Value-based assessment of robotic pancreas and liver surgery

基于价值的机器人胰腺和肝脏手术评估

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Abstract

Current healthcare economic evaluations are based only on the perspective of a single stakeholder to the healthcare delivery process. A true value-based decision incorporates all of the outcomes that could be impacted by a single episode of surgical care. We define the value proposition for robotic surgery using a stakeholder model incorporating the interests of all groups participating in the provision of healthcare services: patients, surgeons, hospitals and payers. One of the developing and expanding fields that could benefit the most from a complete value-based analysis is robotic hepatopancreaticobiliary (HPB) surgery. While initial robot purchasing costs are high, the benefits over laparoscopic surgery are considerable. Performing a literature search we found a total of 18 economic evaluations for robotic HPB surgery. We found a lack of evaluations that were carried out from a perspective that incorporates all of the impacts of a single episode of surgical care and that included a comprehensive hospital cost assessment. For distal pancreatectomies, the two most thorough examinations came to conflicting results regarding total cost savings compared to laparoscopic approaches. The most thorough pancreaticoduodenectomy evaluation found non-significant savings for total hospital costs. Robotic hepatectomies showed no cost savings over laparoscopic and only modest savings over open techniques. Lastly, robotic cholecystectomies were found to be more expensive than the gold-standard laparoscopic approach. Existing cost accounting data associated with robotic HPB surgery is incomplete and unlikely to reflect the state of this field in the future. Current data combines the learning curves for new surgical procedures being undertaken by HPB surgeons with costs derived from a market dominated by a single supplier of robotic instruments. As a result, the value proposition for stakeholders in this process cannot be defined. In order to solve this problem, future studies must incorporate (I) quality of life, survival, and return to independent function alongside data such as (II) intent-to-treat analysis of minimally-invasive surgery accounting for conversions to open, (III) surgeon and institution experience and operative time as surrogates for the learning curve; and (IV) amortization and maintenance costs as well as direct costs of disposables and instruments.

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