Door to Doc (D2D) Reduces ED Patient “Walkout” Rate Twila Burdick Banner Health

Objectives Recognize ED patient flow as a patient safety problem Describe improved patient flow using ED Door to Doc (D2D) Split Patient Flow model Discuss approach for implementing D2D in diverse ED settings Show impact of D2D on patient safety

ED Patient Safety Challenge Capacity constrained EDs Increased visits Holding inpatients Long waits for patients arriving Patients deteriorating in the waiting room Patient complaints, patient dissatisfaction Patients leaving without treatment self-diagnosis is not safe! Long waits to see an ED physician related to LWOTs Issues with ED crowding are pretty well known (increasing visits, not enough ip beds, pts getting sicker as they wait, being unhappy) and patients leaving without being seen Banner began to understand it not just as an “inconvenience” but as a ‘patient safety’ issue—the literature confirmed our conclusion. “A study of the consequences of leaving the emergency department prior to a medical evaluation at one public hospital found that 46 percent of those who left were judged to need immediate medical attention, and 11 percent who left were hospitalized within the next week.”[1] “At follow-up, patients who left without being seen were twice as likely as those who were seen to report that their pain or the seriousness of their problem was worse.”[2] “Of the children who left without being seen, 24 (15%) were triaged as "urgent," and none had a CTAS score of less than 3…Our finding that 15% of patients who left without being seen had been triaged as "urgent" is of concern.”[3] “Forty-six percent of those who left were judged to need immediate medical attention, and 29% needed care within 24 to 48 hours.”[4] “Overall, 60% of LWBS (Left Without Being Seen) cases sought medical attention within one week; 14 patients were hospitalized, and one required urgent surgery.”[5]

Improving ED Safety Challenge: Idea: How to get patients seen by ED physicians sooner in overcrowded, busy EDs across Banner Health Idea: Apply “science of throughput” to change patient flow and reduce delays Start with D2D “straw model” Implement in diverse EDs Once we recognized the impact on patient safety, our challenge was clear—get patients to docs sooner Our IDEA was to use “science” of throughput (based on what we were learning from ASU), start with a model developed at one of our facilities, and see if we could implement this in diverse ED settings.

Designing D2D ED Improvement/Design Oversight Team Care Transformation Clinical Risk Intervention Throughput AHRQ Grant Productivity Common Launch: Learning Session Clarification of Multiple Outcomes Oversight Process Defined Phasing Described Work Design Work Team with Representation from all Stakeholders Dedicated, nearly full time effort for up to 4 weeks Start with “straw model” based on best practices Physician Work Group Consistent application of automation Discharge Process to reduce risk and returns Process and Measures Process Description for Layout ED Improvement/Design Support Team Stakeholder Review Strategic Svs Leadership Conf ED Call Coverage Facility Issues, Designs Behavioral Health Patients Once we recognized our need to address this, the question was how— As we began our work, we began to find that there was a great deal of organizational interest—in lots of different silos! Our first step was to bring the silos together— The Design Process was collaborative with appropriate support As we began our door to doc project, a team of physicians and nurses from all Banner facilities began to look at our current process and discovered we were able to fill a wall with all of the steps needed to bring a patient into our system. By eliminating all of the redundancies in the system we found we could get the patients to the doctor within – minutes……but we didn’t want to move the problem from the front of the ED to the back.

Door to Doc Care Process Quick Registration Quick Look (ESI) Split Patient Flow Intake area for Less acute patients Joint medical screening Patient moves to testing and treatment Informed discharge IP care for admitted patients Along the way, We visited several other facilities and learned about a design that split the patients into “sick” and “not so sick” groups. With our less sick patients, we decided to keep them moving through the system to make room for more patients…this is our “bed ahead” concept. In our sicker area, we designated space for patients who were waiting for testing or needed longer treatments. By this continuous movement of patients we were able to continue seeing patients regardless of our volume…or so we thought. When admitted patients were not moved to the inpatient areas, we felt the pain of being unable to bring more patients in so we designed space for this group of patients and decided best practice would dictate nurses who are best trained to care for them would be assigned to the inpatients.

Common ED Characteristics ED arrival volume patterns are predictable by hour of the day. 9 am-9 pm peak (30% higher) Relative Length of Use by acuity level has a similar pattern across facilities While we were designing the D2D SPF process, we started learning about some characteristics that EDs seem to have in common that are important in thinking about taking a single design to different settings. --ED arrival patterns are predictable by time of date --Relative length of use (or time in the ED) by acuity has a similar pattern

Systems View: Queuing Model Inpatient Transitional Care Hospital Exit rID rIH = 1-rID rOD = 1-fRE = 80% = fA /(rRO*fRE+rRI) rOW = (f3+f4) / (f3+f4+f5) IPED fRE = 20% Intake/ Discharge Results Waiting rWO = 100% From a systems engineering view, here’s how the D2D SPF decomposes into a queuing model rRI = 1-rRO rRO Quick Look LWOT Ambulance Diversion 0%

Choosing ‘Patient Safe’ Capacities Using info specific to each facility along with the Queuing model, the SPF D2D model can be sized appropriately. Recommendations for discussion are in bold

Improvement in Patient Safety through Reduced LWOTs As a result of implementing D2D, Banner facilities have seen improvement in LWOT rates of 35 to 65%--regardless of whether the facility had high LWOT rates or already reasonably low rates. 42% Improvement 63% Improvement 35% Improvement

Here are line graphs that show the changes over time Emergency Department Patients That Leave Without Treatment Sample Size = 24 months Banner Health: Banner Baywood Medical Center Mesa, Arizona, United States of America 21% 20% 19% Door to Doc 18% Implementation 17% 16% 15% 14% 13% 12% 11% % of Patients that Left Without Treatment 10% 9% 8% 7% Emergency Department Patients That Leave Without Treatment Sample Size = 24 months Banner Health: Banner Desert Medical Center Mesa, Arizona, United States of America 0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10% 11% 12% 13% 14% 15% 16% 17% 18% 19% 20% 21% Jul-05 Aug-05 Sep-05 Oct-05 Nov-05 Dec-05 Jan-06 Feb-06 Mar-06 Apr-06 May-06 Jun-06 Jul-06 Aug-06 Sep-06 Oct-06 Nov-06 Dec-06 Jan-07 Feb-07 Mar-07 Apr-07 May-07 Jun-07 Month-Year (month) % of Patients that Left Without Treatment Line = 30% Improvement Door to Doc Implementation 6% Line = 30% improvement 5% 4% 3% 2% 1% 0% Jul-05 Aug-05 Sep-05 Oct-05 Nov-05 Dec-05 Jan-06 Feb-06 Mar-06 Apr-06 May-06 Jun-06 Jul-06 Aug-06 Sep-06 Oct-06 Nov-06 Dec-06 Jan-07 Feb-07 Mar-07 Apr-07 May-07 Jun-07 Month-Year (month) Here are line graphs that show the changes over time

Emergency Department Patients That Leave Without Treatment Sample Size = 24 months Banner Health: Banner Mesa Medical Center Mesa, Arizona, United States of America 0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10% 11% 12% 13% 14% 15% 16% 17% 18% 19% 20% 21% Jul-05 Aug-05 Sep-05 Oct-05 Nov-05 Dec-05 Jan-06 Feb-06 Mar-06 Apr-06 May-06 Jun-06 Jul-06 Aug-06 Sep-06 Oct-06 Nov-06 Dec-06 Jan-07 Feb-07 Mar-07 Apr-07 May-07 Jun-07 Month-Year (month) % of Patients that Left Without Treatment Line = 30% Improvement Door to Doc Implementation Emergency Department Patients That Leave Without Treatment Sample Size = 24 months Banner Health: North Colorado Medical Center Greeley, Colorado, United States of America 0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10% 11% 12% 13% 14% 15% 16% 17% 18% 19% 20% 21% Jul-05 Aug-05 Sep-05 Oct-05 Nov-05 Dec-05 Jan-06 Feb-06 Mar-06 Apr-06 May-06 Jun-06 Jul-06 Aug-06 Sep-06 Oct-06 Nov-06 Dec-06 Jan-07 Feb-07 Mar-07 Apr-07 May-07 Jun-07 Month-Year (month) % of Patients that Left Without Treatment Line = 30% Improvement Door to Doc Implementation

LWOTs and D2D Time There is a strong relationship between LWOT% and D2D time. A linear model (shown) explains 93% of the LWOT% /D2D data variation (correlation coefficient = 0.96).

Lessons Learned ED Patient Safety can be improved Collaboration is key The D2D SPF design reduces LWOTS  Collaboration is key ASU Industrial Engineering Physicians, Staff Implementation is the hardest part Changing minds along with process Leadership matters High level organizational commitment Keep measuring and monitoring Ongoing improvement should occur

The SPF D2D model can apply in many EDs A toolkit with interactive modeling tools is available at www.BannerHealth Innovations.org

Acknowledgements This project was funded under grant U18 HS 15921 from the Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services. Special thanks to the many people who have made this improvement possible! Especially Professor Jeff Cochran!