Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Objective: To construct a framework and calculation tool to compare the consequences of implementing different payment models for high-cost, one-off potentially curative therapies and enable decision making to ultimately enhance timely patient access to innovative health interventions.
Methods: A framework outlining steps to determine potentially suitable payment models was developed. Based on the framework, a supporting calculation tool operationalised as an Excel-based model was constructed to quantify the associated costs for an average patient during the timeframe of the intended payment agreement, the total budget impact and associated benefits expressed in quality-adjusted life-years for the total expected lifetime of the patient population. To demonstrate the potential of the framework, three case studies were used: onasemnogene abeparvovec (Zolgensma), brexucabtagene autoleucel (Tecartus) and etranacogene dezaparvovec (Hemgenix). A hypothetical case study was used to illustrate the output of the calculation tool.
Results: Part 1 of the framework presents steps for matching a suitable reimbursement and payment model with the disease and treatment characteristics. The reimbursement and payment models are further specified in Part 2. Part 3 guides end users through the setup of a calculation tool with which the financial impact can be calculated of two payment models: a price discount model and an outcome-based spread payment model with a discount. Part 4 concerns the output of the calculation tool, showing how different payment models lead to different financial consequences under three assumptions of longer term effectiveness.
Conclusions: The presented framework provides decision makers with insight into the financial consequences of their chosen payment model under different assumptions. This can aid reimbursement negotiations by clarifying the optimal choice given a therapy's characteristics.
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Source |
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http://dx.doi.org/10.1007/s40273-024-01433-4 | DOI Listing |
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