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.
Download
Annually in the U.S., one in three hospitalized patients experiences preventable harm, leading to over 400,000 deaths. These unacceptable rates of avoidable injury make improving patient safety a top priority for healthcare organizations.
Examples of preventable patient harm include wrong-patient order errors, ineffective blood management, hospital-acquired infections, opioid dependence, and more. Fortunately, health systems can use patient safety analytics tools and trigger-based surveillance systems to better understand the types of harm occurring at their facilities, recognize risk, and intervene to avoid adverse events.
Analytics-driven patient safety applications are helping health systems decrease rates of preventable harm by identifying and measuring adverse events and guiding interventions aimed at improvement. The following six examples show how organizations can leverage analytics tools to better understand patient harm their facilities and prevent it from occurring:
There are more than 600,000 wrong-patient orders each year in the U.S.—errors that occur when healthcare digital platform users mistakenly open the wrong patient chart and enter an order for the wrong patient. Retract-and-reorder triggers, which identify when an order has been placed for a patient, retracted, and re-ordered by the same clinician, have demonstrated effectiveness in determining the incidence of wrong-patient orders.
One healthcare organization, comprised of a specialty hospital and multiple clinics, sought to improve safety for its patients, focusing on identifying wrong-patient order errors. By using various detection methods for identifying wrong-patient errors and establishing triggers that detect when a wrong-patient order may have occurred, hospital and clinic staff can investigate instances. As a result, for the first time, the organization has comprehensive wrong-patient order data and the ability to understand the number of wrong-patient orders better, informing its strategies to reduce wrong-patient orders and improve patient safety.
Across the country, 14 million units of red blood cells (RBCs) are transfused annually, with an average of three units used per transfusion at the cost of $300 per unit. While RBC transfusion can save lives, it can also cause harm and is strongly associated with prolonged hospital stays as well as increased costs, morbidity, and early and late mortality.
UnityPoint Health created a task force to develop and implement a plan for maximizing blood management. The task force incorporated decision support to improve transfusion ordering in alignment with the transfusion standards. The health system also leveraged an analytics platform, which monitors the utilization of blood products, including predictive modeling to risk-adjust blood utilization specific to patient case-mix, and data down to the ordering provider level. With its blood management initiative, UnityPoint Health decreased unnecessary RBC transfusion by 58,089, reducing direct costs over six years by $17.4 million and avoiding exposure to RBC by transfusion for 15,601 patients.
Hospital-acquired infections Clostridioides difficile (HA-CDI), Clostridioides difficile, are a significant patient safety concern for healthcare organizations. In the U.S., an estimated 223,900 hospitalized patients develop HA-CDI, resulting in 12,800 deaths annually.
Community Health Network (CHNw) discovered its HA-CDI rate was higher than the national benchmark. The organization knew it needed to decrease infection rates, but without timely, meaningful data, leaders couldn’t identify where to focus improvement efforts. By leveraging a high-level, robust analytics system that allowed better access to data, team members determined where to focus their improvement efforts. CHNw achieved a 31.8 percent relative reduction in hospital-onset CDI rate per 10,000 patient days, with 33 HA-CDIs avoided, resulting in $855,000 in savings in one year.
Chronic knee and back pain associated with morbid obesity increases the risk for opioid dependence among patients undergoing bariatric surgery. Mission Health sought a comprehensive, data-driven, evidence-based approach to reduce opioid prescribing after bariatric surgery, decreasing the risk for misuse and harm. By using comprehensive enhanced recovery after surgery protocols with multimodal pain management interventions, Mission realized substantial reductions in opioid use for pain management among patients undergoing bariatric surgery. Results included a 29.3 percent relative reduction in the number of opioids prescribed during the intraoperative phase of surgery, a 35.4 percent relative reduction in opioids prescribed during post-anesthesia recovery, and 16.9 percent relative reduction in the number of opioids prescribed during the inpatient phase of surgery.
More than 21 percent of people in the U.S. report experiencing a medical error in their care, and 31 percent report an error in the medical care of a relative or friend. Despite a national push to improve the care in U.S. hospitals, lack of safety and resulting patient harm remain a significant concern to hospitals and patients, fueled by the fact that medical errors are now the third leading cause of death in the U.S.
Determined to improve patient safety, Allina Health turned to data analytics to standardize and expand safety event reporting. The organization plans to eventually develop a system of predictive alerts to respond to emerging safety concerns. By utilizing the analytics application and trigger tool, the health system has successfully identified more safety events than voluntary reporting alone, uncovered opportunities for improving patient care, and more.
In the U.S., sepsis impacts more than 1.5 million people annually, of which about 250,000 will die. Health Quest had pursued efforts to reduce sepsis mortality rates yet was unable to make sustainable gains, despite instituting several recommended prevention activities. The organization used analytics to support its collaborative, evidence-based, and data-driven approach to improve the early recognition and treatment of sepsis and improve sepsis mortality rates. Health Quest achieved a systemwide observed over expected (O/E) ratio for sepsis mortality of 0.72, saving 92 lives in 10 months. Health Quest also achieved a 57.1 percent relative reduction in catheter-associated urinary tract infection (CAUTI) standardized infection ratio, and a 30.7 percent relative reduction in C. diff infections.
Because patient harm drives up health system costs, when organizations leverage the right strategies and tools to avoid or reduce harm, they can save patient lives and improve experiences while also reducing costs. With over 400,000 avoidable patient-safety deaths per year, patient safety offers ample opportunities to improve healthcare delivery and, most significantly, save lives.
Would you like to learn more about this topic? Here are some articles we suggest:
Would you like to use or share these concepts? Download the presentation highlighting the key main points.
Click Here to Download the Slides
https://www.slideshare.net/slideshow/embed_code/key/NzGls2t3UYqZYb
