Integration of real-world evidence from different data sources in health technology assessment.

Real-world evidence (RWE) is being increasingly used by a wide range of stakeholders involved in the therapeutic product lifecycle but remains underutilized in the health technology assessment (HTA) process. RWE aims to fill the current evidence gaps, reduce the uncertainty around the benefits of medical technologies, and better understand the long-term impact of health technologies in real-world conditions. Despite the minimal use of RWE in some elements of HTA, there has been a larger push to further utilize RWE in the HTA processes. HTA bodies, as other stakeholders, work towards developing more robust means to leverage RWE from various data sources in the HTA processes. However, these agencies need to overcome important challenges before the broader incorporation of RWE into their routine practice. This paper aims to explore the extensive integration of RWE utilizing diverse sources of RWD. We discuss the utilization of RWE in HTA processes, considering aspects such as when, where, and how RWE can be effectively applied. Additionally, we seek the potential challenges and barriers associated with the utilization of different data sources.

Validation of a Design Architecture to Deliver Health Management and Behavior Change Evidence at Scale.

Forty-four percent of Canadians over the age of 20 have a non-communicable disease (NCD). Millions of Canadians are at risk of developing the complications of NCDs; millions have already experienced those complications. Fortunately, the evidence base for NCD prevention and behavior change is large and growing and digital technologies can deliver them at scale and with high fidelity. However, the current model of in-person primary care is not designed nor capable of operationalizing that evidence. New developments in artificial intelligence that can predict who will develop NCD or the complications of NCD are increasingly available, making the challenge of delivering disease prevention even more urgent. This paper presents findings from stakeholder engagement on a design architecture to address three initial barriers to large-scale deployment of health management and behavior change evidence: 1) the challenges of regulating mobile health apps, 2) the challenge of creating a value-based rationale for payers to invest in deploying mobile health apps at scale, and 3) the high cost of customer acquisition for delivering mobile health apps to those at risk.

Conditional Funding Recommendations for Drugs in Canada: A Cross-Sectional Analysis.

BACKGROUND AND OBJECTIVE: Before listing by drug plans, new drugs that receive regulatory bodies' approval are assessed by the Health Technology Assessment agencies, including the Canadian Agency for Drugs and Technologies in Health (CADTH). Considering the impact of CADTH recommendations on payers' listing decisions, the growing number of high-cost drugs, and conditional listings, conditional recommendations have increasingly been of interest to the users of CADTH recommendations. This study aims to review the conditional reimbursement recommendations issued by CADTH and explores the reasons for those recommendations. METHODS: All final drug reimbursement recommendations posted on the CADTH website since 1 January, 2003 were reviewed. Recommendations were included if accepted for review by 1 May, 2021 and completed before 1 January, 2022. The complete records excluding 'requests for advice' were categorized into 'reimburse,' 'do not reimburse,' and 'reimburse with criteria/condition(s)'. The identified variables were extracted and analyzed descriptively. RESULTS: Of the 889 submissions, 785 (88.6%) completed recommendations were considered relevant to the study purpose. Of 750 recommendations, excluding 35 (4.5%) 'requests for advice,' 500 (66.6%) were 'reimburse with criteria/condition(s)'. 'Clinical criteria' at 481 (96.2%), 'cost-effectiveness improvement to an acceptable level' at 132 (26.4%), and 'the treatment cost not to exceed the cost of the alternative option(s)' at 118 (23.6%) were the most frequently reported conditions. The most frequent reasons for conditional reimbursement were 'clinical benefit and economic evaluation' at 304 (60.8%). Of conditional recommendations, 468 (93.6%) included more than one reason. CONCLUSIONS: CADTH has facilitated patient access to innovative drugs even with limited evidence by conditional recommendations. The clinical criteria are the cornerstone of conditional recommendations. CADTH has developed the assessment process over time.

Canadian trends in spending on liver hospitalizations and transplants: 2004-2020.

Background: The incidence and prevalence of liver disease are increasing and contribute to significant morbidity and mortality. In Canada, more than 3 million people live with liver diseases, accounting for approximately 2% of all hospitalizations. However, it remains unclear how much liver hospitalizations cost the Canadian health care system. Thus, this study estimates the cost of liver-related hospitalization across Canada. Methods: We conducted a population-based, retrospective study using acute inpatient admission data for liver-related hospitalizations obtained from the Canadian Institute for Health Information. We calculated the total and the average nominal spending for liver hospitalizations nationally from April 1, 2004, to March 31, 2020, based on fiscal year (FY). In addition, we stratified the average liver hospitalization spending based on age and sex group. Results: Canada spent $947 million on liver-related hospitalizations in FY2019, a 145% growth in spending from FY2004. The average liver disease-related hospitalization was estimated to be $17,506 in FY2019. Within the sub-group analysis, the age group <30 showed the highest average cost per hospitalization at $21,776; however, there was no significant difference in cost between males and females. Across the different provinces in FY2019, Alberta experienced the highest average spending per hospitalization at $23,150, whereas Ontario had the lowest spending at $15,712. Conclusions: Liver-related hospitalizations are associated with high spending that is increasing nationally with variations across provinces and territories. Our results are of great use for economic evaluations of novel interventions in the future.

Artificial intelligence in outcomes research: a systematic scoping review.

Introduction: Despite the number of systematic reviews of how artificial intelligence is being used in different areas of medicine, there is no study on the scope of artificial intelligence methods used in outcomes research, the cornerstone of health technology assessment (HTA). This systematic scoping review aims to systematically capture the scope of artificial intelligence methods used in outcomes research to enhance decision-makers' knowledge and broaden perspectives for health technology assessment and adoption.Areas covered: The review identified 370 studies, consisted of artificial intelligence methods applied to adult patients who underwent any health/medical intervention and reported therapeutic, preventive, or prognostic outcomes. Artificial intelligence was mainly used for the prediction/prognosis of more frequently reported outcomes, efficacy/effectiveness, among morbidity outcomes. The predictive analysis was common in neoplastic disorders. Neural networks algorithm was predominantly found in surgical method studies, but a mixture of artificial intelligence algorithms was applied to the studies with the rest of the interventions.Expert opinion: There are certain gaps in artificial intelligence applications used in outcomes research across therapeutic areas and further considerations are needed by decision-makers before incorporating artificial intelligence usage into HTA decision-making processes.

Opium consumption in men and diabetes mellitus in women are the most important risk factors of premature coronary artery disease in Iran.

We performed this study to compare of CAD risk factors in young male and female in Iran. In an analytic cross-sectional study, two groups of patients were evaluated with and without Coronary artery disease. The result of study suggests that there is a relationship between CAD and diabetes mellitus, increasing level of LDL and lipoprotein A in women, While CAD in men had more relation with smoking and opium use. High prevalence and uncontrolled diabetes mellitus in females and relatively high prevalence of opium consumption in males result in different premature CAD patterns.