Improving Patient Outcomes with an Innovative Approach to Data

One Health System’s Story

By Josh Rubel, Chief Commercial Officer, MDClone
LinkedIn: Josh R.
X: @MDClone_

Valuable insights are buried inside the massive quantities of data collected in various healthcare settings, but extracting those insights is often challenging and resource-intensive for health systems and hospitals.

At the same time, the need for insights from data has grown dramatically in the healthcare industry, making it difficult to scale analyst teams to meet demand.

Faced with these limitations, Intermountain Healthcare tried a new approach: distributed, clinician-led data exploration data exploration. Intermountain Healthcare realized that placing data exploration directly into the hands of researchers and clinicians could radically transform both patient care and financial performance.

This unique ability to quickly see outcomes and associations across long spans of time and within large datasets and patient populations has helped Intermountain establish clear trends and discern new, authoritative insights. For Intermountain, fast generation of data-driven insights combined with a user’s clinical knowledge has resulted in more insightful queries and a more accessible and repeatable research process.

Based on findings from its self-service data exploration initiatives, Intermountain has launched new patient-care programs that are improving outcomes for chronic kidney disease, pulmonary embolism, diabetes, and more.

Overcoming four major data challenges

Intermountain Healthcare is a not-for-profit healthcare system and the largest provider in the Intermountain West region with 33 hospitals, 385 clinics, a medical group, and a health insurance company, SelectHealth. The health system is a recognized leader in transforming healthcare through innovation and a patient-centric approach.

Because more than 40% of its patients are at full-risk, Intermountain is heavily focused on quality, population health, and value-based care. However, Intermountain’s leadership knew that gathering and reorganizing patient data was only the first step to treating and preventing chronic and acute care conditions.

The health system needed a data analytics platform to help overcome four major barriers:

  • Over-mediated: Analysts and clinicians were unable to guide and complete their own queries and had to rely heavily on IT database experts.
  • Time-intensive: The cycle of time to insights was too long and discouraged optimal engagement from clinicians, both at the back end of processing (after a long wait for results) and at the front end (re-engagement with the same time-intensive process).
  • Unstructured data: Finding meaningful patterns in the data grew more difficult as the data sets grew in size, type, and source.
  • Privacy regulations: Discovering and sharing insights with collaborators was restricted and often not possible due to patient privacy regulations.

For Intermountain, a self-service data platform represented the answer to surmounting these data barriers. The platform enables non-IT users across the organization to directly explore granular longitudinal patient data in a unique model geared towards more rapid and robust insight discovery and care delivery.

Data-driven insights lead to higher-quality care

Chronic kidney disease (CKD): Kidney disease is the ninth-leading cause of death in the United States and accounts for 22% of Medicare’s annual spend, at $80 billion per year. Up to 15% of US adults have CKD and some 90% of those are unaware of their condition. Approximately 70% of late-stage renal disease patients at Intermountain were going into dialysis unaware of their disease, leading to worse outcomes and excessive costs. To reverse the trend, Intermountain set out to reduce hospitalizations and prevent unnecessary morbidity and mortality by identifying and engaging patients in the early stages of CKD. Early detection of progressive kidney disease is important because critical therapies can slow the rate of progression in many patients.

Intermountain used its analytics platform to manage and quantify, from a cost perspective, the many disease processes associated with CKD. Further, the platform helped Intermountain identify at-risk patients, utilize structured and unstructured data elements to implement a course of action or care transformation, and show potential return on investment from enrolling identified patients into a kidney care transformation plan.

The CKD program has generated measurable progress, including:

  • Identification and early engagement of CKD patients enabled early intervention. Thus far, less than 1% of patients identified at earlier stages of disease (at or below stage G3A and G3B) progressed to dialysis, and 86% of newly enrolled patients avoiding hospitalizations with an almost 60% reduction in overall admissions since kicking off the program, resulting in savings to the organization at $1.1 million per year since launch.
  • Among the patients who presented with stage G3A or G3B, none progressed to dialysis.
  • From a research perspective, Intermountain Healthcare has revealed probabilistic measures in comorbidity management upstream of kidney care as predictors for adverse events and stage progression.

Following the success of the CKD program, Intermountain launched other use cases for its data-driven projects, including pulmonary embolism.

Pulmonary embolism: Venous thromboembolism, including deep vein thrombosis and pulmonary embolism, imposes a major burden on the U.S. healthcare system, and Intermountain is no different. To improve care for these patients, Intermountain needed to access and review its data to determine risk stratification and treatment options for patients with pulmonary embolism.

This required the team to analyze the levels of clinical biomarkers in patients with pulmonary embolism, provide information about the mortality rates for these patients, and generate insights into how different treatment options affect outcomes for pulmonary embolism.

Early results of the program demonstrated that:

  • Developing a pre-discharge model for venous thromboembolism treatment could avert approximately 1,180 venous thromboembolism events annually across Intermountain.
  • The delta cost savings of early detection and proactive treatment, as opposed to long-term care, could represent a total savings opportunity of greater than $24 million.
  • With the targeted pulmonary embolism cohort risk model implemented, the estimated per member per month savings from reduced hospitalizations could reach a total of greater than $1 million annually.

In addition to CKD and pulmonary embolism, Intermountain has developed data-driven programs to improve patient outcomes for diabetes and hyperlipidemia. Since pivoting to distributed, self-service data exploration, Intermountain has rapidly accelerated the pace of learning and the speed of insights across the organization.