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HealthCatalyst Recommends
Dr. John Haughom

Decision Support: Why the Executive Dashboard Is a Healthcare CEO’s Best Advisor

Healthcare CEOs and other C-Suite leaders can’t make quality decisions in today’s rapidly changing, complex environment without decision support.

Healthcare CEOs are starting to realize that executive dashboards with personally tailored views of key metrics are no longer a luxury, but an absolute necessity, for three key reasons:

  • Helps leaders analyze and digest large amounts of data relating to care quality, operations, contracting, and major purchasing decisions.
  • Gives leaders a clear understanding of the financial aspects of their systems, such as revenue streams, cost drivers, costs of capital, bundled payments, and payment reforms.
  • Facilitates conflict resolution and helps leaders work collaboratively—using a matrix management approach—with peers, direct reports, and system experts.

Today’s healthcare CEO must be skilled problem solvers, strategic and analytical thinkers, and collaborative leaders who understand both the clinical and financial sides of healthcare—goals made possible with an executive dashboard.

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Dr. Ed Corbett

The Real-World Benefits of Machine Learning in Healthcare

Machine learning in healthcare is already proving its worth in clinical applications. From identifying tumors in mammograms, to diagnosing skin cancer and diabetic retinopathy from images, algorithms can perform certain duties more quickly and reliably than humans. While only used for specialized medicine now, the time will come where every practitioner and patient will benefit from cyber-assisted bedside care. This won’t develop without ethical implications, but the advantages that machine learning will bring to healthcare in terms of lower costs, improved quality of care, and greater provider and patient satisfaction, will easily outweigh those concerns.

In this article, Dr. Ed Corbett explores the intricacies of machine learning from two perspectives: as a physician and as a family caregiver with a personal story about how this data science could benefit patient lives today.

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Data-Driven Process Improvement Raises Patient Safety for Highest-Risk Medication

Intravenous (IV) heparin is widely used to prevent thrombosis in a variety of clinical settings, yet it is considered one of the highest-risk medications used in the inpatient setting because of the potential for dosing errors. Allina Health identified multiple IV heparin protocols among its hospitals, a variation that increased the risk of errors. Standard practices that addressed patients’ clinical needs in a disease-specific way were lacking. Over the course of 1.5 years, more than 9,000 patients at Allina Health had an IV heparin protocol ordered, so IV heparin safety was of utmost concern.

To address this quality issue and improve clinical value, Allina Health created a systemwide interdisciplinary team to standardize IV heparin therapeutic guidelines and monitor the impact of the standard guideline on patient outcomes. Allina Health engaged multiple physician stakeholder groups to review proposed protocols and provide critical feedback to help ensure the best possible patient care and safety. To effectively monitor IV heparin outcomes, patient safety, and the impact of the new, standard guidelines and protocols, Allina Health developed an anticoagulation safety analytics application, using the Health Catalyst Analytics Platform, including the Late-Binding™ Data Warehouse and broad suite of analytics applications. These outcomes improvement efforts resulted in:

  • A seven percent relative improvement in the percentage of patients therapeutic within 24 hours of protocol initiation.
  • Paring 20+ site-based documents (e.g., policies, protocols, and order sets) to one systemwide guideline and four systemwide protocols.
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Health Catalyst

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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