دورية أكاديمية
RWE ready for reimbursement? A round up of developments in real-world evidence relating to health technology assessment: part 16.
| العنوان: | RWE ready for reimbursement? A round up of developments in real-world evidence relating to health technology assessment: part 16. |
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| المؤلفون: | Castanon A; Lane Clark & Peacock LLP, London, W1U 1DQ, UK., Tsvetanova A; Lane Clark & Peacock LLP, London, W1U 1DQ, UK., Ramagopalan SV; Lane Clark & Peacock LLP, London, W1U 1DQ, UK.; Centre for Pharmaceutical Medicine Research, King's College London, London, SE1 9NH, UK. |
| المصدر: | Journal of comparative effectiveness research [J Comp Eff Res] 2024 Aug; Vol. 13 (8), pp. e240095. Date of Electronic Publication: 2024 Jul 05. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Becaris Publishing Country of Publication: England NLM ID: 101577308 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2042-6313 (Electronic) Linking ISSN: 20426305 NLM ISO Abbreviation: J Comp Eff Res Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: 2023- : Royston, UK : Becaris Publishing Original Publication: London : Future Medicine |
| مواضيع طبية MeSH: | Technology Assessment, Biomedical*/methods , Technology Assessment, Biomedical*/economics, Humans ; United States ; Comparative Effectiveness Research ; Research Design ; United States Food and Drug Administration ; Models, Economic ; Reimbursement Mechanisms |
| مستخلص: | In this update, we discuss recent US FDA guidance offering more specific guidelines on appropriate study design and analysis to support causal inference for non-interventional studies and the launch of the European Medicines Agency (EMA) and the Heads of Medicines Agencies (HMA) public electronic catalogues. We also highlight an article recommending assessing data quality and suitability prior to protocol finalization and a Journal of the American Medical Association -endorsed framework for using causal language when publishing real-world evidence studies. Finally, we explore the potential of large language models to automate the development of health economic models. |
| References: | JAMA. 2023 Apr 25;329(16):1376-1385. (PMID: 37097356) J Comp Eff Res. 2023 May;12(5):e230008. (PMID: 37052075) J Comp Eff Res. 2022 Nov;11(16):1147-1149. (PMID: 35998008) BMJ. 2024 Feb 12;384:e076460. (PMID: 38346815) J Comp Eff Res. 2023 Jul;12(7):e230092. (PMID: 37345541) J Comp Eff Res. 2022 May;11(7):473-475. (PMID: 35261285) JAMA. 2024 May 7;331(17):1445-1446. (PMID: 38587830) JAMA. 2024 Jun 4;331(21):1845-1853. (PMID: 38722735) Pharmacoepidemiol Drug Saf. 2022 Jul;31(7):717-720. (PMID: 35471704) Pharmacoecon Open. 2024 Mar;8(2):191-203. (PMID: 38340276) J Comp Eff Res. 2024 Aug;13(8):e240091. (PMID: 38850128) |
| فهرسة مساهمة: | Keywords: FDA guidance; causal inference; causal language framework; data quality assessment; health technology assessment; large language models; non-interventional studies; public electronic catalogues; real-world data; real-world evidence; study design |
| تواريخ الأحداث: | Date Created: 20240705 Date Completed: 20240725 Latest Revision: 20240731 |
| رمز التحديث: | 20240731 |
| مُعرف محوري في PubMed: | PMC11284810 |
| DOI: | 10.57264/cer-2024-0095 |
| PMID: | 38967245 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 2042-6313 |
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| DOI: | 10.57264/cer-2024-0095 |