Implementation of medicinal cannabis in Australia: innovation or upheaval? Perspectives from physicians as key informants, a qualitative analysis
TL;DR: The authors in this paper explored physician perspectives on the prescribing of cannabinoids to patients to gain a deeper understanding of the issues faced by prescriber and public health advisors in the rollout of medicinal cannabis.
Abstract: Objective We sought to explore physician perspectives on the prescribing of cannabinoids to patients to gain a deeper understanding of the issues faced by prescriber and public health advisors in the rollout of medicinal cannabis. Design A thematic qualitative analysis of 21 in-depth interviews was undertaken to explore the narrative on the policy and practice of medicinal cannabis prescribing. The analysis used the Diffusion of Innovations (DoI) theoretical framework to model the conceptualisation of the rollout of medicinal cannabis in the Australian context. Setting Informants from the states and territories of Victoria, New South Wales, Tasmania, Australian Capital Territory, and Queensland in Australia were invited to participate in interviews to explore the policy and practice of medicinal cannabis prescribing. Participants Participants included 21 prescribing and non-prescribing key informants working in the area of neurology, rheumatology, oncology, pain medicine, psychiatry, public health, and general practice. Results There was an agreement among many informants that medicinal cannabis is, indeed, a pharmaceutical innovation. From the analysis of the informant interviews, the factors that facilitate the diffusion of medicinal cannabis into clincal practice include the adoption of appropriate regulation, the use of data to evaluate safety and efficacy, improved prescriber education, and the continuous monitoring of product quality and cost. Most informants asserted the widespread assimilation of medicinal cannabis into practice is impeded by a lack of health system antecedents that are required to facilitate safe, effective, and equitable access to medicinal cannabis as a therapeutic. Conclusions This research highlights the tensions that arise and the factors that influence the rollout of cannabis as an unregistered medicine. Addressing these factors is essential for the safe and effective prescribing in contemporary medical practice. The findings from this research provides important evidence on medicinal cannabis as a therapeutic, and also informs the rollout of potential novel therapeutics in the future.
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TL;DR: In this paper , the authors analysed the TGA SAS-B dataset since inception with respect to age, gender, product type (e.g., oil, flower, etc.), CBD content, indication treated, and prescriber location.
Abstract: A regulatory framework allowing legal access to medicinal cannabis (MC) products has operated in Australia since November 2016. MC prescribing by healthcare practitioners (HCPs) is primarily conducted through the Special Access Scheme - Category B (SAS-B) pathway, through which prescribers apply to the Therapeutic Goods Administration (TGA–the federal regulator) for approval to prescribe a category of product to an individual patient suffering from a specific indication. The dataset collected by the TGA provides a unique opportunity to examine MC prescribing trends over time in the Australian population. Here we analysed this TGA SAS-B dataset since inception with respect to age, gender, product type (e.g., oil, flower, etc.), CBD content, indication treated, and prescriber location. Results are presented descriptively as well as being analysed using non-linear regression models. Relationship between variables were explored via correspondence analyses. Indications were classified with reference to the International Statistical Classification of Diseases and Related Health Problems (10th Revision). As of 31 August 2021, a total of 159,665 SAS-B approvals had been issued for MC products, 82.4% of were since January 2020. Leading indications for approvals were for pain, anxiety, and sleep disorders. Oil products were the most popular product type, while CBD-dominant products (≥98% CBD) accounted for 25.1% of total approvals. Approvals for flower products increased markedly during 2020–2021, as did approvals involving younger age groups (18–31 years old), male patients, and non-CBD dominant products. A disproportionate number of SAS-B MC applications (around 50%) came from HCPs in the state of Queensland. Associations between patient gender and age and/or indication with product type were found. For example, approvals for oil products were commonly associated with approvals for pain. While, overall prescribing increased dramatically over the last 2 years of analysis, stabilization of approval numbers is evident for some indications, such as pain. Current prescribing practices do not always reflect provided TGA guidance documents for MC prescribing. While acknowledging some limitations around the SAS-B dataset, it provides a unique and valuable resource with which to better understand current prescribing practices and utilisation of MC products within Australia.
13 citations
TL;DR: The capture of more highly granulated data, as found in the electronic medical record, patient smartphone applications, and social media provide an opportunity to monitor medicinal cannabis effectiveness and safety across multiple prescribing indications.
Abstract: Medicinal cannabis was legalised in Australia in November 2016. By August 2022, there were 5284 specialist physician and general practitioner (GP) prescribers who submitted Special Access Scheme (SAS) applications to the Therapeutic Goods Administration (TGA) for the provision of medicinal cannabis prescriptions their patients. In this article we examine the impact of the delivery of publicly available clinical guidance documents, provision of education to prescribers, establishment of the TGA online portal, and launching of cannabis clinics on the number of applications approved by the TGA over time. We considered these findings in the context of the need to align the interventions facilitating the prescribing of medicinal cannabis with the establishment of processes to enable the systematic monitoring of patient outcomes. The cumulative number of medicinal cannabis Special Access Scheme-B (SAS-B) prescription approvals from January 2017 to June 2022 was 258,926. SAS-B approvals increased at an average rate of 208.55% p < 0.000, (95% CI 187.25–229.85) per month. Conclusion: There has been a rapid growth in prescribing since the legalisation of medicinal cannabis in Australia and this expansion has not been accompanied by parallel processes for the monitoring of medicinal cannabis. The capture of more highly granulated data, as found in the electronic medical record (EMR), patient smartphone applications, and social media provide an opportunity to monitor medicinal cannabis effectiveness and safety across multiple prescribing indications.
6 citations
TL;DR: In this article , a systematic scoping review was conducted to understand the utility of online user generated text into the use of cannabis as a medicine, and the extent, range, and nature of research that utilises user-generated content to examine to cannabis as medicine.
Abstract: The use of cannabis for medicinal purposes has increased globally over the past decade since patient access to medicinal cannabis has been legislated across jurisdictions in Europe, the United Kingdom, the United States, Canada, and Australia. Yet, evidence relating to the effect of medical cannabis on the management of symptoms for a suite of conditions is only just emerging. Although there is considerable engagement from many stakeholders to add to the evidence base through randomized controlled trials, many gaps in the literature remain. Data from real-world and patient reported sources can provide opportunities to address this evidence deficit. This real-world data can be captured from a variety of sources such as found in routinely collected health care and health services records that include but are not limited to patient generated data from medical, administrative and claims data, patient reported data from surveys, wearable trackers, patient registries, and social media. In this systematic scoping review, we seek to understand the utility of online user generated text into the use of cannabis as a medicine. In this scoping review, we aimed to systematically search published literature to examine the extent, range, and nature of research that utilises user-generated content to examine to cannabis as a medicine. The objective of this methodological review is to synthesise primary research that uses social media discourse and internet search engine queries to answer the following questions: (i) In what way, is online user-generated text used as a data source in the investigation of cannabis as a medicine? (ii) What are the aims, data sources, methods, and research themes of studies using online user-generated text to discuss the medicinal use of cannabis. We conducted a manual search of primary research studies which used online user-generated text as a data source using the MEDLINE, Embase, Web of Science, and Scopus databases in October 2022. Editorials, letters, commentaries, surveys, protocols, and book chapters were excluded from the review. Forty-two studies were included in this review, twenty-two studies used manually labelled data, four studies used existing meta-data (Google trends/geo-location data), two studies used data that was manually coded using crowdsourcing services, and two used automated coding supplied by a social media analytics company, fifteen used computational methods for annotating data. Our review reflects a growing interest in the use of user-generated content for public health surveillance. It also demonstrates the need for the development of a systematic approach for evaluating the quality of social media studies and highlights the utility of automatic processing and computational methods (machine learning technologies) for large social media datasets. This systematic scoping review has shown that user-generated content as a data source for studying cannabis as a medicine provides another means to understand how cannabis is perceived and used in the community. As such, it provides another potential ‘tool’ with which to engage in pharmacovigilance of, not only cannabis as a medicine, but also other novel therapeutics as they enter the market.
3 citations
TL;DR: This paper conducted a systematic review of studies that contained themes of the medicinal use of cannabis and used data from social media and search engine results to examine research approaches and study methodologies that use web-based usergenerated text to study the use of medicinal cannabis as a medicine.
Abstract: Medicinal cannabis is increasingly being used for a variety of physical and mental health conditions. Social media and web-based health platforms provide valuable, real-time, and cost-effective surveillance resources for gleaning insights regarding individuals who use cannabis for medicinal purposes. This is particularly important considering that the evidence for the optimal use of medicinal cannabis is still emerging. Despite the web-based marketing of medicinal cannabis to consumers, currently, there is no robust regulatory framework to measure clinical health benefits or individual experiences of adverse events. In a previous study, we conducted a systematic scoping review of studies that contained themes of the medicinal use of cannabis and used data from social media and search engine results. This study analyzed the methodological approaches and limitations of these studies.We aimed to examine research approaches and study methodologies that use web-based user-generated text to study the use of cannabis as a medicine.We searched MEDLINE, Scopus, Web of Science, and Embase databases for primary studies in the English language from January 1974 to April 2022. Studies were included if they aimed to understand web-based user-generated text related to health conditions where cannabis is used as a medicine or where health was mentioned in general cannabis-related conversations.We included 42 articles in this review. In these articles, Twitter was used 3 times more than other computer-generated sources, including Reddit, web-based forums, GoFundMe, YouTube, and Google Trends. Analytical methods included sentiment assessment, thematic analysis (manual and automatic), social network analysis, and geographic analysis.This study is the first to review techniques used by research on consumer-generated text for understanding cannabis as a medicine. It is increasingly evident that consumer-generated data offer opportunities for a greater understanding of individual behavior and population health outcomes. However, research using these data has some limitations that include difficulties in establishing sample representativeness and a lack of methodological best practices. To address these limitations, deidentified annotated data sources should be made publicly available, researchers should determine the origins of posts (organizations, bots, power users, or ordinary individuals), and powerful analytical techniques should be used.
3 citations
TL;DR: In this paper , the authors provide an overview of various resources that health professionals may use when seeking information about medicinal cannabis in the absence of high-quality evidence and clinical guidelines, and identify examples of international evidence-based resources that support clinical decision-making with medicinal cannabis.
1 citations
References
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Book•
01 Jan 1962
TL;DR: A history of diffusion research can be found in this paper, where the authors present a glossary of developments in the field of Diffusion research and discuss the consequences of these developments.
Abstract: Contents Preface CHAPTER 1. ELEMENTS OF DIFFUSION CHAPTER 2. A HISTORY OF DIFFUSION RESEARCH CHAPTER 3. CONTRIBUTIONS AND CRITICISMS OF DIFFUSION RESEARCH CHAPTER 4. THE GENERATION OF INNOVATIONS CHAPTER 5. THE INNOVATION-DECISION PROCESS CHAPTER 6. ATTRIBUTES OF INNOVATIONS AND THEIR RATE OF ADOPTION CHAPTER 7. INNOVATIVENESS AND ADOPTER CATEGORIES CHAPTER 8. DIFFUSION NETWORKS CHAPTER 9. THE CHANGE AGENT CHAPTER 10. INNOVATION IN ORGANIZATIONS CHAPTER 11. CONSEQUENCES OF INNOVATIONS Glossary Bibliography Name Index Subject Index
38,750 citations
TL;DR: The authors operationalize saturation and make evidence-based recommendations regarding nonprobabilistic sample sizes for interviews and found that saturation occurred within the first twelve interviews, although basic elements for metathemes were present as early as six interviews.
Abstract: Guidelines for determining nonprobabilistic sample sizes are virtually nonexistent. Purposive samples are the most commonly used form of nonprobabilistic sampling, and their size typically relies on the concept of “saturation,” or the point at which no new information or themes are observed in the data. Although the idea of saturation is helpful at the conceptual level, it provides little practical guidance for estimating sample sizes, prior to data collection, necessary for conducting quality research. Using data from a study involving sixty in-depth interviews with women in two West African countries, the authors systematically document the degree of data saturation and variability over the course of thematic analysis. They operationalize saturation and make evidence-based recommendations regarding nonprobabilistic sample sizes for interviews. Based on the data set, they found that saturation occurred within the first twelve interviews, although basic elements for metathemes were present as early as six...
12,951 citations
TL;DR: A parsimonious and evidence-based model for considering the diffusion of innovations in health service organizations, clear knowledge gaps where further research should be focused, and a robust and transferable methodology for systematically reviewing health service policy and management are discussed.
Abstract: This article summarizes an extensive literature review addressing the question, How can we spread and sustain innovations in health service delivery and organization? It considers both content (defining and measuring the diffusion of innovation in organizations) and process (reviewing the literature in a systematic and reproducible way). This article discusses (1) a parsimonious and evidence-based model for considering the diffusion of innovations in health service organizations, (2) clear knowledge gaps where further research should be focused, and (3) a robust and transferable methodology for systematically reviewing health service policy and management. Both the model and the method should be tested more widely in a range of contexts.
6,140 citations
TL;DR: The design and execution of research required to address the additional problems resulting from evaluation of complex interventions, those “made up of various interconnecting parts,” are examined.
Abstract: Randomised controlled trials are widely accepted as the most reliable method of determining effectiveness, but most trials have evaluated the effects of a single intervention such as a drug. Recognition is increasing that other, non-pharmacological interventions should also be rigorously evaluated.1-3 This paper examines the design and execution of research required to address the additional problems resulting from evaluation of complex interventions—that is, those “made up of various interconnecting parts.”4 The issues dealt with are discussed in a longer Medical Research Council paper (www.mrc.ac.uk/complex_packages.html). We focus on randomised trials but believe that this approach could be adapted to other designs when they are more appropriate.
#### Summary points
Complex interventions are those that include several components
The evaluation of complex interventions is difficult because of problems of developing, identifying, documenting, and reproducing the intervention
A phased approach to the development and evaluation of complex interventions is proposed to help researchers define clearly where they are in the research process
Evaluation of complex interventions requires use of qualitative and quantitative evidence
There are specific difficulties in defining, developing, documenting, and reproducing complex interventions that are subject to more variation than a drug. A typical example would be the design of a trial to evaluate the benefits of specialist stroke units. Such a trial would have to consider the expertise of various health professionals as well as investigations, drugs, treatment guidelines, and arrangements for discharge and follow up. Stroke units may also vary in terms of organisation, management, and skill mix. The active components of the stroke unit may be difficult to specify, making it difficult to replicate the intervention. The box gives other examples of complex interventions.
#### Examples of complex interventions
Service delivery and organisation:
Stroke units
Hospital at home
Interventions directed at health professionals' behaviour:
Strategies for implementing guidelines
Computerised decision support
Community interventions:
Community …
3,235 citations
TL;DR: The theory and research on the dissemination of innovations and applications of that theory to health care are examined and at least 7 recommendations for health care executives who want to accelerate the rate of diffusion of innovations within their organizations are suggested.
Abstract: Health care is rich in evidence-based innovations, yet even when such innovations are implemented successfully in one location, they often disseminate slowly-if at all. Diffusion of innovations is a major challenge in all industries including health care. This article examines the theory and research on the dissemination of innovations and suggests applications of that theory to health care. It explores in detail 3 clusters of influence on the rate of diffusion of innovations within an organization: the perceptions of the innovation, the characteristics of the individuals who may adopt the change, and contextual and managerial factors within the organization. This theory makes plausible at least 7 recommendations for health care executives who want to accelerate the rate of diffusion of innovations within their organizations: find sound innovations, find and support "innovators," invest in "early adopters," make early adopter activity observable, trust and enable reinvention, create slack for change, and lead by example.
1,803 citations