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Background & Problem Summary

Organizations choose to focus on joint replacement for these reasons:

  • Rapid growth and increasing overutilization: Total hip replacement (THR) and total knee replacement (TKR) are two of the most commonly performed and fastest growing surgical procedures in the U.S. Studies suggest that total joint replacement (TJR) may be performed inappropriately in approximately 30% of cases.
  • Significant variation in care cost and quality: Treatment costs vary substantially depending on complications, post-discharge care, and geographic area. To address this variation, CMS has launched a bundled payment model that requires eligible hospitals to be accountable for costs and quality of care of Medicare total joint replacement patients from day of surgery to 90 days after surgery.
  • Readmissions and penalties linked to complications:  Preventable conditions such as venous thromboembolism (VTE) and surgical site infection (SSI), account for more than 40% of all complications following TJR, resulting in unplanned readmissions and increased utilization of services.

Accelerator Overview

Brings together data from disparate sources to help teams extrapolate meaningful insight—supporting safety and better care before, during, and after joint-replacement surgery

The Joint Replacement Analytic Accelerator supports a disciplined, data-driven approach to surgical evaluation and care, helping to drive and sustain significant improvement in clinical and financial outcomes. Typical implementations focus on ensuring medical necessity for surgery, readmission risk stratification, adherence to best-practice standards of care, and care transitions—areas where getting it right is especially meaningful to improve quality and cost.

Benefits and Features

Access an at-a-glance, near real-time view of quality of care and its impact.

The application dashboard visualizes outcome and process metrics in an easy-to-consume, one-page summary. One result? You can see trends as they develop—and take timely action to address issues.

Start faster with meaningful, scalable clinical definitions.

The cohorts, definitions, and process measures that come with the accelerator are clinically relevant, standard, and meaningful across domains, ready for customization or adoption in your organization. Instead of spending months debating the definition of LOS or the parameters for average glucose, your teams can quickly begin improvement work. What’s more, the work is scalable: you have only one source of truth to maintain as definitions change.

Focus your team on what matters most.

Outcome metrics typically include complication rate, readmission rate, LOS, and cost per case. Typical process metrics include documentation of medical necessity and compliance with care protocols related to blood utilization, pain management, glycemic control, VTE prophylaxis, and early mobility. The result? Your team understands the priorities and can help solve problems that stand in the way of improvement.

Do more than monitor: understand.

Detailed analytics of each bundle provide dynamic data exploration, real-time filtering, and drill-down to patient-level detail. A Comorbidities tab enriches understanding of the patient and the appropriateness of the care they receive. The application also provides export or print capability for patient list, metric performance, etc. so you can share and follow up.

Compare and contrast.

A Compare tab lets you review patient and care variables—demographics, variation in care, performance in different units, etc.—to determine what’s working and not working to improve outcomes. This feature also allows you to gauge the ROI of improvement work in particular areas: what could you achieve if every unit and provider standardized to match your best performance?

Continually refine your ability to recognize risk and improve treatment.

For organizations implementing the Joint Replacement Analytic Accelerator with machine learning and closed-loop capabilities, AI will drive: stratified risk based on population-specific variables and optimized care process algorithms, readmission prediction for your patients

Use Cases

  • The Chief Medical Officer in a large hospital system observes that the post-joint-surgery readmission rate has been creeping upward over the previous three quarters. What are the drivers of this disturbing trend? He uses the Joint Replacement Analytic Accelerator to explore performance and guide a plan to intervene.
  • The Head of Orthopedic Surgery understands that efforts to lower the LOS of joint-replacement patients can sometimes increase readmission rate. Would pre-habilitation efforts be warranted? As improvement efforts are implemented, she and colleagues use the application to monitor these outcomes, understand the factors that affect these results, and tune local processes and interventions for best results.
  • A guidance team is trying to identify their next area of focus for continuous improvement of their surgical outcomes. They use the application to gauge the potential impact of reducing unwarranted variation in surgical supply usage. What is the best-performing unit using—and what might widespread adoption of their supplies mean for the organization?
Key Measures

Complication rate
Readmission rate
Length of Stay (LOS) and OR case time
Cost per case
Discharge to home with home health or self care
Patient satisfaction
HRQOL