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

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Eddy Nason
Eddy Nason
Eddy Nason
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Philip Jacobs
Philip Jacobs
Philip Jacobs
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Tarry Ahuja
Tarry Ahuja
Tarry Ahuja
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Enkeleida Nika-Fitzgerald
Enkeleida Nika-Fitzgerald
Enkeleida Nika-Fitzgerald
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Abstract

Background Canada 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/Results To 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. Conclusions The 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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... Methodological challenges associated with RWD and RWE include selection bias within international context [34], lower data quality compared to RCTs in various countries including several European countries and Canada [20, 33,36,41]. Standardization issues as well as design and reporting issues of non-RCT studies were also key concerns in European countries [18,23] and limited infrastructure for collecting RWD with data collection issues in Canada for decision-making pertaining to drug pricing and reimbursement in Canada as well as in South American countries [26,41], and concerns about the representativeness of RWD data [20]. ...
... Methodological challenges associated with RWD and RWE include selection bias within international context [34], lower data quality compared to RCTs in various countries including several European countries and Canada [20, 33,36,41]. Standardization issues as well as design and reporting issues of non-RCT studies were also key concerns in European countries [18,23] and limited infrastructure for collecting RWD with data collection issues in Canada for decision-making pertaining to drug pricing and reimbursement in Canada as well as in South American countries [26,41], and concerns about the representativeness of RWD data [20]. ...
... The complementary role of RWE to strengthen evidence as another opportunity was reported within several studies focusing in United Kingdom, Asian countries and several European countries [20, 24,25] while can also serve practical for outcome-based contracting [21]. The collaboration and stakeholder engagement need for RWD utilization improvement is an important aspect [19,20,24,25,36,41,45]. Last, but not least, vital components include implementing effective governance for RWE, establishing comprehensive registries and repositories, and demonstrating commitment to pragmatic trials, ensuring the robustness and reliability of RWE [35], potential usage of RWD and RWE for innovative technologies lacking ample evidence [29]. ...
Real-world data: a comprehensive literature review on the barriers, challenges, and opportunities associated with their inclusion in the health technology assessment process
Article
Full-text available
  • Feb 2024
  • J PHARM PHARM SCI
Objective: This review aimed to assess the current use and acceptance of real-world data (RWD) and real-world evidence (RWE) in health technology assessment (HTA) process. It additionally aimed to discern stakeholders’ viewpoints concerning RWD and RWE in HTA and illuminate the obstacles, difficulties, prospects, and consequences associated with the incorporation of RWD and RWE into the realm of HTA. Methods: A comprehensive PRISMA-based systematic review was performed in July 2022 in PubMed/Medline, Scopus, IDEAS-RePEc, International HTA database, and Centre for Reviews and Dissemination with ad hoc supplementary search in Google Scholar and international organization websites. The review included pre-determined inclusion criteria while the selection of eligible studies, the data extraction process and quality assessment were carried out using standardized and transparent methods. Results: Twenty-nine (n = 29) studies were included in the review out of 2,115 studies identified by the search strategy. In various global contexts, disparities in RWD utilization were evident, with randomized controlled trials (RCTs) serving as the primary evidence source. RWD and RWE played pivotal roles, surpassing relative effectiveness assessments (REAs) and significantly influencing decision-making and cost-effectiveness analyses. Identified challenges impeding RWD integration into HTA encompassed limited local data access, complexities in non-randomized trial design, data quality, privacy, and fragmentation. Addressing these is imperative for optimal RWD utilization. Incorporating RWD/RWE in HTA yields multifaceted advantages, enhancing understanding of treatment efficacy, resource utilization, and cost analysis, particularly via patient registries. RWE complements assessments of advanced therapy medicinal products (ATMPs) and rare diseases. Local data utilization strengthens HTA, bridging gaps when RCT data is lacking. RWD aids medical device decision-making, cancer drug reassessment, and indirect treatment comparisons. Challenges include data availability, stakeholder acceptance, expertise, and privacy. However, standardization, training, collaboration, and guidance can surmount these barriers, fostering enhanced RWD utilization in HTA. Conclusion: This study highlights the intricate global landscape of RWD and RWE acceptance in HTA. Recognizing regional nuances, addressing methodological challenges, and promoting collaboration are pivotal, among others, for leveraging RWD and RWE effectively in healthcare decision-making.
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... Despite the significant efforts by government entities and third-party organizations to harmonize data collection, a recent qualitative study of key stakeholders across Canada on the perspective of RWD noted significant concerns regarding the siloed nature of data assets in the current system [33]. Another study also noted that the varying data access, data governance, and data availability across provinces are barriers to use of RWD for drug funding studies [39]. Notwithstanding the challenges to using RWD, there is a paucity of effort to map and catalogue the data elements that currently exist in each province that can be used for real-world studies in oncology. ...
Mapping Canadian Data Assets to Generate Real-World Evidence : Lessons Learned from Canadian Real-World Evidence for Value of Cancer Drugs (CanREValue) Collaboration’s RWE Data Working Group
Article
Full-text available
  • Mar 2022
  • Curr Oncol
Canadian provinces routinely collect patient-level data for administrative purposes. These real-world data (RWD) can be used to generate real-world evidence (RWE) to inform clinical care and healthcare policy. The CanREValue Collaboration is developing a framework for the use of RWE in cancer drug funding decisions. A Data Working Group (WG) was established to identify data assets across Canada for generating RWE of oncology drugs. The mapping exercise was conducted using an iterative scan with informant surveys and teleconference. Data experts from ten provinces convened for a total of three teleconferences and two in-person meetings from March 2018 to September 2019. Following each meeting, surveys were developed and shared with the data experts which focused on identifying databases and data elements, as well as a feasibility assessment of conducting RWE studies using existing data elements and resources. Survey responses were compiled into an interim data report, which was used for public stakeholder consultation. The feedback from the public consultation was used to update the interim data report. We found that databases required to conduct real-world studies are often held by multiple different data custodians. Ninety-seven databases were identified across Canada. Provinces held on average 9 distinct databases (range: 8–11). An Essential RWD Table was compiled that contains data elements that are necessary, at a minimal, to conduct an RWE study. An Expanded RWD Table that contains a more comprehensive list of potentially relevant data elements was also compiled and the availabilities of these data elements were mapped. While most provinces have data on patient demographics (e.g., age, sex) and cancer-related variables (e.g., morphology, topography), the availability and linkability of data on cancer treatment, clinical characteristics (e.g., morphology and topography), and drug costs vary among provinces. Based on current resources, data availability, and access processes, data experts in most provinces noted that more than 12 months would be required to complete an RWE study. The CanREValue Collaboration’s Data WG identified key data holdings, access considerations, as well as gaps in oncology treatment-specific data. This data catalogue can be used to facilitate future oncology-specific RWE analyses across Canada.
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... These studies need not come from clinical trials, but from real-world data taken from administrative databases maintained by provincial health authorities. 17 In Canada, both Ontario and Alberta collect micro-costing data that would provide the granularity for reporting treatment costs, particularly as they relate to third-line treatments. 18,19 The field of urology should take it upon itself to develop a research agenda that would systematically address the Canadian-specific cost gaps identified through this study. ...
Canadian cost data associated with treating overactive bladder is lacking
Article
  • Aug 2021
Introduction: Cost-effectiveness analysis forms an integral part of the approval process for new medical treatments in Canada, including drug and non-drug technologies. This study's primary objective was to identify peer-reviewed studies that report Canadian-specific cost data for treating overactive bladder (OAB) based on the Canadian Urological Association (CUA) guideline. A secondary objective was to identify studies that report cost data from other healthcare jurisdictions that could be generalizable to the Canadian context. Methods: We conducted a systematic review of the published peer-reviewed literature. We included studies from Organization for Economic Cooperation and Development countries, excluding the U.S., published in English since January 2009. Results: From 165 abstracts identified in our initial search, 18 studies were ultimately included for analysis. This included one Canadian-based study reporting costs in Canadian dollars, all related to second-line treatments. The other studies were primarily from Europe, reporting costs in Euros or British pounds. There were no studies reporting costs for first-line treatments. Gaps in costs for select second-line and third-line treatments recommended by the CUA were also identified. Conclusions: Canadian-specific cost data for OAB treatments published in the peer-reviewed literature is limited to a single study reporting costs for only a few second-line treatments sourced from a single province over 10 years ago. Cost data from other healthcare jurisdictions are available, but the generalizability of costs associated with third-line treatments is questionable.
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... Surveys show that stakeholders are worried about the complexity of modern-day RWE studies and that they do not understand the methodology and, therefore, cannot interpret the validity of a given study. (23,24) The reason that decision makers love RCTs is not only the random treatment assignment and study specific primary data collection, but also the logical clarity of typical parallel group RCTs that make them easy to understand and assess their validity. Substantial efforts are under way to improve transparency, pre-specification, and reproducibility of RWE as pre-requisites to allow reviewers to fully assess a RWE study. ...
Conducting Real-world Evidence Studies on the Clinical Outcomes of Diabetes Treatments
Article
Full-text available
  • Mar 2021
Real-world Evidence (RWE), the understanding of treatment effectiveness in clinical practice generated from longitudinal patient-level data from the routine operation of the healthcare system, is thought to complement evidence on the efficacy of medications from RCTs. RWE studies follow a structured approach: (1) A design layer decides on the study design, which is driven by the study question and refined by a medically informed target population, patient-informed outcomes, and biologically informed effect windows. Imagining the randomized trial we would ideally perform before designing an RWE study in its likeness reduces bias; the new-user active comparator cohort design has proven useful in many RWE studies of diabetes treatments. (2) A measurement layer transforms the longitudinal patient-level data stream into variables that identify the study population, the pre-exposure patient characteristics, the treatment, and the treatment-emergent outcomes. Working with secondary data increases the measurement complexity compared to primary data collection that we find in most RCTs. (3) An analysis layer focuses on the causal treatment effect estimation. Propensity score analyses have gained in popularity to minimize confounding in healthcare database analyses. Well-understood investigator errors, like immortal time bias, adjustment for causal intermediates, or reverse causation, should be avoided. To increase reproducibility of RWE findings, studies require full implementation transparency. This article integrates state-of-the-art knowledge on how to conduct and review RWE studies on diabetes treatments to maximize study validity and ultimately increased confidence in RWE-based decision making.
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... Alguns autores têm se dedicado a entender como o processo de uso das evidências de mundo real está acontecendo. Em países da América do Norte, esse tipo de evidência tem sido utilizada especialmente para avaliação de segurança, manejo da utilização de tecnologias e análises de custo, porém, ainda em menor frequência, para a tomada de decisão sobre incorporação ou aprovação de novas tecnologias (Hampson et al., 2018;Husereau et al., 2019;Malone et al., 2018). No Oriente Médio, há ainda um entendimento de que o uso desses dados para a tomada de decisão é insuficiente, porém há um crescente interesse pelo tema (Akhras et al., 2019). ...
Dados de mundo real no processo de tomada de decisão: uma análise sob a perspectiva do sistema brasileiro de saúde suplementar
Article
Full-text available
  • Dec 2019
The debate about the needs for healthcare resource utilization improvement has been soaring during the last years. As a result, discussions on enhancements of the decision-making process through the leverage of real-world evidence (RWE) has also been fostered. In the 7th Latin American congress of the International Society for Pharmacoeconomics and Outcomes Research, different speakers explored how the management of these data support real life healthcare decisions. Four members representing different segments from the Brazilian Supplementary Healthcare System (SHS) were invited to participate on an expert panel in order to understand their perceptions on this subject. The confidence level on available data ranges from 70% to 90% and information is used on decision-making routine. When the use of real-world evidence to predict decision was considered, panelists reported the absence of an institutional decision matrix, but that existing information is used to build predictive models through the creation of service packages. The prioritization of decision-making today is essentially based on the estimation of costs. However, different situations in which real-world data can guide this process are observed. There was a consensus on a paradigm shift ongoing and that these processes represent a plausible future. The use of RWE is of great importance on decision-making process from the SHS perspective and, above all, in a support of value-based healthcare model which is recommended by Brazilian private agency (ANS) as the strategic pillar to system sustainability.
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Pharmaceutical regulation in 15 European countries review
Article
Full-text available
  • Oct 2016
In the context of pharmaceutical care, policy-makers repeatedly face the challenge of balancing patient access to effective medicines with affordability and rising costs. With the aim of guiding the health policy discourse towards questions that are important to actual and potential patients, this study investigates a broad range of regulatory measures, spanning marketing authorization to generic substitution and resulting price levels in a sample of 16 European health systems (Austria, Belgium, Denmark, England, Finland, France, Germany, Greece, Ireland, Italy, the Netherlands, Poland, Portugal, Scotland, Spain and Sweden). All countries employ a mix of regulatory mechanisms to contain pharmaceutical expenditure and ensure quality and efficiency in pharmaceutical care, albeit with varying configurations and rigour. This variation also influences the extent of publicly financed pharmaceutical costs. Overall, observed differences in pharmaceutical expenditure should be interpreted in conjunction with the differing volume and composition of consumption and price levels, as well as dispensation practices and their impact on measurement of pharmaceutical costs. No definitive evidence has yet been produced on the effects of different cost-containment measures on patient outcomes. Depending on the foremost policy concerns in each country, different levers will have to be used to enable the delivery of appropriate care at affordable prices. World Health Organization 2016 (acting as the host organization for, and secretariat of, the European Observatory on Health Systems and Policies).
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Evaluation Considerations for Secondary Uses of Clinical Data: Principles for an Evidencebased Approach to Policy and Implementation of Secondary Analysis. A Position Paper from the IMIA Technology Assessment & Quality Development in Health Informatics Working Group
Article
Full-text available
  • May 2017
Objectives: To set the scientific context and then suggest principles for an evidence-based approach to secondary uses of clinical data, covering both evaluation of the secondary uses of data and evaluation of health systems and services based upon secondary uses of data. Method: Working Group review of selected literature and policy approaches. Results: We present important considerations in the evaluation of secondary uses of clinical data from the angles of governance and trust, theory, semantics, and policy. We make the case for a multi-level and multi-factorial approach to the evaluation of secondary uses of clinical data and describe a methodological framework for best practice. We emphasise the importance of evaluating the governance of secondary uses of health data in maintaining trust, which is essential for such uses. We also offer examples of the re-use of routine health data to demonstrate how it can support evaluation of clinical performance and optimize health IT system design. Conclusions: Great expectations are resting upon "Big Data" and innovative analytics. However, to build and maintain public trust, improve data reliability, and assure the validity of analytic inferences, there must be independent and transparent evaluation. A mature and evidence-based approach needs not merely data science, but must be guided by the broader concerns of applied health informatics.
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Worldwide inequality in production of systematic reviews
Article
Full-text available
  • Feb 2016
Background: Investment in science is vital for the development and well-being of societies. This study aims to assess the scientific productivity of countries by quantifying their publication of systematic reviews taking the gross national income per capita (GNIPC) into account. Methods: Medline and ISI Web of Science were searched for systematic reviews published between 1st January 2006 and 31st December 2010. The productivity of each country was quantified by exploring the authors' affiliation. The GNIPC was used according to the World Bank Report. Concentration index (CI) was calculated as the index of inequality. Results: CI of percentage of systematic reviews as a function of percentage of countries ranked by GNIPC was 0.82 which indicates inequality in production of systematic reviews in pro rich countries. Countries with high income produced 206.23 times more systematic reviews than low income countries, while this ratio for lower middle and upper middle countries was 9.67 and 12.97, respectively. The highest concentration index was observed in clinical sciences (0.76) and the lowest in public health (0.61). Conclusion: This study demonstrates a significant gap between industrialized and nonindustrialized countries in the production of systematic reviews. Addressing this gap needs tremendous national and international efforts.
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The Population Health Model (POHEM): An overview of rationale, methods and applications
Article
Full-text available
  • Sep 2015
The POpulation HEalth Model (POHEM) is a health microsimulation model that was developed at Statistics Canada in the early 1990s. POHEM draws together rich multivariate data from a wide range of sources to simulate the lifecycle of the Canadian population, specifically focusing on aspects of health. The model dynamically simulates individuals' disease states, risk factors, and health determinants, in order to describe and project health outcomes, including disease incidence, prevalence, life expectancy, health-adjusted life expectancy, quality of life, and healthcare costs. Additionally, POHEM was conceptualized and built with the ability to assess the impact of policy and program interventions, not limited to those taking place in the healthcare system, on the health status of Canadians. Internationally, POHEM and other microsimulation models have been used to inform clinical guidelines and health policies in relation to complex health and health system problems. This paper provides a high-level overview of the rationale, methodology, and applications of POHEM. Applications of POHEM to cardiovascular disease, physical activity, cancer, osteoarthritis, and neurological diseases are highlighted.
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Administrative health data in Canada: Lessons from history
Article
Full-text available
  • Dec 2015
  • BMC MED INFORM DECIS
Health decision-making requires evidence from high-quality data. As one example, the Discharge Abstract Database (DAD) compiles data from the majority of Canadian hospitals to form one of the most comprehensive and highly regarded administrative health databases available for health research, internationally. However, despite the success of this and other administrative health data resources, little is known about their history or the factors that have led to their success. The purpose of this paper is to provide an historical overview of Canadian administrative health data for health research to contribute to the institutional memory of this field. We conducted a qualitative content analysis of approximately 20 key sources to construct an historical narrative of administrative health data in Canada. Specifically, we searched for content related to key events, individuals, challenges, and successes in this field over time. In Canada, administrative health data for health research has developed in tangent with provincial research centres. Interestingly, the lessons learned from this history align with the original recommendations of the 1964 Royal Commission on Health Services: (1) standardization, and (2) centralization of data resources, that is (3) facilitated through governmental financial support. The overview history provided here illustrates the need for longstanding partnerships between government and academia, for classification, terminology and standardization are time-consuming and ever-evolving processes. This paper will be of interest to those who work with administrative health data, and also for countries that are looking to build or improve upon their use of administrative health data for decision-making.
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Challenges of informed consent for pragmatic trials
Article
  • May 2017
The Innovative Medicines Initiative’s (IMI) GetReal consortium aims to develop strategies to incorporate real world evidence earlier into the drug life cycle to better inform health care decision-makers on the comparative risks and benefits of new drugs. Pragmatic trials are currently explored as a means to generate such evidence in routine care settings. The traditional informed consent model for randomized clinical trials has been argued to pose substantial hurdles to the practicability of pragmatic trials: it would lead to recruitment difficulties, reduced generalizability of the results and selection bias. The present paper analyzes these challenges and discusses four proposed alternative informed consent models: integrated consent, targeted consent, broadcast consent and a waiver of consent. These alternative consent models each aim at overcoming operational and methodological challenges, while still providing patients all the relevant information they need in order to make informed decisions. Each consent model, however, relies on different attitudes towards the principle of respect for persons and the related duty to inform patients, and represents different views on whether the common good demands moral duties from patients. Such normative consequences of modifying consent requirements should be at least acknowledged, and ought to be assessed in light of the validity of empirical claims.
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CLINICAL EPIDEMIOLOGY
Article
  • Feb 1969
  • AM J EPIDEMIOL
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LOCAL HEALTH TECHNOLOGY ASSESSMENT IN CANADA: CURRENT STATE AND NEXT STEPS
Article
  • Aug 2016
Objectives: Canada has witnessed expansion of the health technology assessment (HTA) infrastructure in the last 25 years. Local HTA entities at the hospital or regional level are emerging to assist decision makers in the acquisition, implementation, maintenance, and disinvestment of healthcare technologies. There is a need to facilitate collaboration and exchange of expertise and knowledge between these entities regarding the role of local HTA in Canada. Methods: In November 2013, the pan-Canadian Collaborative hosted a symposium, Hospital/Regional HTA: Local Evidence-based Decisions for Health Care Sustainability, bringing together over 60 HTA producers, researchers, stakeholders, and manufacturers involved in local HTA across Canada. The objective was to showcase the diversity of local HTA in Canada, while highlighting common gaps to be addressed. Results: The Symposium focused on current practices in local HTA in Canada to support informed decision making, and opportunities for information sharing and provide equal access to timely evidence-based information to decision makers. The main themes included assessment of evidence for local HTA, contextualization, stakeholder engagement in local HTA, knowledge translation and impact of recommendations, and challenges and opportunities for local HTA. Conclusions: Local HTA in Canada complements HTAs conducted at the provincial and federal levels to improve the efficient and effective health service delivery in institutions or regions faced with limited resources. Some challenges faced by local HTA producers to influence hospital policies and clinical practice involve the engagement of healthcare professionals and potential lack of training and support necessary for the introduction of a new technology.
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