Proponents of technology and data analytics are quick to point out the potential cost-savings of a tech-based approach to patient care. But a few hospitals are backing up those claims with real quantitative data.
A third-party evaluation of 10 hospital systems that were awarded funding by the Centers for Medicare & Medicaid Services shows that several initiatives geared toward high-acuity patients successfully cut millions in Medicare costs by integrating technology and data analytics. The following results were recently published (PDF) by Abt Associates, which conducted the review on behalf of CMS:
- Christus Health System: By combining nurse training with mobile device technology designed to help clinicians recognize early warning signs of high-risk conditions like sepsis and congestive heart failure, Christus Health System in Texas reduced Medicare costs by $1.31 million among hospitalized patients and $2.2 million among long-term post-acute care patients.
- Mayo Clinic: Incorporating a cloud-based analytics system to synthesize patient information within EHRs, lab results and physician orders, clinicians at the Minnesota-based system were able to prioritize ICU patients based on their needs, saving more than $4.2 million in Medicare costs during a two-year period.
- Emory University Healthcare: An eICU program at the Atlanta-based system saved $4.6 million during a 15-month span by ensuring patients were healthy enough to be discharged home rather than to long-term care settings.
- Mount Sinai Health System: With the help of a clinical decision support tool embedded into the New York system’s EHR, Mt. Sinai saved more than $7.5 million in Medicare costs by reducing inpatient admissions and return visits to the ED for patients 65 and older.
Health systems are increasingly utilizing a wide variety of high-tech, high-touch tools, including telehealth programs geared toward patients with complex chronic diseases and predictive analytics to reduce overcrowding.