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Health System Management • January 2017

18 WWW.HEALTHSYSTEMMGMT.COM PRIVACY/SECURITY HEALTH SYSTEM MANAGEMENT | JANUARY | 2017 hospitals under 1% actually, but anything above 2% starts to get to be too high,” he said. “We’ll commonly see hospitals that are at 3% to 10%. Years ago it used to be as high as 15% or more.” If the ED is full, patients who are in the ED waiting room or lobby need to be triaged and treated. Philips helps hospitals find solutions to address this bottleneck. One solution is for hospitals to use the Emergency Severity Index (ESI) to prioritize patient movement. The ESI index categorizes patients into five different levels, with one being the most urgent, and five the least urgent. “If the hospital is not full, we recommend that all patients are immediately bedded and seen by the provider in order to expedite care,” said Feinberg. “What we find in many hospitals and what we end up working with them on is that their practice of ESI-based triage is quite variable and inconsistent,” Feinberg related. “What one nurse might consider a four, another could say is a three.” However, it’s important to use this index correctly because it’s a resource-based system. “If you’re not triaging appropriately,” said Feinberg, “you’re misallocating your resources to care for those patients when they come to the ED.” PAY ATTENTION TO PATIENT TREATMENT It’s also important for hospitals to pay attention to the way that patients are treated by nursing and provider staff from the moment they are greeted until they leave the organization. Does the ED have nursing-instituted protocols? How do the physicians work with the nurses? What processes does the ED have to care for the discharged or admitted patient awaiting a bed upstairs? Once patients have received treatment, whether they are admitted or discharged, how are they transitioned out of the ED? According to Feinberg, it’s not uncommon for a discharged patient to wait another 30 or 60 minutes to actually leave. Patients awaiting a bed can be as long as 12 to 36 hours — which is unimaginable for the public, who expect timely inpatient hospital care. “Those are the projects that we undertake with the idea that we’re going to remove the inefficiencies in the department and the hospital,” Feinberg said. “We streamline the way the patients are moved in and out of the department, and make them more effective utilizers of the resources that they need in the department so they have more time focusing on patient care and less time doing non-value-added activities.” RESULTS According to Feinberg, by implementing data-driven decision making into ED operations, hospitals typically see a greater velocity of patients through the ED, all with their original staff. Feinberg remarked, “It’s not uncommon that we’ll work with a department that said, ‘On a typical day we would see 150 or 160 patients, but once we got to about 165 or 170, it felt like the wheels were falling off the bus. But now we’re seeing 175 or 180, and it seems like a normal day.” Employing a data-driven approach to ED operations can also reduce the percentage of LWBS patients, which leads to additional revenue for volume-based EDs. “That is additional revenue that the organization is expecting,” he said. “There is a financial benefit that comes back to the organization for being able to care for patients in an effective and efficient manner.” “At the end of the day, whether you’re a value-based or volume-based emergency department,” Feinberg said, “if patients come to the ED for care and they have to leave because they are not receiving care in a timely manner and they go somewhere else because it’s faster, that’s just not good community relations. Hospitals have the obligation to treat all patients with the consideration of the dimensions of quality, and those include effective, efficient, timely and patient-centered. Not because they have to, but because it’s the right thing to do.” To illustrate the efficacy of data-driven decision making, Feinberg shared an example of a 460-bed (48,000 annual visits) community hospital that was not meeting its ED expected performance and wait-time targets. By implementing data-driven decision making, the hospital was better able to assess issues and collect relevant data to improve patient care and throughput. As a result, the ED experienced significant improvement in arrival-to-triage rate (68%) and arrival-to-room (77%) rates, compared to its baseline. It also decreased its LWBS rate by 51%. This decrease in ED walk-outs generated over $2 million in annual additional collectable revenue for the organization. “There is a financial benefit that comes back to the organization for being able to care for patients in an effective and efficient manner.” Mark Feinberg WEBEXTRA One key element of improving the emergency department experience is reducing wait times. For strategies to meet this challenge, read “How to Shorten Emergency Room Wait Time” at www. HealthSystemMgmt.com


Health System Management • January 2017
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