How Data Can Reduce Length of Stay and Keep the Revenue Stream Flowing

Many organizations face high costs and diminishing returns due to unnecessarily high length of stay (LOS) and readmission rates. Elevated LOS and readmission rates can indicate low quality care and also result in costly financial penalties. Therefore, addressing LOS and readmission rates can eliminate avoidable financial consequences, while keeping patients out of the hospital and less likely to develop hospital-acquired infections. Health systems can leverage analytic insight to reduce unnecessary patient LOS and readmission rates, resulting in lower costs for health systems and better health for patients, by applying three data-driven strategies:

1. Implement process changes.
2. Remove discharge barriers.
3. Improve care transitions.

Improving Sepsis Care: Three Paths to Better Outcomes

Sepsis affects at least 1.7 million U.S. adults per year, making it a pivotal improvement opportunity for healthcare organizations. The condition, however, has proven problematic for health systems. Common challenges including differentiating between sepsis and a patient’s acute illness and data access. In response, organizations must have comprehensive, timely data and advanced analytics capabilities to understand sepsis within their populations and monitor care programs. These tools can help organizations identify sepsis, intervene early, save lives, and sustain improvements over time.

Healthcare Safety Culture: A Seven-Step Success Framework

Preventable patient harm costs healthcare billions annually, making strategies to improve patient safety an imperative for health systems. To improve patient safety, organizations must establish a safety culture that prioritizes safety throughout the system, supports blame-free reporting of safety events, and ensures that healthcare IT solutions functions and accessibility align with safety goals. A sociotechnical framework gives health systems a seven-part roadmap to improving patient safety culture:

1. Leverages qualitative and quantitative data.
2. Doesn’t rely on HIMSS stage levels to tell the complete safety picture.
3. Gives frontline clinicians a voice in decision making.
4. Makes IT solutions accessible to non-technical users.
5. Encourages frontline clinicians to report safety and quality issues.
6. Treats a safety issue in one area as a potential systemwide risk.
7. Performs thorough due diligence before taking safety IT solutions live.

Six Ways Health Systems Use Analytics to Improve Patient Safety

With preventable patient harm associated with over 400,000 deaths in the U.S. annually, improving safety is a top priority for healthcare organizations. To reduce risks for hospitalized patients, health systems are using patient safety analytics and trigger-based surveillance tools to better understand and recognize the types of harm occurring at their facilities and intervene as early as possible. Six examples of analytics-driven patient safety success cover improvement in the following areas:

1. Wrong-patient order errors.
2. Blood management.
3. Clostridioides difficile (C. diff).
4. Opioid dependence.
5. Event reporting.
6. Sepsis.

A More Accurate Sepsis Identification Method: Leveraging Physiological Data

The traditional sepsis identification method—based on a combination of physician notes, coding, and billing—is often varied and too subjective, leading to inaccurate data. Because margins are tight and health systems can’t afford to waste any resources, clinical teams need to start with the most effective sepsis identification method. Using physiological data, such as vital signs, to identify sepsis is proving to be highly effective. With the physiological data approach, providers rely on the body’s response—rather than being steered by biases, anecdotal information, or reimbursement rates—to more accurately identify patients with sepsis. With a more effective approach to sepsis identification, providers can implement interventions sooner, leading to better outcomes.

Improving Patient Safety: Lessons from a Military Operations Framework

The operational military concept known as “left of bang” endorses continuous situational awareness to avoid harm proactively—before it occurs. Healthcare, however, operates reactively in response to patient harm, often intervening once a patient safety event has occurred, versus using practices and tools to recognize and respond to threats. Applied to patient safety, a left-of-bang approach teaches frontline clinicians to increase sensitivity to and stay in constant vigilance for threats before they happen, moving down a scale of situational awareness levels:

1. White: Tending to the tasks at hand but largely unprepared for disruption and unaware of the conditions around them.
2. Yellow: Constantly understanding the safety vulnerabilities of day-to-day healthcare.
3. Orange: Ready to use the needed skills and tools to react to an event.
4. Red: Taking action and laser focused on the issue at hand.

Engaging Health System Boards of Trustees in Quality and Safety: Six Must-Know Guidelines

The quality and patient safety movement of the early 21^st century called for greater board of trustee involvement in improvement. However, too many health systems still don’t have the resources in place to effectively engage their boards around quality and safety measures. Six guidelines describe how organizations can better leverage data to inform their boards:

1. Emphasize quality and patient safety goals.
2. Leverage National Quality Forum-endorsed measures.
3. Use benchmarking and risk adjustment to select targets.
4. Access data beyond the EHR.
5. Provide data and information for multiple organizational levels.
6. Develop a board-specific measurement and presentation strategy.

How to Use Data to Improve Quality and 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.

Patient Safety Best Practices E-Book: The Intersection of Patient Care and Technology

Patient safety is a top concern for healthcare organizations. Fortunately, health IT assists leadership and frontline clinicians in the ongoing effort to improve patient care. This e-book comprises ten articles outlining the intersection of technology and patient care, highlighting how organizations can implement patient safety best practices.

Preventing Medication Errors: A $21 Billion Opportunity

With a potential industry-wide savings of almost $21 billion and an impact on more than seven million patient lives, preventing harmful medication error is a significant improvement opportunity for health systems. Also known as adverse drugs events (ADEs), harmful medication errors comprise about 37 percent of all medical harm. Approximately 50 percent of ADEs are preventable, making their reduction a highly impactable area of patient safety. Current data and analytics workflow tools are making ADE surveillance, monitoring, and prevention increasingly more effective with four key capabilities:

1. Perspective surveillance for ADEs and identification of previously undescribed ADEs.
2. Identification of the root cause of many ADEs by drug class.
3. Prescription at appropriate doses for patients with compromised kidney or liver functions.
4. Identification of different types of harm to find causes.

A Framework for High-Reliability Organizations in Healthcare

Drs. Allen Frankel and Michael Leonard have developed a framework for creating high-reliability organizations in healthcare. This report, based on their 2018 webinar, covers the components and factors of this frame work, including:

• Leadership
• Transparency
• Reliability
• Improvement and Measurement
• Continuous Learning
• Negotiation
• Teamwork and Communication
• Accountability
• Psychological Safety

Meaningful Machine Learning Visualizations for Clinical Users: A Framework

Health systems can leverage the predictive potential of machine learning to improve outcomes, lower costs, and save lives. Machine learning, however, doesn’t inherently produce insights that are actionable in the clinical setting, and frontline clinicians need information that’s accessible and meaningful at the point of care. Thoughtfully designed visualizations of machine learning insights are a powerful way to give clinical users the information they need, when and how they need it, to support informed decision making. A design framework for machine learning visualizations addresses three key questions about who will use the decision-support insights and how:

1. People: who are the targeted users?
2. Context: in what context or environment do they work?
3. Activities: what activities do they perform?

Six Steps to Managing an Infection Control Breach

Despite widespread efforts to improve patient safety, infection control breaches still happen at an alarming rate. In order to improve patient safety and prevent infections, healthcare organizations need to have infection control procedures in place and regularly assess protocols and adherence to these policies. In the case of an infection control breach, organizations need to be prepared to act quickly and follow a six-step evaluation procedure outlined by the CDC:

1. Identify the infection control breach.
2. Gather additional data.
3. Notify and involve key stakeholders.
4. Perform a qualitative assessment.
5. Make decisions about patient notification and testing.
6. Handle communications and logistical issues.

Survey Shows the Role of Technology in the Progress of Patient Safety

A lack of effective technology is impeding the progress of patient safety, according to a 2018 survey of healthcare professionals. Even though most healthcare organizations claim safety as a priority, serious challenges remain to making a significant impact on patient safety outcomes. Survey respondents said ineffective information technology and the related lack of real-time warnings for possible harm events were the top barriers to improving patient safety. They cited a number of key obstacles:

1. Lack of resources.
2. Organization structure.
3. Lack of reimbursement for safety measures.
4. Changes in patient population.

This survey of more than 400 healthcare professionals tackles a big question many hospital leaders are asking: Why aren’t we seeing improvements in patient safety despite our efforts?

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.

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.