 PDF Version |
Innovations: Designed for Patients, Built for Results
An ED in Pennsylvania has dramatically reduced wait times, lowered – nearly eliminating – left-with-out-being-seen (LWBS) rates, and improved patient satisfaction rates by turning the old triaging paradigm on its head.
Instead of using acuity as the main lever for determining how a patient gets routed through the ED, Penn State Hershey Medical Center’s (PSU-HMC) department of emergency medicine decided to approach the issue of long waits and crowding from a new standpoint: through the eyes of the patient.
PSU-HMC is a Level I trauma center caring for 50,000 patients annually in a 29-bed facility originally designed to care for 33,000 patients. Crowding was a problem with an LWBS rate of 5-10%, door-to-doctor time of 90 minutes and a total length of stay over seven hours. They came to a crossroads when a consultant advised them they were loo
king at a $20 million dollar, 20,000 square foot expansion project based on their volume. Lacking resources, Dr. Chris DeFlitch, Vice Chair of Emergency Medicine and PSU-HMC Chief Medical Information Officer, rose to the challenge of finding a solution to the crowding problem.
king at a $20 million dollar, 20,000 square foot expansion project based on their volume. Lacking resources, Dr. Chris DeFlitch, Vice Chair of Emergency Medicine and PSU-HMC Chief Medical Information Officer, rose to the challenge of finding a solution to the crowding problem.The traditional model of ED care often involves long waits, or queues, for check-in, triage, procedures, tests, admission, and discharge. Timeliness of care is strongly correlated with patient satisfaction. Having familiarized himself with queuing theory and tapping into his experience in mapping processes, DeFlitch knew that effective management of patient flow and waiting time increases the safety, effectiveness, and patient-centeredness of care. DeFlitch and a team comprised of members from PSU’s department of emergency medicine, industrial engineering and information technology set out to improve efficiencies and develop strategies for maximizing interval steps in processes, and wait times.
Engineering a New Paradigm
The team examined existing ED processes, using operational data such as patient arrival rates, length of stay, door-to-doctor times, room utilization, and staffing. Process flowcharts helped identify bottlenecks and inefficiencies. It became evident that waits were inherent in the traditional processes of ED care – some wasteful, others necessary. Using queuing theory, process mapping, and other healthcare engineering methods, DeFlitch developed a new system, Physician Directed Queuing (PDQ), to systematically address these queues and reduce door-to-doctor time by allowing diagnostic and therapeutic actions to occur closer to a patient’s time of arrival.
The team examined existing ED processes, using operational data such as patient arrival rates, length of stay, door-to-doctor times, room utilization, and staffing. Process flowcharts helped identify bottlenecks and inefficiencies. It became evident that waits were inherent in the traditional processes of ED care – some wasteful, others necessary. Using queuing theory, process mapping, and other healthcare engineering methods, DeFlitch developed a new system, Physician Directed Queuing (PDQ), to systematically address these queues and reduce door-to-doctor time by allowing diagnostic and therapeutic actions to occur closer to a patient’s time of arrival.
The PDQ Experience
Instead of utilizing a waiting room where patients wait for a provider, PDQ places a provider at the physical place of patient arrival. This provider is used to determine the queues, if any, that the patient will experience and the different components of their total ED visit – arrival, care, wait times and locations, registration. DeFlitch says the department has experienced a paradigm shift.
Instead of utilizing a waiting room where patients wait for a provider, PDQ places a provider at the physical place of patient arrival. This provider is used to determine the queues, if any, that the patient will experience and the different components of their total ED visit – arrival, care, wait times and locations, registration. DeFlitch says the department has experienced a paradigm shift.
When a patient enters the ED, they find a greeting area, but no waiting room. “There are a couple of chairs in the front to help people in case they stumble into the ED, but there’s no waiting area on arrival,” says DeFlitch. Patients complete a quick, initial registration (name, address, primary complaint). A provider team that includes a nurse, ED technician and a physician or physician assistant then conducts a triage assessment. The provider conducts a medical evaluation and, as necessary, orders tests, or sends the patient to an ED room for complex resuscitative care. While critical patients are sent immediately to a room, many patients can be treated and discharged without using a room. “Whenever patients need to wait, they’re waiting with value – as opposed to waiting for a room before care is initiated,” says DeFlitch.
DeFlitch explains: “Care is a process. The essential piece is matching the provider and patient in time and space. Moving people through the ED has allowed us to create a different kind of treatment space using virtual beds. Now, they get taken care of in a limited diagnostic queue.”
Suppose a patient with head injury enters: while the case is deemed high acuity, it’s categorized as a case requiring relatively low resource use. The required CT scan and neurological evaluation can be performed by a physician quickly using limited resources. “This differs from a traditional physician at triage model by defining resource utilization on arrival of the patient,” explains DeFlitch. On the other hand, low acuity laceration repairs are considered high resource utilization, based upon the time required for care.
From Theory to Results
DeFlitch and the team put PDQ through a battery of testing, modeling, simulation and refinement. Before the March 2009 completion of the ED renovation, they piloted the new process without adding any new staff. Results were astonishing. The left-without-being-seen rate dropped from 5.6% to 2.7%, and the total length of stay was reduced by two hours. Door-to-doctor time fell from 90 to 60 minutes accompanied by an increase in patient and provider satisfaction.
DeFlitch and the team put PDQ through a battery of testing, modeling, simulation and refinement. Before the March 2009 completion of the ED renovation, they piloted the new process without adding any new staff. Results were astonishing. The left-without-being-seen rate dropped from 5.6% to 2.7%, and the total length of stay was reduced by two hours. Door-to-doctor time fell from 90 to 60 minutes accompanied by an increase in patient and provider satisfaction.
The team built a simulation model to examine how PDQ would perform under different scenarios (varying patient loads), and used th
e results to inform the design of the expanded ED. PDQ results (July 2009-July 2010) continued their upswing after the completion of the renovation in March 2009. Using this data, a physical plant was constructed expanding the ED by only 7,000 square feet at a cost of about six million dollars. By July 2010, despite a volume increase to over 60,000 visits per year, the door-to-doctor time decreased to 18 minutes, the total length of stay was reduced from 6 to 3 hours, and the LWBS rate was nearly eliminated (0.4%). Patient satisfaction rose from the 17th to the 75th percentile.
e results to inform the design of the expanded ED. PDQ results (July 2009-July 2010) continued their upswing after the completion of the renovation in March 2009. Using this data, a physical plant was constructed expanding the ED by only 7,000 square feet at a cost of about six million dollars. By July 2010, despite a volume increase to over 60,000 visits per year, the door-to-doctor time decreased to 18 minutes, the total length of stay was reduced from 6 to 3 hours, and the LWBS rate was nearly eliminated (0.4%). Patient satisfaction rose from the 17th to the 75th percentile.Patient’s-Eye View
According to DeFlitch,“It comes down to understanding your operational data that includes both patient and family experiences, and using that to your advantage when you create a system of care like PDQ, or a physical plant to support that system of care.” With PDQ firmly entrenched at the hospital, patient complaints “went away almost completely,” says DeFlitch. “Patients would say, ‘I brought my book, but I didn’t even get to open it.’”
According to DeFlitch,“It comes down to understanding your operational data that includes both patient and family experiences, and using that to your advantage when you create a system of care like PDQ, or a physical plant to support that system of care.” With PDQ firmly entrenched at the hospital, patient complaints “went away almost completely,” says DeFlitch. “Patients would say, ‘I brought my book, but I didn’t even get to open it.’”
The impact of PDQ on the culture of the ED has been dramatic. DeFlitch says, “When we used the traditional model, patients were irritated with the wait, and their first attitude toward the care provider was of anger, frustration and annoyance. Once we initiated the pilot, people finally understood that if we can exceed patients’ expectations upon arrival, it makes your life as a provider so much easier. Patients are much more pleasant and providers are much happier.”
Chris DeFlitch, MD, Vice Chair of Emergency Medicine and PSU-HMC Chief Medical Information Officer
