SBIR Phase II: A Blockchain Ecosystem for Encrypting Real World Data and Developing Artificial Intelligence to Optimize Pharmacy Prior Authorization

这个小企业创新研究（SBIR）二期项目的更广泛的影响/商业潜力是显着减少药品效益管理过程中的行政效率低下。具体重点是事先授权处理，其中付款人和处方者必须就医疗必要性达成共识。该项目提供了一种解决方案，可以优化处方授权，并提供比当前健康技术市场上其他可用产品更全面的患者病史，以满足临床授权标准。缺乏对可靠患者病史的有效访问是延迟授权的主要原因，从而导致延迟获得护理。2022年的一项调查显示，93%的医生报告说，事先授权经常或总是会造成护理延误；82%报告延误导致放弃治疗。安全但逐步分散的患者数据传输协议将提高临床决策过程的透明度，并增加患者在事先批准医疗处方期间参与的机会。此外，由于行政成本增加了福利成本，这反过来又增加了获得护理的成本，潜在的商业影响是，降低行政成本的付款人将更有能力以越来越低的成本为更多的优质治疗选择提供更高的报销率。这个SBIR第二期项目提议提供一个具有特定于制药利益领域的智能合约的分布式分类账。由于处理效率低下的原因在于孤立和不完整的患者病史，该协议通过分布式账本技术解决了管理效率低下的问题，该技术支持处方者、支付者和患者之间快速和合规的加密健康数据共享。研究目标包括：1)实现标准自动化，减少行政浪费；2)利用机器学习自动化更简单的案例审查；3)设计一个共享的组织间处理协议，能够适应修订后的临床标准的引入。智能合约将部署到分布式账本基础设施中，以在组织间层面正式确定和执行临床标准以及合同指定的财务规则和精算分析。通过在授权过程中嵌入智能合约，在每个处方生命周期内自动管理更可靠的临床病史，满足合同规定的临床审查质量标准的可用真实世界数据将会增加。历史授权数据将反馈到越来越复杂的案例中，推进授权决策支持的人工智能。预期的结果是改善对临床风险的实时洞察，使付款人能够以更高的精度和灵活性在财务和战略上适应患者的需求。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to significantly reduce administrative inefficiency in pharmaceutical benefit management processing. The specific focus is on prior authorization processing, where payers and prescribers must reach a consensus on medical necessity. The project delivers a solution to optimize prescription authorization and provide more comprehensive patient histories for clinical authorization criteria fulfillment than other available products on the current health technology market. Lack of efficient access to reliable patient histories is the principal reason for delayed authorizations, resulting in delayed care access. A 2022 survey showed 93% of physicians reported that prior authorization often or always creates care delays; 82% reported delays that led to treatment abandonment. A secure yet progressively decentralized patient data transfer protocol would heighten transparency of clinical decision-making processes and also increase opportunities for patient engagement during prior authorization of medical prescriptions. Further, since administrative costs increase the cost of benefits, which in turn increases the cost of care access, the potential commercial impact is that payers who lower administrative costs will be better positioned to offer higher reimbursement rates for a greater range of quality treatment options, at increasingly lower cost.This SBIR Phase II project proposes to deliver a distributed ledger with smart contracts specific to the domain of pharmaceutical benefits. Since the cause of processing inefficiency lies with siloed and incomplete patient histories, this protocol resolves administrative inefficiencies through distributed ledger technology supporting fast and compliant encrypted health data sharing among prescribers, payers, and patients. Research objectives include: 1) automating criteria fulfillment to reduce administrative waste; 2) leveraging machine learning to automate simpler case reviews; and 3) designing a shared interorganizational processing protocol capable of adapting to an introduction of revised clinical standards. Smart contracts will be deployed to a distributed ledger infrastructure to formalize and enforce clinical standards as well as contractually specified financial rules and actuarial analyses at an interorganizational level. With smart contracts embedded in the authorization process to automatically curate more robust clinical histories over each prescription lifecycle, available real world data meeting contractually specified quality standards for clinical review will increase. Historical authorization data will feed back into incrementally complex cases, advancing artificial intelligence for authorization decision support. The expected result is improved real-time insight into clinical risk, affording payers the ability to financially and strategically adapt to patient needs with increasing precision and agility.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.