Solution overview

Every year, the US witnesses around 50 million surgeries, incurring a staggering $32 billion financial burden due to surgical complications. Complications arise in 15% of all surgical procedures, a number that can skyrocket to 50% in high-risk cases. This alarming trend has spurred a nationwide push to enhance preoperative and perioperative support, particularly for high-risk and high-cost patients.

High-risk patients face elevated rates of surgical postoperative complications, mortality, and readmissions, particularly affecting minority, and lower socioeconomic status individuals. Frailty, closely linked to high-risk and low SES categories, strongly predicts perioperative and postoperative complications, increased mortality rates, longer hospital stays, and higher 30/60/90-day readmission rates. These challenges significantly impact the financial performance and hospital quality ratings of healthcare organizations.

One potent strategy is the implementation of specialized preoperative intervention clinics, which have shown success in improving postoperative outcomes. However, identifying high-risk patients preoperatively is challenging due to limited access to timely patient care data and the absence of robust predictive models.

Dss Solutions and Cloudera have forged a strategic partnership to introduce the SDss onto the cutting-edge Cloudera CDP platform. This groundbreaking solution integrates AppliedAI, predictive, and prescriptive analytics models for proactive healthcare management. It leverages locally stored silo data from hospitals and other pertinent healthcare data within a versatile hybrid cloud environment.

Key Highlights of Dss Solutions Surgical Decision Support Solutions (SDss): Utilizing Cloudera's robust Enterprise Data Platform, our solution adeptly handles data, regardless of its location—be it in the cloud or on-premises. This transformative technology delves into comprehensive patient data, constructing predictive models that pinpoint high-risk patients well before surgery, along with actionable prescriptive instructions. Notably, SDss stands alone in the market as the solution capable of empowering hospitals to effectively manage surgical outcomes, minimize mortality and readmission rates, all while enhancing profitability. 

One Platform: SDss is a comprehensive platform that seamlessly integrates data collection, curation, Dss analytical models, real-time analytics, and pre-built integration dashboards, enabling streamlined data flow to various enterprise applications. 

Prebuild Data Curation: SDss comes equipped with pre-built curation models, facilitating seamless connections to diverse assets without any additional setup. It efficiently processes and structures data into a standardized format, making it readily available for utilization by SDss Healthcare's pre-built analytics. 

Prebuild Analytics Models: SDss includes pre-built data visualizations, diagnostics, descriptive, predictive, and prescriptive analytics models that leverage hospital healthcare data to establish a comprehensive knowledge base. 

Bedside Streaming & Analytics: SDss acquires bedside surgical patient data via its prebuilt dashboard and seamlessly streams this data to its analytic modules. This process enables the derivation of patient risk factors and the generation of prescriptive instructions for each step of the surgical procedure. 

Continuum Surgical Insights: Data will flow through the SDss Dashboard at each stage of the surgical process, facilitating the provision of prescriptive instructions and the accumulation of knowledge for future sharing and predictive insights. 

OR/RM Usage Optimization and Planning: Upon identifying a high-risk patient, SDss assesses the hospital's resource needs and adjusts them if the patient's condition deteriorates, ensuring optimal allocation of resources, Operation Room and Resource Management for effective patient care and Hospital Resource Planning.

SDss Solutions-Blueprint: below picture visually demonstrates how the Dss Healthcare Analytics team leverages Cloudera CDP to ingest and curate hospital and healthcare data. This process leads to the creation of predictive and prescriptive analytics models, enabling the prediction of surgical patient risk factors during the surgical evaluation process or pre-op floor. These models also provide prescriptive instructions for each step of the process.