Academic Medical Center

Success Stories

Health Catalyst

Using Analytics to Automate Heart Failure Data Aggregation

For each heart failure admission, registered nurses at Guy’s and St Thomas’ NHS Foundation Trust collected data from five different sources, and then filled out a 10-page form for each patient. Information from the forms was then manually entered into the National Institute for Cardiovascular Outcomes Research (NICOR) web portal. This manual process for data collection and reporting was not only time-consuming and resource-intensive—but was also highly susceptible to error. To address these challenges, the organization leveraged the Health Catalyst® Data Operating System (DOS™) to integrate the data from the five source systems and extract data for nearly all of the elements required for heart failure readmissions—streamlining the NICOR submission process and improving data quality and accuracy.

Health Catalyst

Analytics Reveal AAA Programme Improvement Success

As part of its efforts to improve the timeliness of care for patients undergoing abdominal aortic aneurysm (AAA) repair, Guy’s and St Thomas’ NHS Foundation Trust needed to collect data to guide care redesign, help assess the impact of specific interventions, and gauge progress toward desired outcomes. Guy’s and St Thomas’ implemented the Health Catalyst® Data Operating System (DOS™) platform, including a Referral Pathway analytics application, allowing the organization to aggregate and standardize data across source systems. Improved data and analytics have enabled Guy’s and St Thomas’ to analyze, evaluate, and monitor outcomes for the entire AAA cohort and evaluate operational performance and associated patient outcomes.

Health Catalyst

Using Analytics to Improve Clinical Coding

Responsible for coding approximately 380,000 episodes annually, clinical coders at Guy’s and St Thomas’ NHS Foundation Trust review documentation across several systems. The overwhelming amount of data, burdensome manual review processes, and limited coding resources made reviewing all data unfeasible. To address its coding challenges, Guy’s and St Thomas’ leveraged its data platform to combine and standardise data across disparate source systems. The organization now has access to data and technology that can be used to augment coders’ work, automating data gathering to better identify patients whose diagnostic coding could be improved.

Health Catalyst

Optimizing Space Utilization Improves Patient Access and Revenue

Texas Children’s Hospital had dramatically improved patient access, yet it recognized that it could advance access further by improving space utilization and proactively reallocating underutilized exam rooms. The organization developed a space visualization analytics application, and conducted a comprehensive space assessment, identifying opportunities to improve utilization of current space to increase clinic offerings—resulting in improved access for patients and families by utilizing space efficiently.

Health Catalyst

Virtual Visits and Analytics Enable Continued Delivery of Ambulatory Services During COVID-19 Pandemic

With the emergence of COVID-19, Texas Children’s Hospital was challenged to make data-informed decisions that would allow it to continue offering critically needed healthcare services, while ensuring the safety of its patients, staff, and providers. Texas Children’s dramatically expanded telehealth capacity, converting most in-person primary, specialty, and mental healthcare visits to a phone or video appointment to better meet patient needs. The organization leveraged the Health Catalyst® Data Operating System (DOS™) platform and a virtual health platform to visualize, monitor, and manage the conversion to virtual health, in addition to managing in-person visit volume—enabling the effective management of outpatient capacity, utilization, and financial performance.

Health Catalyst

Removing Discharge Barriers Reduces Hospital Length of Stay

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.

Health Catalyst

Improved Data Access Drives Effective Care Delivery

Texas Children’s Hospital knew that improving data access was key to driving improvements and sought to improve analytics adoption and democratize its data. By focusing on developing a culture of data access and sharing, Texas Children’s has shifted its data and analytics culture, establishing the foundation required for it to continue to advance its analytics adoption, including engaging in predictive analytics. Leaders and employees are actively investigating and sharing data, and operations are more data-driven than ever before.

Health Catalyst

Integrated Analytics Shows True Cost of Patient Care

To gain more efficient access to data that could reduce unwarranted variation and reduce costs, Dartmouth-Hitchcock Health (D-HH) leveraged a data platform to automate analysis of its financial data. D-HH has substantially improved its ability to use clinical, operational, and financial data to perform opportunity analysis, decrease unwarranted variation, and decrease costs.

Health Catalyst

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.

Health Catalyst

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.

Health Catalyst

Care Transitions Improvements Reduces 30-Day All-Cause Readmissions Saving Nearly $2 Million

It is estimated that $25 to $45 billion is spent annually on avoidable complications and unnecessary hospital readmissions—the result of inadequate care coordination and insufficient management of care transitions. By implementing care coordination programs and leveraging its analytics platform, the University of Texas Medical Branch reduced its readmission rate and achieved significant cost avoidance.

Health Catalyst

Clinical and Financial Partnership Reduces Denials and Write-Offs by More than $3 Million

CMS denies nearly 26 percent of all claims, of which up to 40 percent are never resubmitted. The bane of many healthcare systems is the inability to identify and correct the root causes of these denials, which can end up costing a single system tens of millions of dollars. Yet almost two-thirds of denials are recoverable and 90 percent are preventable.1 Despite previous initiatives, The University of Kansas Health System’s denial rate (25 percent) was higher than best practice (five percent), and leadership realized that, to provide its patients with world-class financial and clinical outcomes, it would need to engage differently with its clinical partners.
To effectively reduce revenue cycle and implement effective change, The University of Kansas Health System needed to proactively identify issues that occurred early in the revenue cycle process. To rethink its denials process, it simultaneously increased organizational commitment, refined its improvement task force structure, developed new data capabilities to inform the work, and built collaborative partnerships between clinicians and the finance team.
As a result of its renewed efforts, process re-design, stakeholder engagement, and improved analytics, The University of Kansas Health System achieved impressive savings in just eight months.

$3 million in recurring benefit, the direct result of denials reduction.
$4 million annualized recurring benefit.
Successfully partnered with clinical leadership to transition ongoing denial reduction efforts to operational leaders.

Health Catalyst

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.

Health Catalyst

Collaborative Partnerships and a Three-System Approach to Driving Healthcare Transformation

Healthcare organizations are among the most complex forms of human organization ever attempted to be managed, making transformation a daunting task. Despite the challenges associated with change, Texas Children’s Hospital identified that it needed to evolve into a data-driven outcomes improvement organization.
Texas Children’s embarked on a journey to transform care, building a three-systems approach—analytics, best practice, and adoption—designed to develop a data-driven quality improvement organization that could achieve outcomes improvement expediently and at scale across the entire organization. Texas Children’s leadership knew that the foundation for clinical systems integration would be meaningful, actionable data. That realization prompted the organization to implement the Health Catalyst Analytics Platform including a Late-Binding™ Data Warehouse (EDW) and a broad suite of analytics applications.
After deploying the analytics platform supported by multidisciplinary quality improvement teams, Texas Children’s was able to improve patient outcomes related to the following:

35 percent relative decrease in hospital-acquired conditions (HACs).
44 percent relative decrease in LOS for patients with Diabetic ketoacidosis (DKA).
30.9 percent relative reduction in recurrent DKA admissions per fiscal year.

 

Health Catalyst

How Texas Children’s Turned Child Diabetes Management into a Community Cause

Patients with diabetes are at a high risk for infections and substantial complications, including the risk of death from infections. Further, social determinants in these patients’ communities have a tremendous influence on their health.
Texas Children’s Hospital, ranked as one of the top four Best Children’s Hospitals by U.S. News & World Report, recognized that there were gaps in diabetes care coordination in the community—where the majority of a child’s diabetes management takes place. The hospital initiated a coordinated community response, aided with an analytics platform, which is setting the standard for community management of pediatric diabetes.
Results

4 percent relative improvement in the percentage of patients with diabetes who received the influenza vaccine.
3 percent relative improvement in pediatric provider diabetes knowledge.
90 percent of patients now have individualized school packets developed and available in the EHR.