Process Improvement- Reduction in Wait Time for Patients in a Doctor Office.
A Lean Six Sigma Case Study
If you want to prosper for a year, grow rice. If you want to prosper for a decade, plant trees. If
you want to prosper for a century, grow people — a wise old farmer reflecting back on a life
of toil in the soil
The following Lean Six Sigma case study will reflect a real-life healthcare problem with
Continuous Improvement and Lean Six Sigma Tools to show how some of the tools are put into
place in the real world. You will be required to complete the project along with some analysis
for each section.
Student Case Study
Process Improvement – Reduction in Wait Time for Patients in a Doctor Office
Executive Summary Dr. Deasley is a popular Doctor in Tampa, Florida specializing in primary care. He spends a great deal of time with each of his patients, typically, 45 minutes to one (1) hour. Dr. Deasley’s patients and staff love him for his patience and attention. However, there are many other patients waiting in the waiting room who become impatient at the long wait time. Dr. Deasley’s office hours are 7:30 AM to 5:30 PM Monday through Friday. He conducts patient call backs between patients, during his lunch hour and after office hours. We triage the calls so he gets back to more seriously sick patients first. However, sometimes he doesn’t call back non-emergencies until the next AM. Dr. Deasley becomes overbooked because he likes to have 10 patients scheduled per day. However, he frequently needs to rebook patients he is unable to see due to time constraints. As a result, several long-term patients have been leaving his practice.
This has resulted in a decrease in revenue for the office. In addition, his office is experiencing a rather high rate of staff turnover. Staff are responsible for booking patients and managing the workflow in the office. When backlogs occur and patients become annoyed about wait times, the staff usually experience the brunt of the patient dissatisfaction, which effects staff morale. Each time the office hires replacement staff, it takes a significant amount of time to train new employees and it is costly to advertise and recruit competent staff. Dr. Deasley is very concerned about both his patients and staff.
His Office Manager, Ms. Smith, who recently was employed at Memorial Hospital of Tampa, participated in several Continuous Improvement Projects at the hospital. She is a certified Lean Six Sigma Green Belt. As a result, Ms. Smith has suggested a plan to the doctor to conduct a Lean Six Sigma project with the objective of Reducing Patient Wait Time and Improving Office Workflow. Ms. Smith explained the project improvements and objectives. Dr. Deasley has approved the project. As an initial step, the Office Manager has established her team. Each employee has a role in the project. Based on patient complaints and the doctor’s requirements, they have some initial Voice of Customer (VOC). Patients would like to see the Doctor within 10 minutes of arriving and spend no more than 30 minutes in the office total for routine visits. The Doctor would like to see 15 patients per day. These changes need to be made within 3 months in order to minimize patient dissatisfaction, stop patients leaving the practice due to long wait times and rescheduling and improve employee morale and retention.
Define Please fill out the project charter. Write the Goal Statement utilizing S.M.A.R.T. objectives
(Specific, Measurable, Attainable, Relevant and Time Bound): Please complete a High Level “As Is” Process Map. Please create a SIPOC of the process based on the information that you know. Feel free to use
your imagination for this. Describe methods for collecting Voice of the Customer. (SEE APPENDIX A for VOC) Please create an Affinity Diagram or List based on VOC so you can identify Customer “NEEDS”
for CTQ Tree Please create a Critical to Quality Tree utilizing the Voice of the Customer. Identify the Needs,
Drivers and Requirements or Metric to needed to meet these needs
Conclusion of Define: The output of the DEFINE stage is a PROJECT CHARTER (PC) and identified stakeholders. The PC shall include a Problem Statement with Goals utilizing S.M.A.R.T. methodology to address the problems identified. The Goal will be aligned with the customer CTQ Requirements. A clearly defines SCOPE is included in the PC. What is IN SCOPE and What is OUT OF SCOPE? Your Team is identified, and Roles & Responsibilities are defined. A SIPOC Map is completed. An “As Is” Process Map is completed in order to better visualize the Workflow in the current process. The DEFINE Phase provides for identification of the VOC and CTQs, their needs, drivers and requirements. The student will have evaluated and Affinitized the VOC. CTQ trees were created to identify key requirements for meeting the customer’s needs. The Project Team should have a list of external Key stake Holders, if applicable, e.g., Hospital Radiology, who may be impacted by process changes within the Doctor’s medical practice. If the Doctor’s staff schedule testing appointments for patients and are required to make frequent changes, this has an impact on the department or entity conducting the testing. The Project Team will have met with Dr. Deasley for his approval to proceed and now has a baseline to begin the Measure phase.
Measure Based on Customer requirements the project team collected initial data. Use Pareto Analysis of
# occurrences to determine the 5 factors which are causing over 75% of the problem with wait time. You need to determine the biggest contributors to the problem. One tool to accomplish this is the Pareto Chart. You need to know if it is reasonable to assume that these five ‘parameters’ are normally distributed. (SEE APPENDIX B)
Based on Pareto Analysis what are the focus areas? What are the Key Performance Indicators (KPI’s)?
Define your Data Collection Plan. Include the types of data you will be collecting (Discrete or Continuous), Why? (In many instances you will have a mix of both types of data depending on the Data source.
Based on the data collected Construct FIVE (5) histograms for the below data sets. (SEE APPENDIX C) for data sets
Interpret each of the histograms to determine whether the assumption of normality is reasonable.
If the data are not approximately normally distributed, why not? The team also believed there was a Motorola shift during the process. Please describe the
Motorola Shift and potential causes that they could have experienced the shift. Calculate the DPMO for the entire process considering the 5 main opportunities for defects.
Determine the baseline sigma with the Motorola shift. Calculate the Process Performance, Pp and Ppk, based on the time the Doctor spends with the
patient. Student will be able to compare current Process performance to Capability Study performed for process improvements. Tint: drawing a picture of the data based on a Normal Curve may help student visualize if data is skewed when evaluating population distribution. Use UCL = 60 minutes and LCL = 0 Minutes. In Healthcare LCL will frequently be “O” Pp = (Upper Spec – Target Value)/(6*Standard Deviation) Ppk = (Upper Spec – Mean)/(3*Standard Deviation)
Conclusion of Measure: A Data Collection Plan was created. Data was taken of as many parameters as possible before changing any variables. Key Data has been provided for your use as directed in the instructions above. Pareto charts have been created based on the VOC. The 5 Largest Contributing Factors have been Identified. These should have aligned with the data provided. A method for tracking data to capture for analysis should have been identified even if the actual data is already provided. Then from the categories and data “collected”, 5 Histograms should have been created along with the narrative for Analysis, specifically related to determination if data was normally distributed. An explanation of the Motorola Shift is provided. DPMO is calculated. Pp/Ppk are calculated and current process Sigma Level is defined. It was found that Dr. Deasley was spending more time with his patients than necessary. The process needs to be analyzed based on the data.
Analyze Create a Stem and Leaf Plot that were captured from the patient wait times in the waiting
rooms. (SEE APPENDIX D for data set) Calculate the measures of central Tendency. What can you interpret from these measures?
Please document a conclusion (SEE APPENDIX D for data set)
Two individual staff members were being observed performing identical activities in the Doctor’s office. 25 random samples were taken. One of the Medical Assistants is a new employee. Medical Assistant #1 has been with Dr. Deasley for several years. Medical Assistant #2 is a new employee and has been with this medical practice for 9 months. We want to determine how Medical Assistant #2 performs when compared to Medical Assistant #1 since she is a new employee. (SEE APENDIX E for data sets)
Assume this is a one-sided t-test and the historical average of Medical Assistant #1 is .0126
Medical Assistant #1 data will be considered the population mean
Please provide the following information based on your analysis of the two Medical Assistants • Medical Assistant #2 Average • Medical Assistant #2 Standard Deviation • Null Hypothesis • Alternative Hypothesis • T-Test Statistic • Critical Value • Statistical Conclusion for the null and alternative hypothesis.
Conclusion of Analyze: Stem and Leaf Plots were created; Measures of Central Tendency were also determined, and an interpretation of the results were made. Data was analyzed to review if different staff members were performing similarly or not. Students should have established a Null Hypothesis and Alternative Hypothesis from the data for the 2 staff members. A one-sided T-Test was performed, and conclusions made based on the outcome.
IMPROVE A staff member has been stating for months that there is a correlation between the Room Availability and the Patient arrival time. Should the Office Manager have listened to this staff member’s observation? Refer back to the Pareto to serve as guidance.
Construct a scatter diagram and calculate the correlation coefficient to see if she is correct. SEE APPENDIX F for data set
o Is there strong correlation between room availability and patient arrival time? o IF there is strong correlation, is it positive or negative? (Answer with positive, negative
or N/A) o What is the correlation coefficient between the two variables? (Use 6 decimal places)
Discuss the 8 Deadly Wastes (MUDA) of the process. Create a Fishbone Diagram. List Potential Root Causes. Narrow Potential Root Causes to Key
Root Causes. Explain some of the key Root causes. Discuss Improvements that you would suggest based on findings from FISHBONE Analysis.
Conclusion of Improve: A Scatter Plot was constructed, and a Correlation was completed. The determination of whether the 2 factors Correlate based on a Correlation Coefficient determination is stated and comments on whether the correlation is Positive or Negative are included. 8 Wastes were evaluated and identified where applicable. A FISHBONE DIAGRAM was created, and many ideas were brainstormed for Potential Root Cause. These were then narrowed to the critical few Root Causes. Many improvement suggestions were made.
CONTROL An I-MR chart was plotted for the Doctor’s office to ensure the specifications were performing as planned and the patients and Doctors were satisfied.
Please indicate if the control chart is stable and if any Shewhart Rules have occurred.
A normality test was conducted. Please advise if the data is normal.
A capability study was completed. Please advise if the process is stable and any analysis you find is relevant.
Please complete a Control and Monitoring Plan for the project. Please state your conclusions of Dr Deasley’s office
Conclusion of Control: A conclusion regarding the stability of the Control Chart was made and any violations of the Shewhart Rules were noted. Students then observed the Normality of the data. A Capability Study was done presumably using data from improvements made and analysis of the output was discussed. A Control and Monitoring Plan was created to ensure monitoring of improvements for Sustainability. Finally, a control plan was developed to be used for staff to visually track their performance and for discussion with Dr. Deasley. We have collected data after making many improvements to see if the process is now stable. We will continue to monitor our progress and follow the control plan.
APPENDIX A: VOICE OF THE CUSTOMER
Feedback from Patients:
I wait too long. I only have an hour for Lunch. I make my appointments specifically at Lunch time because I can’t come after work.
I like to come very early and be one of Dr. D’s first patients. If I am not his 1st, I end up waiting and am late for work. My company is very strict about being on time.
I wouldn’t mind if the doctor spent less time with me. I only usually come for an Annual Checkup and a Flu shot. If I feel really sick, I call the office. When I broke my arm last year, the doctor sent me right to the hospital. You guys made the arrangements for my X-Ray, so I didn’t need to wait.
I can’t be late when I come in the afternoon. I need to pick my daughter up from school. If I come in the afternoon, can you make it a short visit?
The doctor spends so much time asking me questions, can’t he look at my chart before I get into the exam room?
The last time I was here, you put me in a room with someone else’s clothes. The woman had gone to the Ladies’ room and came back to get dressed. I had to wait in the hallway.
Feedback from Staff
We need to organize the exam rooms. Dr. Deasley is always looking for something and I need to go find it.
We can’t have multiple people at the Front desk assigning patients to rooms. They don’t always assign patients to the right room and equipment is not available
Dr. D keeps taking equipment with him from room to room,
The patients are not getting here early enough to get them ready for the doctor. He like to have their Blood Pressure, Weight and Temperature done before he comes in.
Patients keep arriving the last minute, then they get angry because they miss their appointment and need to wait.
I hope I never have to reschedule Mrs. Smyth for a new appointment because the doctor couldn’t see her. She was practically screaming at me.
We had 2 patients, Mrs. Jones and Mr. Thomas ask for their records to be sent to a new doctor’s office. That is the 4th time that has happened this year and we are only ½ way through the year.
The new Medical Assistant was complaining because she said there is too much chaos here. I think she might be sorry she came her. I hope she doesn’t go back to the hospital. It takes so much time to find good people and train them.
Feedback from Doctor
I don’t always have the instruments I need in the Exam Room. I need to have my Assistant go find what I need. I’ve started taking Instruments with me to my next patient only to find 3 of the same instrument I am carrying in the next Exam Room.
I have seen several patients waiting in the hall outside the Exam Room. I don’t like that situation. We need to stop this practice.
I see some staff running around like crazy and others sitting around appearing to have nothing to do.
I am not one of these “hands off’ doctors, I like to spend time with my patients. But sometimes a patient will sit there with nothing to say and another patient will have a long list of issues.
If this improvement project is successful, I would like to see 15 Patients a day. We need to keep operating costs in mind. We need to keep our equipment up to date and I need to ensure we plan for salaries and bonuses at year end.
I notice we have had 3 people leave within the past 18 months. I would like to understand why. It is very expensive to recruit staff and it takes time before they are proficient in their jobs. The team we have now is very good. I would like to keep all of them. We do monitor salaries and compare with market standards, so I know our salaries and benefits are competitive.
Feedback from Other Sources
Radiology Department is complaining because they state we make too many changes to the patient appointments.
The Laboratory department is complaining because our patients are coming for testing outside their assigned appointment time and too late in the day.
APPENDIX B: Based on VOC data to be used to construct CTQ’s. Project Team will identify key focus areas in Doctor’s Office using Pareto Diagram. These focus areas will then be monitored as defined in Data Collection Plan.
Time the Doctor was spending with Patients – 79
Number of times Dr arrives late – 4
Proper Medical Devices not Available – 30
Number of times patient is left in the hallway – 17
Rooms Available at Doctor’s Office -22
Number of times staff arrive late – 3
Staffing of Doctor’s Office -41
Number of times scheduling changes were made for patient testing – 15
Number of times patient had to be rescheduled for Dr visit – 10
Arrival Time of Patients – 52
APPENDIX C: Data set to be used to construct 5 Histograms
1. Percent of Rooms fully equipped with Proper Medical Devices
• This varies between 10.5 and 11. This is the number of devices or number of times devices were not available in the rooms.
2. Rooms available –
• Varies from 7.45 -7.66. This is the percentage of rooms available
3. Staffing at Dr. Office
• Varies from 0.54-0.56. Effort per day (which is a value used depicting that people that had multiple duties so you could have a fraction of a person available).
4. Arrival Time of Patients
• Minutes late
5. Time Dr. Spends with Patients
% of Rooms
with Proper Medical Devices
% Rooms Available
at Dr. Office
Staffing at Dr. Office Percent
Time Dr. Spends
4-Jul 10.82 7.45 0.5502 172 48
5-Jul 10.82 7.55 0.5522 169 34
6-Jul 10.86 7.67 0.546 177 23
7-Jul 10.87 7.65 0.5462 170 32
8-Jul 10.84 7.62 0.5491 174 19
9-Jul 10.85 7.59 0.5486 175 37
10-Jul 10.86 7.6 0.5428 167 20
11-Jul 10.87 7.52 0.5532 171 47
12-Jul 10.89 7.49 0.5472 168 27
13-Jul 10.8 7.54 0.5522 172 31
14-Jul 10.81 7.52 0.5494 168 44
15-Jul 10.89 7.61 0.5519 163 27
16-Jul 10.81 7.52 0.5509 174 61
17-Jul 10.9 7.61 0.5412 169 17
18-Jul 10.87 7.53 0.5518 171 26
19-Jul 10.86 7.57 0.5523 172 50
20-Jul 10.85 7.59 0.5415 172 11
21-Jul 10.85 7.55 0.5477 168 53
22-Jul 10.86 7.61 0.553 169 18
23-Jul 10.86 7.54 0.55 166 75
24-Jul 10.83 7.57 0.5437 172 27
25-Jul 10.89 7.51 0.5463 168 36
26-Jul 10.76 7.63 0.5566 174 40
27-Jul 10.78 7.5 0.541 175 30
28-Jul 10.86 7.58 0.5542 164 23
29-Jul 10.9 7.55 0.5569 173 15
30-Jul 10.83 7.51 0.5432 168 15
31-Jul 10.82 7.5 0.5487 170 35
1-Aug 10.87 7.59 0.5537 173 45
2-Aug 10.88 7.58 0.541 170 25
3-Aug 10.67 7.64 0.5554 173 42
4-Aug 10.72 7.48 0.5521 167 64
5-Aug 10.65 7.57 0.5532 169 23
6-Aug 10.7 7.46 0.5563 172 53
7-Aug 10.67 7.53 0.5508 165 50
8-Aug 10.65 7.6 0.5527 170 16
9-Aug 10.6 7.49 0.5546 169 41
10-Aug 10.66 7.65 0.5478 170 7
11-Aug 10.61 7.55 0.5468 165 31
12-Aug 10.69 7.55 0.5566 172 18
13-Aug 10.71 7.51 0.5531 168 53
14-Aug 10.66 7.49 0.5482 173 34
15-Aug 10.64 7.49 0.5473 172 37
16-Aug 10.62 7.49 0.5442 170 80
17-Aug 10.63 7.56 0.5491 176 19
18-Aug 10.67 7.59 0.5596 175 26
19-Aug 10.62 7.47 0.5491 170 13
20-Aug 10.62 7.58 0.5507 169 18
21-Aug 10.63 7.55 0.556 177 36
22-Aug 10.65 7.47 0.5428 178 7
23-Aug 10.68 7.63 0.5488 172 34
24-Aug 10.68 7.47 0.5531 171 28
25-Aug 10.63 7.68 0.5483 171 44
26-Aug 10.68 7.55 0.5431 171 18
27-Aug 10.58 7.47 0.545 177 23
28-Aug 10.59 7.59 0.5392 172 17
29-Aug 10.64 7.57 0.5512 170 25
30-Aug 10.64 7.53 0.5465 169 15
1-Sept 10.68 7.58 0.5479 164 23
2-Sept 10.6 7.6 0.5452 174 21
Upper Spec 11 7.66 0.56 180 60 Lower Spec 10.5 7.45 0.54 165 0
Target 10.75 7.55 0.55 170 20
APPENDIX D: Data represents Wait Time in minutes beyond their scheduled Appointment Time for the last 70 patients. Use to create Stem and Leaf Plots.
16 15 19 48 14 47 21 16 17 16 45 80 20 46 17 13 26 50 6 71 48 37 47 17 49 49 47 20 47 11 65 63 48 50 64 32 47 15 17 47 95 16 48 38 17 22 48 47 44 21 17 48 10 52 20 82 18 20 16 18 46 50 51 75 49 44 51 48 35 58
APPENDIX E: Data set for determining performance for Medical Assistant #2. The historical mean for Medical Assistant #1 was .0126.
MEDICAL ASSISTANT #2 Data
% time/hour 0.009
APPENDIX F: This is the data set for evaluating Correlation between Room Availability and Patient Arrival
Room # Availability Patient Arrival Time 154 0.554 153 0.553 152 0.552 152 0.551 151 0.549 151 0.549 151 0.548 151 0.548 151 0.548 151 0.547 151 0.547 151 0.547 151 0.547 151 0.547 151 0.547 151 0.546 150 0.546 150 0.546 150 0.546 150 0.546 150 0.546 150 0.545 150 0.545 150 0.545 149 0.545