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.
Integrated Delivery System
Length of stay (LOS) is an essential indicator of hospital operational efficiency. Albany Med compared its performance with benchmark data and determined that it could improve inpatient LOS. By convening a multidisciplinary team of providers committed to decreasing hospital LOS and leveraging its data and analytics platform, Albany Med was able to uncover underlying issues causing unnecessary extended hospital stays and substantially reduce LOS.
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.
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.
Albany Med’s clinical documentation improvement specialists provide high-quality care to complex, acute-care patients; however, Albany Med was experiencing lower reimbursement rates due to gaps in clinical documentation. The organization created a seamless process for clinical documentation with the use of an analytics application as driven by clinical leadership.
To ensure it continues the widespread use of data and analytics, Allina Health needed a plan to ensure ongoing data utilization and continuous, data-driven improvement, increasing the number of people learning from the valuable data in its data platform. By leveraging an advanced data platform and a robust suite of analytics accelerators, the health system observed significant improvements.
Managing and retaining a talented workforce represents approximately 60 percent of hospital costs. In an effort to improve staffing efficiency, Hawai‘i Pacific Health (HPH) sought to realign its staffing practices to better manage and predict its labor needs. Utilizing its data platform and analytics, HPH was able to forecast its workforce needs and effectively manage staff schedules—two changes that led to significant cost savings.
Mission Health trauma services provide evidence-based care. Despite its efforts to measure the impact of this care on outcomes, the overwhelming burden of manual data review limited its ability to effectively monitor key process measures in a timely manner. This prompted Mission to use data and analytics for timely insights into injury-specific process measure performance and concurrent chart review to improve trauma care.
Actionable Analytics Enables Improved Care, Reduced LOS, and Costs in Patients with Traumatic Brain Injury
To provide high-quality, cost-effective care to patients with traumatic brain injury (TBI), Mission Health needed insight into individual patient and provider performance data. Without access to accurate data, Mission couldn’t accurately pinpoint patient outliers, understand causes of TBI, and identify opportunities to improve TBI patient care. By utilizing its data platform and analytics accelerators, Mission was able to utilize patient data to identify patients suffering from TBI.
To leverage data from its trauma registry database to improve patient outcomes, Mission Health utilized its data platform and analytics, providing real-time access to data and a more comprehensive understanding of each trauma case. With an analytics-driven approach, Mission reduced emergency department (ED) length of stay (LOS) for patients with Level II trauma activation across its populations.
Emergency departments (ED) provide care for a staggering 145 million patients a year. Improving throughput times remains a top priority for hospitals as overcrowding and long wait times can lead to potential safety events and dissatisfaction with care. To improve ED throughput, Orlando Regional Medical Center (ORMC) assembled an improvement team to analyze the problem, utilizing data analytics and staff feedback to help identify a series of workflow changes designed to improve ED throughput and improve care delivery.
Annually, U.S. hospital supply chain overspend costs an estimated $25.4 billion, which represents 30 percent of all hospital spending. Utilizing data and analytics, Hawai’i Pacific Health gained a deep understanding of its supply chain processes and data, allowing it to improve and maintain the reliability of this information, leading to meaningful and sustained improvements across the system.
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:
For every hour of direct patient care they provide, primary care physicians spend nearly two hours on EMR tasks. Registered nurses also spend a substantial amount of their time, up to 45 percent, in the EMR as part of their regular workflow. Using closed-loop analytics integrated into its EMR and COPD application, UnityPoint Health has automated and improved workflow, gained operational efficiency, and improved staff satisfaction.
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:
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.
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.
Thirty percent of the entire world’s data is generated in the healthcare industry, with valuable information often locked in the EMR. For Orlando Health, the data required by operational leaders to effectively run emergency department operations were not easily accessible. By utilizing its analytics platform, Orlando Health leadership has expanded access and visibility to data to drive improvement efforts.
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.
For patients, safety in hospitals and health systems remains a serious concern as medical errors are now the third leading cause of death in the U.S. Determined to improve patient safety, Allina Health turned to predictive analytics to standardize and expand safety event reporting.
Medical errors account for 10 percent of all deaths. To improve patient safety, Allina Health utilized its machine learning, analytics platform, and a trigger-based data-driven surveillance tool to identify and investigate a broader base of harm events, enabling the organization to:
For healthcare organizations, the ability to analyze problems and implement timely, effective improvements is necessary to maintain a competitive advantage, requiring a consistent, systematic approach to introduce and implement change. By developing a new strategy focused on uniform adoption, education, and ongoing oversight, Community Health Network changed the way it approached all organizational improvement efforts.
With patients responsible for an increasing amount of their healthcare costs, self-pay accounts are now the top contributor to bad debt for hospitals and health systems—accounting for more than $55 billion annually. Allina Health partnered with Health Catalyst, using catalyst.ai™, to create a predictive model that could successfully support a propensity to pay strategy.
Learn how The Queen’s Health Systems (QHS) and The Queen’s Clinically Integrated Physician Network (QCIPN) adopted a Rapid Response Analytics Solution, enabling the accelerated implementation of custom algorithms to better identify patients.
Operating room (OR) costs are substantial—time in the OR can cost between $22 and $133 per minute. Even a slight delay in start time can cost organizations hundreds of thousands, if not millions, annually. Learn how John Muir Health utilized analytics in the OR—giving the organization the ability to access the data it needed to educate staff on the reasons behind delays so that start times could be improved.