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.
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:
Leverages qualitative and quantitative data.
Doesn’t rely on HIMSS stage levels to tell the complete safety picture.
Gives frontline clinicians a voice in decision making.
Makes IT solutions accessible to non-technical users.
Encourages frontline clinicians to report safety and quality issues.
Treats a safety issue in one area as a potential systemwide risk.
Performs thorough due diligence before taking safety IT solutions live.
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:
Wrong-patient order errors.
Clostridioides difficile (C. diff).
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.
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:
White: Tending to the tasks at hand but largely unprepared for disruption and unaware of the conditions around them.
Yellow: Constantly understanding the safety vulnerabilities of day-to-day healthcare.
Orange: Ready to use the needed skills and tools to react to an event.
Red: Taking action and laser focused on the issue at hand.
The quality and patient safety movement of the early 21st 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:
Emphasize quality and patient safety goals.
Leverage National Quality Forum-endorsed measures.
Use benchmarking and risk adjustment to select targets.
Access data beyond the EHR.
Provide data and information for multiple organizational levels.
Develop a board-specific measurement and presentation strategy.
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 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.
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:
Perspective surveillance for ADEs and identification of previously undescribed ADEs.
Identification of the root cause of many ADEs by drug class.
Prescription at appropriate doses for patients with compromised kidney or liver functions.
Identification of different types of harm to find causes.
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:
Improvement and Measurement
Teamwork and Communication
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:
People: who are the targeted users?
Context: in what context or environment do they work?
Activities: what activities do they perform?
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:
Identify the infection control breach.
Gather additional data.
Notify and involve key stakeholders.
Perform a qualitative assessment.
Make decisions about patient notification and testing.
Handle communications and logistical issues.
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:
Lack of resources.
Lack of reimbursement for safety measures.
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?
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.
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:
Use data and analytics to inform strategies that reduce opioid availability
Adopt prescription drug monitoring programs to prevent misuse
Adopt evidence-based guidelines
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.
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:
Identifies risk: provides concurrent daily surveillance for all-cause harm events in a health system population.
Stratifies patients at risk: places at-risk patients into risk categories (e.g., high, medium, and low risk).
Shows modifiable risk factors: by understanding patient risk factors that can be modified, clinicians know where to intervene to prevent harm.
Shows impactability: helps clinicians identify high-risk patients and prioritize treatment by patients who are most likely to benefit from preventive care.
Makes risk prediction accessible: integrates risk prediction into workflow tools for immediate access.
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:
S (situation): The patient’s current situation.
B (background): Information about the current situation.
A (assessment): Assessment of the situation and background and potential treatment options.
R (recommendation): Recommended action.
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):
Early ED recognition
Three-hour sepsis bundle compliance
Six-hour sepsis bundle compliance
In-house recognition of sepsis
Sepsis readmissions: prioritize risk stratification
Evidence-based medicine is an important model of care because it offers health systems a way to achieve the goals of the Triple Aim. It also offers health systems an opportunity to thrive in this era of value-based care. In specific, there are five reasons the industry is interested in the practice of evidence-based medicine: (1) With the explosion of scientific knowledge being published, it’s difficult for clinicians to stay current on the latest best practices. (2) Improved technology enables healthcare workers to have better access to data and knowledge. (3) Payers, employers, and patients are driving the need for the industry to show transparency, accountability, and value. (4) There is broad evidence that Americans often do not get the care they need. (5) Evidence-based medicine works. While the practice of evidence-based medicine is growing in popularity, moving an entire organization to a new model of care presents challenges. First, clinicians need to change how they were taught to practice. Second, providers are already busy with increasingly larger and larger workloads. Using a five-step framework, though, enables clinicians to begin to incorporate evidence-based medicine into their practices. The five steps include (1) Asking a clinical question to identify a key problem. (2) Acquiring the best evidence possible. (3) Appraising the evidence and making sure it’s applicable to the population and the question being asked. (4) Applying the evidence to daily clinical practice. (5) Assessing performance.
Healthcare’s journey to improving care and reducing preventable medical errors is a difficult one. But those who embrace the changes are finding new, exciting opportunities. Some of the new realities are reflected in the American Board of Medical Specialties Maintenance of Certification program: Professionalism, Patient care, Medical knowledge, Practice-based learning and improvement, Interpersonal and communication skills, and Systems-based practice. While this has created considerable friction, it is possible to make this shift as part of an integrated practice, like Mayo Clinic and M.D. Anderson Cancer Center have done. Healthcare needs an environment to better manage complexity, not add to it. This is possible and it is happening today.