Four Effective Opioid Interventions for Healthcare Leaders

The crisis of opioid abuse in the U.S. is well known. What may not be so well known are the ways for clinicians and healthcare systems to minimize misuse of these addictive drugs. This article describes the risks for patients when they are prescribed opioids and the need for opioid intervention. It offers four approaches that healthcare systems can take to tackle the crisis while still relieving pain and suffering for the patients they serve:

1. Use data and analytics to inform strategies that reduce opioid availability
2. Adopt prescription drug monitoring programs to prevent misuse
3. Adopt evidence-based guidelines
4. Consider promising state strategies for dealing with prescription opioid overdose

Opioid misuse is a public health epidemic, but treatments are available and it’s time for those involved in the delivery of healthcare to change practices.

Improving Patient Safety: Machine Learning Targets an Urgent Concern

With over 400,000 patient-harm related deaths annually and costs of more the $1 billion, health systems urgently need ways to improve patient safety. One promising safety solution is patient harm risk assessment tools that leverage machine learning. An effective patient safety surveillance tool has five core capabilities:

1. Identifies risk: provides concurrent daily surveillance for all-cause harm events in a health system population.
2. Stratifies patients at risk: places at-risk patients into risk categories (e.g., high, medium, and low risk).
3. Shows modifiable risk factors: by understanding patient risk factors that can be modified, clinicians know where to intervene to prevent harm.
4. Shows impactability: helps clinicians identify high-risk patients and prioritize treatment by patients who are most likely to benefit from preventive care.
5. Makes risk prediction accessible: integrates risk prediction into workflow tools for immediate access.

Saving Lives: Effective Healthcare Communication Empowers Care Management

With an estimated 80 percent of medical errors resulting from miscommunication among healthcare teams, organizations can significantly improve outcomes with better communication. A communication methodology outlines the essential information clinicians need to share, giving care teams the knowledge they need, when they need it, to make informed treatment decisions. One communication toolkit, SBAR (Situation, Background, Assessment, Recommendation), defines the essential information clinicians must share when they hand off patient care from the inpatient to the ambulatory setting:

1. S (situation): The patient’s current situation.
2. B (background): Information about the current situation.
3. A (assessment): Assessment of the situation and background and potential treatment options.
4. R (recommendation): Recommended action.

Sepsis Treatment: Target Five Key Areas to Improve Sepsis Outcomes

More people in the U.S. die from sepsis than from prostate cancer, breast cancer, and AIDS…combined. Although health systems continue working to improve outcomes for septic patients, there is tremendous room for improvement. Preparing health systems to most effectively tackle sepsis starts with an awareness of consensus definitions of sepsis and continues with following evidence-based recommendations from credible organizations, such as the Surviving Sepsis Campaign and the Sepsis Alliance. Distilling ever-evolving recommendations and best practices for sepsis is time intensive. This article facilitates healthcare’s distillation effort by highlighting the five key areas health systems can target to improve sepsis outcomes (based on evidence-based guidelines and Health Catalyst’s first-hand experience with healthcare partners):

1. Early ED recognition
2. Three-hour sepsis bundle compliance
3. Six-hour sepsis bundle compliance
4. In-house recognition of sepsis
5. Sepsis readmissions: prioritize risk stratification

How to Use Data to Improve Patient Safety

Healthcare organizations have worked hard to improve patient safety over the past several decades, however harm is still occurring at an unacceptable rate. Though the healthcare industry has made efforts (largely regulatory) to reduce patient harm, these measures are often not integrated with health system quality improvement efforts and may not result in fewer adverse events. This is largely because they fail to integrate regulatory data with improvement initiatives and, thus, to turn patient harm information into actionable insight. Fully integrated clinical, cost, and operational data coupled with predictive analytics and machine learning are crucial to patient safety improvement. Tools that leverage this methodology will identify risk and suggest interventions across the continuum of care.