Real-world evidence (RWE) refers to data obtained from real-world settings, such as electronic health records, claims databases, wearable devices, and patient registries. Health Technology Assessment (HTA) is a systematic evaluation of the clinical, economic, and social impacts of healthcare technologies. The use of real-world evidence in HTA is gaining traction as a valuable complement to traditional randomized controlled trials (RCTs) and can provide additional insights into the effectiveness, safety, and value of healthcare interventions. Here are some key points exploring the use of real-world evidence in HTA

1. Welcome
Exploring the Use of Real-World Evidence in Health
Technology Assessment (HTA)
Deepika Thammineni
B. Pharmacy
106/062023
10/18/2022
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2. Agenda
- Overview of HTA
- Objective of HTA
- Traditional sources of evidence in HTA
- Importance of Real-World Evidence (RWE) in HTA
- Advantages of RWE
- Long-term safety and effectiveness evaluations
- Potential to inform HTA decisions more comprehensively
- Challenges in Using RWE in HTA
- Strategies for Incorporating RWE in HTA
- Conclusion & Future directions
- References
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3. Overview of HTA
- Health Technology Assessment (HTA) is a multidisciplinary and systematic evaluation process
that assesses the medical, social, economic, and ethical implications of healthcare technologies. -
- HTA is to inform healthcare decision-making by providing evidence-based information on the
value and appropriateness of different technologies, thus facilitating resource allocation, policy
development, and healthcare improvement.
Objectives of HTA
- HTA aims to ensure that healthcare technologies are effective, safe, cost-effective, and aligned
with the needs of patients and healthcare systems.
- Determine if a healthcare technology works well and is safe
- Assess if the technology provides value for money
- Help decision-makers make informed choices
- Influence healthcare policies
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4. Traditional sources of evidence in HTA
Traditional sources of evidence in Health Technology Assessment (HTA) refer to the commonly used types
of information and data that are considered in the evaluation of healthcare interventions. These sources
include:
1. Randomized Controlled Trials (RCTs)
2. Systematic Reviews and Meta-analyses
3. Clinical Guidelines
4. Health Economic Evaluations
5. Expert Opinion
These traditional sources of evidence in HTA are essential in evaluating the effectiveness, safety, and cost-
effectiveness of healthcare interventions, and they form the basis for decision-making in healthcare policy
and practice.
Importance of Real-World Evidence (RWE) in HTA
- Real-World Evidence (RWE) refers to data collected from real-world settings, outside the constraints of
clinical trials, to assess the effectiveness, safety, and value of healthcare interventions. It provides insights
into how interventions perform in routine clinical practice and captures a broader range of
patients, treatments, and outcomes.
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5. Advantages of RWE
- Broader Patient Population Representation
- Long-Term Safety and Effectiveness Evaluations
- Comparative Effectiveness Research
- Potential to Inform HTA Decisions More Comprehensively
Long-term safety and effectiveness evaluations
- Long-term safety and effectiveness evaluations using Real-World Evidence (RWE) enable the
assessment of interventions over extended periods of time, providing insights into their sustained
benefits and potential risks.
- RWE captures real-world clinical practice and patient outcomes beyond the controlled setting of
clinical trials, allowing for a more comprehensive understanding of interventions' long-term
performance.
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6. Potential to inform HTA decisions more
comprehensively
- The use of Real-World Evidence (RWE) has the potential to provide a more comprehensive
understanding of healthcare interventions, which can inform Health Technology Assessment (HTA)
decisions.
- RWE captures data from real-world settings, beyond the controlled conditions of clinical trials,
allowing for a broader representation of patients and a longer-term evaluation of intervention
effectiveness and safety.
Challenges in Using RWE in HTA
Data quality and standardization
RWE is derived from various sources, such as electronic health records, registries, and
administrative databases, which may vary in terms of data completeness, accuracy, and
consistency. The lack of standardized data collection methods and definitions can introduce
challenges in comparing and synthesizing RWE across different studies.
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7. Bias and confounding factors
- RWE is often derived from observational studies where interventions are not randomly
assigned, leading to potential biases in treatment assignment and outcome assessment.
- Confounding factors, such as differences in patient characteristics or healthcare practices, can
influence the observed effects of interventions.
- Controlling for these biases and confounders is essential to ensure the validity and reliability of
RWE in HTA.
Lack of control groups
- Unlike randomized controlled trials (RCTs), RWE is often based on observational data where
interventions are implemented as part of routine clinical care without a defined control group.
- The absence of a control group makes it challenging to establish a direct comparison between
the intervention and an alternative or standard treatment.
- This can limit the ability to attribute observed outcomes solely to the intervention and may
introduce uncertainties in assessing its true effectiveness and safety.
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8. Generalizability of findings
- RWE studies often have specific inclusion and exclusion criteria, which may result in a study
population that differs from the broader patient population.
- This can limit the generalizability of the findings to real-world clinical practice.
- Factors such as patient demographics, healthcare settings, and treatment patterns can vary across
different regions or healthcare systems, further impacting the generalizability of RWE findings.
Strategies for Incorporating RWE in HTA
Methodological frameworks for RWE integration:
- Observational studies
These studies leverage existing data sources to assess the effectiveness, safety, and value of
healthcare interventions in real-world settings, providing valuable insights beyond controlled
clinical trials.
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9. Registries and electronic health records (EHRs)
- Registries collect standardized data on specific patient populations or conditions, providing
comprehensive and longitudinal information for evaluation.
- EHRs contain patient health records, enabling the extraction of real-time data on treatment
patterns, outcomes, and adverse events.
Data linkage and data sharing initiatives
- These initiatives involve integrating data from various sources, such as registries, electronic
health records, administrative databases, and other healthcare data repositories.
- By linking and sharing data across different systems, researchers and HTA bodies can access
comprehensive datasets that provide a more holistic view of patient outcomes, treatment patterns,
and healthcare utilization.
Data quality assurance and validation processes
- Data cleaning and preprocessing
- Data validation and verification
- Standardization and harmonization
- Quality control measures
By implementing robust data quality assurance and validation processes, HTA bodies can enhance
the reliability and credibility of RWE, leading to more accurate and trustworthy evidence for
informing healthcare decision-making.
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10. Statistical techniques for addressing bias and confounding
- Propensity Score Matching
- Propensity Score Adjustment
- Instrumental Variable Analysis
- Sensitivity Analysis
- Multiple Imputation
- These statistical techniques, when applied appropriately, help mitigate bias and
confounding in RWE analyses, providing more reliable and valid estimates of treatment
effects in HTA.
Conclusion
Potential benefits of incorporating RWE in HTA
- Enhanced understanding of intervention effectiveness, safety, and value in real-world settings.
- Broader patient population representation, leading to more inclusive and equitable healthcare
decision-making.
- Timely and up-to-date data capture, providing insights into long-term outcomes and real-world
treatment patterns.
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11. Future directions and challenges in RWE utilization utilization include:
- Advancing data quality and standardization
- Addressing methodological and analytical complexities
- Strengthening collaboration and data sharing
- Ensuring privacy and data protection
- Building capacity and expertise
- Addressing generalizability and external validity
- Overcoming these challenges and pursuing these future directions will contribute to maximizing
the potential of RWE in informing healthcare decision-making, improving patient outcomes, and
advancing evidence-based healthcare practices.
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12. References
• Makady, A., Stegenga, H., & Grutters, J. (2019). Using real-world
data in health technology assessment (HTA) practice: a comparative
study of five HTA agencies. PharmacoEconomics, 37(11), 1387-
1403.
• Garrison, L. P., Neumann, P. J., & Erickson, P. (2017). Using real-
world data for coverage and payment decisions: the ISPOR Real-
World Data Task Force report. Value in Health, 20(7), 979-988.
• RWE Generation & Use Project Team. (2017). Use of real-world
evidence in US payer decision-making: a benchmark survey. Journal
of Comparative Effectiveness Research, 6(1), 25-34.
• Eichler, H. G., Abadie, E., Breckenridge, A., Flamion, B., Gustafsson,
L. L., Leufkens, H., ... & Schneider, C. K. (2012). Bridging the
efficacy-effectiveness gap: a regulator's perspective on addressing
variability of drug response. Nature Reviews Drug Discovery, 10(7),
495-506.
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13. Thank You!
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