Clinical

Success Stories

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$17.4M Saved Through Analytics-Driven Patient Blood Management Improvements

UnityPoint Health created a task force to develop and implement a plan for maximizing blood management. The task force incorporated decision support to improve transfusion ordering in alignment with the transfusion standards. An analytics platform has also been leveraged, which monitors the utilization of blood products, including predictive modeling to risk-adjust blood utilization specific to patient case-mix, and data down to the ordering provider level.

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Reducing Mortality Through Earlier Sepsis Intervention

Community Health Network had implemented evidence-based care; however, the sepsis mortality rate remained higher than desired. To address this situation, the health system established a sepsis council to coordinate a sepsis improvement plan and implemented an analytics platform to gain insight into sepsis care performance.

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Machine Learning and Feature Selection for Population Health

Christiana Care Health System (CCHS) had used a machine learning model to inform population segmentation. The initial model used “black box” algorithms to predict risk that care managers didn’t have input on or understand. CCHS leaders and experts wanted an efficient model that they understood and trusted to predict 90-day inpatient admission. CCHS used a feature selection process to build the simplest model possible—and AI insight tools for selecting the best model, setting triggers for action, and explaining how the model worked.

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Medically Integrated Wellness Program Reduces Modifiable Risk Factors

Thibodaux Regional Medical Center conducted a community health needs assessment (CHNA) as part of its vision for a healthier community. The CHNA reinforced the hospital’s identified need for a data-driven, medically integrated wellness program designed to benefit the health of the community by educating, advocating, and supporting healthy lifestyle changes to address modifiable health risks. Using a wellness analytics application, Thibodaux Regional is able to track program outcomes.

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Data-Driven Evidence-Based Practices Reduce Clostridioides Difficile Infections

To improve the care of patients with Clostridioides difficile (C. diff), Thibodaux Regional Medical Center used data and analytics to monitor completion of early recognition screening, protocol compliance, antimicrobial stewardship rounds, and probiotic administration. Thibodaux Regional’s leadership, culture, evidence-based practices, and data-driven improvement approach have positively impacted its patients.

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Big-Data and Prescriptive Analytics Decreases Pediatric Sepsis Mortality

Pediatric sepsis remains a key concern for hospitals due to the serious nature of the disease. Early diagnosis and timely care are a top priority, as this significantly improves a patient’s chance of recovery. With the help of big data and prescriptive analytics, Texas Children’s Hospital developed an early alert system and workflow changes to improve its pediatric sepsis care. The hospital’s investment in new processes, decision support, and analytics has substantially improved pediatric sepsis outcomes.

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Multimodal Pain Management Approach Reduces Opioid Prescriptions After Bariatric Surgery

Chronic knee and back pain associated with morbid obesity increases the risk for opioid dependence among patients undergoing bariatric surgery. Mission Health sought a comprehensive, data-driven, evidence-based approach to reduce opioid prescribing after bariatric surgery, decreasing the risk for misuse and harm. By using comprehensive ERAS protocols with multimodal pain management interventions, Mission realized substantial reductions in opioid use for pain management among patients undergoing bariatric surgery, including a:

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Robust Data and Analytics Enables Comprehensive Program Evaluation, Securing Continued Funding

Community Health Network (CHNw) was keenly aware of the needs of the elderly population in its communities of impact. However, despite the development and implementation of a successful geriatric program, the organization lacked access to, and visibility of, meaningful data to quantify program outcomes. The CHNw Geriatric Evaluation and Management (GEM) team used an analytics application to demonstrate the sizeable, positive impact of the GEM team care and interventions on both patient and financial outcomes:

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Data-Driven Workflow Improves Diabetes Education Program Effectiveness

To optimize the impact of its diabetes self-management education program, Allina Health enhanced its service model, aligning resources to proactively meet patient demand, while also maintaining high-quality clinical outcomes. Utilizing analytics in the redesign process has allowed Allina Health to understand patient needs better and monitor the impact of planned changes to the program on patient outcomes.

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Population Health Analytics Enables Rapid Identification of Super-Utilizers

Seeking to drive down unnecessary cost, Hospital Sisters Health System (HSHS) needed a way to automate risk stratification of patients who may benefit from care management services and eliminate the burdensome manual work its care managers were performing to identify at-risk patients. HSHS utilized a population health analytics platform to accurately risk stratify its care management and identify patients who would benefit from additional care management interventions.

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Data-Driven Approach Successfully Engages Orthopedic Surgeons in Decreasing Opioid Use

Community Health Network (CHNw) was keenly aware of the impact that opioid prescribing patterns have on potential opioid misuse and set a focus on decreasing opioid prescriptions; however, it lacked access to meaningful data that could be used to understand the volume of opioids that were prescribed postoperatively. CHNw created an orthopedics guidance team and leveraged data within its analytics platform to gain insight into prescribing habits over time.

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Analytics Helps Population Health Coordinators to Better Treat Chronic Conditions

Improving the management of chronic diseases for patients is crucial for reducing expenses and improving health outcomes. Newton-Wellesley Hospital, a member of the Partners HealthCare system, adopted the population health coordinator role and utilized analytics to help identify variations in chronic disease management across practices and develop standardized best practices aimed at reducing costs through better outcomes for patients.

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Machine Learning Improves Accuracy of Risk Predictions and Improves Operational Effectiveness

Hospital readmissions can impact the health outcomes for patients and result in costly readmission penalties from CMS. Learn how the data analytics teams at Westchester Medical Center Health Network and network member Bon Secours Charity Health System utilized its analytics platform, in coordination with a machine learning algorithm, to build a knowledgeable and accurate readmission risk model that better reflected its patient population.

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