Situation
Premature readmissions are a growing problem for healthcare providers and payers. The fines and penalties they trigger cost an estimated $15B to $20B a year. They lead to low satisfaction ratings from patients as well, which create additional financial pressures under value-based reimbursement models.
Many premature readmissions could be avoided if better information—that sheds light on a patient’s life and circumstances and identifies possible readmission risks—was available during the discharge decision process.
Uninformed Discharge Considerations
Let’s take Paula as an example. She’s 84 years old and is being considered for discharge after treatment for an episode of acute asthma. Her case manager, Karen, considers information at hand at the hospital, including Paula’s medical history and her record of treatment, and it seems like it should suffice. But it doesn’t.
Karen recognizes that only 20% of personal health risk factors are related to actual health issues. But she doesn’t have a way to access the other 80% that are found in extra-clinical determinants including environmental, behavioral and social factors.
The Bellrock Breakthrough
Now let’s look at Paula’s discharge process when enhanced by Bellrock Intelligence technology, which has the unique ability to look at that missing 80%. Bellrock scoured the web and discovered that the air quality index near Paula’s home was over 100. It also learned that her home is near an ongoing construction project. That’s why Karen decides to meet with Paula and a social worker to assess the air quality in Paula’s home and possibly implement controls.
Bellrock also learned that Paula’s son, who lives with her, has just been released from prison. This prompts Karen and the social worker to explore whether Paula has the support she needs to deal with this situation. Paula also arranges for Karen to get a second opinion on Paula’s orthopedic issues. Why? Because Bellrock flagged that she lives in a walk-up apartment and discovered quality issues in orthopedic treatments with her in-hospital physician. Karen also recruits a family friend to monitor and report on any changes in Paula’s mobility that could result in a readmission.
But Bellrock isn’t finished. Its scan of external “non-institutional” data reveals that Paula’s primary care physician is associated with a higher narcotic prescription rate, so Karen offers to help Paula look for a new doctor. It flags that that the visiting nurse in Paula’s community is associated with higher costs, so Karen directs the visiting nurse association to assign a different nurse.
Conclusion
Thanks to Bellrock, critical gaps in Paula’s patient profile have been filled, resulting in a more complete picture of her social and physical environment. It has identified a number of factors that could cause a costly premature readmission that could lead to low patient satisfaction ratings and penalties. Bellrock information has empowered Paula and her care team to make better-informed decisions going forward.
Bellrock Intelligence enables an improved and more profitable practice of medicine, enhances margins on bundled care payments, and raises patient satisfaction that can lead to bonus reimbursements, higher ratings and lower readmission costs. And it has done it all silently in the background, without any need for queries or instructions.
That is the Bellrock breakthrough.
Premature readmissions are a growing problem for healthcare providers and payers. The fines and penalties they trigger cost an estimated $15B to $20B a year. They lead to low satisfaction ratings from patients as well, which create additional financial pressures under value-based reimbursement models.
Many premature readmissions could be avoided if better information—that sheds light on a patient’s life and circumstances and identifies possible readmission risks—was available during the discharge decision process.
Uninformed Discharge Considerations
Let’s take Paula as an example. She’s 84 years old and is being considered for discharge after treatment for an episode of acute asthma. Her case manager, Karen, considers information at hand at the hospital, including Paula’s medical history and her record of treatment, and it seems like it should suffice. But it doesn’t.
Karen recognizes that only 20% of personal health risk factors are related to actual health issues. But she doesn’t have a way to access the other 80% that are found in extra-clinical determinants including environmental, behavioral and social factors.
The Bellrock Breakthrough
Now let’s look at Paula’s discharge process when enhanced by Bellrock Intelligence technology, which has the unique ability to look at that missing 80%. Bellrock scoured the web and discovered that the air quality index near Paula’s home was over 100. It also learned that her home is near an ongoing construction project. That’s why Karen decides to meet with Paula and a social worker to assess the air quality in Paula’s home and possibly implement controls.
Bellrock also learned that Paula’s son, who lives with her, has just been released from prison. This prompts Karen and the social worker to explore whether Paula has the support she needs to deal with this situation. Paula also arranges for Karen to get a second opinion on Paula’s orthopedic issues. Why? Because Bellrock flagged that she lives in a walk-up apartment and discovered quality issues in orthopedic treatments with her in-hospital physician. Karen also recruits a family friend to monitor and report on any changes in Paula’s mobility that could result in a readmission.
But Bellrock isn’t finished. Its scan of external “non-institutional” data reveals that Paula’s primary care physician is associated with a higher narcotic prescription rate, so Karen offers to help Paula look for a new doctor. It flags that that the visiting nurse in Paula’s community is associated with higher costs, so Karen directs the visiting nurse association to assign a different nurse.
Conclusion
Thanks to Bellrock, critical gaps in Paula’s patient profile have been filled, resulting in a more complete picture of her social and physical environment. It has identified a number of factors that could cause a costly premature readmission that could lead to low patient satisfaction ratings and penalties. Bellrock information has empowered Paula and her care team to make better-informed decisions going forward.
Bellrock Intelligence enables an improved and more profitable practice of medicine, enhances margins on bundled care payments, and raises patient satisfaction that can lead to bonus reimbursements, higher ratings and lower readmission costs. And it has done it all silently in the background, without any need for queries or instructions.
That is the Bellrock breakthrough.