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Improving Transitions of Care for Patients with Pneumonia

Nationally, the readmission rate for patients over age 65 with pneumonia is 15.8 percent. Though not all hospital readmissions are preventable, high readmission rates may reflect performance on care quality, effectiveness of discharge instructions, and smooth transitioning of patients to their home or other setting.

Piedmont Healthcare wanted to standardize pneumonia care across its entire system but lacked the data it needed to identify patients who could benefit from additional transition support. Piedmont convened a care management steering committee and deployed analytics tools to generate actionable data for appropriate and effective transitions of care for its Medicare patients with pneumonia. In less than one year, it reduced its readmission rate for patients with pneumonia by 26 percent.

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Successfully Sustaining Elective Colon Surgery Outcome Improvements

For healthcare organizations, sustaining improvements that have been adopted in more than one part of an organization remains a serious challenge. After improvement initiatives have been successfully implemented, it is estimated that less than 40 percent of gains are sustained in the long term. Because improvement initiatives are necessary to maintain a high standard of care, sustaining them so that further improvements can be made remains a top priority for health systems.

MultiCare Health System, a not-for-profit healthcare system serving Washington state, successfully implemented improvement efforts for patients undergoing elective colon surgery, which resulted in significant reductions in 30-day readmission, LOS, and surgical site infections (SSIs). However, without ensuring ongoing engagement, accountability, and visibility into performance, MultiCare was concerned improvements could slip away. By supporting continued monitoring powered by insights gained from relevant data, and by closely listening to provider feedback, MultiCare was able to sustain previous improvements while identifying new opportunities.

Results:

  • 32.7 percent relative reduction in 30-day readmission rate for patients having elective colon surgery.
  • 3.4-day median LOS for patients having elective colon surgery, sustaining previous improvement.
  • Among patients who had the complete enhanced recovery after surgery protocol implemented for elective colon surgery, there were no surgical site infections—for an entire year.
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Care Transitions Improvements Reduces 30-Day All-Cause Readmissions Saving Nearly $2 Million

Researchers estimate that in just one year, $25 to $45 billion is spent on avoidable complications and unnecessary hospital readmissions, the result of inadequate care coordination and insufficient management of care transitions.

While increasing its efforts to reduce its hospital readmission rate, the University of Texas Medical Branch (UTMB) discovered that it lacked standard discharge processes to address transitions of care, leading to a higher than desired 30-day readmission rate. To address this problem, UTMB implemented several care coordination programs, and leveraged its analytics platform and analytics applications to improve the accuracy and timeliness of data for informing decision making and monitoring performance.

This combination of approaches proved successful, resulting in:

  • 14.5 percent relative reduction in 30-day all-cause readmission rate.
  • $1.9 million in cost avoidance, the result of a reduction in 30-day all-cause readmission rate.
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Accuracy of Readmission Risk Assessment Improved by Machine Learning

Hospital readmissions carry significant financial costs and are associated with negative patient outcomes. While the reasons behind patient readmissions are multi-factorial, and the specific rates vary by institution, nearly 20 percent of all Medicare discharges nationwide led to a readmission within 30 days. Preventing even 10 percent of these readmissions could save Medicare $1 billion.

North Carolina’s only not-for-profit, independent community healthcare system, Mission Health, is comprised of seven hospitals, 750 employed/aligned providers, and one of the largest Medicare Shared Savings ACOs in the nation. Mission had been using the LACE index to predict risk for readmission, and while it was helpful, Mission’s patient population was different than the population used to develop the LACE index, leaving the health system with some uncertainty regarding the readmission risk of its patients. With the help of data analytics, Mission developed its own predictive model for assessing readmission risk, aimed at preventing readmissions and improving outcomes for patients.

Results:

  • The area under the curve (AUC) for Mission’s readmission risk predictor is 0.784, outperforming LACE, and meeting the organization’s goal for performance.
  • Mission’s readmission rate is 1.2 percentage points lower than its top hospital peers.
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Machine Learning, Predictive Analytics, and Process Redesign Reduces Readmission Rates by 50 Percent

The estimated annual cost of readmissions for Medicare is $26 billion, with $17 billion considered avoidable. Readmissions are driven largely by poor discharge procedures and inadequate follow-up care. Nearly one in every five Medicare patients discharged from the hospital is readmitted within 30 days.

The University of Kansas Health System had previously made improvements to reduce its readmission rate. The most recent readmission trend, however, did not reflect any additional improvement, and failed to meet hospital targets and expectations.

To further reduce the rate of avoidable readmission, The University of Kansas Health System launched a plan based on machine learning, predictive analytics, and lean care redesign. The organization used its analytics platform, to carry out its objectives.

The University of Kansas Health System substantially reduced its 30-day readmission rate by accurately identifying patients at highest risk of readmission and guiding clinical interventions:

  • 39 percent relative reduction in all-cause 30-day.
  • 52 percent relative reduction in 30-day readmission of patients with a principle diagnosis of heart failure.
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