5 ways automation can help reduce adverse events in labor and delivery

The labor and delivery floor is the one place in the hospital where everyone going in is happy.  The excitement and expectation of a healthy new baby is almost universal. So, when things go wrong, bad outcomes are uniformly crushing — to the family, the clinicians, the reputation of the hospital and the hospital's balance sheet.

With so much at stake, clinicians and hospital administrators are recognizing the need to rely less on subjective, anecdotal assessments and more on exacting, computational data.

Obstetric claims typically account for the first or second highest-risk service within a hospital.  A 2010 study published by CRICO, a medical malpractice company owned by and serving the Harvard medical community, shows OB claims costing twice as much as those in other departments —$980,000 on average.  This same study estimates that approximately one in 1,000 births (more than 4,000 annually) involve a preventable adverse outcome, primarily in the active stage of labor. That frequency and that average expense should sound alarm bells for organizations moving toward accountable care and other shared-risk, value-based models.  In a litigious society that views hospitals and physicians as "deep pocket" defendants, hospitals need to reduce their financial exposure by reducing their risk of preventable adverse events during L&D. Automation should be able to help here, but legacy fetal monitoring and surveillance systems fall far short of what our clinicians need.

One of the most significant factors affecting quality in L&D is that many decisions made around labor progress are subjective, and there is generally significant variation even within a unit. They depend on the knowledge and experience of nurses interpreting the paper strips with limited information from legacy electronic fetal monitors developed more than 10 years ago. If the nurse believes there is a problem, she or he must then convince the physician the readings are cause for concern.

That may not be difficult when the labor is category 1 or category 3, where the course of action is clear. But for category 2, where 75 to 80 percent of labors fall, making a definitive interpretation using paper EFMs and convincing a physician that the situation requires leaving a waiting room full of patients can be challenging.

This is where automated clinical decision support will be a necessity in an outcomes-based environment. Since the most common cause of L&D-related claims is for fetal monitoring hypoxia (a deceleration in the fetal heart rate) being able to depend on hard data based on clinical analytics from thousands of previous EFM patterns rather than relying on opinions, subjective interpretations and persuasive skills can reduce adverse events and claims by 40 percent — a huge plus for patients, nurses, physicians and hospitals.

Following are five ways this type of next generation technology can help reduce L&D adverse outcomes:

1. Removes subjective interpretation. In any healthcare quality initiative, one of the first goals is to standardize care around best practices. But that is difficult to do when one of the most impactful variables is how the nurse interprets the readings on a legacy paper fetal monitoring strip. Even the best can overlook an indicator, especially when one nurse is tending to several patients in active labor. Next-generation automation technology removes that variable by comparing current and previous fetal heart tracings to evidence-based guidelines and alerting nurses in real time when non-reassuring trends such as late deceleration or uterine tachysystole  — excessive uterine contractions — are occurring. It also acts as a training tool for new or inexperienced nurses (such as those in small rural hospitals that don't experience many births) and as a safety net/second opinion for all.

2. Allows nurses to communicate facts. When L&D nurses escalate issues to the physician, they often meet resistance because physicians know the information is subjective. With evidence-based automated bedside pattern recognition and analysis, nurses relay hard data, helping them escalate issues more effectively. This is particularly true when the technology has been officially validated by an outside source, such as National Institutes of Health. In a review of one technology, three experts selected by the NIH agreed with the technology's interpretation of the data 97 percent of the time — which is more than they agreed with each other. Presenting this type of hard evidence promotes collaboration and agreement about the need to take action.

3. Identifies non-reassuring trends earlier. Subtle changes in fetal heart rates may be easy to miss in the early stages, especially at the end of a long shift when nurses are tired. But the sooner they're caught monitored and addressed if necessary, the better the outcome. Automated monitoring with easy-to-read visual cues immediately recognizes even subtle trends that are difficult to see with the naked eye and creates a notation that is clear and obvious. It provides the information nurses need based on pre-determined protocols.

 4. Eliminates manual calculations of contractions. With legacy strips, nurses must review the readings at specific intervals and calculate contractions manually. These calculations, while necessary, take away from nurses' ability to provide care to the mother and fetus. They also introduce the possibility of human error. Next-generation EFM technology removes those issues by performing all the calculations automatically and providing trending data. Nurses can see instantly if there is an issue and address it based on hospital best practice protocols. For example, any nurse on the floor of one hospital is empowered to stop the administration of Pitocin immediately if UT occurs during an induction, eliminating a risk factor for serious injury to the fetus.

5. Easily provides a longer-term view. Legacy technologies relying on paper strips typically offer a 15-minute view on the monitor screen. Yet that is often not enough time to spot trends or problems. Nurses can look at earlier paper printouts, but, in a labor lasting hours, this method is impractical and wastes valuable time. Next-generation surveillance technology offers a much longer view on the monitor screen — sometimes up to two hours — to automatically look across a long labor and spot developing trends early. Nurses can then zero in on potential trouble spots.

When things go well in L&D, it is the happiest place in the hospital. When they don't, however, it can be the darkest. Next generation automated EFM and decision-support technology has been proven effective in reducing adverse outcomes by approximately 40 percent, helping ensure better results for patients, clinicians and the hospital's bottom line.

Matthew Sappern is CEO of PeriGen, Inc., the global leader in fetal surveillance systems employing patented, pattern-recognition and obstetrics technologies to improve perinatal outcomes. He has also served in leadership roles at Allscripts, Eclipsys, WebMD, Time Warner, Primedia and Young & Rubicam.

More articles on healthcare quality:
BCBS of Michigan starts statewide anesthesiology patient safety program  
St. Elizabeth Physicians to post patient satisfaction scores on website  
Antibiotic resistance: 4 areas of progress, 6 challenges 

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