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Three Ways Evidence-Based Medicine Improves Machine Learning

As health systems continue to adopt machine learning to impact significant outcomes (e.g., reducing readmissions, preventing hospital-acquired infections, and reducing length of stay), they must also leverage evidence-based medicine. Evidence adds critical insight to machine learning models, ensuring that models incorporate all necessary variables in their risk prediction, and builds credibility among clinicians.
Evidence-based medicine brings three essential elements to healthcare machine learning:

Boosts machine learning model credibility.
Engages data experts around healthcare projects.
Saves time and money and increases ROI.

Introducing the Health Catalyst Monitor™ Patient Safety Suite: Surveillance Module

Unlike the standard post-event reporting process, the Patient Safety Monitor Suite: Surveillance Module is a trigger-based surveillance system, enabled by the unique industry-first technological capabilities of the Health Catalyst Data Operating System platform, including predictive analytic models and AI. The Health Catalyst PSO creates a secure and safe environment where clients can collect and analyze patient safety events to learn and improve, free from fear of litigation. Coupled with patient safety services, an organization’s active all-cause harm patient safety system is fully enabled to deliver measurable and meaningful improvements.

Improving Healthcare Outcomes: Keep the Triple Aim in Mind

The battle cry for healthcare organizations throughout the United States? Improve outcomes! However, as organizations begin to measure outcomes they realize not all outcomes are created equal and the question of what constitutes an improvement becomes more challenging. Healthcare leaders would be wise to keep the Triple Aim in mind when creating a strategy for optimizing outcomes. Achieving the appropriate balance among the three dimensions of the Triple Aim is critical to driving real, long-term change in healthcare delivery outcomes.

3 Ways to Decrease Nosocomial Infections in Hospitals

Health systems waste enormous amounts of money on treating and tracking nosocomial infections. Instead of waiting for hospital-acquired infections to surface, health systems should proactively work to prevent such easily preventable infections. These three suggestions will help health systems reduce the rate of nosocomial infections: 1) Use an EDW to reduce wasted tracking time. 2) Create a data-driven culture of commitment. 3) Manage the data on an enterprise level.

4 Ways to Reduce Penalties Under the Hospital-Acquired Condition Reduction Program

Hospitals with high rates of hospital-acquired conditions face steep financial penalties if they can’t adhere to CMS’ new rule. But by following these four tips, hospitals will decrease their risk of penalty for HACs: (1) Proactively evaluate, measure, and optimize critical care processes and outcomes.  (2) Put the right coding processes in place to accurately capture your patients’ POA data.  (3) Apply what you’ve learned to create a culture of safety. (4) Consider active surveillance systems to identify HACs and potential patient harm.

CMS Reporting Requirements – 4 Changes Hospitals Need to Know for 2014

Hospitals need to be proactive to avoid the penalties from CMS’ reporting measures. In specific, there are 4 changes to be aware of: 1) Value based purchasing will include two additional outcome measures: CLABSI and PSI. 2) The Readmissions Reduction Program will be expanded to include COPD and THA/TKA, plus there’s a proposed 3 percent penalty for readmission. 3) Under the new proposed HAC Reduction Program, hospitals with the highest rate of HACs will receive a 1 percent reduction in Medicare inpatient payments. 4) Medicare proposes to align reporting for the Electronic Health Record and Inpatient Quality Reporting.

Understanding Population Health Management: A Diabetes Example

Measuring is where successful population health management starts. You can’t do much to manage your diabetes population if you can’t accurately identify that population or see how your population is trending. Identifying diabetes patients and measuring compliance has been difficult in the past—but today, with a healthcare enterprise data warehouse (EDW) and analytics tools, it doesn’t have to be. (Your EMR won’t be enough.) By establishing an EDW, you create a data foundation that enables you to manage your diabetes population in sophisticated ways.

How to Decrease Hospital Acquired Infections with the Power of Healthcare Data

How much time do you routinely spend on hospital-acquired infection (HAI) surveillance activities and reporting for Central-Line Associated Bloodstream Infections (CLABSIs) and Catheter-Associated Urinary Tract Infections (CAUTIs)? CLABSIs and CAUTIs are largely preventable infections that typically result in longer patient stays, increased mortality, as well as increased care costs- estimated at over $20,000 per CLABSI. Do you wish you could decrease surveillance waste and spend more time preventing hospital acquired infections? A client of ours just reduced their time for CLABSI and CAUTI surveillance activities by 90%.