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research-article2014
AJMXXX10.1177/1062860614564618American Journal of Medical QualityLovett et al
Article
A Successful Model for a Comprehensive Patient Flow Management Center at an Academic Health System
American Journal of Medical Quality 1–10 © The Author(s) 2014 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/1062860614564618 ajmq.sagepub.com
Paris B. Lovett, MD, MBA, FACEP1, Megan L. Illg, MHSA1, and Brian E. Sweeney, RN, MBA, FACHE1
Abstract This article reports on an innovative approach to managing patient flow at a multicampus academic health system, integrating multiple services into a single, centralized Patient Flow Management Center that manages supply and demand for inpatient services across the system. Control of bed management was centralized across 3 campuses and key services were integrated, including bed management, case management, environmental services, patient transport, ambulance and helicopter dispatch, and transfer center. A single technology platform was introduced, as was providing round-the-clock patient placement by critical care nurses, and adding medical directors. Daily bed meetings with nurse managers and charge nurses drive action plans. This article reports immediate improvements in the first year of operations in emergency department walkouts, emergency department boarding, ambulance diversion, growth in transfer volume, reduction in lost transfers, reduction in time to bed assignment, and bed turnover time. The authors believe theirs is the first institution to integrate services and centralize bed management so comprehensively. Keywords patient flow, academic medical centers, hospital bed capacity, length of stay, quality improvement Patient flow is widely recognized as being critical for hospitals to achieve goals in quality and safety, patient experience, cost management, and growth.1,2 Improving patient flow3-5 can be defined as optimizing provision and utilization of resources to meet demand and avoid delays and non-value-added processes for patients across the entirety of an inpatient encounter. Multiple disciplines, departments, and support services are involved in providing inpatient resources. In many acute care hospitals these services do not share management or reporting relationships, do not have shared goals or metrics, and do not share a workspace. Control of beds is not fully centralized in many institutions.6,7 Despite published reports of the benefits from having dedicated nurses8 and physicians9 involved in patient flow management, many institutions have not implemented such roles. Inefficiencies in patient flow typically reflect systematic mismatching of demand and supply for inpatient resources across an institution. However, the most visible effects may be concentrated in certain areas of the hospital: the emergency department (ED), the post–anesthesia care unit (PACU), intensive care units (ICUs), and admissions. Less visibly, patients may have long waits in physicians’
offices, or at other institutions where they await transfer. The sources of mismatching may be absolute shortfalls in resources, inability to meet peak demand, lack of coordination, or mismatching of supply between resource silos. This descriptive report outlines severe patient flow problems faced at a large academic medical center, a comprehensive, centralized, and systematic approach that was taken to improving these problems, and changes in associated performance measures.
Setting In 2010, the study institution was experiencing poor patient flow. The institution is a 953-bed academic health system and Level 1 trauma center with 3 campuses and 46 000 annual inpatient admissions, 100 000 ED visits, 1
Thomas Jefferson University and Thomas Jefferson University Hospitals, Philadelphia, PA Corresponding Author: Paris Lovett, MD, MBA, FACEP, Patient Flow Management Center, Thomas Jefferson University, 111 South 11th Street, Gibbon Building, Suite 2130, Philadelphia, PA 19107. Email: [email protected]
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and 8000 employees. Supply and demand continued to be mismatched despite the fact that 50 ICU beds were added recently and the ED bed capacity was expanded by 30%. The study institution was experiencing a decrease in external transfers related to inefficiencies in the accepting process, and delays in assigning beds that sometimes resulted in patients waiting days at referring institutions. Adverse patient safety events occurred when direct admission patients waited extended periods for beds. It routinely took more than 2 hours to turn over an inpatient room, from the time it was vacated until it was clean and available. The PACU and ED had significant boarding and overcrowding. (Boarding refers to patients who require admission having to wait hours for beds to be assigned so they can leave the ED or PACU.) The ED had 10 000 hours of boarding per month, which resulted in multiple undesirable outcomes. The rate of patients leaving without being seen (LWBS) reached as high as 9.5%. Patients arriving in the ED had median waits before they were seen by providers that were as long as 135 minutes. Ambulance diversion got as high as 164 hours per month. (Ambulance diversion refers to the ED reaching a state of critical overcrowding during which the ED requests that ambulances not bring patients to the ED.) Patient experience and the working environment for staff were adversely affected by this overcrowding. Every strategic imperative is affected by poor patient flow: quality and safety are affected by delays and crowding, which in turn affect malpractice exposure; patient experience is adversely affected, which in turn affects value-based purchasing financial outcomes; staff and provider stress adversely affect the goal of being the regional employer of choice; and ambulance diversion, walkouts, and lost transfers directly affect finances and the ability to meet growth goals. A performance improvement initiative focused on improving patient flow had the potential to impact every aspect of the operation.
Methods Following is a narrative of the change process that led to the development of the Patient Flow Management Center (PFMC), and an overview of PFMC processes and operations. Then a range of key metrics are presented that compare pre-PFMC and post-PFMC means along with 95% confidence intervals for differences between means. Data analysis was performed using IBM SPSS Statistics for Windows, version 20.0 (IBM Corporation, Armonk, New York). The metrics presented include (a) measures of volume: total admissions, ED visits, and total completed patient transport jobs per month; (b) measures of process failure resulting from overcrowding in the ED: ambulance diversion (hours/month), LWBS (percentage of ED
visits), and boarding hours (hours per month); (c) process cycle times: ED door-to-provider time (median time from patient arrival in the ED to evaluation by a medical provider, minutes), nursing pull time (mean time from a clean and ready bed assigned to patient occupying that bed, which includes nursing handoff, in minutes), mean patient transport total trip time (minutes), mean Environmental Services (EVS) response time (time from bed reported dirty to cleaning commenced, in minutes), mean EVS turn time (time from bed reported dirty to cleaning completed, in minutes), and mean bed request to assign time (minutes).
Beginnings of Change During the strategic planning process for fiscal year 2011, the chief operating officer sponsored a project for the Balanced Scorecard: Develop a centralized operational control center for bed management. To develop a solution, the study institution utilized internal facilitators from its operations support group and formal change acceleration processes. Three half-day WorkOuts focused on process mapping of the current admission, transfer, and discharge process; identifying barriers to timely admission and discharge; and brainstorming solutions to improve performance. A WorkOut is a team-based decision-making approach, developed by GE, involving experienced, knowledgeable individuals with a stake in a clearly identified issue. The session is a 1-day event focused on developing solutions and action plans. Lean tools can be utilized during a WorkOut; however, a WorkOut differs from a Kaizen in that it is shorter in duration and new processes are not piloted during the event. A priority–payoff matrix was used to determine the focus of change initiatives. It was clear that there was an opportunity to improve communication and coordination, and it was suggested that this be done through the creation of a PFMC that would control patient flow for the entire clinical enterprise. Key decisions that emerged from this process were the set of services to be integrated, a single physical operations suite, technological integration on a single platform, real-time data reporting to drive decisions, and alignment of key departments and services. The need for top-down, visible support from the senior executive team was clear. Just as important was the need to involve, educate, and raise awareness among frontline staff and leadership about the importance of patient flow to the institution.
Project Planning Administrative leadership immediately began to look for unified physical space and to examine the required staffing mix and levels.
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Figure 1. Patient flow dashboard.
Abbreviations: BMT, bone marrow transplant; CDU, clinical decision unit; CVIR, cardiovascular and interventional radiology; ED, emergency department; EMU, epilepsy management unit; PACU, post–anesthesia care unit.
A decision was made to increase bed management nursing staff to assure coverage 24 hours a day, 7 days a week. A key goal was to staff bed management around the clock and to always have a clinician (nurse) as part of that coverage. Previously, bed management was open during weekday business hours, and other departments took over those duties during the off shifts. A team was formed to look at the physical space and held weekly meetings with the project architects. The architects were tasked with designing a floor plan that would facilitate collaboration and create open sight lines, yet allow staff to concentrate on tasks at the same time. The team created 6 Y-shaped “pods” containing 3 workspaces each, for a total of 18 workspaces. The design team emphasized many design details to optimize team performance: dividers between workspaces were set at a height that allowed a balance of noise reduction and communication between colleagues. All workspaces are configured to allow for flexibility and ergonomics. The desks can be adjusted to sitting or standing heights, the chairs are ergonomic, and the lighting is adjustable throughout the center and at each workspace.
The sound environment was optimized to combine individual work and collaboration. Wall surfaces, double-layered curtains, carpets, and workstation overhead “fans” were designed to provide sound absorption and deflection. Microphones were chosen to minimize pickup of background noise and headsets to further cancel noise. Tablet computers also were deployed, to be carried by supervisors and managers of bed management, transport, and EVS so that the patient flow software can be accessed during rounding. This also enables managers to be visible on the floors and to hold staff accountable.
Technology Patient Flow Software. It was clear that a single technology platform for managing every bed across all campuses was needed, as others have described.10-12 Task automation and real-time data reporting were considered critical. A full suite of patient flow software was implemented and considerable time was spent on customizing the software, such as a patient flow dashboard that summarizes demand, supply, and throughput for each campus (Figure 1). This dashboard was displayed across units of the hospital on
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large LCD screens, including hospital administration, the ED, and the nursing staffing office to generate awareness of the real-time status of patient flow and create transparency. The dashboard is fed automatically by the patient flow software and shows at a glance how many pending bed requests there are by department and the overall census on nonspecialty units (critical care, intermediate care, telemetry, and general medical/surgical), and displays the following by bed type: occupancy, number of pending transfers out, and number of confirmed discharges (patients with discharge orders). The patient flow software provides real-time tracking of all patient flow activity, including bed assignment, bed cleaning, bed occupied status, patient transportation, and discharges. It is a Web-based application accessible anywhere in the hospital. Every nursing unit and every support service can thereby view detailed information in real time and respond accordingly. The reporting system built into this software suite allows the design of custom reports, many of which are automated to be sent to various stakeholders at regular intervals, further building transparency and trust. The reports have proven very helpful in being able to hold individual staff, units, and departments accountable for meeting targets. Call Management Software. The PFMC is managed as a high-volume call center and utilizes an Automated Call Distribution (ACD) system to route telephone calls and track them. Several features of the ACD system were of key importance: ease of use; the ability to conference multiple physicians for external transfers; advanced reporting on call volume, talk time, abandonment rates, and other key metrics; and finally, the ability to record all outgoing and incoming calls, which is critical for both quality assurance and incident investigation.
Education and Driving Change To integrate PFMC operations into the culture of the hospital and achieve updates regarding PFMC technology and processes, nurses, patient transporters, EVS staff, and other staff were educated on use of the patient flow software. This information technology education process served not only to familiarize staff with the software, it also served as a venue in which the mission for the PFMC could be communicated, and the new role of PFMC in centralizing and standardizing bed management and other processes could be discussed. The software training served as a foundation for education, communication, and culture change. Beyond these software training opportunities, a communications plan was developed that identified key audiences. The team reached these audiences via a variety of
forums and channels, including giving presentations at meetings, intranet messages, e-mail blasts, and promotional mouse pads. Audiences included staff nurses and nurse managers, attending physicians, residents, nonphysician providers, physician leaders, patient transport, and EVS.
Meetings Even before the formal opening of the PFMC operations suite, some important new meetings were developed to improve coordination, communication, and accountability. Daily Bed Meeting. Each day at 9:15 AM, nurse managers and charge nurses from all units at all 3 campuses join a 10-minute meeting during which overall demand and capacity are reviewed and critical issues for patient flow discussed and action plans are developed. This meeting was later enhanced with the Real-Time Demand Capacity (RTDC) process discussed in a later section of this article. Operations Meeting. A weekly meeting was established to focus on the design and implementation of the PFMC site and operating processes. Over time, this meeting was repurposed into a venue in which all services involved in patient flow reviewed targets and performance and developed action plans for performance improvement. These meetings involved leadership from nursing, bed management, transfer center, EVS, patient transport, case management, the ED, perioperative services, and the PFMC medical directors. The meeting was driven by the scorecard, which combined data tables and graphs for all key metrics on a single sheet (Table 1). Aggressive best practice targets for each of the metrics on the scorecard were established based on data from the University HealthSystem Consortium, the Institute for Healthcare Improvement (IHI), and the patient flow software vendor.
Establishing Control of All Beds: Culture Change Historically, the study institution had a decentralized bed management model, in which individual nursing units, sometimes with input from physicians, assigned beds and determined which beds could be used by which patients. As a result, there often were situations in which patients waited in the ED or PACU for beds while empty beds in units went unused. Support from top hospital leadership was essential in moving away from this model. The chief operating officer and chief medical officer met privately with key physician and nursing stakeholders to underline this support.
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Lovett et al Table 1. Patient Flow Management Center Management Metrics. Department Overall demand ED Transfer center PACU Bed management Nursing EVS Transport Case management
Indicator Total admissions OR cases ED volume ED admissions Observation status cases External transfers (TJUH and JHN) Inpatient LOS (TJUH and JHN) Case mix index (TJUH and JHN) Occupancy—Nonspecialty units Occupancy—All units ED RTM compliance ED diversion hours ED LWBS rate ED decision to leaves ED (% within 4 hours) Lost business due to bed availability Transfers sent to other facilities by requester PACU boarders PACU RTM compliance ED—% Beds assigned within 15 minutes of RTM PACU—% Beds assigned within 15 minutes of RTM Direct admits—% Beds assigned within 15 minutes of request External transfers—% Beds assigned within 15 minutes of RTM Internal transfers—% beds assigned within 60 minutes of RTM RTM compliance (% beds assigned after RTM) Cycle time—Average bed assigned to bed clean—new admits (minutes) ED pull time—% within 60 minutes PACU pull time—% within 60 minutes Internal transfers pull time—% within 60 minutes Internal transfers RTM compliance % of Dispatched transport jobs cancelled or rescheduled Total requests % Response time >120 minutes Cycle time—Average turn time (minutes) Cycle time—Average response time (minutes) Total completed jobs Total dispatches Average total trip time (minutes) Wait time—Average pending to in progress (minutes) Pending discharge compliance Pending discharge accuracy
Abbreviations: ED, emergency department; EVS, environmental services; JHN, Jefferson Hospital for Neuroscience; LOS, length of stay; LWBS, leaving without being seen; OR, operating room; PACU, post–anesthesia care unit; RTM, ready to move; TJUH, Thomas Jefferson University Hospital.
At the same time, the PFMC operations team worked to build trust by addressing key concerns. Two processes were particularly important to assure patients were placed in the correct bed the first time: incorporating patient attributes and using bed matrices. Patient Attributes. The patient flow software is designed so that very specific information regarding individual
patients can be communicated to optimize patient placement. Attributes can be selected for each patient, including any isolation information, any social or behavioral issues, as well as any interventions the patient is receiving. The sending units select the patient attributes when completing a bed request for each patient, allowing the attributes of the patient to be matched to the attributes of each bed. The attributes are completely customizable, so
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attributes were able to be created for specific patient populations such as postpartum women. Bed Matrices. As part of a proactive approach to patient flow, the PFMC team developed patient placement matrices. A matrix was developed for medicine, surgery, and the critical care and intermediate units. Each matrix outlines the priority unit for each patient type as well as a secondary unit and other backup units in the event that there is not a bed immediately available on the primary bed assignment. These matrices have been approved by nursing and physician leadership. They help reduce delays because there is no need for real-time discussion or negotiation when patients must be placed in secondary units.
Medical Directors Two medical directors were recruited, one from emergency medicine and one from internal medicine. Initially, the medical directors were able to intervene in real-time situations in which physicians were not collaborating effectively or were not aligned with organizational patient flow goals, or to arbitrate disputes between services. The medical directors also worked to build relationships across all clinical departments, to build long-term alignment and foster trust and communication, and to respond to physician concerns. The medical directors brought a clinical perspective to strategic planning in the PFMC leadership group and led many performance improvement projects, some of which are described in the following section.
Projects Collaboration With ED on Front End Redesign. The PFMC staff and leadership worked collaboratively with ED leadership to introduce comprehensive redesign of frontend processes, including introduction of immediate bedding whenever the ED was below complete utilization of all beds, bedside triage, bedside registration, use of vertical spaces (chairs) to increase functional capacity of the ED, expansion of the scope of the Fast Track area in the ED to more acute patients, and adoption of a physician in triage at peak times. Cross-Campus Admissions. The medical directors worked with ED leadership and associate chief medical officers to create a process to effectively utilize treatment spaces across all 3 campuses, so that low-acuity patients from the main teaching campus could be admitted to the community campus and transported promptly via ambulance. This more effectively matched patient complexity to resource intensity and utilized available beds to reduce crowding.
Telemetry Utilization. At the study institution, telemetry (cardiac monitoring) is tied to specific beds, so that telemetry and nontelemetry beds exist in separate silos. In the past this has frequently led to supply–demand mismatches. Overuse of telemetry contributes to the problem. The PFMC medical directors led efforts to develop evidence-based guidelines for telemetry utilization so that an approved indication is always used when ordering telemetry. Providers and departments can receive aggregate data on utilization and compliance. Apart from ameliorating bed utilization problems, this also is assisting with alarm fatigue and the Joint Commission 2014 National Patient Safety Goal on Alarm Management.13 Cohorting Methicillin-Resistant Staphylococcus Aureus (MRSA) Patients. The study institution has many semi private rooms in which 2 patients are cohorted in a single room. Historically, patients with multi-drug-resistant organisms were required to be placed in isolation, often worsening waits for bed assignment because the other bed in the semiprivate room was blocked. The medical directors led efforts to identify evidence, expert recommendations, and practices at leading institutions and implemented a policy under which 2 patients with MRSA can be safely cohorted at times of high census. Clinical Pathways. The medical directors were involved with organization-wide efforts to create standardized, efficient care through the development of care pathways including gastrointestinal bleeding, hip fracture, and sickle-cell disease to minimize variation in care and optimize length of stay. Judicious Use of Observation Unit. The medical directors worked with ED leadership and case management to ensure that patients were appropriately placed in the observation unit, thereby reducing denials and downgrades for inpatient status and also managing observation length of stay. Surge Plan. Several times each year the study institution was experiencing periods of critically high census that lasted several days. The PFMC medical directors and managers worked with heads of clinical services to systematize and codify the ad hoc responses that were developed during these surges in inpatient demand. They created a surge policy with 3 levels of response, each with defined triggers and responses for each clinical department, discipline, and support services. ED Acute Overcrowding Plan. Distinct from hospital surges, there are periods lasting hours during which the ED can become markedly overcrowded, even in the absence of sustained high inpatient census. At such times, an ED
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Lovett et al Table 2. Means for Volume Measures, ED Process Failure Metrics, and Cycle Times, Pre-PFMC Versus Post-PFMC, with 95% Confidence Intervals for the Differences Between Means. Pre-PFMC Mean
Post-PFMC Mean
Difference (95% CI)
2677 4850 11 475 86 6.20% 7047 74 115 35 77 115 153.33
2810 5224 13 967 7 3.60% 4011 41 81 36 32 72 104.71
132 (49, 216) 374 (207, 540) 2492 (1740, 3243) −79 (−111, −46) −2.5% (−4.1%, −1.0%) −3036 (−4205, −1868) −33 (−44, −22) −33 (−37, −29) 1 (−1, 3) −45 (−56, −34) −43 (−53, −32) −49 (−73, −24)
Total admissions (per month) ED visits (per month) Patient transport total completed jobs (per month) Ambulance diversion (hours/month) ED LWBS (% of ED visits) ED boarding hours (total hours/month) ED door to provider time (median, minutes) Nursing pull time (mean, minutes) Patient transport total trip time (mean, minutes) EVS response time (mean, minutes) EVS turn time (mean, minutes) Bed request to assign time (mean, minutes)
Abbreviations: ED, emergency department; EVS, environmental services; LWBS, leaving without being seen; PFMC, Patient Flow Management Center.
overcrowding plan is deployed, focusing on rapid mitigation of overcrowding. Measures included in the ED acute overcrowding plan include activation based on NEDOCS14 score and ED attending judgment; huddles with attendings and the charge nurse to identify patients who can be discharged or moved from beds to chairs; identification of patients who can be assessed, treated, and discharged from the waiting room without being assigned an ED bed; using all beds in the observation unit; working with consult services to expedite disposition decisions; notification of ED and hospital leadership, plus support services (transport, environmental, dietary, registration) and other clinical services (lab, pharmacy, radiology) to provide additional resources and expedite services; assignment of additional nurses, techs, and transporters to the ED from elsewhere in the hospital; and enhanced vigilance for cross-campus admission opportunities. Blocked Beds. Prior to PFMC, staff on units could close beds, with little consistency regarding indications or timing. By centralizing and standardizing this process and removing unit control of inpatient beds transparency was achieved, along with a sustained reduction in blocked beds. Education on Length of Stay and Time of Discharge. The medical directors have an important role in aligning providers and service leaders with institutional efforts to improve length of stay and time of discharge. The medical directors communicate how excess length of stay and time of discharge impact every strategic goal, from quality and safety, to patient experience, to the financial bottom line. RTDC. Every bed meeting is structured around the RTDC model developed by IHI.15 In this model, each nursing unit is responsible for predicting how many patients will
be discharged from the unit that day, as well as how many patients they expect to be admitted that day based on historical data. Using projected discharges and available beds, each unit determines unit capacity for the day. Using historical data, as well as known admissions, each unit determines unit demand for the day. If unit demand is greater than capacity, the unit must develop and share an action plan in the bed meeting. Examples of an action plan can include using a sister unit that has extra capacity, working with physicians to identify more discharges or transfers, or working with case management to expedite long-term placement issues. This model has not only helped improve patient flow but also has helped to increase nursing engagement in patient flow.
Results Table 2 and Figures 2 and 3 show several key metrics, comparing pre-PFMC data (June 2010 to February 2011) to post-PFMC data (April 2011 to March 2013) along with 95% confidence intervals for the difference between pre- and post-PFMC means. Total admissions, ED visits, and transport volumes all increased from pre-PFMC to post-PFMC. There were operationally and statistically significant improvements in all metrics except for patient transport total trip time, which did not change to an operationally significant degree. The improvements included dramatic reductions in ED process failure metrics (ambulance diversion, LWBS, and boarding), and reductions in cycle times for ED door-to-provider, nursing pull times, EVS response and bed turn, and bed assignment times. Periodic spikes in measures such as bed assignment time occurred at periods of increased volume or severity, often seasonal. An example is seen in January/February
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Volume
ED Process Failure Measures Total Admissions (/month)
3500
Ambulance Diversion (hrs/month) 180 160
3000
140
2500
120
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1500
80 60
1000
40
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20
0
0
ED Visits (/month) 7000
ED LWBS (% ED visits) 10.0% 9.0%
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4000
5.0% 3000
4.0% 3.0%
2000
2.0%
1000
1.0%
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Pa ent Transport Total Completed Jobs (/month)
ED Boarding (total hrs/month) 10000
18000
9000
16000
8000
14000
7000
12000
6000
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Figure 2. Graphs of volume (left) and of ED process failure (right). In each graph, the line segment on the left shows pre-PFMC performance, and the line segment on the right shows post-PFMC performance. Note that data for many metrics were not available for March 2011, the month in which the PFMC opened. Abbreviations: ED, emergency department; LWBS, leaving without being seen; PFMC, Patient Flow Management Center.
of 2013, which was believed to be related to seasonal influenza. Although performance worsened at this time, it
is believed that the surge process reduced the severity of the spike in process times.
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Cycle Times ED Door-to-Provider Time (mins)
EVS Response Time (mins)
120
120
100
100
80
80
60
60
40
40
20
20
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Nursing Pull Time (mins)
EVS Turn Time (mins)
140
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Pa ent Transport: Total Trip Time (mins)
Bed Request to Assign Time (mins) 250
50 200
45 40 35
150
30 25
100
20 15
50
10 5 0
0
Figure 3. Graphs of cycle time metrics. In each graph the line segment on the left shows pre-PFMC performance, and the line segment on the right shows post-PFMC performance. Note that data for many metrics were not available for March 2011, the month in which the PFMC opened. Abbreviations: ED, emergency department; EVS, environmental services; PFMC, Patient Flow Management Center.
Return on Investment A total of $1.2 million was invested to construct the space and equip it with new computers, telephone systems, and
furniture. Gaps in staffing were addressed by hiring additional nurses to achieve 24/7 clinical coverage and assure that patients were placed efficiently on the proper units.
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The total incremental annual salary and benefit cost for these nurses was $700 000. Following an intense focus on process improvement and an investment in space, technology, and staff, the study institution saw an increase in admissions, transfers, and ED visits. This is attributed to the significant reduction in ED diversion and the decline in the ED LWBS rate that was achieved with this project. The reduction in the LWBS rate alone is estimated to have increased the contribution margin by $2.1 million annually, demonstrating a quick return on the space and staff investments.
Limitations This article reports on interventions and results at a single institution, and one with severe patient flow problems before the interventions, and this may limit generalizability. Because multiple interventions were made, with multivariate analysis not being feasible, and no comparison arm available, no causal relationship can be inferred from the before-and-after results. As such this should be regarded as a descriptive report.
Conclusions Hospitals face increased pressure to improve clinical quality and efficiency and reduce operating expenses given the recent adoption of value-based purchasing payment models. Hospitals around the world continue to struggle to manage patient flow effectively given the complexities of the normal admission, discharge, and transfer process— many processes must be completed in synchrony to achieve the ideal length of stay. Centralizing the management of patient flow through a PFMC and supporting this system with information technology and data is critical to improving organizational communication, coordination, and accountability, and to achieving top performance. Acknowledgment Lucas Lax assisted with retrieving and collating historical data for this report.
Declaration of Conflicting Interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding The authors received no financial support for the research, authorship, and/or publication of this article.
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research-article2014
AJMXXX10.1177/1062860614564618American Journal of Medical QualityLovett et al
Article
A Successful Model for a Comprehensive Patient Flow Management Center at an Academic Health System
American Journal of Medical Quality 1–10 © The Author(s) 2014 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/1062860614564618 ajmq.sagepub.com
Paris B. Lovett, MD, MBA, FACEP1, Megan L. Illg, MHSA1, and Brian E. Sweeney, RN, MBA, FACHE1
Abstract This article reports on an innovative approach to managing patient flow at a multicampus academic health system, integrating multiple services into a single, centralized Patient Flow Management Center that manages supply and demand for inpatient services across the system. Control of bed management was centralized across 3 campuses and key services were integrated, including bed management, case management, environmental services, patient transport, ambulance and helicopter dispatch, and transfer center. A single technology platform was introduced, as was providing round-the-clock patient placement by critical care nurses, and adding medical directors. Daily bed meetings with nurse managers and charge nurses drive action plans. This article reports immediate improvements in the first year of operations in emergency department walkouts, emergency department boarding, ambulance diversion, growth in transfer volume, reduction in lost transfers, reduction in time to bed assignment, and bed turnover time. The authors believe theirs is the first institution to integrate services and centralize bed management so comprehensively. Keywords patient flow, academic medical centers, hospital bed capacity, length of stay, quality improvement Patient flow is widely recognized as being critical for hospitals to achieve goals in quality and safety, patient experience, cost management, and growth.1,2 Improving patient flow3-5 can be defined as optimizing provision and utilization of resources to meet demand and avoid delays and non-value-added processes for patients across the entirety of an inpatient encounter. Multiple disciplines, departments, and support services are involved in providing inpatient resources. In many acute care hospitals these services do not share management or reporting relationships, do not have shared goals or metrics, and do not share a workspace. Control of beds is not fully centralized in many institutions.6,7 Despite published reports of the benefits from having dedicated nurses8 and physicians9 involved in patient flow management, many institutions have not implemented such roles. Inefficiencies in patient flow typically reflect systematic mismatching of demand and supply for inpatient resources across an institution. However, the most visible effects may be concentrated in certain areas of the hospital: the emergency department (ED), the post–anesthesia care unit (PACU), intensive care units (ICUs), and admissions. Less visibly, patients may have long waits in physicians’
offices, or at other institutions where they await transfer. The sources of mismatching may be absolute shortfalls in resources, inability to meet peak demand, lack of coordination, or mismatching of supply between resource silos. This descriptive report outlines severe patient flow problems faced at a large academic medical center, a comprehensive, centralized, and systematic approach that was taken to improving these problems, and changes in associated performance measures.
Setting In 2010, the study institution was experiencing poor patient flow. The institution is a 953-bed academic health system and Level 1 trauma center with 3 campuses and 46 000 annual inpatient admissions, 100 000 ED visits, 1
Thomas Jefferson University and Thomas Jefferson University Hospitals, Philadelphia, PA Corresponding Author: Paris Lovett, MD, MBA, FACEP, Patient Flow Management Center, Thomas Jefferson University, 111 South 11th Street, Gibbon Building, Suite 2130, Philadelphia, PA 19107. Email: [email protected]
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and 8000 employees. Supply and demand continued to be mismatched despite the fact that 50 ICU beds were added recently and the ED bed capacity was expanded by 30%. The study institution was experiencing a decrease in external transfers related to inefficiencies in the accepting process, and delays in assigning beds that sometimes resulted in patients waiting days at referring institutions. Adverse patient safety events occurred when direct admission patients waited extended periods for beds. It routinely took more than 2 hours to turn over an inpatient room, from the time it was vacated until it was clean and available. The PACU and ED had significant boarding and overcrowding. (Boarding refers to patients who require admission having to wait hours for beds to be assigned so they can leave the ED or PACU.) The ED had 10 000 hours of boarding per month, which resulted in multiple undesirable outcomes. The rate of patients leaving without being seen (LWBS) reached as high as 9.5%. Patients arriving in the ED had median waits before they were seen by providers that were as long as 135 minutes. Ambulance diversion got as high as 164 hours per month. (Ambulance diversion refers to the ED reaching a state of critical overcrowding during which the ED requests that ambulances not bring patients to the ED.) Patient experience and the working environment for staff were adversely affected by this overcrowding. Every strategic imperative is affected by poor patient flow: quality and safety are affected by delays and crowding, which in turn affect malpractice exposure; patient experience is adversely affected, which in turn affects value-based purchasing financial outcomes; staff and provider stress adversely affect the goal of being the regional employer of choice; and ambulance diversion, walkouts, and lost transfers directly affect finances and the ability to meet growth goals. A performance improvement initiative focused on improving patient flow had the potential to impact every aspect of the operation.
Methods Following is a narrative of the change process that led to the development of the Patient Flow Management Center (PFMC), and an overview of PFMC processes and operations. Then a range of key metrics are presented that compare pre-PFMC and post-PFMC means along with 95% confidence intervals for differences between means. Data analysis was performed using IBM SPSS Statistics for Windows, version 20.0 (IBM Corporation, Armonk, New York). The metrics presented include (a) measures of volume: total admissions, ED visits, and total completed patient transport jobs per month; (b) measures of process failure resulting from overcrowding in the ED: ambulance diversion (hours/month), LWBS (percentage of ED
visits), and boarding hours (hours per month); (c) process cycle times: ED door-to-provider time (median time from patient arrival in the ED to evaluation by a medical provider, minutes), nursing pull time (mean time from a clean and ready bed assigned to patient occupying that bed, which includes nursing handoff, in minutes), mean patient transport total trip time (minutes), mean Environmental Services (EVS) response time (time from bed reported dirty to cleaning commenced, in minutes), mean EVS turn time (time from bed reported dirty to cleaning completed, in minutes), and mean bed request to assign time (minutes).
Beginnings of Change During the strategic planning process for fiscal year 2011, the chief operating officer sponsored a project for the Balanced Scorecard: Develop a centralized operational control center for bed management. To develop a solution, the study institution utilized internal facilitators from its operations support group and formal change acceleration processes. Three half-day WorkOuts focused on process mapping of the current admission, transfer, and discharge process; identifying barriers to timely admission and discharge; and brainstorming solutions to improve performance. A WorkOut is a team-based decision-making approach, developed by GE, involving experienced, knowledgeable individuals with a stake in a clearly identified issue. The session is a 1-day event focused on developing solutions and action plans. Lean tools can be utilized during a WorkOut; however, a WorkOut differs from a Kaizen in that it is shorter in duration and new processes are not piloted during the event. A priority–payoff matrix was used to determine the focus of change initiatives. It was clear that there was an opportunity to improve communication and coordination, and it was suggested that this be done through the creation of a PFMC that would control patient flow for the entire clinical enterprise. Key decisions that emerged from this process were the set of services to be integrated, a single physical operations suite, technological integration on a single platform, real-time data reporting to drive decisions, and alignment of key departments and services. The need for top-down, visible support from the senior executive team was clear. Just as important was the need to involve, educate, and raise awareness among frontline staff and leadership about the importance of patient flow to the institution.
Project Planning Administrative leadership immediately began to look for unified physical space and to examine the required staffing mix and levels.
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Figure 1. Patient flow dashboard.
Abbreviations: BMT, bone marrow transplant; CDU, clinical decision unit; CVIR, cardiovascular and interventional radiology; ED, emergency department; EMU, epilepsy management unit; PACU, post–anesthesia care unit.
A decision was made to increase bed management nursing staff to assure coverage 24 hours a day, 7 days a week. A key goal was to staff bed management around the clock and to always have a clinician (nurse) as part of that coverage. Previously, bed management was open during weekday business hours, and other departments took over those duties during the off shifts. A team was formed to look at the physical space and held weekly meetings with the project architects. The architects were tasked with designing a floor plan that would facilitate collaboration and create open sight lines, yet allow staff to concentrate on tasks at the same time. The team created 6 Y-shaped “pods” containing 3 workspaces each, for a total of 18 workspaces. The design team emphasized many design details to optimize team performance: dividers between workspaces were set at a height that allowed a balance of noise reduction and communication between colleagues. All workspaces are configured to allow for flexibility and ergonomics. The desks can be adjusted to sitting or standing heights, the chairs are ergonomic, and the lighting is adjustable throughout the center and at each workspace.
The sound environment was optimized to combine individual work and collaboration. Wall surfaces, double-layered curtains, carpets, and workstation overhead “fans” were designed to provide sound absorption and deflection. Microphones were chosen to minimize pickup of background noise and headsets to further cancel noise. Tablet computers also were deployed, to be carried by supervisors and managers of bed management, transport, and EVS so that the patient flow software can be accessed during rounding. This also enables managers to be visible on the floors and to hold staff accountable.
Technology Patient Flow Software. It was clear that a single technology platform for managing every bed across all campuses was needed, as others have described.10-12 Task automation and real-time data reporting were considered critical. A full suite of patient flow software was implemented and considerable time was spent on customizing the software, such as a patient flow dashboard that summarizes demand, supply, and throughput for each campus (Figure 1). This dashboard was displayed across units of the hospital on
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large LCD screens, including hospital administration, the ED, and the nursing staffing office to generate awareness of the real-time status of patient flow and create transparency. The dashboard is fed automatically by the patient flow software and shows at a glance how many pending bed requests there are by department and the overall census on nonspecialty units (critical care, intermediate care, telemetry, and general medical/surgical), and displays the following by bed type: occupancy, number of pending transfers out, and number of confirmed discharges (patients with discharge orders). The patient flow software provides real-time tracking of all patient flow activity, including bed assignment, bed cleaning, bed occupied status, patient transportation, and discharges. It is a Web-based application accessible anywhere in the hospital. Every nursing unit and every support service can thereby view detailed information in real time and respond accordingly. The reporting system built into this software suite allows the design of custom reports, many of which are automated to be sent to various stakeholders at regular intervals, further building transparency and trust. The reports have proven very helpful in being able to hold individual staff, units, and departments accountable for meeting targets. Call Management Software. The PFMC is managed as a high-volume call center and utilizes an Automated Call Distribution (ACD) system to route telephone calls and track them. Several features of the ACD system were of key importance: ease of use; the ability to conference multiple physicians for external transfers; advanced reporting on call volume, talk time, abandonment rates, and other key metrics; and finally, the ability to record all outgoing and incoming calls, which is critical for both quality assurance and incident investigation.
Education and Driving Change To integrate PFMC operations into the culture of the hospital and achieve updates regarding PFMC technology and processes, nurses, patient transporters, EVS staff, and other staff were educated on use of the patient flow software. This information technology education process served not only to familiarize staff with the software, it also served as a venue in which the mission for the PFMC could be communicated, and the new role of PFMC in centralizing and standardizing bed management and other processes could be discussed. The software training served as a foundation for education, communication, and culture change. Beyond these software training opportunities, a communications plan was developed that identified key audiences. The team reached these audiences via a variety of
forums and channels, including giving presentations at meetings, intranet messages, e-mail blasts, and promotional mouse pads. Audiences included staff nurses and nurse managers, attending physicians, residents, nonphysician providers, physician leaders, patient transport, and EVS.
Meetings Even before the formal opening of the PFMC operations suite, some important new meetings were developed to improve coordination, communication, and accountability. Daily Bed Meeting. Each day at 9:15 AM, nurse managers and charge nurses from all units at all 3 campuses join a 10-minute meeting during which overall demand and capacity are reviewed and critical issues for patient flow discussed and action plans are developed. This meeting was later enhanced with the Real-Time Demand Capacity (RTDC) process discussed in a later section of this article. Operations Meeting. A weekly meeting was established to focus on the design and implementation of the PFMC site and operating processes. Over time, this meeting was repurposed into a venue in which all services involved in patient flow reviewed targets and performance and developed action plans for performance improvement. These meetings involved leadership from nursing, bed management, transfer center, EVS, patient transport, case management, the ED, perioperative services, and the PFMC medical directors. The meeting was driven by the scorecard, which combined data tables and graphs for all key metrics on a single sheet (Table 1). Aggressive best practice targets for each of the metrics on the scorecard were established based on data from the University HealthSystem Consortium, the Institute for Healthcare Improvement (IHI), and the patient flow software vendor.
Establishing Control of All Beds: Culture Change Historically, the study institution had a decentralized bed management model, in which individual nursing units, sometimes with input from physicians, assigned beds and determined which beds could be used by which patients. As a result, there often were situations in which patients waited in the ED or PACU for beds while empty beds in units went unused. Support from top hospital leadership was essential in moving away from this model. The chief operating officer and chief medical officer met privately with key physician and nursing stakeholders to underline this support.
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Lovett et al Table 1. Patient Flow Management Center Management Metrics. Department Overall demand ED Transfer center PACU Bed management Nursing EVS Transport Case management
Indicator Total admissions OR cases ED volume ED admissions Observation status cases External transfers (TJUH and JHN) Inpatient LOS (TJUH and JHN) Case mix index (TJUH and JHN) Occupancy—Nonspecialty units Occupancy—All units ED RTM compliance ED diversion hours ED LWBS rate ED decision to leaves ED (% within 4 hours) Lost business due to bed availability Transfers sent to other facilities by requester PACU boarders PACU RTM compliance ED—% Beds assigned within 15 minutes of RTM PACU—% Beds assigned within 15 minutes of RTM Direct admits—% Beds assigned within 15 minutes of request External transfers—% Beds assigned within 15 minutes of RTM Internal transfers—% beds assigned within 60 minutes of RTM RTM compliance (% beds assigned after RTM) Cycle time—Average bed assigned to bed clean—new admits (minutes) ED pull time—% within 60 minutes PACU pull time—% within 60 minutes Internal transfers pull time—% within 60 minutes Internal transfers RTM compliance % of Dispatched transport jobs cancelled or rescheduled Total requests % Response time >120 minutes Cycle time—Average turn time (minutes) Cycle time—Average response time (minutes) Total completed jobs Total dispatches Average total trip time (minutes) Wait time—Average pending to in progress (minutes) Pending discharge compliance Pending discharge accuracy
Abbreviations: ED, emergency department; EVS, environmental services; JHN, Jefferson Hospital for Neuroscience; LOS, length of stay; LWBS, leaving without being seen; OR, operating room; PACU, post–anesthesia care unit; RTM, ready to move; TJUH, Thomas Jefferson University Hospital.
At the same time, the PFMC operations team worked to build trust by addressing key concerns. Two processes were particularly important to assure patients were placed in the correct bed the first time: incorporating patient attributes and using bed matrices. Patient Attributes. The patient flow software is designed so that very specific information regarding individual
patients can be communicated to optimize patient placement. Attributes can be selected for each patient, including any isolation information, any social or behavioral issues, as well as any interventions the patient is receiving. The sending units select the patient attributes when completing a bed request for each patient, allowing the attributes of the patient to be matched to the attributes of each bed. The attributes are completely customizable, so
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attributes were able to be created for specific patient populations such as postpartum women. Bed Matrices. As part of a proactive approach to patient flow, the PFMC team developed patient placement matrices. A matrix was developed for medicine, surgery, and the critical care and intermediate units. Each matrix outlines the priority unit for each patient type as well as a secondary unit and other backup units in the event that there is not a bed immediately available on the primary bed assignment. These matrices have been approved by nursing and physician leadership. They help reduce delays because there is no need for real-time discussion or negotiation when patients must be placed in secondary units.
Medical Directors Two medical directors were recruited, one from emergency medicine and one from internal medicine. Initially, the medical directors were able to intervene in real-time situations in which physicians were not collaborating effectively or were not aligned with organizational patient flow goals, or to arbitrate disputes between services. The medical directors also worked to build relationships across all clinical departments, to build long-term alignment and foster trust and communication, and to respond to physician concerns. The medical directors brought a clinical perspective to strategic planning in the PFMC leadership group and led many performance improvement projects, some of which are described in the following section.
Projects Collaboration With ED on Front End Redesign. The PFMC staff and leadership worked collaboratively with ED leadership to introduce comprehensive redesign of frontend processes, including introduction of immediate bedding whenever the ED was below complete utilization of all beds, bedside triage, bedside registration, use of vertical spaces (chairs) to increase functional capacity of the ED, expansion of the scope of the Fast Track area in the ED to more acute patients, and adoption of a physician in triage at peak times. Cross-Campus Admissions. The medical directors worked with ED leadership and associate chief medical officers to create a process to effectively utilize treatment spaces across all 3 campuses, so that low-acuity patients from the main teaching campus could be admitted to the community campus and transported promptly via ambulance. This more effectively matched patient complexity to resource intensity and utilized available beds to reduce crowding.
Telemetry Utilization. At the study institution, telemetry (cardiac monitoring) is tied to specific beds, so that telemetry and nontelemetry beds exist in separate silos. In the past this has frequently led to supply–demand mismatches. Overuse of telemetry contributes to the problem. The PFMC medical directors led efforts to develop evidence-based guidelines for telemetry utilization so that an approved indication is always used when ordering telemetry. Providers and departments can receive aggregate data on utilization and compliance. Apart from ameliorating bed utilization problems, this also is assisting with alarm fatigue and the Joint Commission 2014 National Patient Safety Goal on Alarm Management.13 Cohorting Methicillin-Resistant Staphylococcus Aureus (MRSA) Patients. The study institution has many semi private rooms in which 2 patients are cohorted in a single room. Historically, patients with multi-drug-resistant organisms were required to be placed in isolation, often worsening waits for bed assignment because the other bed in the semiprivate room was blocked. The medical directors led efforts to identify evidence, expert recommendations, and practices at leading institutions and implemented a policy under which 2 patients with MRSA can be safely cohorted at times of high census. Clinical Pathways. The medical directors were involved with organization-wide efforts to create standardized, efficient care through the development of care pathways including gastrointestinal bleeding, hip fracture, and sickle-cell disease to minimize variation in care and optimize length of stay. Judicious Use of Observation Unit. The medical directors worked with ED leadership and case management to ensure that patients were appropriately placed in the observation unit, thereby reducing denials and downgrades for inpatient status and also managing observation length of stay. Surge Plan. Several times each year the study institution was experiencing periods of critically high census that lasted several days. The PFMC medical directors and managers worked with heads of clinical services to systematize and codify the ad hoc responses that were developed during these surges in inpatient demand. They created a surge policy with 3 levels of response, each with defined triggers and responses for each clinical department, discipline, and support services. ED Acute Overcrowding Plan. Distinct from hospital surges, there are periods lasting hours during which the ED can become markedly overcrowded, even in the absence of sustained high inpatient census. At such times, an ED
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Lovett et al Table 2. Means for Volume Measures, ED Process Failure Metrics, and Cycle Times, Pre-PFMC Versus Post-PFMC, with 95% Confidence Intervals for the Differences Between Means. Pre-PFMC Mean
Post-PFMC Mean
Difference (95% CI)
2677 4850 11 475 86 6.20% 7047 74 115 35 77 115 153.33
2810 5224 13 967 7 3.60% 4011 41 81 36 32 72 104.71
132 (49, 216) 374 (207, 540) 2492 (1740, 3243) −79 (−111, −46) −2.5% (−4.1%, −1.0%) −3036 (−4205, −1868) −33 (−44, −22) −33 (−37, −29) 1 (−1, 3) −45 (−56, −34) −43 (−53, −32) −49 (−73, −24)
Total admissions (per month) ED visits (per month) Patient transport total completed jobs (per month) Ambulance diversion (hours/month) ED LWBS (% of ED visits) ED boarding hours (total hours/month) ED door to provider time (median, minutes) Nursing pull time (mean, minutes) Patient transport total trip time (mean, minutes) EVS response time (mean, minutes) EVS turn time (mean, minutes) Bed request to assign time (mean, minutes)
Abbreviations: ED, emergency department; EVS, environmental services; LWBS, leaving without being seen; PFMC, Patient Flow Management Center.
overcrowding plan is deployed, focusing on rapid mitigation of overcrowding. Measures included in the ED acute overcrowding plan include activation based on NEDOCS14 score and ED attending judgment; huddles with attendings and the charge nurse to identify patients who can be discharged or moved from beds to chairs; identification of patients who can be assessed, treated, and discharged from the waiting room without being assigned an ED bed; using all beds in the observation unit; working with consult services to expedite disposition decisions; notification of ED and hospital leadership, plus support services (transport, environmental, dietary, registration) and other clinical services (lab, pharmacy, radiology) to provide additional resources and expedite services; assignment of additional nurses, techs, and transporters to the ED from elsewhere in the hospital; and enhanced vigilance for cross-campus admission opportunities. Blocked Beds. Prior to PFMC, staff on units could close beds, with little consistency regarding indications or timing. By centralizing and standardizing this process and removing unit control of inpatient beds transparency was achieved, along with a sustained reduction in blocked beds. Education on Length of Stay and Time of Discharge. The medical directors have an important role in aligning providers and service leaders with institutional efforts to improve length of stay and time of discharge. The medical directors communicate how excess length of stay and time of discharge impact every strategic goal, from quality and safety, to patient experience, to the financial bottom line. RTDC. Every bed meeting is structured around the RTDC model developed by IHI.15 In this model, each nursing unit is responsible for predicting how many patients will
be discharged from the unit that day, as well as how many patients they expect to be admitted that day based on historical data. Using projected discharges and available beds, each unit determines unit capacity for the day. Using historical data, as well as known admissions, each unit determines unit demand for the day. If unit demand is greater than capacity, the unit must develop and share an action plan in the bed meeting. Examples of an action plan can include using a sister unit that has extra capacity, working with physicians to identify more discharges or transfers, or working with case management to expedite long-term placement issues. This model has not only helped improve patient flow but also has helped to increase nursing engagement in patient flow.
Results Table 2 and Figures 2 and 3 show several key metrics, comparing pre-PFMC data (June 2010 to February 2011) to post-PFMC data (April 2011 to March 2013) along with 95% confidence intervals for the difference between pre- and post-PFMC means. Total admissions, ED visits, and transport volumes all increased from pre-PFMC to post-PFMC. There were operationally and statistically significant improvements in all metrics except for patient transport total trip time, which did not change to an operationally significant degree. The improvements included dramatic reductions in ED process failure metrics (ambulance diversion, LWBS, and boarding), and reductions in cycle times for ED door-to-provider, nursing pull times, EVS response and bed turn, and bed assignment times. Periodic spikes in measures such as bed assignment time occurred at periods of increased volume or severity, often seasonal. An example is seen in January/February
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Volume
ED Process Failure Measures Total Admissions (/month)
3500
Ambulance Diversion (hrs/month) 180 160
3000
140
2500
120
2000
100
1500
80 60
1000
40
500
20
0
0
ED Visits (/month) 7000
ED LWBS (% ED visits) 10.0% 9.0%
6000
8.0%
5000
7.0% 6.0%
4000
5.0% 3000
4.0% 3.0%
2000
2.0%
1000
1.0%
0
0.0%
Pa ent Transport Total Completed Jobs (/month)
ED Boarding (total hrs/month) 10000
18000
9000
16000
8000
14000
7000
12000
6000
10000
5000
8000
4000
6000
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4000
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Figure 2. Graphs of volume (left) and of ED process failure (right). In each graph, the line segment on the left shows pre-PFMC performance, and the line segment on the right shows post-PFMC performance. Note that data for many metrics were not available for March 2011, the month in which the PFMC opened. Abbreviations: ED, emergency department; LWBS, leaving without being seen; PFMC, Patient Flow Management Center.
of 2013, which was believed to be related to seasonal influenza. Although performance worsened at this time, it
is believed that the surge process reduced the severity of the spike in process times.
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Cycle Times ED Door-to-Provider Time (mins)
EVS Response Time (mins)
120
120
100
100
80
80
60
60
40
40
20
20
0
0
Nursing Pull Time (mins)
EVS Turn Time (mins)
140
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140 120
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80
80 60
60
40
40
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20
0
0
Pa ent Transport: Total Trip Time (mins)
Bed Request to Assign Time (mins) 250
50 200
45 40 35
150
30 25
100
20 15
50
10 5 0
0
Figure 3. Graphs of cycle time metrics. In each graph the line segment on the left shows pre-PFMC performance, and the line segment on the right shows post-PFMC performance. Note that data for many metrics were not available for March 2011, the month in which the PFMC opened. Abbreviations: ED, emergency department; EVS, environmental services; PFMC, Patient Flow Management Center.
Return on Investment A total of $1.2 million was invested to construct the space and equip it with new computers, telephone systems, and
furniture. Gaps in staffing were addressed by hiring additional nurses to achieve 24/7 clinical coverage and assure that patients were placed efficiently on the proper units.
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The total incremental annual salary and benefit cost for these nurses was $700 000. Following an intense focus on process improvement and an investment in space, technology, and staff, the study institution saw an increase in admissions, transfers, and ED visits. This is attributed to the significant reduction in ED diversion and the decline in the ED LWBS rate that was achieved with this project. The reduction in the LWBS rate alone is estimated to have increased the contribution margin by $2.1 million annually, demonstrating a quick return on the space and staff investments.
Limitations This article reports on interventions and results at a single institution, and one with severe patient flow problems before the interventions, and this may limit generalizability. Because multiple interventions were made, with multivariate analysis not being feasible, and no comparison arm available, no causal relationship can be inferred from the before-and-after results. As such this should be regarded as a descriptive report.
Conclusions Hospitals face increased pressure to improve clinical quality and efficiency and reduce operating expenses given the recent adoption of value-based purchasing payment models. Hospitals around the world continue to struggle to manage patient flow effectively given the complexities of the normal admission, discharge, and transfer process— many processes must be completed in synchrony to achieve the ideal length of stay. Centralizing the management of patient flow through a PFMC and supporting this system with information technology and data is critical to improving organizational communication, coordination, and accountability, and to achieving top performance. Acknowledgment Lucas Lax assisted with retrieving and collating historical data for this report.
Declaration of Conflicting Interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding The authors received no financial support for the research, authorship, and/or publication of this article.
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