like electronic health records (EHRs), claims databases, or patient registries.

[3] Setting: Clinical trials are conducted in specific, controlled environments and follow a strict protocol. RWE studies are conducted in routine clinical practice settings, making them more representative of ‘real-world’ conditions.

[4] Population: Clinical trials often have strict inclusion and exclusion criteria, resulting in a relatively homogeneous group of participants. This can limit the generalisability of the results. RWE studies, in contrast, involve broader, more diverse populations (including those often excluded from trials like the elderly, people with multiple co-morbidities, etc.), making the findings more generalisable to everyday practice.

[5] Data Collection: In clinical trials, data collection is rigorous, detailed, and specific to the trial endpoints. Adverse events are actively sought and documented. RWE studies primarily rely on existing data sources such as EHRs, patient registries, or insurance claims data. This can potentially lead to incomplete or inaccurate data.

[6] Intervention: In clinical trials, the intervention (dosage, frequency, duration, etc.) is pre-specified and strictly monitored. In RWE studies, interventions reflect routine clinical practice and may vary widely.

[7] Follow-up: Clinical trials have a defined follow-up period while RWE studies can often provide information on long-term outcomes, given they use data from routine clinical practice over longer periods.

Despite these differences, both RWE and clinical trials play critical roles in healthcare research. While clinical trials provide the highest level of evidence for determining a treatment’s efficacy, RWE studies complement this by providing evidence on real-world effectiveness and long-term safety.

HARPER PROTOCOL TEMPLATE

Regulatory agencies, health technology assessors, and payers are increasingly interested in studies that make use of real-world data to inform regulatory and other policy or clinical decision-making. However, concerns over the credibility of real-world evidence studies have led to calls for more transparency on the design and conduct of RWE studies.

A joint task force between ISPE and ISPOR created a harmonized protocol template for RWE studies that evaluate a treatment effect and are intended to inform decision-making [1]. The HARPER template provides clarity, structure, and a common denominator regarding the level of operational detail, context, and rationale necessary in a protocol.

HARPER = HARmonized Protocol Template to Enhance Reproducibility of hypothesis evaluating real-world evidence studies on treatment effects

Link: https://onlinelibrary.wiley.com/doi/10.1002/pds.5507 

Four protocol templates were identified for RWE studies: 

      1. The European Medicines Agency’s (EMA) Guideline on Good Pharmacovigilance Practices (GVP) Module VIII – post-authorisations safety studies (PASS) template,
      2. ISPE’s guidelines for good pharmacoepidemiology practice (ISPE GPP) section on protocol development, 
      3. The National Evaluation System for health Technology (NEST) protocol guidance, and
      4. The Structured Template and Reporting Tool for Real World Evidence (STaRT-RWE).

The HARPER protocol contains nine sections, including a title page, abstract, and a table for amendments and updates. Each section includes structured free text, a structured table, or a figure, and a free-text section to lay out context and rationale for scientific choices.

The study design diagram shows the context and rationale for the study setting, time 0 (index date), inclusion criteria, exclusion criteria, variables, exposure, outcome, follow up, covariates, sensitivity analyses, data sources, metadata, and software used in the study.

The data sources section includes a free text component followed by a structured table for specifying data sources. The data sources section can also include a detailed evaluation of the fitness-for-purpose of data source options.

Overall, the HARPER framework is a valuable resource for researchers and clinicians who are planning or conducting RWE studies. The framework can help to ensure that protocols are well-designed and will produce high-quality evidence.

References

1. Wang, SV, Pottegård, A, Crown, W, et al. HARmonized Protocol Template to Enhance Reproducibility of hypothesis evaluating real-world evidence studies on treatment effects: A good practices report of a joint ISPE/ISPOR task force. Pharmacoepidemiol Drug Saf. 2023; 32( 1): 44- 55. doi:10.1002/pds.5507

Link: https://onlinelibrary.wiley.com/doi/10.1002/pds.5507 

RWR Insights | Regulatory Considerations for Non-Interventional Study Protocols2023-08-04T13:06:33+00:00

EU | 11th Revision of the ENCePP Guide on Methodological Standards in Pharmacoepidemiology Published

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EU | 11th Revision of the ENCePP Guide on Methodological Standards in Pharmacoepidemiology Published2023-08-04T12:08:22+00:00

ITALY | Delay in Establishing Territorial Ethics Committees (CETs) in the Provinces of Trento and Bolzano

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ITALY | Delay in Establishing Territorial Ethics Committees (CETs) in the Provinces of Trento and Bolzano2023-08-04T11:35:50+00:00
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