| 摘要: | AI 醫療產品公司在進入市場時，多數面臨無法透過與醫療機構實際合作，創造收益流之困境。醫療機構於評估是否採納新技術時，將考量到實際院內使用需求及保險機構給付率之不確定性，這使得醫療機構傾向沿用原有之臨床治療流程，而非效益更高之技術，公司在無法建立與醫療機構合作的情況下，將更難以取得更多真實世界中的臨床證據，優化演算法，最終將無法順利將更有價值之檢測或治療方法帶給有需要之人。為因應此雙重壓力，美國 NTAP 制度成為一項對政府監管機構、醫療機構及 AI 醫療產品公司皆有利之制度，有助於推動 AI 在醫療領域的應用。然而，目前針對 NTAP 如何提升 AI 醫療產品進入市場之可行性，尚未有完整之論述與探討，因此如何讓持續投入此巨大市場之公司得以評估是否將NTAP納為公司策略之一為一重要課題。
基於上述背景，本研究採用多重個案研究法進行分析，首先針對過往美國保險支付制度及 AI 醫療產品之進入市場困境進行文獻探討，了解其運作機制與進入市場之可能影響因素，最終篩選出 5 家公司，運用次級資料針對其既有商業模式進行多重個案分析，以需求性、可行性及存續性，解析AI 醫療產品在制定進入市場策略上之異同，並進一步探討 NTAP 於其中扮演之角色 ，以期作為未來 AI 醫療產品公司於評估進入市場策略之參考。
透過本研究分析後發現所得結論如下：目前AI 醫療產品公司多採取 B2B2C 作為主要商業模式，其中發現案例公司為提升商業可行性，有 3 種不同進入市場路徑，分別為: (1) 研發單一適應症之檢測 AI 軟體，結合現有硬體進行策略合作；(2) 串連多種適應症之檢測 AI 軟體，整合至醫院內部資訊系統；(3) 同時發展單一適應症之硬體及AI 軟體，提供完整創新治療。針對 NTAP 用於提升商業模式存續性之關鍵角色，本研究觀察到 AI 醫療產品公司於初期進入市場階段，公司僅有零星合作之醫療機構時，即於取得上市許可後第 2 年主動申請取得 NTAP，推測美國之 AI 醫療產品公司確實期待 NTAP 能幫助提升臨床機構合作機會；在結束 NTAP 授權後，公司的確獲得私人與公共保險之合作，並成功進入其他國家市場如英國、日本等地之醫療機構。
故此，本研究建議AI 醫療產品公司未來進入市場策略方向之重點在於：(1) 若於市場上具足夠創新性，可申請 NTAP 以提升與美國臨床機構合作、取得真實世界臨床效益評估之機會；(2) 與大型知名醫療器材廠商建立策略合作，透過此種類型公司原先合作之機構，取得與臨床機構之合作機會；(3) 透過研發串接、整合或擴充軟硬體應用於更多種適應症，以因應臨床機構更多元之服務需求。
Upon entering the market, AI healthcare product companies often face challenges in revenue generation without establishing practical collaborations with healthcare institutions. When evaluating the adoption of new technologies, healthcare institutions consider the uncertainty of in-house demand and insurance reimbursement rates. This inclination leads healthcare institutions to adhere to existing clinical treatment processes rather than embracing potentially more effective technologies. Without meaningful collaborations, companies struggle to acquire real-world clinical evidence, optimize algorithms, and ultimately encounter difficulties introducing more valuable diagnostics or treatments to those in need. In response to these challenges, the U.S. New Technology Add-On Payment (NTAP) system emerges as a beneficial framework for government regulatory bodies, healthcare institutions, and AI healthcare product companies, facilitating the advancement of AI applications in the medical field. However, a comprehensive exploration of how NTAP enhances the feasibility of AI healthcare product entry into the market remains lacking, creating a gap for companies actively investing in this substantial market to evaluate its inclusion as a strategic component.
To address this gap, this study employs a multiple case study approach. It begins with a literature review of the historical U.S. insurance payment system and the challenges AI healthcare products face when entering the market, aiming to comprehend their operational mechanisms and potential influencing factors. Five companies are then selected for in-depth analysis, utilizing secondary data to scrutinize their existing business models. The objective is to comprehend the differences and similarities in formulating market entry strategies based on the considerations of desirability, feasibility, and viability. Furthermore, the study explores the role of NTAP within this context, providing insights for future AI healthcare product companies when assessing market entry strategies.
Based on the analysis conducted in this study, the following conclusions were drawn: Presently, AI healthcare product companies predominantly adopt a B2B2C business model. Within this context, to enhance business feasibility, the company employs three distinct market entry pathways, including developing single-indication diagnostic AI software, collaborating with existing hardware through strategic partnerships, integrating multi-indication diagnostic AI software into hospital information systems, and simultaneously developing hardware and AI software for a specific indication to offer a comprehensive innovative treatment. Regarding the pivotal role of NTAP in enhancing the sustainability of the business model, it was observed that in the initial market entry phase, AI healthcare product companies, with sporadic collaborations with medical institutions, obtained NTAP in the second year after obtaining market clearance. It is speculated that US-based AI healthcare product companies anticipate NTAP to enhance opportunities for collaboration with clinical institutions. After the conclusion of NTAP authorization, companies indeed secured collaborations with private and public insurance and successfully entered healthcare institutions in other countries such as the UK and Japan.
Therefore, this study suggests key strategic directions for AI healthcare product companies in future market entry: (1) If the market presence is sufficiently innovative, consider applying for NTAP to enhance collaboration with US clinical institutions and gain opportunities for real-world clinical effectiveness assessments; (2) Establish strategic partnerships with large, well-known medical equipment manufacturers, leveraging existing collaborations of such companies to gain opportunities for collaboration with clinical institutions; (3) Through research and development integration, expand or enhance the application of software and hardware for a broader range of indications to meet the diverse service needs of clinical institutions. |
