Although improvement has been made over time, hospitalized patients are still at a significant risk of harm from medical errors. Writing for the Wall Street Journal, Lauren Landro explains how hospitals are utilizing technology, including EMRs and artificial intelligence (AI) algorithms, to reduce the potential for medical errors and improve patient safety.
Over 20 years ago, a national patient safety movement was launched to reduce medical mistakes in hospitals. And while research has shown some improvement over time, many hospitalized patients are still at risk for medication errors, hospital infections, and more.
According to a study of data from 11 Massachusetts hospitals affiliated with Harvard Medical School, adverse events, which can cause serious harm, prolong hospital days, and even contribute to death, affected almost one in four patients who were hospitalized. Of these events, the researchers found that roughly a quarter could have been prevented with checklists and other safety measures.
The COVID-19 pandemic significantly strained the healthcare system. Therefore, many of the gains made to reduce medical errors were impacted.
According to David Westfall Bates, medical director of clinical and quality analysis for Mass General Brigham and the lead author of the study on Massachusetts hospitals, "[h]arm is still distressingly frequent in hospitals, but with wider adoption of robust interventions, many of which use new technology, we can make hospitals safer for patients."
Currently, many organizations are testing technologies, including EMRs and AI algorithms, to tackle different medical errors, including:
Mistakes with medications
According to Landro, "[m]edications are the common preventable sources of patient injury." Sometimes patients may get the wrong drug or the wrong dose of a drug. They may also experience unanticipated side effects from a certain drug.
To prevent medication errors, hospitals are using AI algorithms to scan EMRs for any signs or patterns that an error has occurred, such as a patient becoming oversedated. The algorithms can also notify clinicians of potential harm in real time by identifying changes in lab results that could be out of place.
At Cook Children's Medical Center, a patient safety risk software from Pascal Metrics is used to identify or prevent an adverse event, such as abnormal lab results, based on 41 triggers. For example, the tool has identified patients who were on three or more medications that could be toxic to their kidneys, which allowed pharmacists to notify physicians of potential risks and make changes as needed.
"This allows us to not only intervene but to look for trends and things that might be happening across the system," said Joann Sanders, Cook Children's chief quality officer, who noted that the program has been well received by clinicians. "It's not Big Brother watching, we know how hard your job is and we've got your back."
In the United States, as many as 1 million hospitalized patients fall each year, leading to fractures, cuts, and internal bleeding — often prolonging their hospital stays. According to researchers, the estimated cost of these falls ranges between $35,000 and $65,000 per patient.
In 2007, Brigham and Women's Hospital developed a program called Fall Tips (Tailoring Interventions for Patient Safety) to help prevent falls. The program was later enhanced through collaborations with other hospitals, including Montefiore Medical Center.
Through the program, nurses calculated a patient's fall risk using a scale with six common predictors. EMRs then automatically link each risk factor to a certain preventive action, such as scheduling assisted bathroom breaks.
These plans are reviewed by both the patient and their family at admission and reiterated to the patient at each shift change. "As patients become more knowledgeable about their risk factors and plans, they are less likely to fall," said Patricia Dykes, research program director at Brigham and Women's Center for Patient Safety, Research and Practice.
At Montefiore, Fall Tips has helped reduce total falls by 29% and total falls with injury by 35% since 2016. It has also helped the hospital save $6.5 million in associated costs, according to Maureen Scanlan, SVP and chief nurse executive at Montefiore.
Although surgeons often use checklists before a procedure to avoid potential mistakes, a study found that postoperative complications occur in as many as 15.5% of surgeries, leading to more than $19,000 in increased hospital costs per surgery.
At the University of Florida, researchers have created an AI system called "MySurgeryRisk" that predicts which patients have a higher risk of postsurgery complications and may need more care during or after an operation.
A study of 67 surgeons who used the algorithm found that the surgeons' initial predictions were more likely to underestimate the risk of certain complications, such as blood clot formation, and overestimate the risk of others, such as severe sepsis. After using the algorithm, the accuracy of surgeons' repeated risk assessment improved.
Overall, half of the surgeons in the study said they found the algorithm helpful, 25% were neutral, and the remainder did not find it helpful.
Hospitals have protocols in place to help them prevent infections, but adherence can be difficult when providers are overwhelmed with patients. To ensure that a checklist is followed, some hospitals are implementing quality and safety dashboards into their EMRs.
At Jefferson Health, a quality and safety dashboard helps reduce the risk of central line and urinary catheter infections. Clinicians can quickly identify in real time when caregivers are not following best practices and make necessary changes.
"Hospital units are able to quickly assess which clinical risks are in need of attention and rescue patients from the unintended and unanticipated complexity of daily work, which has gotten even more unpredictable with Covid," said Oren Guttman, an anesthesiologist and Jefferson's EVP for high reliability and patient safety.
Between January 2020 and December 2022, Jefferson's dashboard reduced central line infections by 25%. "The machines are no longer our tools, they are our partners," Guttman said. (Landro, Wall Street Journal, 3/12)
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