As health care demands more efficiency within hospitals, it’s possible to adapt existing teams to respond to the challenge in a transformative way.
Evolving reimbursement models have made managing hospital patient throughput, or patient flow, critical to the overall success of academic and community medical centers alike. While every hospital has unique challenges, a disciplined approach to evaluation, assessment and performance improvement allows leaders to identify problems and find opportunities to improve them. Tools and skills acquired through change management education and leadership development training can provide the framework for optimization. Effective use of data to provide meaningful information to each workgroup makes progress possible. And transformational leadership matched to empowered followership drives success.
In federal fiscal year 2012, the Centers for Medicare & Medicaid Services added efficiency measures to the Inpatient Prospective Payment System rule. Efficiency and cost-reduction measures account for 25 percent of the total value-based purchasing program.1 Additionally, in the Medicare Shared Savings Program, CMS calculates the total cost of health care spending for each Medicare beneficiary over a calendar year and measures each participant against total Medicare spending.2 The transition from traditional volume based payments to measurement-based reimbursement broadens the focus from such measures as total visits and level of intensity of each visit, to measures of processing time and complexity of studies ordered.
At the same time, the number of emergency department visits has grown annually for the past 20 years..3 Growth rates that exceed a hospital’s ability to expand physical space create logistical challenges when it comes to patient movement, often leading to patients who leave without being seen and delays in treatment.
Similarly, overall reduction in the number of hospital beds over a geographic region increases each hospital’s capacity percentage, further complicating the flow of hospitalized patients. While this is offset by shorter lengths of stay and fewer hospitalizations, increased transitions over a shorter period of time create logjams in ancillary services such as radiology, physical therapy and environmental services. The net result is patients for hospitalization being held in the emergency department longer than desired.
That leads to decreased efficiency scores and has been associated with higher hospital readmission rates, increased mortality and potentially sick patients leaving before receiving clinical care.4,5 Satisfaction and experience scores also drop during periods of emergency department crowding.6,7
But collaboration, cooperation and communication, along with frontline staff empowerment and standardization through the use of concrete and transparent measures, can increase efficiency and allow for better patient placement.8,9 Evidence supporting the placement of patients of a service together on a common floor is antithetical to the idea of rapid placement to any available bed from the emergency department when bed capacity nears 100 percent.10,11
While there’s little evidence of the benefit of early-in-day discharges for individual patients, systemwide literature supports the notion at a population level.8 Finally, pressures to rush through the discharge process or inappropriately discharge a patient before safe transition can occur can lead to poor outcomes, warranting specific measures to prevent it.
For general patient flow tracking, CMS and the Joint Commission require data tracking on the average time from a patient’s arrival in the emergency department to the time an admitted patient receives a hospital bed and from the time the decision to admit is made until a bed is received. CMS also requests data for the time that elapses from a patient’s arrival to when a qualified medical professional performs a diagnostic evaluation, as well as percentage of patients who leave the emergency department after registration without being seen.
CMS uses other time-based measures to assess quality of care delivery in specific conditions. Beyond the required reporting, emergency departments typically measure the number of patients in the waiting room, sorted by triage level. Hospitals also might measure the number of admitted patients occupying beds in the emergency department and the percent of time the emergency department is on “divert” status or otherwise unavailable to ambulance services.
Within the hospital, common measurements include percent occupancy, average daily census, length of stay, case mix index and the average time of day for discharges. Other measures can include more-subjective data, such as causes of delayed transitions and concerns about staffing. Less-common measures, such as bed turnover time, also contribute to a better understanding of bed use.
Process for Optimization
At Temple University Hospital in Pennsylvania, an inter-professional team meets weekly to review patient flow data and address concerns that range from geographic patient assignment to delayed discharges. Physicians, residents, nurses, case managers, social workers, registrars and ancillary services coordinate improvement efforts through this group, using the institutional project management office along with hospital performance improvement coordinators. One result of the work is geographic placement of patients by service line.
Historically, patients receiving similar treatment would be scattered throughout the hospital’s nine floors, making rounds less efficient and creating difficulty for staff to locate physicians. Setting geographic parameters based on treatment allowed the assignment of unit-based medical directors working in dyadic partnerships with nurse managers. Together, they were responsible for service unit outcomes in quality, efficiency and customer experience.
During times of moderate occupancy, 90 to 95 percent of patients are placed geographically. The system created via the geo-throughput team allows flexibility to place patients off the designated service unit during periods of high bed occupancy and sets a minimum target of 80 percent.
More recently, local hospital closures, increasingly complex patients through the recruitment of highly focused subspecialists, and an expanded secondary service area have increased our average daily occupancy to 90 percent, surging to capacity. The resulting effect of delayed discharges, increased admission holds in the emergency department, increased waiting room times and decreased customer experience scores led the geo-throughput team to take a fresh look at the patient flow challenge.
Historically, the team worked through administration directives and solved challenges presented by senior leaders. The proposition of a new paradigm required a change in seeking, defining and addressing opportunities for improvement in patient throughput. Rather than top-down techniques of change, leaders infused a grass-roots, bottom-up process of idea generation and solution implementation.
Initial resistance, stemming from a new organizational leader incorporating novel approaches, led to a series of one-on-one meetings to engage team members and other hospital leaders in the process. Using an eight-step process for change,12 the leadership team set course for the new process. The geo-throughput team provided the structure and direction while hospital leadership broadcast the vision of a more efficient environment leading to fewer emergency department admission holds and less time on “divert.”
The performance improvement team engaged in the effort first and offered to provide guidance in rapid-cycle change techniques, using Lean management tools as necessary. The project management director developed a plan to provide data upon request in a timely fashion. The hospitalist program director and associate chief nursing officer continued as co-team leaders with a new associate CMO joining them, and all three readily embraced the revised technique. Other key nursing leaders committed to giving the method a chance. The regular weekly meetings were adjusted to fit the process without adding additional time commitments to team members. Sessions included brainstorming, idea evaluation and determination of achievable projects. The ideas included one that warranted escalation to the hospital’s senior leadership team for consideration; it involved reorganization and simplification of the bed coordination and distribution process.
Tasks at Hand
Three projects made the final cut for project work. A full session dedicated to fleshing out the vision for the team and the goals and objectives for each project helped align the work. The team formed subgroups based on interest and ability to influence the final outcomes. Team leaders and performance improvement specialists joined the smaller groups with the directive to guide and coach rather than lead the project work. The project management office provided charter and change framework tools along with data for the overarching and individual subgroup goals.
Brainstorming began with ground rules that all ideas would be documented and that no bad ideas existed. Instructions called for focus on positive ideas for change with strict time and number limits for identifying barriers. Each step of the patient flow process warranted dedicated thinking time. Ideas were displayed without judgment and categorized into the major phases of admission, bed placement and discharge. Presented as “opportunities,” ideas became potential projects. Later, after reviewing the ideas, members voted on the projects of their choice in each phase. The three projects with the most votes became the chosen project work.
Subgroups formed by asking members to lead each project and allowing each to choose the people they wanted to join. Once formed, the subgroups began by determining membership gaps and resource needs. Each subgroup leader independently contacted potential teammate additions while the geo-throughput leaders allocated the necessary resources. From there, charter development, process flow mapping and brainstorming for change ideas resulted in the development of small tests of change.
The full geo-throughput team continued meeting weekly; subgroup work occurred two of every three weeks, with a check meeting on the third week to ensure progress and alignment. Full team meetings also provided opportunities for celebration and identification of barriers. Work continued in this format as projects developed and teams evolved. Regular touch points with subgroup leaders helped maintain focus, energy and alignment.
One project focused on patient flow huddles coordinated by bed placement services. Before the redesign, each nursing unit participated in a variety of time-consuming meetings each day to discuss throughput, tying up charge nurses, nurse managers and case managers. The project team created a table of meetings, identified the stakeholders for each meeting and outlined the objectives and outcomes. Next, the team streamlined the meeting agendas and determined which were to be in-person meetings vs. phone conferences, and which could be written reports. Finally, the team rolled out the new meeting structure and solicited feedback on the redesign. On average, the redesign reduced the time spent in meetings by 25 percent (45 minutes) for all stakeholders and standardized the data received during the meetings.
Another initiative focused on identifying causes preventing early discharge. Case management, nursing and physicians met daily at 11 a.m. to discuss pending discharges. Once categorical causes could be identified, specific interventions were implemented on the unit to address the major causative factors. For example, 34 percent of the delayed discharges resulted from consultant visits not being completed by the time of anticipated discharge. With the factors identified, consultants were educated and received reminder phone calls from the unit manager. That led to greater responsiveness of those services and fewer stated delays of that nature.
A third project involved arranging shuttles at specified times for discharged patients to receive rides home. This involved moving discharged patients from the nursing floor to a shuttle waiting area no more than 15 minutes before a scheduled pickup. The shuttle driver, from a participating transportation company, is to greet patients and take them where they need to go. This project requires coordination of many areas inside and outside the system and has taken longer to implement.
For these projects, the geo-throughput team regularly updated hospital and system leaders on the work and broadly disseminated the strategies to all stakeholders as the changes went live. Scorecards summarized the quantifiable results, and storytelling humanized the work. Continual evaluation of the work and development of new projects will help meet the needs of an evolving health care system.
Patient throughput continues to be a challenge in hospitals as the complexity of patients increases and financial restrictions grow. By organizing an integrated workgroup focused on flow, from entry into the emergency department waiting room through hospital discharge, holistic approaches can be taken. Iterative process improvement through grass-roots ideas can be successful in an environment favorable to employee engagement, frontline leadership and transformative system leaders. Tools can aid the process; however, people form the backbone for successful change initiatives.
Tony S. Reed, MD, MBA, CPE, FAAFP, FAAPL, is associate chief medical officer at Temple University Hospital.
- Centers for Medicare and Medicaid Services (September 2015). Hospital Value-Based Purchasing. Retrieved May 23, 2016, from Medicare Learning Network. cms.gov/Outreach-and-Education/Medicare-Learning-Network-MLN/ MLNProducts/downloads/Hospital_VBPurchasing_Fact_Sheet_ICN907664.pdf
- Office of the Federal Register (2015). Title 42, Part 425: Medicare Shared Savings Program. Retrieved May 24, 2016, from Code of Federal Regulations: http://www.ecfr.gov/cgi-bin/retrieveECFR?gp=1&SID=9cbc79f810 3dc64535741369912f044f&ty=HTML&h=L&r=PART&n=42y22.214.171.124.12
- Hernandez-Boussard T, Burns CS, Wang NE, Baker LC and Goldstein BA (2014). “The Affordable Care Act Reduces Emergency Department Use by Young Adults: Evidence from Three States,” Health Affairs, 33(9), 1648- 1654. doi:10.1377/hlthaff.2014.0103
- Bindman AB, Grumbach K, Keane D, Rauch L and Luce JM (1991). “Consequences of queuing for care at a public hospital emergency department,” JAMA, 266(8), 1091-1096.
- Miro O, Antonio MT, Jimenez S, De Dios A, Sanchez M, Borras A and Milla J (1999). “Decreased health care quality associated with emergency department overcrowding,” European Journal of Emergency Medicine, 6(2), 105-107.
- McMillan JR, Younge MS and DeWine LC (1986). “Satisfaction with hospital emergency department as a function of patient triage,” Health Affairs, 11(3), 21-27.
- Thompson DA, Yarnold MS, Williams DR and Adams SL (1996). “Effects of actual waiting time, perceived waiting time, information delivery, and expressive quality on patient satisfaction in the emergency department,” Annals of Emergency Medicine, 28(6), 657-665.
- Jweinat J, Damore P, Morris V, D'Aquila R, Bacon S and Balcezak TJ (2013). “The safe patient flow initiative: a collaborative quality improvement journey at Yale-New Haven Hospital,” The Joint Commission Journal on Quality and Patient Safety, 39(10), 447-459.
- Society of Hospital Medicine Benchmarks Committee (2005). “Maximizing throughput and improving patient flow,” The Hospitalist (supplement). thehospitalist.org/details/article/279433/Maximizing_Throughput_and_Improving_Patient_Flow.html
- Pronovost P, Weast B, Rosenstein B, Sexton JB, Holzmueller CG, Paine L and Rubin HR (2005). “Implementing and validating a comprehensive unit-based safety program,” Journal of Patient Safety, 1(1), 33-40.
- Pardini-Kiely K, Greenlee E, Hopkins J, Szaflarski NL and Tabb K (2010). “Improving and sustaining core measure performance through effective accountability of clinical microsystems in an academic medical center,” The Joint Commission Journal on Quality and Patient Safety, 36(9), 387-398.
- Kotter International (2015). The 8-Step Process for Leading Change. Retrieved May 1, 2016, from kotterinternational.com/the-8-step-processforleading-change/