Overcoming Barriers in Hospital-Based Health Technology Assessment (HB-HTA): International Expert Panel Consensus.

The purpose of this article is to investigate the common facilitators and barriers associated with the implementation of hospital-based health technology assessment (HB-HTA) across diverse hospital settings in seven countries. Through a two-round Delphi study, insights were gathered from a panel of 15 HTA specialists from France, Hungary, Italy, Kazakhstan, Poland, Switzerland, and Ukraine. Experts initially conducted a comprehensive review of the HB-HTA implementation in their respective countries, identifying the barriers and facilitators through descriptive analysis. Subsequently, panel experts ranked these identified barriers and facilitators on a seven-point Likert scale. A median agreement score ≥ 6 and interquartile range (IQR) ≤ 1 was accepted as reaching a consensus. Out of the 12 statements categorized as external and internal barriers and facilitators, the expert panel reached consensus on six statements (two barriers and four facilitators). The external barrier, which achieved consensus, was the lack of the formal recognition of the role of HB-HTA in national or regional legislations. The internal barrier reaching consensus was the limited availability of human resources dedicated to HB-HTA. This qualitative study indicates that HB-HTA still has progress to make before being formally accepted and integrated across most countries, although by building on the facilitating factors we identified there may be an opportunity for the implementation of internationally developed strategies to strengthen HB-HTA practices.

Impact of Early Access Reform on Oncology Innovation in France: Approvals, Patients, and Costs.

BACKGROUND: An ambitious reform of the early access (EA) process was set up in July 2021 in France, aiming to simplify procedures and accelerate access to innovative drugs. OBJECTIVE: This study analyzes the characteristics of oncology drug approvals through the EA process and its impact on real-life data for oncology patients. METHODS: The number and characteristics of EA demands concerning oncology drugs submitted to the National Health Authority (HAS, Haute Autorité de Santé) were reviewed until 31 December 2022. A longitudinal retrospective study on patients treated with an EA oncology drug between 1 January 2019 and 31 December 2022 was also performed using the French nationwide claims database (Systeme National des Données de Santé [SNDS]) to assess the impact of the reform on the number of indications and patients, and the costs. RESULTS: Among 110 published decisions, the HAS granted 88 (80%) EA indications within 70 days of assessment on average, including 46 (52%) in oncology (67% in solid tumors and 33% in hematological malignancies). Approved indications were mostly supported by randomized phase III trials (67%), whereas refused EA relied more on non-randomized (57%) trials. Overall survival was the primary endpoint of 28% of EA approvals versus none of denied EAs. In the SNDS data, the annual number of patients with cancer treated with an EA drug increased from 3137 patients in 2019 to 18,341 in 2022 (+ 484%), whereas the number of indications rose from 12 to 62, mainly in oncohematology (n = 17), lung (n = 12), digestive (n = 9) and breast cancer (n = 9). Reimbursement costs for EA treatments surged from €42 to €526 million (+ 1159%). CONCLUSION: The French EA reform contributed to enabling rapid access to innovations in a wide range of indications for oncology patients. However, the findings highlight ongoing challenges in financial sustainability, warranting continued evaluation and adjustments.

Hospital-based health technology assessment of innovative medical devices: insights from a nationwide survey in France.

OBJECTIVES: To better understand the process of hospital acquisition of innovative medical devices (MDs) and the hospital-based health technology assessment (HB-HTA) pathways in France, an in-depth study based on a quantitative approach is needed. The aim of the present study was to assess through a national survey how HB-HTA is currently implemented in French hospitals and to identify its level of formalization. METHODS: A quantitative online survey was conducted among hospitals performing HB-HTA in France, with a focus on the acquisition of innovative MDs for individual use. The survey, conducted between March and June 2022, was developed by a scientific board composed of members of the French-speaking Society for HB-HTA. RESULTS: Sixty-seven out of 131 surveyed hospitals with HB-HTA activities responded, including 29 university hospitals, 24 nonprofit private hospitals, and 14 local hospitals. Sixty-one respondents (91 percent) reported the existence of a process dedicated to evaluating innovative MDs; of these, 16 declared that their hospitals had a formalized unit with HB-HTA activity. These units were more frequently found in larger hospitals with more than 500 inpatient beds (n = 16, p = 0.0160) and in university hospitals (n = 12, p = 0.0158). No hospital reported any collaboration with HAS, the French national HTA agency. CONCLUSION: A diverse range of HB-HTA organizations with different structural levels exist in France for MD procurement linked to the category of hospitals. The study highlights the need for recognition of HB-HTA activity at the regulatory level in France and for direct collaboration between HTA activities performed at local and national levels.

Are current clinical studies on artificial intelligence-based medical devices comprehensive enough to support a full health technology assessment? A systematic review.

INTRODUCTION: Artificial Intelligence-based Medical Devices (AI-based MDs) are experiencing exponential growth in healthcare. This study aimed to investigate whether current studies assessing AI contain the information required for health technology assessment (HTA) by HTA bodies. METHODS: We conducted a systematic literature review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses methodology to extract articles published between 2016 and 2021 related to the assessment of AI-based MDs. Data extraction focused on study characteristics, technology, algorithms, comparators, and results. AI quality assessment and HTA scores were calculated to evaluate whether the items present in the included studies were concordant with the HTA requirements. We performed a linear regression for the HTA and AI scores with the explanatory variables of the impact factor, publication date, and medical specialty. We conducted a univariate analysis of the HTA score and a multivariate analysis of the AI score with an alpha risk of 5 %. RESULTS: Of 5578 retrieved records, 56 were included. The mean AI quality assessment score was 67 %; 32 % of articles had an AI quality score ≥ 70 %, 50 % had a score between 50 % and 70 %, and 18 % had a score under 50 %. The highest quality scores were observed for the study design (82 %) and optimisation (69 %) categories, whereas the scores were lowest in the clinical practice category (23 %). The mean HTA score was 52 % for all seven domains. 100 % of the studies assessed clinical effectiveness, whereas only 9 % evaluated safety, and 20 % evaluated economic issues. There was a statistically significant relationship between the impact factor and the HTA and AI scores (both p = 0.046). DISCUSSION: Clinical studies on AI-based MDs have limitations and often lack adapted, robust, and complete evidence. High-quality datasets are also required because the output data can only be trusted if the inputs are reliable. The existing assessment frameworks are not specifically designed to assess AI-based MDs. From the perspective of regulatory authorities, we suggest that these frameworks should be adapted to assess the interpretability, explainability, cybersecurity, and safety of ongoing updates. From the perspective of HTA agencies, we highlight that transparency, professional and patient acceptance, ethical issues, and organizational changes are required for the implementation of these devices. Economic assessments of AI should rely on a robust methodology (business impact or health economic models) to provide decision-makers with more reliable evidence. CONCLUSION: Currently, AI studies are insufficient to cover HTA prerequisites. HTA processes also need to be adapted because they do not consider the important specificities of AI-based MDs. Specific HTA workflows and accurate assessment tools should be designed to standardise evaluations, generate reliable evidence, and create confidence.