Value-based care (VBC) organizations – and especially Accountable Care Organizations – rely on strategies that shift care from hospitals to skilled nursing facilities to manage costs and still ensure high quality, effective care. 

To provide affordable, sustainable, high-caliber, patient-centric care, SNFs increasingly need VBC strategies and advanced technology. 

Improving care quality in SNFs with technology

Care quality metrics are essential for achieving VBC success, and many VBC payment structures center around achieving quality metrics for a patient population. Advanced analytics are a critical success factor to provide the best solution to accurately measure and report on quality scores.

Analytics tools allow facilities to customize data that aligns with distinct organizational metrics and regulatory demands, allowing for flexibility to report on metrics specific to a region or patient cohort. These metrics offer actionable recommendations, allowing users to delve deeper into any metric and data source, fostering collaborative discussions and strategic decision-making.

To generate actionable insights that can help improve care from analytics software, providers need high-value data. That’s where most organizations run into significant challenges. 

Data for SNF patients can come from a variety of disparate sources, including: 

  • Primary care providers
  • Specialists
  • Hospital facilities
  • Ambulatory surgical centers
  • Lab or imaging centers
  • Pharmacies

When information from these sources is inaccessible in a patient’s record, it can seriously impact care quality. In some cases, those gaps can result in harmful (and avoidable) outcomes. Because datasets have different formats, file names and programming languages, integration becomes difficult or impossible. Application programming interfaces (APIs) are a step in the right direction, but even they can’t create seamless interoperability between siloed systems.

More advanced platforms can now normalize patient-specific data within a single “data lake” and enrich it to offer insights. This ensures everyone can access all the necessary information to achieve patient outcomes. That provides analytics with near-real-time data and predictive and prescriptive insights, offering transparency, efficiency and a path forward to improve outcomes. 

Decreasing total cost of care through predictive technology 

To curb adverse outcomes and reduce expenses, SNFs are incorporating predictive technology. They can leverage volumes of patient data insights to reduce more costly care events and the risk of post-discharge readmissions. AI models and algorithms have become central to advanced, preventive and early intervention-focused VBC. These technologies review information from past adverse events and predict the triggers that can lead to future ones. Over time, the software can further enhance its predictive accuracy as it analyzes more data.

For example, machine learning models in analytics software can predict the risk of post-surgical complications for patients with a comorbid chronic condition like diabetes who enters a SNF. Software can quickly sort these patients into a cohort so care teams know who needs additional surveillance or monitoring. Providers can take proactive steps that reduce the risk of adverse events, leading to better outcomes. 

Building a successful VBC network

Analytics technology offers SNFs valuable tools to foster efficient and cost-effective referral networks. These facilities are at the forefront of providing specialized care to patients with complex medical needs. For those participating in VBC programs, having a referral network of providers and facilities who are similarly focused on cost and quality improvements will improve their ability to achieve clinical and financial goals.

Analytics software specifically built for a VBC future enables these types of analyses. Organizations can evaluate and benchmark multiple cost, quality and patient satisfaction metrics to build a high-performing referral network. This ensures smooth transitions in care from acute to post-acute care environments, and after discharge.

Creating a patient-centered care facility

Putting patients at the center of their care is the goal of VBC, and SNFs play an essential role in reaching this goal. Data analytics and predictive modeling can help identify areas for improvement, enabling facilities to continually fine-tune processes and care plans. It’s a pivotal shift from reactive to proactive care, and a profound reshaping of long-term care delivery. 

Technology empowers VBC-focused care facilities to forge a sustainable path toward better outcomes and resource optimization while prioritizing timely interventions that effectively curtail acute events. Advancements in analytics capabilities and predictive tools facilitate informed decision-making based on quantitative insights, helping reach the ultimate goal of enhancing patient outcomes and experiences.

David L. Morris is Executive Vice President and Chief Commercial Officer at Cedar Gate Technologies, managing over 50M covered lives, and supporting over 118,000 providers, 178,000 self-funded employers, 300 health delivery systems, 330 IPAs and 80 MSOs. He has over 30 years of operational and executive leadership experience at blue chip companies throughout the healthcare ecosystem.

The opinions expressed in McKnight’s Long-Term Care News guest submissions are the author’s and are not necessarily those of McKnight’s Long-Term Care News or its editors.

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