p2

Decreasing Wait Times and Increasing Patient Satisfaction

A Lean Six Sigma Approach Mary Godley, DNP, MSN, RN, NE-BC; Jeanne B. Jenkins, PhD, MBA, RN

ABSTRACT Background: Patient satisfaction scores in the vascular interventional radiology department were low, es- pecially related to wait times in registration and for tests/treatments, with low scores for intentions to recommend. Purpose: The purpose of our quality improvement project was to decrease wait times and improve patient satisfaction using Lean Six Sigma’s define, measure, analyze, improve, and control (DMAIC) framework with a pre-/postintervention design. Results: There was a statistically significant decrease in wait times (P < .0019) and an increase in patient satisfaction scores in 3 areas: registration wait times (from 17 to 99 percentiles), test/treatment (from 19 to 60 percentiles), and likelihood to recommend (from 6 to 97 percentiles). Conclusions: Lean Six Sigma was an effective framework for use in decreasing wait times and improving patient satisfaction. Key words: interventional radiology, Lean Six Sigma, patient satisfaction, quality improvement, wait time

The number of outpatient visits in commu- nity hospitals across the United States has

increased substantially, from approximately 390 million visits in 1994 to approximately 690 mil- lion visits in 2014.1 Moreover, the patients re- ceiving outpatient procedures are often elderly. People 65 years and older currently account for 15% (46 million) of the US population, and this number is expected to grow to 74 million by 2030.2 Of the older Americans 65 years and older in 2012, 35% received outpatient hospital and physician care.2 These changes are similar to those found in the project hospital. Unexpected waiting may increase anxiety and stress for these patients and their families and may demonstrate disorganization of the processes and disrespect for those waiting.3,4

Author Affiliations: Alamance Regional Medical Center-Cone Health, Burlington, North Carolina (Dr Godley); and School of Nursing, The University of North Carolina at Greensboro (Dr Jenkins).

The authors declare no conflicts of interest.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (www.jncqjournal.com).

Correspondence: Mary Godley, DNP, MSN, RN, NE-BC, Alamance Regional Medical Center-Cone Health, 1240 Huffman Mill Rd, PO Box 202, Burlington, NC 27215 (mary.godley@conehealth.com; mpgodley@alumni.uncg.edu).

Accepted for publication: February 7, 2018 Published ahead of print: June 8, 2018

DOI: 10.1097/NCQ.0000000000000332

LOCAL PROBLEM

Nursing leadership in the vascular interventional radiology (VIR) department noticed that patient satisfaction scores as measured by Press Ganey (PG)5 were low, especially related to wait times in registration and test/treatment, and were low for intentions to recommend. Patients verbally com- plained to nursing staff about long wait times in registration and in the preprocedure area and fre- quently cancelled procedures or left before the procedure began. There was no consistent pro- cess for scheduling patients, and procedures were often overbooked. The patients were scheduled by the hospital and office schedulers on a first available time slot process and were given an ap- pointment without regard to type or length of procedure and its effect on staffing. In addition, this patient population was not preregistered and often waited in long lines during registration. These issues caused patient dissatisfaction due to longer-than-expected wait times on the day of procedure, along with nursing and vascular ra- diology technician dissatisfaction around consis- tently unplanned hours of operation.

Therefore, due to the importance of timeliness, patient satisfaction, and the need to be compet- itive, the purpose of this quality improvement (QI) project was to improve processes to de- crease wait times and increase patient satisfac- tion in the VIR department. The framework used

Copyright © 2019 Wolters Kluwer Health, Inc. Unauthorized reproduction of this article is prohibited.

J Nurs Care Qual • Vol. 34, No. 1, pp. 61–65 • Copyright © 2019 Wolters Kluwer Health, Inc. All rights reserved. www.jncqjournal.com 61

62 Decreasing Wait Times and Increasing Patient Satisfaction Journal of Nursing Care Quality

was Lean Six Sigma and its define, measure, an- alyze, improve, and control process (DMAIC).

LITERATURE REVIEW Specific areas in health care, such as operating rooms, emergency departments, and ambulatory surgical settings, often have inefficiencies around scheduling variations, flow, staffing, and man- agement of information, all of which may impact wait times.6-9 These inefficiencies are the same is- sues experienced in outpatient procedure depart- ments. In a landmark study by Leddy et al,3 wait time trends and patient satisfaction with care in outpatient treatment/test facilities were exam- ined. The authors concluded that the patient may view his or her appointment time as an agree- ment or pledge, and if not seen on time, the wait is then viewed as a broken promise. Leddy and colleagues,3 as well as a study by Lemos et al,10

noted a negative correlation between wait times and satisfaction ratings.

Two studies specifically used Lean Six Sigma methodology.6,9 Cima et al6 evaluated efficiency in an 88-bed operating room system between 2 hospitals. The authors6 demonstrated that sur- gical patient wait times longer than 10 minutes were significantly decreased after implementa- tion of a Lean Six Sigma methodology project across numerous surgical specialties (P < .0001). In addition, on-time arrival to the preoperative area was significantly improved from 52% to 81% (P < .0001).6 The authors6 developed interventions that redefined preoperative and scheduling processes and decreased nonopera- tive times, such as turnover. Likewise, Groom and Mayeaux9 provided a conceptual frame- work using Six Sigma and statistical process control tools to reduce patient wait times by conducting a prospective study of wait times in an obstetric outpatient clinic. The authors argued that patient satisfaction was related to waiting, although it was not directly measured. In addition, Groom and Mayeaux9 explained how a root cause analysis helped identify specific causes within the system for the prolonged wait time and found that differences in the mean wait times were statistically significant (P <

.001). Furthermore, the researchers9 noted the frequently cited reasons for clinic delays were the provider starting late and improper appoint- ment scheduling, which are reasons cited for delays in the current project.

Lastly, several studies used PG patient satis- faction survey results within their QI projects to explore variables that attributed to patient sat- isfaction or to seek ways for improving patient flow and decreasing wait times.7,8,11 Like the PG survey questions used in the current project, a retrospective study by Handel et al7 reviewed PG patient satisfaction surveys in an emergency department to identify any variables associ- ated with the questions on “overall experience,” “wait time in the treatment area before you were seen by a physician,” and “likelihood to recom- mend to others.”7(p605) The authors7 analyzed PG survey results from 2034 patients and found that increased door-to-room time was associated with lower scores (a 0.61-point decrease in score for each 1-hour increase in time).

METHODS Setting The setting for this QI project was an outpatient vascular procedure department of a commu- nity hospital in the Southeastern United States. On average, 600 to 700 outpatient procedures are performed per year in this department. The department consists of a 9-bed prepara- tion/recovery area and 1 VIR laboratory.

Sample The sample size consisted of all adult vascular patients, 18 years and older, who were scheduled for an outpatient nonemergency procedure in the VIR department. Other patient demograph- ics, such as age and gender, were not consid- ered for this project. Data were collected for the preintervention period between August 1, 2015, and December 31, 2015, and the postin- tervention period of January 1, 2016, and April 30, 2016. In addition, there are no seasonal im- plications or variation in procedure types pre-/ postintervention periods. For the preprocedure wait times, there were 287 patients in the prein- tervention group and 276 patients in the postin- tervention group. PG survey results for wait time in registration, test/treatment, and likeli- hood to recommend were used to measure pa- tient satisfaction (n = 56 preintervention; n = 26 postintervention).

Intervention Define A project team led by a Six Sigma black belt specialist was formed consisting of all process

Copyright © 2019 Wolters Kluwer Health, Inc. Unauthorized reproduction of this article is prohibited.

January-March 2019 • Volume 34 • Number 1 www.jncqjournal.com 63

stakeholders including (a) the nurse assistant director, (b) a preprocedure RN, (c) a cardiovas- cular (CV) technician from the VIR laboratory, (d) the physicians’ office manager and sched- uler, and (e) the hospital schedulers and their supervisor. The team developed a project charter and time line to establish goals of decreasing wait time and increasing patient satisfaction for the improvement project. The primary metric was time waiting for procedure from scheduled time to actual start time. The plan included the following: educate all staff on the project and flowchart processes and identify possible issues, collect patient procedure times from the current data form, observe processes in registra- tion and VIR departments, monitor PG patient satisfaction scores, implement identified areas of improvement, and monitor processes.

The black belt specialist performed a gemba (where the work occurs) investigation in the vas- cular preprocedure and registration areas.12 Ob- servations included the registration process and the patient flow in the prep-recovery nursing area. Findings included long lines to register, no preregistration, patients waiting for procedures up to 2 hours longer than expected, and cases taking longer than scheduled.

The team met biweekly and staff were asked to share the information from the meetings with their respective departments. The team exam- ined patient satisfaction scores and wait times in the VIR and registration departments, pre- and postintervention. Registration wait time was de- fined as the time a patient arrives at registration on the day of procedure to the time registration is complete. The preprocedure wait time was de- fined as the period from patients’ expected pro- cedure start time until they are taken to the pro- cedure room. The customer was defined as the patient having a procedure in the VIR depart- ment during the project time line. Finally, patient satisfaction was defined as the patient’s rating of their experience regarding wait time in registra- tion, test and treatment area, and overall experi- ence (likelihood to recommend) as measured by the PG scores.

Measure During the preintervention period, the team de- veloped a process map, or a formal flowchart diagram, of the VIR department’s current pro- cesses. The processes began with the physician’s office calling to schedule a VIR procedure and

ended with the time the patient left the prep area to go to the procedure room. In addition, the VIR scheduler provided a report that captured the top 5 procedures performed, along with the average procedure times versus the scheduling system de- fault times. This report allowed the team to ex- amine whether enough time was being allowed for each of the 5 procedures per physician. More- over, a manual log was being kept by the charge nurse in the prep-recovery area that recorded the time the patient arrived in the department and the time the patient left for the procedure in the VIR laboratory. Finally, the PG survey (Hospital Consumer Assessment of Healthcare Providers and Systems) was used for patient satisfaction re- sults. The following PG questions were used for data collection: (a) registration: waiting time in registration, (b) test and treatment, and (c) like- lihood of recommending.

Analyze A failure mode and effects analysis (FMEA) was conducted to identify possible process failures and determine variables and recommendations for improvement. The team reviewed patient sat- isfaction scores and the average length of time patients waited for procedures, from the ex- pected to the actual procedure start time. The results were displayed using a statistical process control chart with average weekly wait times from August 1, 2015, to April 30, 2016 (see Sup- plemental Digital Content, the Figure, available at: http://links.lww.com/JNCQ/A431).

Improve After brainstorming solutions for primary fail- ure causes, changes were made between January 1, 2016, and February 28, 2016, to the existing processes. First, the team suggested scheduling changes in times allowed for the physicians’ pro- cedures based on their average case times, which were obtained from the review of each physi- cian’s average procedure times. For example, one physician performed the longest case type in an average of 90 minutes, while another performed the same case type in an average of 120 min- utes. Historically, this longer case type caused an increase in patient waiting due to inaccurate scheduled case duration. Any proposed process changes and education concerning how to con- duct them were presented before implementation to all staff involved to ensure understanding.

Copyright © 2019 Wolters Kluwer Health, Inc. Unauthorized reproduction of this article is prohibited.

64 Decreasing Wait Times and Increasing Patient Satisfaction Journal of Nursing Care Quality

Another major change was to schedule the longer procedures in the morning and the shorter procedures in the afternoon, since the longer procedures usually had a longer recovery time and were causing staff to incur overtime. In addition, the patients historically believed the arrival time was the beginning of the procedure time; therefore, the office redesigned the proce- dure information handout to inform the patient that they would be arriving approximately 1 hour prior to the procedure for preoperative processes. The team also agreed to not schedule skilled nursing facility patients as the first case in the morning due to challenges in schedul- ing transportation to the outpatient vascular procedure department and causing late first case starts. Since many of the first cases were frequently arriving late to the procedure area, these patients were asked to come 75 minutes before the procedure was scheduled, instead of 60 minutes, to also prevent late first case start times. Finally, the office staff and the registration department together developed a preregistration form. The patient completed the form while in the office preprocedure, and it was faxed to hospital registration, where the registration staff would preregister the patient. This task decreased wait time while in registration.

Control No additional process changes were made be- tween March 1, 2016, and April 30, 2016. The purpose of this control phase was to monitor the processes to ensure any changes that had already occurred were maintained and being used as re- designed. Data were reviewed every 2 weeks for changes in wait times and patient satisfaction. In addition, regular team meetings continued to en- sure processes were being maintained and under- stood as purposed.

RESULTS An independent t test for unequal variance was performed on the mean weekly procedure wait times pre- and postintervention. The mean wait time decreased from 36.89 minutes preinterven- tion to 20.49 minutes postintervention (t = 3.35, P = .0019). In addition, a control chart demon- strated a gradual decline in procedure wait times in minutes between August 2015 and April 30, 2016 (Supplemental Digital Content, the Figure, available at: http://links.lww.com/JNCQ/A431).

The PG patient satisfaction scores in the all database percentile ranking comparisons

increased in all 3 categories, which are based on the percentage of patients who rated the highest possible score on the survey’s 5-point Likert scale. These responses were converted by PG into a 100-point scale to aid in a better understanding with statistical mean scores.5 The wait time in registration category increased from an average of the 17th percentile (n = 54) to an average of the 99th percentile (n = 26), the test/treatment category increased from an aver- age of the 19th percentile (n = 56) to the 60th percentile (n = 26), and the likelihood to recom- mend category increased from an average of the 6th percentile (n = 56) to an average of the 97th percentile (n = 26). Although the PG sample size for the satisfaction scores was markedly different, there was still a noticeable increase in ranking. Inferences may be made that the change in the satisfaction scores was a result of the new processes.

DISCUSSION Using Lean Six Sigma via the DMAIC process, a multidisciplinary team was formed to develop a charter and perform an FMEA to identify pos- sible process failures in the outpatient vascular procedure department. Using this methodology, the team redesigned the processes and decreased patient wait times by an average of about 16 minutes. Patient satisfaction scores, as mea- sured by PG, were also improved in the 3 areas of registration, test/treatment, and likelihood to recommend. Even though average staff overtime did not change, the staff verbalized they were satisfied with a better predictability for it because of the QI interventions. Furthermore, due to the project resulting in improved patient satisfaction and decrease in waiting, a loss could be avoided of approximately $30 000 per case not cancelled.

The interventions implemented during this QI project resulted in a significant decrease in wait times and increased PG patient satisfaction scores. As described by Hughes,13 the project team found that Six Sigma concepts can be used effectively with tools such as FMEA and the plan-do-study-act (PDSA) cycle. Equally impor- tant to the positive results were clarification of the problem, involvement of key stakeholders, and monitoring of performance. Furthermore, the project findings of decreased wait times and increased patient satisfaction using Lean Six Sigma via the DMAIC framework were like those found in other studies.6,7,9

Copyright © 2019 Wolters Kluwer Health, Inc. Unauthorized reproduction of this article is prohibited.

January-March 2019 • Volume 34 • Number 1 www.jncqjournal.com 65

Limitations The setting of a small community hospital out- patient vascular procedure department with 1 laboratory and a 9-bed preoperative area made it more difficult to change some processes due to limited time slots. This constraint prohibited process changes, such as leaving an open hour block of time midday for emergencies. Further- more, the number of PG surveys returned for this procedure area was small for the postinterven- tion period and could affect the validity of the patient satisfaction data comparison between the pre- and postintervention data. Another limita- tion was the use of a manual tool to record pa- tient entrance times, which was often rounded to the nearest 5 minutes by staff and may have caused erroneous time information due to hu- man error.

CONCLUSIONS After the changes were implemented in this QI project, patient satisfaction was increased signif- icantly related to wait times. Patient complaints also lessened. The process for scheduling patients based on the type of procedure and time needed has also remained consistent. This QI project may be useful to all nurse leaders as an exam- ple of the tools available to improve patient care processes. In addition, an increase in staff aware- ness for communication to patients and families regarding expected and unexpected waits may lead to an increase in patient satisfaction and decrease in anxiety, and make the wait more pleasant.

Patient satisfaction is important for hospitals to remain competitive and for nurse leaders who are held accountable for their unit scores. Due to a lack of studies examining patient wait times and patient satisfaction in VIR procedure depart- ments, more QI studies are needed for a better

understanding of actual versus alleged wait times and patient satisfaction. Moreover, improving timeliness in health care is essential for reducing delays in care and thus improving quality.

REFERENCES 1. American Hospital Association. Chartbook: Trends af-

fecting hospitals and health systems. http://www.aha.org/ research/reports/tw/chartbook/index.shtml. Published June 2016. Accessed September 30, 2016.

2. Federal Interagency Forum on Aging-Related Statistics. Older Americans 2016: Key Indicators of Well-Being. Washington, DC: US Government Printing Office. https:// agingstats.gov/docs/LatestReport/Older-Americans-2016- Key-Indicators-of- WellBeing.pdf. Published August 2016. Accessed September 30, 2016.

3. Leddy K, Kaldenberg D, Becker B. Timeliness in ambulatory care treatment. J Ambul Care Manage. 2003;26(2):138-149.

4. Freeman K, Denham SA. Improving patient satisfaction by addressing same day surgery wait times. J Perianesth Nurs. 2008;23(6):387-393.

5. Press Ganey Associates home page. http://www.pressganey. com/. Accessed July 20, 2015.

6. Cima RR, Brown MJ, Hebl JR, et al. Use of Lean and Six Sigma methodology to improve operating room efficiency in a high-volume tertiary-care academic medical center. J Am Coll Surg. 2011;213(1):83-92.

7. Handel DA, French LK, Nichol J, Momberger J, Fu R. As- sociations between patient and emergency department oper- ational characteristics and patient satisfaction scores in an adult population. Ann Emerg Med. 2014;64(6):604-608.

8. Sayah A, Rogers L, Devarajan K, Kingsley-Rocker L, Lobon LF. Minimizing ED waiting times and improv- ing patient flow and experience of care. Emerg Med Int. 2014;2014:981472.

9. Groome LJ, Mayeaux EJ. Decreasing extremes in patient waiting time: Qual Manag Health Care. 2010;19(2):117- 128.

10. Lemos P, Pinto A, Morais G, et al. Patient satisfaction fol- lowing day surgery. J Clin Anesth. 2009;21(3):200-205.

11. Farber J. Measuring and improving ambulatory surgery pa- tients’ satisfaction. AORN J. 2010;92(3):313-321.

12. McClam Liebengood S, Cooper M, Nagy P. Going to the Gemba: identifying opportunities for improvement in radi- ology. J Am Coll Radiol. 2013;10(12):977-979.

13. Hughes RG. Tools and strategies for quality improvement and patient safety. In: Hughes RG, ed. Patient Safety and Quality: An Evidence-Based Handbook for Nurses. Ad- vances in Patient Safety. Rockville, MD: Agency for Health- care Research and Quality (US); 2008. http://www.ncbi.nlm. nih.gov/books/NBK2682/. Accessed April 8, 2017.

Copyright © 2019 Wolters Kluwer Health, Inc. Unauthorized reproduction of this article is prohibited.