A win for patients, hospitals and payers: 5 takeaways on personalized post-acute care navigation

In Collaboration with Health at Scale - Print  | 

As health systems and health plans strive to deliver optimal patient outcomes, new technology solutions have emerged as effective tools to protect patients and improve post-acute care quality.

During a June webinar hosted by Becker's Hospital Review and sponsored by Health at Scale, two leaders from the technology company discussed how personalized post-acute care navigation solutions can help reduce readmissions and improve patient outcomes:

Five key takeaways:

  1. Precision care delivery identifies individually-optimal post-acute care choices for patients. The goal of precision care delivery is to match patients to hyper-relevant care customized for each patient’s needs at the moment. Using advanced machine intelligence, Health at Scale’s Precision NavigationTM identifies post-acute providers (skilled nursing facilities [SNFs], home health agencies [HHAs], primary care physicians, and specialists) optimally suited to each patient’s individual health characteristics and needs at the point of discharge. "Our approach is deeply personalized to the individual. We look at thousands of health characteristics for each individual to determine the best guidance," Ms. Berger said.

  2. There is a significant opportunity to better match patients to post-acute care choices that are right for their individual needs. Data from studies in multiple cohorts conducted by Health at Scale show that roughly 82% of patients are presently discharged to sub-optimal post-acute care choices. This leaves significant opportunities for improvement. Understanding the right care settings and identifying the SNFs or HHAs most likely to prevent readmissions and emergent care can greatly impact outcomes, experience, access and affordability.

  3. Navigating patients to the right skilled nursing facility or home health agency is a win for patients, hospitals and payers. A recent study by researchers affiliated with the University of Michigan, MIT and Health at Scale, published in the American Journal of Managed Care, evaluated post-acute outcomes for Medicare beneficiaries based on which SNF they were sent to. The researchers compared rates of emergent hospitalization for respiratory infections between patients discharged to SNFs highly rated for these patients by Health at Scale’s specialized and personalized Precision NavigationTM technology vs. SNFs that were determined to be not well-matched for these individuals. "The results show that when patients were discharged to a SNF that was top matched for their unique health characteristics , ED rates dropped from 8.7 to 5.5 percent and hospitalization rates dropped from 6.1 to 3.9 percent," Dr. Saeed said.

  4. Precision care delivery reduces the total cost of care while leading to better outcomes. A second study published in the Journal of Medical Internet Research last fall compared outcomes for patients who underwent surgery from providers ranked highly for their individual needs by Precision NavigationTM with individuals undergoing procedures from providers rated highly by popular consumer ratings, reputation rankings, process-based and volume-based metrics. Health at Scale's approach resulted in a 16 percent to 18 percent reduction in readmission and post-procedure hospitalization rates. "One of the most interesting things was that the Precision Navigation matches reduced the total cost of care by $3,300 compared to the average," Dr. Saeed said, "while patients that used consumer ratings to select an orthopedic surgeon saw anywhere from a $1,300 increase to a $1,000 decrease in total cost of care. Health at Scale’s machine intelligence for precision care delivery is at least three times better than the next closest technique."

  5. Healthcare organizations must think boldly about adopting machine intelligence-based solutions for care navigation. Health systems and health plans need clinical decision support tools that improve patient outcomes and enhance the patient experience. "Being at the forefront of adopting machine learning-based tools will lead to better outcomes based on quantitative information," Dr. Saeed said. "I think these tools will be welcomed by many providers."

To view the full webinar, click here

To register for upcoming webinars, click here.


1. "Machine Intelligence for Early Targeted Precision Management and Response to Outbreaks of Respiratory Infections," by T. Zhan, D. Goyal, J. Guttag, R. Mehta, Z. Elahi, Z. Syed, M. Saeed, American Journal of Managed Care 2020; 26(10):445-448.
2. "Comparing Precision Machine Learning With Consumer, Quality, and Volume Metrics for Ranking Orthopedic Surgery Hospitals: Retrospective Study," by D. Goyal, J. Guttag, Z. Syed, R. Mehta, Z. Elahi, M. Saeed, Journal of Medical Internet Research 2020;22(12):e22765.

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