Enterprise Data Warehouse

Success Stories

Driving Strategic Advantage Through Widespread Analytics Adoption

With the current state of uncertainty facing healthcare organizations, survival requires unprecedented agility when it comes to acquiring and responding to meaningful, strategic information. After adopting the Health Catalyst Analytics Platform, including the Late-Binding™ Data Warehouse and broad suite of analytics applications, Partners HealthCare promoted a philosophy of expanded access to the enterprise data warehouse (EDW) to increase adoption and self-service analytics to improve patient care and outcomes.
Partners needed widespread adoption of the EDW so that information could be meaningfully incorporated into strategic, clinical and operational decision making to support patient care. This meant that users who had a legitimate need to access data to support their job function were encouraged to seek access to the EDW. The organization continues to focus on further increasing the effectiveness of this strategy by ensuring that users have the means to acquire the skills, knowledge, and support they need to effectively use data stored in the EDW.
Results:

243 percent increase in user base—achieved over a two-year period (700+ unique users).
More data available to a broader audience than ever before.
Physician time to access data reduced from weeks to clicks.
87 percent of user community satisfied with the effectiveness of communication provided to support their use of the EDW.

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MultiCare’s Transformational Journey Toward Sustained Outcomes Improvement

Mixed reviews of the effectiveness of pay-for-performance programs leave hospitals wondering how to affect meaningful change in patient care and outcomes. However, MultiCare’s experience with focused improvement efforts supported by analytics for pneumonia, sepsis, and women’s care showed that better data consistently leads to better patient outcomes.
Committed to improving population health, and informed by their experience as well as national trends and outcomes, MultiCare formed a new partnership with Health Catalyst, a next-generation data, analytics, and decision support company. The shared risk partnership generated an improvement framework and governance structure formed around a Shared Governance Committee which is responsible for prioritizing, resourcing, and aligning improvement initiatives across MultiCare. The committee and the projects it ultimately approves are informed by data-driven opportunity analysis and ongoing analytics support. This partnership and structure have achieved the following:
Results

Strategic alignment of outcomes goals across the organization.
Established an Analytics Center of Excellence.
Integrated financial data into outcomes improvement initiatives.

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Faster Data Acquisition Delivers Speedy Time to Value

Effective data integration enables high value through more strategic, data-driven decision-making, while faster data acquisition feeds and speeds up the process. Orlando Health, one of Florida’s most comprehensive private, not-for-profit healthcare networks, recognized the need for effective data integration to successfully manage to the organization’s changing business needs. The health system needed the ability to rapidly acquire and link disparate healthcare data sources in various ways in order to answer clinical and business questions.
Leaders at Orlando Health needed a data warehouse that better met their needs. They determined that switching from an early binding data process to a late-binding process would provide greater flexibility and expand their access to critical data, with shorter data acquisition times.
With the new EDW, Orlando Health achieved the following efficiencies:

245 fewer days and 1.0 less full time employee (FTE) needed to integrate encounter billing summary system data.
56 fewer days and 0.4 less FTE needed to integrate Infection control system data.
99 percent reduction (90 days saved) in the amount of time needed to implement system enhancements.
98 percent reduction in the work hours needed to incorporate system enhancements.

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How to Reduce Clinical Variation and Improve Outcomes While Demonstrating a Positive ROI

Clinical variation can be frustrating for patients and their families, often leaving the impression that healthcare team members are not on the same page and don’t agree on the plan for the patient’s diagnosis or treatment. It is also costly—the Institute of Medicine estimates that $265 billion (30 percent) of healthcare spending is waste that directly results from clinical variation.
To reduce unwanted variation, Texas Children’s Hospital invested considerable resources to develop clinical standards tools, including evidence-based order sets; however, demonstrating the effectiveness and utilization of those guidelines, pathways, and order sets had been daunting. To that end, Texas Children’s deployed an analytics platform from Health Catalyst to aggregate and analyze the data needed to perform both of these critical functions.
Results:

$2,401 reduction in cost per patient with order set utilization, and an 8.4-day difference in average length of stay (LOS).
$15 million reduction in total direct variable costs in Fiscal Year 2015, $32 million anticipated reduction in Fiscal Year 2016 at the current order set usage rate, and a potential $64 million annual reduction with a hypothetical 80 percent order set usage rate.
1,629 percent return on investment (ROI).

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Turning Data from Five Different EHR Vendors into Actionable Insights

When healthcare information systems don’t talk to each other, countless inefficiencies and patient safety issues may arise.
Community Health Network (CHNw) believes in delivering outstanding care to every patient. In order to minimize patient safety risks and inefficiencies resulting from using different EHRs, CHNw embarked on a journey to integrate its healthcare information technologies. After implementing a Late-Binding™ Data Warehouse from Health Catalyst that integrates all key data sources, CHNw now has a consistent and comprehensive perspective for multiple patient encounters across the enterprise. It has achieved the following results:

Data from multiple EHR vendors, including four inpatient EHRs and two ambulatory EHRs, plus five transactional systems—HR, patient experience, patient safety, finance, and supply chain— were integrated within 12 months.

More than 55,000 data elements and over 18 billion rows of data were incorporated.

Patient-to-patient matching was implemented for over one million patients across the four inpatient EHRs. This is vital for managing patient populations.

Operational efficiency was improved by 70 percent, with data architects spending an estimated 15 percent of time supporting interfaces compared to an estimated 40-50 percent before the integration. In one example, CHNw linked its ERP/costing system to the EDW’s EHR source marts with just a single interface; previously, this would have required building separate interfaces for all six EHRs.

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Allina Health’s Dedication to Quality Improvement Delivers On the Triple Aim

Improving clinical outcomes is good for patients and good for health systems. In fact, Allina Health’s focus on data-driven outcomes improvement realized a total financial improvement of $125 million in a single year.
Allina embraced the mandate of achieving the Triple Aim: improving the quality and cost of care, as well as the patient experience. To achieve this goal, Allina’s leaders recognized that they would need to realign their strategies, organizational structures, and management practices. Confident that data would help the health system improve the quality of patient care and reduce costs, they implemented a data-driven performance improvement strategy.
The results are astounding. This strategy has achieved financial improvements for the health system of $100+ million per year, four years running, while also advancing Allina Health’s Triple Aim goals of improved clinical outcomes and a better patient experience through dozens of improvement initiatives.

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Patient Identification and Matching—An Essential Element of Using an Enterprise Data Warehouse to Manage Population Health

In a healthcare industry transitioning to value-based reimbursement and population health management (PHM), matching patients accurately to their care events across multiple sites of care and sources of information is becoming ever more important. Being able to accurately track utilization of services for a particular patient, patient population, or provider is fundamental to the strategies underlying effective population health management. Partners HealthCare developed an effective patient matching solution for more than 10.5 million patients achieving a 20 percent improvement in patient matching accuracy and a 96-99 percent high-risk patient matching rate. This has allowed the organization to accurately “flag” high risk patient populations and better manage risk under risk-based contracts.

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Partners’ Enterprise Data Warehouse: Focus on Service and Value

As the healthcare industry rapidly evolves, implementing an enterprise data warehouse has become essential both for population health management and economic survival. While this requires building analytics competency across the enterprise, once adopted, the benefits are abundant—from improved patient outcomes to reduced waste and costs. To rapidly gain value from this platform, healthcare organizations should follow an implementation strategy that, before anything else, identifies the problems analytics is intended to solve. It should also place as much emphasis on people and processes as it does technology. Partners HealthCare is an example of how implementing a data warehouse can quickly leverage analytics across the enterprise to achieve value with high end-user engagement and satisfaction.

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The Enterprise Data Warehouse (EDW): Creating the Foundation for Effective Healthcare Improvement Analytics

Population health management and value-based care has arrived. However, many healthcare organizations don’t have a single source of truth for their data, nor can they easily access their information. In the absence of integrated data visibility, many hospitals are relying on manual workarounds that can take months, and sometimes even years to implement—and in the end, may still fall short of delivering the level of insight needed. Learn how Partners HealthCare consolidated its disparate data warehouses, incorporating more than 27,000 data elements from multiple sources systems—and implemented on time and on budget. Partners’ enterprise data warehouse now serves as the analytics foundation for its overall value strategy.

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Effective Healthcare Data Governance: How One Hospital System is Managing its Data Assets to Improve Outcomes

As healthcare invests in analytics to meet the IHI Triple Aim, data has become its most valuable asset—and one of the most challenging to manage. Healthcare organizations must integrate data from a complex array of internal and external sources. To establish a single source of truth, The University of Kansas Hospital deployed an enterprise data warehouse (EDW). However, they quickly realized that without an effective data governance program clinicians and operational leaders would not trust the data. Led by senior leadership commitment, The University of Kansas Hospital established processes to define data, assign data ownership and identify and resolve data quality issues. They also have 70+ standardized enterprise data definition approvals planned for completion in the first year and have created a multi-year data governance roadmap to ensure a sustained focus on data quality and accessibility.

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Improving Healthcare Performance through Analytics and Cultural Transformation: One Healthcare Organization’s Journey

OSF HealthCare, a pioneer accountable care organization (ACO), was looking to deliver superior clinical outcomes, improve the patient experience, and enhance the affordability and sustainability of its services. OSF’s leaders recognized that to effectively achieve these goals, they needed to reinvent the organization’s performance improvement measurement and reporting system. In addition to deploying new analytics technology, OSF knew they needed to drive a cultural shift throughout the organization to embrace a data-empowered system. By engaging leadership, aligning the initiative with business strategies, and building data-driven clinical and operational improvement teams, OSF was able to save $9-12 million over three years—through both process improvement and cost avoidance. OSF also drove clinical performance improvements in key areas including heart failure and palliative care.

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How to Integrate an EHR into a Healthcare Enterprise Data Warehouse in Just 77 Days

Integrating EHR data into a healthcare enterprise data warehouse (EDW) can take years, depending on the EDW platform and data model. Crystal Run — a physician-owned medical group in New York with more than 300 physicians in 40 medical specialties — couldn’t wait that long. They need a solution that could integrate their EHR data in a matter of months, not years. Using a late-binding model, Crystal Run was able to integrate their EHR data in just 77 days, with easy-to-use tools for data acquisition and storage and metadata management. 

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Improving Healthcare Data Quality to Drive Lower C-Section Rates

Cesarean deliveries have become one of the most common surgical procedures performed in the United States each year.  Between 1998 and 2008, the rate of cesarean delivery in the United States rose by 50 percent — from 22-33 percent of all births. Many healthcare stakeholders have turned their attention to reducing this rate for clinical, financial and regulatory reasons. Read how this healthcare system developed a Women and Newborn’s population health registry and discovered they had to start first with addressing their healthcare data quality issues.

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To Build or To Buy a Healthcare Enterprise Data Warehouse? A Health System Experience

Many healthcare organizations are facing the decision to buy or build an enterprise data warehouse (EDW). Their home grown solution can’t scale to meet their growing healthcare analytics needs for population health and accountable care organizations. But, how do you they make the decision to buy or build. Learn how Crystal Run Healthcare, a physician-owned medical group in New York with more than 300 physicians in 40 medical specialties — made the decision to set aside its legacy EDW in favor of buying the Health Catalyst Late-Binding™ Data Warehouse and launched a scalable, cost-effective and platform in 54 days.

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The Fastest Way to Integrate Source Marts into a Healthcare Data Warehouse

Making sure data from source systems is moved quickly, accurately and consistently into an enterprise data warehouse (EDW) is an important task for Information Systems (IS) departments. Indiana University (IU) Health IS was tasked with increasing the value decision-makers get from their health system’s data – and doing it with fewer resources. Using the Health Catalyst Source Mart Designer IU Health achieved: a) 75 percent faster design and development of its’ Source Marts, b) well-structured data fields within their EDW, c) autonomy of data architects while ensuring enterprise supportability, and d) improved analysis through the use of meta data.

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