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Selected HCMs covered cancer, rare diseases, diabetes, and multiple sclerosis, but delivered incremental gains under two life years. Redirecting spending toward cost-effective essential services could substantially increase health gains and address coverage gaps.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/healthcare/","Healthcare",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/op82-the-opportunity-cost-of-funding-high-cost-medicines-two-case-studies-in-latin-america/445550/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/op82-the-opportunity-cost-of-funding-high-cost-medicines-two-case-studies-in-latin-america/445550.png","ImageObject",300,407,{"name":42,"@type":43},"Emma 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system.",{"name":70,"@type":61,"acceptedAnswer":71},"What do the results imply about reallocating resources away from high-cost medicines?",{"text":72,"@type":64},"Funding the analyzed HCMs instead of the best available alternatives implied substantial additional costs and opportunity costs, while reallocating those resources to cost-effective essential services could increase quality-adjusted life years and help close essential service coverage gaps.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},445550,1790895872,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,101,106,109,114,119,122,126],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & 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\nCatalina Gutiérrez, Santiago Palacio, Ursula Giedion, Pamela Gongora ([pamelago@iadb.org](pamelago@iadb.org)), Lucia Bettati, Natalia Jorgensen, Marcella Distrutti and Dan Ollendorf  \nIntroduction: Like many Latin American countries, Colombia and the Dominican Republic grapple with the financial burden of covering high-cost medicines (HCMs) . While some of these drugs are highly effective, others have reduced clinical effectiveness. Each of these drugs carries an opportunity cost in terms of the health gains lost by allocating these resources elsewhere. We quantified the health opportunity cost of funding HCMs in Colombia and the Dominican Republic.  \nMethods: An identification strategy for HCMs was employed in both countries, based on their significant budgetary impact or high cost per case. This resulted in a shortlist of 10 molecules for Colombia and another 10 for the Dominican Republic. The health opportunity costs were estimated using the standard methodology of net health benefit, with the country-specific cost-effectiveness threshold employed as a proxy for average health production per dollar invested in the health systems of the two cases under study.  \nResults: The selected HCMs included drugs for cancer, rare diseases, diabetes, and multiple sclerosis. The incremental health gains provided by these drugs were less than two life years in perfect health. In Colombia, funding the analyzed HCMs instead of the best available therapeutic alternatives implied an additional cost ofUSD642million for the treatment of 22,155 covered patients. If these resources were allocated to expand services available within the system, the net gain would be 122,507 quality-adjusted life years (QALYs) . In the Dominican Republic, the additional cost was estimated to be USD154 million (14,577 patients), with an estimated opportunity cost of 35,221 QALYs.  \nConclusions: The significant health opportunity costs for two countries with gaps in essential health services highlight the need for policies prioritizing efficient spending. Redirecting resources from the analyzed HCMs to cost-effective essential services could enhance health gains, addressing coverage gaps and advancing progress toward universal health coverage.  \nOP83 Uncovering The Hidden Evidence: Harnessing Perplexity Artificial Intelligence To Revolutionize Grey Literature Retrieval In Health Technology Assessment  \nLisa Tjosvold ([tjosvold@ualberta.ca](tjosvold@ualberta.ca)), Dagmara Reimer and Janice Kung  \nIntroduction: Health technology assessments (HTAs) demand exhaustive evidence retrieval, encompassing both peer-reviewed research and often elusive and poorly indexed grey literature, to guide informed healthcare decisions. This case study investigates Perplexity, a generative artificial intelligence (AI)-powered search engine, asa novel tool for uncovering diverse, often overlooked grey literature sources crucial for comprehensive HTA.  \nMethods: Iterative searches in Perplexity were conducted utilizing a diverse range oftailored prompts to identify evidence sources, including organizational reports, guidelines, epidemiological data, statistical analyses, and white papers. Search results were evaluated for relevance and uniqueness, with comparisons made against traditional retrieval methods. Feedback from participating information professionals provided additional insights into Perplexity’s strengths, limitations, and overall usability. Furthermore, the characteristics of effective prompt engineering strategies were explored and methods for integrating Perplexity into evidence retrieval workflows for HTA were examined.  \nResults: The results obtained through the Perplexity approach revealed several unique sources that were not identified using traditional search methods. Furthermore, the time required to locate and retrieve these distinctive sources was significantly reduced, making","cbCaiqqATS9NuSwc","https://ap.wps.com/l/cbCaiqqATS9NuSwc","pdf",28670,"English","# OP82 The Opportunity Cost Of Funding High-Cost Medicines: Two Case Studies In Latin America\n## Introduction\n## Methods\n## Results\n## Conclusions\n# OP83 Uncovering The Hidden Evidence: Harnessing Perplexity Artificial Intelligence To Revolutionize Grey Literature Retrieval In Health Technology Assessment\n## Introduction\n## Methods\n## Results\n## Conclusions","[{\"question\":\"How were high-cost medicines selected for analysis in the two countries?\",\"answer\":\"They were selected using an identification strategy based on significant budgetary impact or high cost per case, resulting in a shortlist of 10 molecules in Colombia and 10 in the Dominican Republic.\"},{\"question\":\"What method estimated health opportunity costs in OP82?\",\"answer\":\"Health opportunity costs were estimated using net health benefit, applying a country-specific cost-effectiveness threshold as a proxy for average health production per dollar invested in each health system.\"},{\"question\":\"What do the results imply about reallocating resources away from high-cost medicines?\",\"answer\":\"Funding the analyzed HCMs instead of the best available alternatives implied substantial additional costs and opportunity costs, while reallocating those resources to cost-effective essential services could increase quality-adjusted life years and help close essential service coverage gaps.\"}]","OP82 The Opportunity Cost Of Funding High-Cost Medicines - Two Case Studies In Latin America | PDF",1790712374]