The University of Michigan Radiation Oncology Clinic Analysis of Waste in the Radiation Oncology Clinic Patient Flow Process.

Transcription

1 The University of Michigan Radiation Oncology Clinic Analysis of Waste in the Radiation Oncology Clinic Patient Flow Process Final Report Prepared for: Kathy Lash, Director of Operations University of Michigan Radiation Oncology Clinic Sheri Moore, Project Coordinator and Lead Industrial Engineer University of Michigan Hospital Program & Operations Analysis Prepared by: Katie Mickley, Senior IOE Greta Schaltenbrand, Senior IOE Sara Swenson, Senior IOE Student Lean Team, Group 8 Date of Submission: December 10, 2007

2 Executive Summary The Radiation Oncology Clinic at The University of Michigan Hospital has reported a high incidence of waste in the patient treatment process. Waste is defined as missing documents, incomplete information, and/or incorrect information that occur in a patient s chart and on a patient s body. When waste is identified, it is often passed on to subsequent machine visits resulting in rework, rather than being corrected immediately. This waste leads to longer process times, frustration among patients and employees, and unnecessary rework. Waste may also cause a patient to visit the clinic more times than are necessary. Therefore, the clinic needed to quantify the amount and type of waste being produced before and during the first two machines visits. The clinic also requested recommendations to reduce the amount of waste produced during the patient treatment process. Thus, the main goal of this project was to quantify the amount of waste produced, and to recommend ways to reduce this waste, before and during the first and second machine visits to the Radiation Oncology Clinic at The University of Michigan Hospital. The key issues driving this project were large amounts of waste and rework, long patient delays, extended workday duration, and unfinished treatments during the patients' first machine visit. To complete this project, the team performed a literature search, completed 60 total hours of observations in the clinic, conducted interviews of 8 clinic staff members, created and collected 67 Quality Assurance data sheets, and analyzed the data in an Excel spreadsheet. The team's qualitative and quantitative findings are as follows: Interviewees reported the greatest source of waste is incomplete Patient Activity Document (PAD) The team observed that patients were sometimes treated on machines other than the machine on which they were scheduled to maintain clinic flow The data showed that first time quality at the first machine visit is 39% The data showed that treatments are completed on the first machine visit 90% of the time The three greatest sources of waste can be seen in Table 1 below: Table 1: The most frequent cause of waste for all of the data is patients missing tattoos. All Data Missing Tattoo 53% 36 Move Imaged Fields at least once (2 nd Visit) 44% 55 Missing Face Photo 30% 67 The team stratified the data collected based on type of machine (EX 1 and EX 2, EX 3 and EX 4, and 600 C/D), IMRT patients, Doctor (I - V), and shift (morning and afternoon). 1

3 Based on the data analysis, the team concluded that the greatest source of waste is patients missing a tattoo, which occurs 53% of the time. Missing Tattoo refers to a patient who needed a tattoo to help set the Iso-Center but did not have one at the first machine visit. Other common sources of waste were moving imaged fields on both the first and second machine visits, and missing face photo. The results from the stratified categories are consistent with the overall data and are examined in detail in the report. To reduce waste in the Radiation Oncology Clinic patient treatment process, the team recommends the following: Perform a root cause analysis on top three sources of overall waste Use Quality Assurance during all machine visits Prepare a patient s chart at least ½ day in prior to his scheduled machine visit The team recommends that a root cause analysis only be performed on the highest sources of waste that occur in the clinic: missing tattoos, moving imaged fields during both the first and second machine visits, and missing face photos. To further analyze the root causes of waste, the team recommends focusing on the differences between the two shifts (morning and afternoon) to determine whether or not preparation time affects the amount or type of waste produced. The team also recommends that the RTT s use Quality Assurance during each machine visit and do not move forward in the treatment process if there is missing or incomplete information on a patient or on a patient s chart. Instead, the RTT s should work to correct the waste thus preventing waste from being passed on to the next treatment stage. Also, the team learned that patient s charts were usually not reviewed until the day of a patient s appointment, if not during the treatment; therefore, the team further recommends that a staff member review a patient s chart at least ½ day in advance. The implementation of these recommendations will cause a reduction in waste in the patient treatment process. The reduction in waste will result in a reduction in patient and employee frustration, a reduction in workday duration, and, potentially, fewer visits to the clinic for patients. 2

4 Introduction Services at the Radiation Oncology Clinic at The University of Michigan Hospital are in high demand. The Director of Operations of the Clinic reported that during the patients first two machine visits, there is a high incidence of waste which leads to longer process times, frustration among patients and employees, and unnecessary rework. The team and the client defined waste as missing documents, incomplete information, and/or incorrect information that occur in a patient s chart or on a patient s body. The Director of Operations has tried implementing check sheets listing information for each step in the treatment process; however, these check sheets were ineffective because employees did not fill them out appropriately. Therefore, the client needed to quantify the amount of waste being produced so that further improvements could be made to the patient treatment process. An analysis of the treatment process flow was initially performed in September 2006 by a student lean team. At that time, the team found that most treatment days last until 7PM, with some days extending until 10PM. As reported in the previous team s findings, these long hours result from a lack of standardized work, delay in communication, missing or incomplete patient information (known as waste), and variation in appointment times. The previous team made several recommendations to streamline the treatment process, including standardizing work and creating a scheduling station. In addition, recommendations were made by a second student lean team to better utilize the examination rooms, including improving the communication among the staff and improving the flexibility of machine usage, as well as scheduling more appropriate appointment durations. The Radiation Oncology Clinic implemented these changes, and the Clinic s Director of Operations stated that the workday was reduced by two hours. The client believed, however, that there was still room for improvement. In response to this problem, the team collected data on the amount and type of waste produced prior to and during the patients first two machine visits to the clinic. The team used the term machine visit rather than treatment visit because patients are not always treated on their start day. The team developed Quality Assurance (QA) sheets that the Radiation Treatment Therapists (RTT s) filled out during the patients first two machine visits (See Appendix A). The team believed that the RTT s would more thoroughly fill out these check sheets than they had filled out past check sheets because these data was only collected for three weeks and the results of this study will benefit the RTT s. The team analyzed the data collected from the QA sheets to quantitatively determine the amount of waste that occurs from missing and/or incomplete information in a patient s chart. The team also determined the root causes of the waste production and developed recommendations to reduce waste in the treatment process. The purpose of this report is to present the team s findings, the results of the team s analysis, and the team s recommendations. 3

5 Goals and Objectives The main goal of this project was to quantify the amount of waste and to recommend ways to reduce the waste coming into the first and second machine visits from the pretreatment process in the Radiation Oncology Clinic at The University of Michigan Hospital. The team used QA checklists to quantify how often a specific type of waste is being produced in the clinic. This information has been quantified and the team has determined the root causes of waste in the Clinic and developed recommendations to reduce waste in the treatment process. As a result of this study, the team has developed recommendations to reduce the amount of waste in the treatment process, the length of the workday, the level of frustration among patients and employees, and process inefficiencies. More importantly, these recommendations will result in fewer visits to the clinic for the patients and greater patient satisfaction. The expected impact of this study is that the clinic will know the main types of waste produced prior to and during the patients first two machine visits and will be able to make changes to the current patient treatment process to reduce the amount of waste produced in the process. A reduction in waste will result in a more efficient patient flow process, shorter workdays, less frustration for the clinic s patients and RTT s, and, potentially, fewer visits to the clinic for patients. Background Upon a cancer diagnosis, a patient receives an initial consult to determine the appropriate treatment option: radiation, chemotherapy, surgery, or a combination of treatments. If the decision is made to treat with radiation, the patient undergoes a series of consultations and a simulated radiation treatment. Simulations occur during the pre-treatment process prior to a patient s first machine visit (known as a start ). After the simulation, a patient s information is sent to Dosimetry, where the patient s treatment plan is established. The plan is then reviewed by the Physics Department, the patient s chart is finalized, and the patient is ready for his start (see Figure 1 below). However, excessive waste sometimes results when simulations, rather than an actual treatment, occur on the treatment start day. 4

6 Figure 1. Flowchart of a patient s pre-treatment process and first two machine visits to the University of Michigan Radiation Oncology Clinic Prior to a patient s arrival on the treatment start day, the RTT obtains basic patient information, including the following: Patient chart Signed script Move sheet Face photo Digitally reconstructed radiograph (DRR) Set-up sheet When the patient arrives for the first visit, or start, the RTT verifies the following information: Tattoo present Marks present Iso-center defined Images match plan Move imaged fields On the second visit, the RTT verifies the following information: 5

7 Clear set-up instructions Set-up photos Tattoo defined Move image fields Treatments scheduled Charge capture Images match plan During each of these first two machine visits, documents and information can be missing, producing waste in the process. Missing information at any point in the treatment process causes delays in the processing time while the missing item is located. Sometimes this waste is passed on through successive treatments because rather than fixing the problem, a workaround is devised. An example of a workaround is if a patient s face photo is missing from the chart, an RTT would ask the patient for picture identification for verification and take a picture of the patient later in the treatment process. Until missing information is located, rework and delays remain a significant part of the treatment process. Key Issues The following factors in the Radiation Oncology Clinic necessitated this study: Large amounts of waste prior to and during the first two machine visits Large amounts of time wasted due to rework Patient delays Late treatment start times and treatments going over scheduled time Employees often working past normal business hours First treatment not being completed during patients first machine visit As a result of this project, the treatment process will run more efficiently, thus reducing the duration of the workday in the Radiation Oncology Clinic, the level of frustration among patients and employees, and process inefficiencies. A patient who can be treated on the first machine visit will have to visit the clinic one less time. Project Scope This project included: Analysis of waste production during a patient s first two machine visits Determination of root causes of waste Recommendation of process improvements to reduce waste 6

8 This project did not include: Processes that occur before or after the patient enters the clinic for his first two machine visits Cost analysis of late starts Measurement of the length of the workday Methodology The team examined waste in The University of Michigan Radiation Oncology Clinic through the first two machine visits. The primary parties involved in this project included the Clinic s Director of Operations, the Physics and Dosimetry staff, the Patient Clerks, and the RTTs. Throughout the project, the team met with both the coordinator and the client weekly to review the progress of the project. To conduct this study, the team made preliminary observations, conducted interviews, collected and analyzed data, and performed a literature search. From this work, the team developed recommendations to reduce waste in patients charts. Observations The team observed the current state of the Radiation Oncology Clinic, including approximately 75 radiation treatments and approximately 60 hours of patient treatment. The team shadowed the RTT s treating patients on all five machines and observed approximately 20 patients first machine visits. The team also observed the Patient Clerks and the Simulation and Dosimetry processes for approximately three hours each. Interviews The team created a list of interview questions (see Appendix B) and interviewed 3 RTT s, 2 Dosimetrists, and 2 Patient Clerks on October 25, 20007, and 1 Physicist on November 9, During these interviews, the team learned about perceived common sources and frequency of waste, and suggestions for process improvement. Quantitative Data Collection The data collection consisted of the RTT s gathering data about information missing from patients charts during the first two machine visits of the treatment process. Using the QA sheets, the RTT s verified that necessary patient information was present before and during the first two machine visits. The team organized and entered the data from 67 QA sheets into an Excel spreadsheet. The data collection started October 15, 2007 and ended November 7,

9 Literature Search The team reviewed previous IOE 481 projects including: Analysis of Treatment Process and Start Times During Radiation Therapy, by Nitin Gupta, Emily Servinsky, and Kelly Wendling and Utilization of Linear Accelerators in the Radiation Oncology Department, by Sepehr Mowlavi, Zach Shoup, and Alex Wang. The team also read articles from medical journals including: Program Operations Guidelines for STD Prevention: Evaluation and Quality Assurance, by The Centers for Disease Control and Prevention (CDC); Quality Assurance Guidelines for HIV Testing, by The CDC; and Key Issues for Expanded Electronic Laboratory Reporting, by Meade Morgan, CDC. These subjects of these articles included late starts in patient clinics, waste production, and Quality Assurance programs. The bibliography for the literature search can be found in Appendix C. Data Analysis Based on the data collected, the team quantified the amount and type of waste produced in the clinic. The team stratified the data collected based on type of machine (EX 1 and EX 2, EX 3 and EX 4, and 600 C/D), IMRT patients, Doctor, and shift (morning and afternoon). The team determined the greatest sources of waste for each category and compared those percentages to the overall percentages of missing data. In addition to comparing the stratified data to the overall data, the team compared the groups within each stratified category to each other. For example, machines EX 1 and EX 2 were compared to machines EX 3 and EX 4 and to the 600 C/D to detect differences between machine types. The client informed the team that all types of waste are considered equally critical to the patient treatment process. Based on this analysis, the team developed recommendations to reduce waste in the patient treatment process. Lessons Learned After completing the analysis, the team identified some potential improvements that could be made to the study if it were to be repeated. The potential improvements are discussed in the following section. Small Sample Size One of the main potential sources of error in this project was a relatively small sample size. Each category had a different sample size because percentages were calculated based on opportunities for waste rather than overall data collected. Percentages were calculated using the following formula: (Total Waste Responses) / (Total Opportunities for Response Blank Responses Responses of N/A) 8

10 Due to the number of blank responses or responses of Not Applicable (N/A), some categories had a relatively small sample size. Any sample size less than five was deemed inconclusive, and the team recommends that results based on small sample sizes be verified by further study. Ambiguous Wording Another possible source of error for this study was the wording of the categories on the QA sheets. For example, the category of Chart was ambiguous because a response of YES could mean either of the following: 1. Yes, I had to look for the chart 2. Yes, the chart was present In case number one, YES is a response indicative of waste, whereas in case number two a YES response indicates a lack of waste. In order to solve this problem, the team piloted the QA sheet to make sure the RTT's understood them. However, a few ambiguous categories were not discovered until the final data analysis, so the team tried to understand ambiguities using the comments section in order to accurately analyze the data. N/A Write-Ins The last potential source of error is the presence of N/A responses written in by the RTT's. N/A was not a choice for every item on the QA sheet, but sometimes the RTT s wrote N/A next to the available choices and circled it. This resulted in difficulty with data analysis because it was unclear whether blank data points were intentionally left blank because they were N/A or left blank due to oversight on the part of the RTT filling out the QA sheet. The main occurrence of this problem was linked to patients tattoos. Some patients, such as those using a mask for treatment, e- beam treatments, or children, do not require tattoos. Therefore it was unclear whether a response of W/O (Without) Tattoo meant the patient needed a tattoo and did not have one or whether it meant the patient did not need at tattoo and did not have one. To solve this problem, the team reviewed each QA sheet that had a W/O Tattoo response. If W/O was marked, the team then looked at the type of patient and additional notes to determine whether a tattoo was necessary for that patient. If the team could determine that a tattoo was not needed for that patient, the response of W/O was changed to N/A. This prevented over-reporting of waste for the tattoo category. However, the team still felt that the percentage of waste was unexpectedly high, possibly because the team could not determine that a tattoo was actually needed for every W/O response to the tattoo question. Findings 9

11 Based on the team s methodology, the following qualitative and quantitative findings were apparent. Qualitative Findings The team analyzed the qualitative data obtained through observations, staff interviews, the literature search, and RTT s comments on the QA sheets. The following sections describe the team s findings from the qualitative data. Findings from Observations The team made several interesting observations in the pre-treatment process and during the patients first two machine visits. The most frequent observations follow: Appointments were not scheduled for the correct duration Patients were not always treated on their scheduled machine due to machine backups Matching anatomy was difficult and time consuming Patient health issues hampered patient treatment Additional staff members were often called by RTT s Findings from Interviews According to the Radiation Oncology staff interviewed, the most common piece of missing information in a patient s chart was the Patient Activity Document (PAD). The PAD is a form required for every patient treated in the Radiation Oncology clinic. It contains standard information that is filled out by physicians and RTT s and dictates whether or not a patient should be treated on the first day. If the PAD is not filled out correctly and/or completely, delays in the patient process can occur. Although the PAD is outside the scope of this project, it was mentioned by all 8 interviewees as a common source of waste in the Radiation Oncology Clinic. The staff also stated that common pieces of missing/incomplete information were: match anatomy, indication of pacemakers, patients plans and scripts, and imaged fields. Other interview results showed that patients charts are checked by the RTT s anywhere from 2 hours prior to a patient s appointment time to minutes before. Dosimetry stated that a patient s plan was completed as early as 24 hours before the patient s appointment, and physics checks the plan anywhere from 12 to 0 hours prior to a patient s arrival. Collectively, each area of the Radiation Oncology clinic felt that they were paged, or needed to page someone due to missing information, several times throughout the day. However, the RTT s felt that they treated patients on the first day about 80% of the time, which has improved due to the streamlining of the scheduling process. A common suggestion for improving the overall patient treatment process was the use of an electronic system for patient charts. 10

12 Findings from Literature Search According to the studies performed by previous IOE 481 teams, the most common reason for late starts in the Radiation Oncology Clinic was a lack of standardized work amongst the RTT s, incomplete patient charts, and under-utilization of treatment rooms and machines. The Centers for Disease Control and Prevention had several articles that discussed the importance of Quality Assurance programs and listed steps on how to establish and organize such a program. Important factors such as the identification of participants and verification of the testing process were taken into consideration when the team developed the QA checklists. STD clinics have also implemented Quality Assurance programs to periodically distribute data quality reports to laboratories and providers with feedback information on performance. Findings from RTT s Comments on QA Sheets In addition to circling a choice for each category on the QA sheet, RTT s were also given the opportunity to make additional comments regarding problems that arose throughout the treatment process. There were spaces for comments after specific categories and an area for general comments on the back of the QA sheet. Many of the comments made by the RTT s were noted several times throughout the data collection process. A list of the most common comments in the general comments section can be found below: Match anatomy incomplete or missing Equipment missing No problems during treatment Chart not received by treatment time Marks are wrong or incomplete Documents in the wrong place No patient photo Directions written wrong Problems with Bolus (directions, placement, changes) Head tilt off In addition to the general comments section on the QA sheets, there was space for the RTT s to comment on what was missing from setup instructions prior to a patient s first machine visit. The comments for this section are listed below: No eyes open or closed instructions Face photo No chin extension There was also space on the QA sheets for RTT s to comment on why a treatment was not complete on the first visit. A list of these comments can be found below: Films only Scheduled appointment time not long enough Patient late 11

13 The last space on the QA sheet for comments was How was the problem resolved? after the section Did you have to call another staff member? The main comments in this section are listed below: Doctor was unavailable Called physicist to determine Thermoluminesent Dosimeter (TLD) placement Called doctor for Bolus The comments sections of the QA sheet allowed for more complete data collection. Through these comments, the Team was able to learn about problems outside of the binary questions filled out on the sheet. Quantitative Findings The team analyzed the quantitative data obtained from the QA sheets filled out by the RTT s. The following sections describe the team s findings from the quantitative data. First Time Quality First Time Quality is the percentage of time that there is no waste prior to the first machine visit. This is an important statistic because, rather than measuring particular sources of waste, the entire process is evaluated. First time quality was 39%. After calculating the first time quality, data that had zero waste prior to the first visit was analyzed and the team found that 79% of this data had zero waste after the first machine visit. Therefore, 21% waste was generated during the first machine visit. After analyzing this data, the data that had zero waste after the first machine visit was analyzed. The results were that 42% of this data had no waste after the second machine visit. Therefore, 66% waste was generated during the second machine visit, which is more waste than was generated during the first machine visit. Main Sources of Waste for All Data The three main sources of waste during the first two machine visits to the Radiation Oncology Clinic are presented in Table 2 below. The complete table of percentages of sources of waste can be found in Appendix D. Table 2: The most frequent source of waste for all of the data was patients missing tattoos. All Data Missing Tattoo 53% 36 Moved Imaged Fields at least once (2 nd Visit) 44% 55 Missing Face Photo 30% 67 The most frequent source of waste for all of the data is patients missing tattoos, which occurs 53% of the time. This piece of information is determined during the patient s first machine visit. Moving imaged fields during the second machine visit was the second most 12

14 common source of waste. Missing face photo during the first machine visit had the third highest percentage and occurred 30% of the time. The team observed that when a face photo is missing, it is not always corrected before the second machine visit; rather, it is worked-around. Main Sources of Waste Stratified by Machine The following section shows the most frequently occurring sources of waste for each machine type (EX 1 and EX 2, EX 3 and EX 4, and 600). Some categories have a higher percentage of waste than the overall data for every machine because the overall data included QA sheets that did not have machine type filled out. Table 3 below shows the most frequently occurring sources of waste for treatments performed on machines EX 1 and EX 2. Table 3: The most frequent source of waste for the EX 1 and EX 2 machines was moved imaged fields on the 2nd visit EX 1 and EX 2 Moved Imaged Fields at least once (2nd Visit) 57% 14 Missing Face Photo 29% 17 Moved Imaged Fields more than twice (1st Visit) 29% 17 Unclear Set-Up Instructions 27% 17 As shown in the table above, on a patient's second machine visit, the RTT's had to move the imaged fields at least once during the second machine visit 57% of the time, compared to 44% for the overall data. On the first machine visit, they had to move the imaged fields more than twice during the first machine visit 29% of the time, compared to 15% overall. These percentages show that RTT's have to move imaged fields during the first and second machine visits considerably more on the EX 1 and EX 2 machines than the overall data. Missing face photo and unclear set-up instructions were also some of the greatest sources of waste for machines EX 1 and EX 2. However, since this information occurs prior to the first machine visit, the team did not analyze it because it is not affected by machine type. Set-up instructions were unclear much more frequently on machines EX 1 and EX 2 (27%) than in the overall data (14%). The most frequent sources of waste from machines EX 3 and EX 4 are listed in Table 4. Table 4: The most frequent source of waste from the EX 3 and EX 4 machines was moved imaged fields at least once during 2nd machine visit EX 3 and EX 4 Moved Imaged Fields at least once (2nd Visit) 63% 26 Moved Imaged Fields more than twice (1st Visit) 60% 15 Missing Face Photo 39% 33 Missing Chart 35% 27 Calculation Not Signed 33% 22 Had to Call Doctor 27% 33 13

15 The greatest source of waste for machines EX 3 and EX 4 was moved imaged fields at least once during the second visit. This percentage (63%) is much higher than for the overall data (44%). Moved imaged fields more than twice during the first visit was the second greatest source of waste for the EX 3 and EX 4 machines. Again, this percentage of waste (60%) is much higher than for the overall data (15%). RTT s had to call a doctor 21% of the time, compared to 12% overall. Missing face photos, missing charts, and calculations not signed also accounted for a considerable amount of waste on the EX 3 and EX 4 machines; however, like the EX 1 and EX 2 machines, this data is not important to our analysis of waste based on machine type because it occurs prior to the machine visit. Table 5 presents the most common sources of waste that occurred in the 600 C/D machine. Table 5: The most frequent source of waste from the 600 machine was moved imaged fields at least once on the 2nd visit 600 Moved Imaged Fields at least once (2nd Visit) 42% 12 Missing Face Photo 33% 12 Had to Call Dosimetry 25% 12 Moved Imaged Fields more than twice (1st Visit) 22% 12 Similar to the other two machine types, moved imaged fields during the second machine visit and moved imaged fields more than twice during the first machine visit were among the most common forms of waste for the 600 machine. Had to call Dosimetry was also in the top four sources of waste at 25%, compared to 10% overall. The percentage of time the imaged fields were moved during both the first and second visits on the 600 machine was not substantially different than the overall. Table 6 below shows the percentages for the sources of waste with the greatest range over the three machine types (EX 1 and EX 2, EX 3 and EX 4, and 600 C/D). 14

16 Table 6. Comparison of sources of waste with the greatest range over the machine types. Machine EX 1 and EX 2 n EX 3 and EX 4 n 600 n 1st Visit Moved Imaged Fields More than 2 Times (1 st Visit) 29% 7 60% 28 22% 9 Treatments Not Scheduled O.K. 0% 14 17% 28 0% 10 Treatment Incomplete 20% 15 5% 32 20% 10 2nd Visit Unclear Set-up Instructions 27% 15 0% 29 0% 12 Missing Set-Up Photos 20% 15 11% 29 0% 12 Charge Capture Not O.K. 9% 11 0% 10 0% 11 Did You Have to Call Dosimetry 18% 17 4% 33 25% 12 Doctor 6% 17 26% 33 8% 12 As Table 6 shows, treatments on the EX 1 and EX 2 machines are incomplete considerably more than the EX 3and EX 4 machines. Unclear set-up instructions, missing set-up photos, and the charge capture not O.K. occur considerably more often for the EX 1 and EX 2 machines than for both of the other types of machines. RTT s working at the EX 1 and EX 2 and 600 machines had to call Dosimetry considerably more often than did the RTT s at the EX 3 and EX 4 machines. Table 6 also shows that moved imaged fields at least twice during the first machine visit occurred more often on the EX 3 and EX 4 machines than for the other types of machines. Likewise, treatments not scheduled O.K., missing set-up photos, and had to call Doctors occur more frequently for machines EX 3 and EX 4 than for the other types of machines. Table 6 also shows that the 600 machine has treatments incomplete more often than the EX 3 and EX 4 machines and RTT's had to call Dosimetry to the 600 machine more often than for either other machine type. Main Sources of Waste Stratified by IMRT Cases IMRT cases are specialized cases that account for a considerable amount of the patients treated in the Radiation Oncology Clinic. According to Dosimetry, IMRT cases comprise of about 25% of the clinic s cases, and that number is increasing. Table 7 below shows the three most frequent causes of waste for IMRT patients. Table 7. The most frequent source of waste for IMRT patients is missing face photos IMRT Moved Imaged Fields at least once (2nd Visit) 67% 7 Missing Face Photo 43% 7 Had to Call Doctor 29% 7 As shown in the table above, moved imaged fields during the second visit occurred 67% of the time, which is considerably higher than the 44% overall. Missing face photos 15

17 occurred 43% of the time, which is also considerably higher than 30% overall. Had to call a Doctor occurred 29% of the time for IMRT patients, which is also considerably higher than the 12% overall. Main Sources of Waste Stratified by Doctor The group stratified the sources of waste by Doctor (I V) to determine if any sources of waste occurred more frequently in certain Doctors patients than in others. Table 8 below shows the three most frequent causes of waste for Dr. I s patients. Table 8. The most frequent cause of waste for Dr. I s patients is missing tattoos Dr. I Missing Tattoo 57% 7 Had to Call Another Staff Member 25% 8 Treatment Not Completed 25% 8 Plan Not Signed 25% 8 As the table above shows, Dr. I's patients who need tattoos are missing tattoos 57% of the time, which is the close to the overall percentage of 53%. RTT's had to call another staff member 25% of the time, which is also the same as the overall data. The only difference between the sources of waste for Dr. I's patients and the overall sources of waste was that plan not signed occurred 25% of the time, which is higher than the overall rate of 11%. Table 9 below shows the three most frequent causes of waste for Dr. II's patients. Table 9. The most frequent cause of waste for Dr. II s patients is missing tattoos Dr. II Missing Tattoo 78% 9 Moved Imaged Fields at least once (2nd Visit) 44% 9 Had to Call Another Staff Member 40% 10 Had to Call Doctor 30% 10 As the table above shows, patients needing tattoos were missing tattoos 78% of the time, which is considerably higher than to 53% overall. Dr. II's patients had their imaged fields moved during the second visit 44% of the time, which is the same as the overall. During Dr. II's patients' treatments, another staff member was called 40% of the time, which is considerably higher than the overall percentage of 25%. Table 10 below shows the top three causes of waste for Dr. III's patients. 16

18 Table 10. The most frequent cause of waste for Dr. III s patients is missing face photo Dr. III Missing Face Photo 40% 5 Match Anatomy Incomplete 25% 4 Iso-Center not Identified 25% 4 Treatments Not Scheduled O.K. 25% 3 As shown by the table above, Dr. III's patients are missing face photos 40% of the time, which is higher than the overall rate of 30%. Match anatomy is incomplete 25% of the time, which is much higher than the overall rate of 8.3%. Likewise, the Iso-Center was not identified 25% of the time in Dr. III's patients, which is much higher than the average of 5.4%. Treatments not scheduled O.K. occurred 25% of the time, which is also much higher than the average of 3%. Table 11 below shows the most frequent sources of waste for Dr. IV s patients. Table 11. The most frequent cause of waste for Dr. IV s patients is moved imaged fields at least once during the 2 nd machine visit Dr. IV Moved Imaged Fields at least once (2nd Visit) 50% 6 Missing Tattoo 43% 7 Missing Chart 25% 8 Treatment Not Completed 20% 5 As shown by Table 11, moved imaged fields at least once during the second machine visit occurred 50% of the time for Dr. IV s patients. This percentage is higher than the overall percentage for this category (44%). Missing tattoo occurred 43% of the time and missing chart occurred 25% of the time for Dr. IV s patients. Compared to the overall data, patients were missing tattoos 53% of the time and missing charts 18% of the time. A patient s treatment was not completed on the first machine visit 20% of the time, compared to only 10% for the overall data. Table 12 below shows the top three causes of waste for Dr. V's patients. Table 12. The most frequent cause of waste for Dr. V s patients is moved imaged fields at least once during the 2 nd machine visit Dr. V Moved Imaged Fields at least once (2nd Visit) 71% 9 Missing Face Photo 50% 10 Had to Call Another Staff Member 50% 10 Missing D.R.R. 25% 10 17

19 As the table above shows, moved imaged fields at least once during the second machine visit occurred 71% of the time for Dr. V's patients. This was much higher than the overall percentage of 44%. Missing face photos occurred 50% of the time, which is considerably higher than the overall percentage of 30%. Had to call another staff member occurred 50% of the time, which is also much higher than the overall percentage of 25%. Missing D.R.R. occurred in Dr. V s patients charts 25% of the time, which is also considerably higher than the overall of 8%. Table 13 below presents the sources of waste with the greatest range between each of the five doctors. Table 13. Sources of waste with the greatest range between doctors. Doctor I n II n III n IV n V n Missing Chart 0% 8 0% 9 20% 5 25% 8 0% 9 Missing Consent 0% 8 0% 8 20% 5 0% 7 0% 9 Script Not Signed 13% 8 0% 10 0% 5 0% 8 0% 10 Plan Not Signed 25% 8 0% 8 0% 5 0% 8 0% 9 Calculation Not Signed 17% 6 0% 8 20% 5 0% 8 0% 9 Missing Move Sheet 17% 6 0% 9 0% 4 0% 7 0% 10 Missing Face Photo 13% 8 20% 10 40% 5 0% 8 50% 10 Missing D.R.R. 14% 7 0% 9 0% 5 0% 8 25% 10 CT Set-Up Photos Incomplete 13% 8 0% 8 0% 5 0% 8 14% 9 Set-up Instructions Incomplete 14% 7 0% 9 20% 5 0% 8 0% 10 Treatment Devices Not in Room 13% 8 11% 9 0% 5 0% 8 0% 10 Match Anatomy Incomplete 14% 7 0% 9 25% 4 0% 8 0% 9 Sequence Templates Incomplete 13% 8 0% 8 0% 5 0% 8 0% 9 Field Scheduling Incomplete 13% 8 0% 9 20% 5 0% 8 13% 10 Had to Call Dosimetry 25% 8 20% 10 0% 5 13% 8 25% 10 Had to Call Doctor 0% 8 30% 10 20% 5 0% 8 25% 10 As Table 13 above shows, some of the sources of waste with the greatest variation between doctors are missing chart, missing consent, plan not signed, calculation not signed, and missing face photo. Patients of Drs. III and IV are missing charts 20% and 18

20 25% of the time, respectively, while the other doctors patients never have missing charts. Patients of Dr. III are missing consents 20% of the time while patients of the other doctors are never missing consents. Planned not signed occurs 25% of the time for Dr. I s patients, but never occurs for the patients of the other four Doctors. Calculation not singed occurs 17% of the time for Dr. I s patients and 20% of the time for Dr. III s patients, but never occurs for the patients of the other Doctors. Missing face photo never occurs for Dr. IV s patients, but occurs 50% of the time for Dr. V s patients. Main Sources of Waste Stratified by Shift The following section presents the most common sources of waste based on each shift. The shifts were broken into the morning shift (7 am to 12 pm) and the afternoon shift (12 pm to the end of day). The data was further stratified based on the first machine visit shifts and the second machine visit shifts. The first machine visit shifts includes the information from before a patient arrives and during the first visit. Table 14 below shows the three greatest causes of waste in the morning shift of the first machine visit. Table 14. The most frequent source of waste for the morning shift on the first machine visit is missing tattoos 1st Visit Morning Shift Missing Tattoo 60% 10 Missing Marks 29% 14 Treatments Not Scheduled O.K. 8% 13 As the table above shows, patients who need tattoos are missing tattoos 60% of the time in the morning shift of the first machine visit. This percentage is greater than the percentage of missing tattoos for the overall data (53%) and is still consistent with being one of the most common sources of waste. A patient missing marks was the second highest source of waste, occurring 29% of the time which, is greater than the overall data of 20%. Table 15 below shows the three most common causes of waste for the afternoon shift of the first machine visit. Table 15. The most frequent source of waste for the afternoon shift of the first machine visit is missing tattoos 1st Visit Afternoon Shift Missing Tattoo 37% 19 Missing Marks 16% 44 Treatment Not Completed 13% 39 As shown in the table above, patients needing tattoos were missing tattoos 37% of the time during the afternoon shift of the first machine visit. This percentage is lower than the overall data percentage (53%). The third highest percentage of waste during the afternoon 19

21 shift o the first machine visit was treatment not completed which 13% of the time. Overall, treatment not completed on the first machine visit occurred 10% of the time. Table 16 below shows the three most frequent causes of waste in the morning shift of the second machine visit. Table 16. The most frequent source of waste for the morning shift of the second machine visit is moved imaged fields at least once 2nd Visit Morning Shift Moved Imaged Fields at least once 59% 13 Missing Set-Up Photos 13% 15 Unclear Set-Up Instructions 7% 15 Table 16 above shows that RTT's had to move imaged fields 59% of the time during the morning shift of the second machine visit. Comparatively, the overall data showed that moved imaged fields occurred 43% of the time. The second most common source of waste for the morning shift of the second machine visit was missing set-up photos which occurred 13% of the time. The overall data shows that missing set-up photos occurred 8% of the time during the second machine visit. Table 17 below shows the three most frequent sources of waste for the second visit afternoon shifts. Table 17. The most frequent source of waste for the afternoon shift of the second machine visit is moved imaged fields at least once 2nd Visit Afternoon Shift Moved Imaged Fields 50% 24 Unclear Set-Up Instructions 8% 25 Missing Set-Up Photos 8% 25 As shown by Table 17, RTT's had to move imaged fields during the afternoon shift of the second visit 48% of the time, which is close to 44% of the time for the overall data. Unclear set-up instructions and missing set-up photos were the next two most common sources of waste; however, each source occurred only 8% of the time. Table 18 below shows the sources of waste for the first and second machine visits with the greatest range between the morning and afternoon shifts. 20

22 Table 18. Sources of waste with the greatest range between morning and afternoon shifts. 1st Visit Morning Shift Afternoon Shift Missing Tattoo 60% 37% Missing Marks 29% 16% 2nd Visit Morning Shift Afternoon Shift Moved Imaged Fields At Least Once 54% 48% The table above shows that during the first machine visit, both missing tattoos and missing marks occur more often during the morning shift (60% and 29%, respectively) than during the afternoon shift (37% and 16%, respectively). During the second machine visit, moved imaged fields at least once occurred more often during the morning shift (54%) than during the afternoon shift (48%). Main Sources of Waste Stratified by Patients Missing Tattoos Missing tattoos was the highest overall percentage of waste and occurred 53% of the time. This category was important because it is indicative of other waste occurring in the patient treatment process. The tattoo is a necessary marking for setting the Iso-Center, or point about which the accelerator machine revolves. The client suspected that there could be a positive correlation between missing tattoos and other forms of waste. The team stratified the data by patients missing tattoos and compared it to the overall data. The only percentage that was considerably different than the overall data was moved imaged fields more than twice during the first machine visit. Overall, 15% of the time more than two moves are performed during the first machine visit, compared to 31% for patients missing tattoos. By the second machine visit, the percentages were very comparable at 44% overall and 40% for patients missing tattoos. Conclusions and Recommendations From the data analysis, the team concluded that the most common source of waste for the overall data is a missing tattoo, which occurred 53% of the time. Other common sources of waste for the overall data are moved imaged fields more than twice during the first machine visit, moved imaged fields at least once during the second machine visit, and missing face photos. Based on the stratified data analysis, the team also concluded that the results from the stratification categories are consistent with the top percentages of waste from all of the data. The most common sources of waste for the data stratified by machine type was moved imaged fields at least once during the second machine visit, moved imaged fields more than twice during the first machine visit, and missing face photos. The sources of waste with the greatest range between machine types was moved imaged fields more than twice during the first machine visit and unclear set-up instructions during the second machine visit. Missing face photos and unclear set-up instructions, however, are not affected by machine type because these particular types of waste occur before the first machine visit. Patients missing tattoos, RTT s calling another staff member, and moved imaged fields 21

23 during the second visit were three of the most common sources of waste for the data stratified by Doctor. Patients missing face photos, tattoos, and marks; unclear set-up instructions; and moved imaged fields during both machine visits were the most common sources of waste for the data stratified by shift. Based on the team s data analysis of the stratification by shift, the team concluded that there tends to be less waste during the afternoon shifts than the morning shifts of both the first and second machine visits. The team hypothesized that perhaps less waste occurs during the afternoon shifts because there is more preparation time before afternoon appointments than before morning appointments. Based on the conclusions drawn from the findings, the team recommends that the clinic perform a root cause analysis of the most common sources of waste. A root cause analysis is only necessary for the most common sources of waste in the Clinic: missing tattoos, moved imaged fields on the first and second machine visit, and missing face photos. The team also recommends analyzing the differences between shifts (morning and afternoon) to determine whether increased preparation time before a patient arrives for treatment is a factor in reducing waste. The team also determined that different types of waste occur from the different machine types; therefore, we recommend a root cause analysis of each machine type to determine what factors are causing the different sources of waste. Some possible categories to stratify the machine data by include: Individual Machine Work Procedures Staff Type of Patient The team also recommends that the clinic use Quality Assurance during all machine visits during the radiation therapy treatment process. Using Quality Assurance during each machine visit means that the RTT's do not move forward with the treatment process if any piece of information is missing or incomplete on a patient s body or a on patient's chart. Instead, the RTT s should work to obtain the missing or incomplete information before moving forward in the treatment process. By doing so, waste will not be passed on from one treatment stage to the next but instead, waste will be eliminated. From the data collected, the team learned that patients charts were not prepared until the day of the patients appointments, if not during the patients treatments. Therefore, the team further recommends reviewing a patient s chart at least ½ day in advance of the appointment time. One way of achieving this would be designating one staff member per machine type (EX 1 and EX 2, EX 3 and EX 4, and 600 C/D) to review patients' charts at least ½ day in advance of a patient's appointment time. The staff member can identify missing or incomplete information and correct the problem before waste is produced and rework is necessary. This staff member should also ensure the completeness of the PAD well in advance of the patients' Simulation appointments. It is necessary that the Doctors' portion of the PAD is completely filled out before Simulation to ensure an appropriate treatment plan can be established and reviewed to avoid rework. By ensuring that patients charts are checked at least ½ day in advance of the patients appointment times, 22

24 unnecessary rework will be avoided and process inefficiencies will be eliminated. The implementation of the team's recommendations will cause a reduction in waste in the patient treatment process. The reduction in waste will result in a reduction in patient and employee frustration, in workday duration, and potentially fewer visits to the clinic for patients. 23