Real World Evidence: From Vision to Reality

Framework of Developing Real world Evidence (RWE)

There has been a burgeoning bid about the use of Real-World data in healthcare. The National Institute for Health and Care Excellence (NICE) has released the NICE real-world evidence framework on 23rd June 2022 which comprehensively deals with the use of real-world data to remove gaps in data, reduce uncertainty, and improve guidance.
Real-world data also known as non-randomised data, is collected outside the context of controlled clinical trials. The major sources of real-world data are electronic health records, administrative data, claims data, patient generated data, patients’ registries, audit and service reviews, observational cohort with primary data collection, health surveys, interviews etc. The need for RWE arises from the difference between the health outcomes expected and those realized from conventional RCTs.

  • The NICE has been using real world data across various programmes, especially where the effects of an intervention are not to be determined. Examples include, among others:
  • Patient generated data, characterizing health conditions, interventions, care pathways, and patient outcomes and experiences including natural history used multiple sources of real-world data to characterize spinal muscular atrophy,
  • Estimating economic burden reported data from Clinical Practice Research Datalink (CPRD) GOLD linked to Hospital Episode Statistics (HES),
  • Designing, populating, and validating among others.

Real-world data can also be used to augment and contextualize the randomized trial results to patient in the National Health Service (NHS) and estimate intervention effects. For newly developed interventions, the use of real-world data can be contended since it can be used to create a comparator arm or can be added as a control to Randomized Controlled Trials (RCTs). Besides, the real-world data enables using data from early access to medicines scheme, cross country comparison for technologies that are introduced prior to the UK.

The document lays down the framework for real world data usage under various heads. Under the conduct of quantitative real-world evidence studies, the NICE prescribes approaches that need to be followed while planning, conducting, and reporting the real-world evidence studies. The principles in this regard mainly revolve around the data provenance, data relevance and data sufficiency. Another principle that has been in focus is the need for transparency and integrity throughout the various stages of generating evidence, starting from planning to final reporting.

A general prescription that NICE has given is that patients should be consulted throughout the evidence generation scheme.

Defining the Research question must include defining the key study variables that must include population eligibility, criteria, intervention, outcomes, covariates, cofounders, subgroups, and the target quantity to be estimated (like prevalence or the average effect of an intervention). The list is only representative and not exhaustive. The developers should pre-specify the objective of the study along with the protocol regarding data identification, collection, curation, study design, and analytical methods including the subgroup and sensitivity analysis (especially for the studies concerning comparative effects).

The framework remarks that the data collection should be carried out in a systematic, transparent, and reproducible manner. The data collection should follow a predefined protocol to ensure quality, integrity, and consistency of data. The framework also canvasses an outline for the target trial approach concerning methods for real-world studies of comparative effects. A crisp representation of the guidelines is represented in the figure below.

 

Summary representation of planning and reporting cohort studies using real world data

As per the framework, the study design should reflect the following characteristics:

  • Nature and distribution of the outcome variable
  • Sample size
  • Structure of the data including data hierarchies or clustering (for example, patients may be clustered within hospitals or data may be collected on a patient at multiple timepoints)
  • Heterogeneity in outcomes across population groups
  • Whether data is cross-sectional or longitudinal.
  • The document outlines the common considerations under sensitivity analysis must include:
  • Varying operational definitions of key study variables
  • Differing time windows to define study variables and follow up
  • Use of alternative patient eligibility criteria
  • Address to missing data and measurement error
  • Alternative model specifications
  • Address to treatment switching or loss to follow up
  • Adjustments for non-adherence

he NICE framework necessitates, a quantitative bias analysis should be adhered to in case the residual bias remains high. It is required that while reporting results, the information should be presented in form flow diagrams representing each stage and aspect of evidence generation, patient characteristics across groups or levels of exposure, and differences in patient characteristics in analytical sample and target population. Communicating the real-world evidence studies can be challenging given the highly complex and extensive use of scientific terminology. Thus, as per the framework released, the studies should be documented in as simple a manner as possible that are easy to interpret with relevant explanations of the scientific terminology.

The NICE framework provides the “Data Suitability Assessment Tool (DataSAT)” that may be used to provide consistent and structured information on data suitability.

The document has included case studies on the reporting on methods of minimizing the risk of bias and reporting information on selected analytical methods. Interestingly, the framework was developed after thorough consultation and feedback from all stakeholders including patient organizations, health charities, healthcare professionals, the pharmaceutical and medical technologies industries, data controllers and contract research organizations, academia, international health technology assessment bodies, UK health system partners and NICE committee members.
The RCTs remain the gold standard for determining the efficacy of medicines, medical devices, and therapies. However, given the high cost and ethical issues with the use of RCTs, it is the need of the hour to recognise non-randomised data as a potential and effective way of evaluating the efficacy and safety of the new interventions. The NICE framework with respect to the use of real-world data and generating evidence is a step much awaited and is welcomed by the stakeholders. However, there is a need for proactively furthering the use of real-world data to suit our requirements and improve the quality of the research and development of new interventions.

Authors – Jyoti Sharma and Kunal Hriday

Reference:

https://www.nice.org.uk/about/what-we-do/real-world-evidence-framework-feedback

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Judit Banhazi

Specialty
Value and Access

Role
Vice President

Degree
MD Medicine, JD Law

Judit Banhazi

MD Medicine, JD Law

Judit Banhazi, based in Basel, Switzerland, brings over 20 years of experience in HEOR, Market Access, and Health Policy.
She has led HEOR strategies in hematology and initiated EU HTA policy activities. Judit began her career as a physician and has worked at prime global pharma companies. Her academic prowess is excellent with a peculiar combination of an MD in Medicine and a JD in Law, she has been at forefront of health economics by being involved in HTA policy discussions with EFPIA and HTAi.
Known for her collaborative spirit and practical approach, Judit is passionate about learning and delivering quality work. Outside of work, she enjoys spending time with family and friends, travelling, and running.

Adam Ball

Specialty
Business Development Manager

 

Adam Ball

Business Manager

I am delighted to be part of the team here at ConnectHEOR. To tell you a bit about me, I have 10 years experience within Talent Acquisition within HEOR, RWE and Market Access. I have built a global network during this time and am excited to utilize this to help us grow as business. 

 

Outside of work I love sports, playing football and squash regularly, as well as going to the gym. I also enjoy watching sports mainly football and tennis. I have a new born daughter too so she is taking up a lot of my time and is a bundle of joy. I also play drums and like to think I have a broad taste in Music.

 

Eleni Tente

Specialty
Medical writing, Evidence planning

Role
Consultant, Medical writer

Degree
PhD – Molecular biology and genetics

Eleni Tente

PhD – Molecular biology and genetics

Eleni Tente is an experienced medical writer with proven ability to translate complex scientific information into clear, concise, and impactful content to diverse audiences. She has a strong background in integrated evidence planning, publications, internal communications and e-learning development, complemented by an understanding of various therapeutic areas.

Eleni holds a PhD in molecular biology and genetics from the University of Cambridge and an MSc in plant genetic manipulation from the University of Nottingham.

In her free time, Eleni enjoys diving into a good book, fishing along the coast, or planning her next thrilling scuba diving adventure to swim with sharks.

Syed Salleh

Specialty
HTA Modelling and Discrete-event Simulation

Role
Consultant, Modeling & Analytics

Degree
PhD – Health & Related Research

Syed Salleh

PhD. Health & Related Research

Syed Salleh brings extensive experience in HTA modeling, having successfully led the development of both de novo and adaptation models for HTA listings across multiple countries, including Malaysia, Philippines, and the UK. His work spans key therapeutic franchises such as oncology, cardiometabolic, and respiratory. Syed has also delivered critical insights to healthcare professionals through MYSPOR, ITTP, and IKN virtual CME events and numerous publications.

He holds a PhD in Health and Related Research from the School of Health and Related Research (ScHARR) at the University of Sheffield, UK, with a specialization in HTA and operational research, specifically in discrete-event simulation (DES) technique.

During his time in a leading pharmaceutical company, Syed played a key role in securing the listing of several key products in the Malaysia Ministry of Health Formulary and served as the primary contact for DES-related projects.

Besides work, Syed enjoys traveling, listening to music, and spending quality time with his family.

Thai-Son Tong

Specialty
Model Conceptualization and Data Analytics

Role
Senior Consultant

Degree
PhD – Health Economics

Thai-Son Tong

PhD. Health Economics

Thaison Tong has extensive work experience in health economics, decision modelling and big data analysis. He has a unique mix of experience in HEOR and RWE related research in academia and pharmaceutical industry. His expertise lies in health technology assessments (HTA), health economic modelling, simulation modelling, big data analytics and decision analysis. He has hands-on experience in a range of software and programming languages including R, R Shiny, R Markdown, Python, MS Excel, VBA, and Simul8. He has substantial experience of the health care system in the UK and other European countries.

Thaison has direct experience in building cost-effectiveness models from scratch and conducting big data analysis in several disease areas including dementia, vascular disease, and cancer.

Thaison’s PhD focus was to develop a de novo patient level model for the evaluation of different cognitive screening tests for early detection of dementia and mild cognitive impairment in primary care. He also looked at different methods for conducting economic evaluation in health care taking a broader/societal perspective. In addition, he investigated the use of Multiple Criteria Decision Analysis (MCDA) for economic evaluation.

Thaison also holds Academic Researcher position in School of Health and Related Research (ScHARR), University of Sheffield, UK and Honorary Researcher position in University of Bristol, UK.

Thaison’s likes to meditate, and play badminton, basketball and tennis.

Shilpi Swami

Specialty
Consulting and strategy

Role
Vice President

Degree
MSc. International Economics

Shilpi Swami

MSc. International Economics

Shilpi Swami is a seasoned Health Economics and Outcomes Research (HEOR) expert with experience spanning across multiple healthcare systems and therapy areas. At her current role of Vice President, HTA and Strategy, ConnectHEOR, she provides technical and strategic leadership. Additionally, Shilpi serves as the Member Engagement Co-Chair at ISPOR Oncology Special Interest Group.

Shilpi has a comprehensive track record of leading HTA submissions and devising market access strategies on a global scale, including the EU-5, Canada, US, Latin America, Australia, and Asia. Shilpi has worked across various sectors within health economics, including academia, consulting, and biopharma. This multidimensional experience equips her with a unique ability to offer strategic insights from various stakeholders’ perspectives.

Formerly a Research Fellow at the University of York, Shilpi has made significant contributions to public health projects and the development of best practices in the academic side of health economics. In her professional endeavors, she remains dedicated to improving healthcare through data-driven insights and evidence-based research

Hugo Pedder

Specialty Statistical Analysis and Evidence Synthesis

Role Senior Consultant

Degree PhD – Statistical Modelling

Hugo Pedder

PhD – Statistical Modelling

Hugo brings in a wealth of experience to ConnectHEOR from his extensive work in academia, focusing primarily on evidence synthesis and meta-analysis. Hugo holds PhD in Statistical Modelling from University of Briston and MSc in Medical Statistics from the London School of Hygiene and Tropical Medicine, and his background in neuroscience remains a passionate interest. Alongside working with ConnectHEOR, Hugo continues to part of NICE committee. His expertise includes advanced indirect treatment comparisons technique and has extensive experience of working with the NICE in UK. 

Beyond professional endeavors, Hugo is an enthusiastic outdoor adventurer, particularly enjoying mountain activities, climbing and ski mountaineering. From building rafts to exploring rivers in north of Sweden, he has lived an adventurous life outside of work and plans to continue to do so.

Kunal Hriday

Specialty
Data science and Strategy

Role
Senior Consultant

Degree
MSc. Quantitative Economics

Kunal Hriday

MSc. Quantitative Economics

Kunal Hriday is a business strategy and data science professional with experience in helping organizations crack through notorious business challenges. Kunal is proficient in business analytics, data analytics, product lifecycle management and business development. Working as a Data analytics consultant he has spent time in problem solving across variety of industries including Banking, logistics and Health and is now fully dedicated to HEOR. Kunal has hands on experience in various statistical programming tools and languages like R, Python, SAS, Excel VBA, Data Robot and data visualization tools like Power BI, Tableau and SAS VA.

Kunal also holds a Masters in Quantitative Economics from Indian Statistical Institute and a bachelors degree in Business Economics. Excellent in business communication, he is passionate about studying environmental economics and related theories of welfare optimization.

Raju Gautam

Specialty
Evidence Review

Role
Principal Consultant

Degree
PhD (Pharmacy)

Raju Gautam

PhD Pharmacy

Raju Gautam spearheads evidence review at ConnectHEOR and  has extensive work experience in evidence review and synthesis, value communications, scientific publications, medical writing and project management.
His expertise lies in systematic and targeted literature reviews, meta-analyses, network meta-analyses, value communications (AMCP and Global Value Dossiers), RWE study design and publications (manuscripts, posters, and abstracts).
He has experience working in Global pharma companies, consulting and CRO environment for several therapy areas including Cardiovascular, Oncology, Neurology, Respiratory, Ophthalmic, Rare Diseases, and Vaccines. He has more than 40 publications in international journals as an author.
Raju also likes jogging, yoga and meditation.

Radha Sharma

Specialty:
Patient preference research, survey, In-depth interviews, COA, Evidence review and conceptualisation of study

Role:
Director – Patient-Centered Outcomes Research

Degree:
MBBS (Bachelor of Medicine and Bachelor of Surgery), PhD (Global Public Health) – University of York

Radha Sharma

PhD (Global Public Health)

Radha Sharma spearheads Patient-Centered Outcomes Research at ConnectHEOR. She has a background in medicine, public health, and epidemiology.

Her expertise includes global health research, preference elicitation, mixed-method studies, consensus workshops, qualitative health research, epidemiological analysis of big data sets, RWE study design, scientific writing, and literature reviews. Her primary focus is integrating patient perspectives into all stages of health technology assessment (HTA) and healthcare decision-making processes.

Her extensive expertise in mixed-method studies and active patient/stakeholder engagement ensures that her research is methodologically rigorous and patient-centric. Radha is an avid hiker and enjoys exploring the beautiful Canadian Rockies.

Kate Ren

Specialty
Statistical Analysis and Evidence Synthesis

Role
Director of Statistics

Degree
Ph.D Probability and Statistics

Kate Ren

PhD Probability and Statistics

Kate spearheads Statistics and Evidence Synthesis at ConnectHEOR. She has more than 10 years of experience in conducting statistical analysis in HTA. Kate has PhD in Probability and Statistics specialising in Bayesian methods in clinical trial design.

She specializes in Bayesian methods in health economics and the elicitation of experts’ beliefs and has extensive experience of conducting evidence synthesis, including, meta-analysis, network meta-analysis, MAIC, STC, ML-NMR etc. Besides working with ConnectHEOR, she is also a part of NICE Committee and University of Sheffield.

Tushar Srivastava

Specialty
Decision Modelling and AI Initiatives

Role
Director and Principal Consultant

Degree
MSc – Statistics and Computing

Tushar Srivastava

MSc – Statistics and Computing

Endorsed as a ‘Global Talent’ by prestigious ‘The Royal Society, UK’, Tushar is dynamic and enjoys approaching complex problems with a holistic approach. He also holds an MSc. in Statistics and has authored a handbook on higher Mathematics, “A concise handbook of vector space theory and field theory, Srivastava T.”

In ConnectHEOR, Tushar spearhead all HEOR activities.

Tushar’s technical expertise lies in different techniques including cost-effectiveness modelling, budget impact modelling, simulation modelling, statistical modelling and indirect comparisons analysis. He brings a unique blend of academic research, technical modelling and statistical skills and industry professionalism to support the life science industry at every stage of the product life cycle. He has a good experience in statistical analyses, including survival analysis and health related quality of life data analysis from clinical trials.

Besides work, Tushar enjoys playing badminton, jogging, and meditating.