Use of Real-World Data Sources for Canadian Drug Pricing and Reimbursement Decisions: Stakeholder Views and Lessons for Other Countries

AbstractBackgroundCanada has a long history of the use of clinical evidence to support healthcare decision making. Given improvements in data holdings and analytic capacity in Canada and stakeholder interest, the purpose of this study is to reflect on perceptions of the value of real-world evidence in pricing and reimbursement decisions, barriers to its optimal use in pricing and reimbursement, current initiatives that may lead to its increased use, and what role the pharmaceutical industry may play in this.Methods/ResultsTo capture stakeholder perceptions, ninety-one participants identified as key stakeholders were identified according to background roles and geography and invited to participate in four round table discussions conducted under Chatham House rule. Important themes emerging from these discussions included: (i) the need to understand what “real world” evidence means; (ii) barriers to using real world evidence from differences in access, governance, inter-operability, system structures, expertise, and quality across Canadian health systems; (iii) differing views on industry's role.ConclusionsThe use of real-world data in Canada to inform pricing and reimbursement decisions is far from routine but nascent and slowly increasing. Barriers, including interoperability concerns, may also apply to other federated health systems that need to focus on the networking of healthcare administrative data across provincial jurisdictional boundaries. There also appears to be a desire to see better use of pragmatic trials linked to these administrative data sets. Emerging initiatives are under way to use real world evidence more broadly, and include identification of common data elements and approaches to networking data.

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Leveraging Real-World Data for the Selection of Relevant Eligibility Criteria for the Implementation of Electronic Recruitment Support in Clinical Trials

Applied Clinical Informatics ◽

10.1055/s-0040-1721010 ◽

2021 ◽

Vol 12 (01) ◽

pp. 017-026

Author(s):

Georg Melzer ◽

Tim Maiwald ◽

Hans-Ulrich Prokosch ◽

Thomas Ganslandt

Keyword(s):

Data Warehouse ◽

Real World ◽

Chart Review ◽

Patient Recruitment ◽

Real World Data ◽

Eligibility Criteria ◽

Health Records ◽

World Data ◽

Paper Chart ◽

Data Elements

Abstract Background Even though clinical trials are indispensable for medical research, they are frequently impaired by delayed or incomplete patient recruitment, resulting in cost overruns or aborted studies. Study protocols based on real-world data with precisely expressed eligibility criteria and realistic cohort estimations are crucial for successful study execution. The increasing availability of routine clinical data in electronic health records (EHRs) provides the opportunity to also support patient recruitment during the prescreening phase. While solutions for electronic recruitment support have been published, to our knowledge, no method for the prioritization of eligibility criteria in this context has been explored. Methods In the context of the Electronic Health Records for Clinical Research (EHR4CR) project, we examined the eligibility criteria of the KATHERINE trial. Criteria were extracted from the study protocol, deduplicated, and decomposed. A paper chart review and data warehouse query were executed to retrieve clinical data for the resulting set of simplified criteria separately from both sources. Criteria were scored according to disease specificity, data availability, and discriminatory power based on their content and the clinical dataset. Results The study protocol contained 35 eligibility criteria, which after simplification yielded 70 atomic criteria. For a cohort of 106 patients with breast cancer and neoadjuvant treatment, 47.9% of data elements were captured through paper chart review, with the data warehouse query yielding 26.9% of data elements. Score application resulted in a prioritized subset of 17 criteria, which yielded a sensitivity of 1.00 and specificity 0.57 on EHR data (paper charts, 1.00 and 0.80) compared with actual recruitment in the trial. Conclusion It is possible to prioritize clinical trial eligibility criteria based on real-world data to optimize prescreening of patients on a selected subset of relevant and available criteria and reduce implementation efforts for recruitment support. The performance could be further improved by increasing EHR data coverage.

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Squaring the Circle? Using Real World Data from Early Access Programs to Inform Pricing and Reimbursement Decision Making

Value in Health ◽

10.1016/j.jval.2018.04.434 ◽

2018 ◽

Vol 21 ◽

pp. S52

Author(s):

R Macaulay ◽

B Anell

Keyword(s):

Decision Making ◽

Real World ◽

Reimbursement Decision ◽

Real World Data ◽

World Data ◽

Squaring The Circle ◽

Early Access ◽

Pricing And Reimbursement ◽

Access Programs

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Real-World Data and Real-World Evidence

Innovative Methods for Rare Disease Drug Development ◽

10.1201/9781003049364-8 ◽

2020 ◽

pp. 141-166

Author(s):

Shein-Chung Chow

Keyword(s):

Real World ◽

Real World Data ◽

World Data ◽

Real World Evidence

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Development of an Innovative Real-World Evidence Registry for the Herpes Simplex Virus: Case Study

JMIR Dermatology ◽

10.2196/16933 ◽

2020 ◽

Vol 3 (1) ◽

pp. e16933 ◽

Cited By ~ 2

Author(s):

Michelle Helena van Velthoven ◽

Ching Lam ◽

Caroline de Cock ◽

Terese Stenfors ◽

Hassan Chaudhury ◽

...

Keyword(s):

Herpes Simplex Virus ◽

Herpes Simplex ◽

Real World ◽

Physical Symptoms ◽

Use Cases ◽

Real World Data ◽

World Data ◽

Real World Evidence ◽

Simplex Virus

Background Infection with the herpes simplex virus (HSV) is common but not well understood. Furthermore, there remains a social stigma surrounding HSV that can have psychosocial implications for those infected. Despite many patients infected with HSV experiencing mild-to-severe physical symptoms, only one subeffective treatment is available. A registry collecting real-world data reported by individuals potentially infected with HSV could help patients to better understand and manage their condition. Objective This study aimed to report on the development of a registry to collect real-world data reported by people who might be infected with HSV. Methods A case study design was selected as it provides a systematic and in-depth approach to investigating the planning phase of the registry. The case study followed seven stages: plan, design, prepare, collect, analyze, create, and share. We carried out semistructured interviews with experts, which were thematically analyzed and used to build use cases for the proposed registry. These use cases will be used to generate detailed models of how a real-world evidence registry might be perceived and used by different users. Results The following key themes were identified in the interviews: (1) stigma and anonymity, (2) selection bias, (3) understanding treatment and outcome gaps, (4) lifestyle factors, (5) individualized versus population-level data, and (6) severe complications of HSV. We developed use cases for different types of users of the registry, including individuals with HSV, members of the public, researchers, and clinicians. Conclusions This case study revealed key considerations and insights for the development of an appropriate registry to collect real-world data reported by people who might be infected with HSV. Further development and testing of the registry with different users is required. The registry must also be evaluated for the feasibility and effectiveness of collecting data to support symptom management. This registry has the potential to contribute to the development of vaccines and treatments and provide insights into the impact of HSV on other conditions.

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Automated Diagnosis through Ontologies and Logical Descriptions

Engineering Effective Decision Support Technologies ◽

10.4018/978-1-4666-4002-3.ch007 ◽

2013 ◽

pp. 117-134

Author(s):

Alejandro Rodríguez-González ◽

Ángel García-Crespo ◽

Ricardo Colomo-Palacios ◽

José Emilio Labra Gayo ◽

Juan Miguel Gómez-Berbís ◽

...

Keyword(s):

Decision Making ◽

Health Systems ◽

Real World ◽

Information Age ◽

Semantic Technologies ◽

Automated Diagnosis ◽

Real World Data ◽

World Data ◽

Degree Of Maturity ◽

Automate Diagnosis

The combination of the burgeoning interest in efficient and reliable Health Systems and the advent of the Information Age represent both a challenge and an opportunity for new paradigms and cutting-edge technologies reaching a certain degree of maturity. Hence, the use of Semantic Technologies for Automated Diagnosis could leverage the potential of current solutions by providing inference-based knowledge and support on decision-making. This paper presents the ADONIS approach, which harnesses the use of ontologies and the underlying logical mechanisms to automate diagnosis and provide significant quality results in its evaluation on real-world data scenarios.

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