Background

An innovative, data-driven, cost-effective clinical model was deployed to manage our surgical bariatric service line. This foundational change was designed to assess if our surgical providers and staff could safely and effectively migrate from our current evidence-based service line model to a purely value-based and data-driven service.

Methods

An extensive analysis of ten years of historical and real-time clinical bariatric data using two outcome engines [TransMed CS & Providence VOA] was used to perform a 'per-resource breakdown' of each in-hospital care episode and to re-design them into dynamic, real-time, data-driven care-components delivery of care protocols. Once implemented, cost and outcome data were compared and validated across our healthcare system during two different time frames [T1 pre-Covid,T2 post-Covid]. Our measurements were only interrupted during the height of the COVID-19 pandemic as we experienced significant disruption of our supply chain and clinical staff.

Results

For T1, upon implementation, our Cost Per Case [CPC] dropped 37% from our system average [SA]. At 24 months, CPC was maintained at 36% below SA. For T2, CPC was 44% below the system average over 12 months [2023 fiscal year], resulting in impressive cost savings. Other standard clinical outcome indices showed no deterioration, while our average LOS [Length of Stay] increased to 1.53 vs a SA of 1.35.

Conclusions

These analytics demonstrate that data-driven clinical protocols can dramatically reduce surgical performance costs in this service line and lead to a value-based, sustainable healthcare model. In contrast, some standard outcome data analytics benchmarks may need reassessment.