University of Michigan Health SystemProgram & Operations Analysis

Analyzing Patient Flow and Process Waste at the Urology Clinic at the Livonia Center for Specialty Care

Final Report

Prepared for:John Wei, M.D., Professor of Urology, Client

Karen Moore, Ambulatory Care Manager, ClientUniversity of Michigan Health System

Livonia Center for Specialty Care, Urology

Mary Duck, Project CoordinatorIndustrial Engineering Expert and Lean Coach

Programs & Operations Analysis

Kyle Worley, Project CoordinatorIndustrial Engineer

Programs & Operations Analysis

Course Instructor:Professor Mark Van Oyen

University of MichiganIndustrial and Operations Analysis

Prepared By:Rebekah Andrews

Kaywee LianKristen Ydoate

Date Submitted:December 13th, 2016

Table of ContentsExecutive Summary.........................................................................................................................1

Background..................................................................................................................................1

Project Goals and Objectives.......................................................................................................1

Methods........................................................................................................................................1

Findings and Conclusions............................................................................................................2

Recommendations........................................................................................................................3

Introduction......................................................................................................................................4

Background......................................................................................................................................4

Key Issues........................................................................................................................................6

Project Goals and Objectives...........................................................................................................7

Project Scope...................................................................................................................................7

Data Collection and Analysis Methodology....................................................................................7

Observations.................................................................................................................................7

Literature Search..........................................................................................................................8

MiChart Data................................................................................................................................8

Time Study Form.........................................................................................................................8

Pilot Phase................................................................................................................................8

Combined Time Study Form....................................................................................................9

Interviews.....................................................................................................................................9

Surveys.......................................................................................................................................10

Analysis of Data.........................................................................................................................10

Findings and Conclusions..............................................................................................................10

Value Stream Mapping..............................................................................................................11

Return Procedural Patient Flow Most Inefficient...................................................................11

Monday, Tuesday, and Wednesdays Experience Longer MA and Provider (Mondays and Tuesday) Wait Times.............................................................................................................12

Excessive Wait Time for MA, Nurse and Provider................................................................12

Patients with elevated PSA spend the longest times in the clinic..............................................13

Top 5 Waste Identified in the Clinic..........................................................................................14

Patients Spend More Than 60 Minutes in the Clinic..............................................................15

Excess Wait Time for MA......................................................................................................17

Excess Wait Time for Provider..............................................................................................18

Actual Prep Time Exceeds Scheduled Prep Time..................................................................22

Late Patients...........................................................................................................................26

Summary of Conclusions...............................................................................................................28

Value Stream Mapping..............................................................................................................28

Patients With Elevated PSA Diagnosis Spend The Longest Times in Clinic............................29

Top 5 Waste in the Clinic..........................................................................................................29

More Than 60 Minutes at the Clinic......................................................................................29

Excess Wait Time for MA......................................................................................................29

Excess Wait Time for Provider..............................................................................................29

Actual Prep Time Exceed Scheduled Prep Time...................................................................30

Late Patients...........................................................................................................................30

Recommendations..........................................................................................................................30

Expected Impact and Outcome......................................................................................................32

References......................................................................................................................................34

Appendix A: Time Study Forms.................................................................................................A-1

Appendix B: Value Stream Maps................................................................................................B-1

Appendix C: Data Analysis Charts..............................................................................................C-1

Appendix D: Provider Indirect Care Perception Survey.............................................................D-1

Appendix E: Provider Indirect Care Perception Survey Responses............................................E-1

List of Figures and TablesTable EX-1: Value Stream Map Summary Table for Steps in the Patient Flow Process in Minutes.........................................................................................................................................................2Figure 1: Decision Tree for Patient Scheduling Timing..................................................................3

Figure 2: General Process Flow for Consultation Appointment/Nurse Visit..................................3

Figure 3: General Process Flow for Procedure Appointment..........................................................4

Figure 4: Patient Stratification by Patient Type, Visit Type and Patient Diagnosis........................4

Table 1: Statistics on form completion during pilot, broken down into days..................................7

Table 2: Value Stream Map Summary Table Stratified by Patient and Visit Type........................9

Table 3: Value Stream Map Summary Table for Steps in the Patient Flow Process in Minutes. .11

Figure 5: MiChart data shows that 6 is significantly higher than 5, 3 and 1.................................12

Figure 6: Pareto chart of the frequency of waste within the clinic................................................13

Figure 7: Average time in clinic by provider.................................................................................14

Figure 8: Percent of patient visits greater than 60 minutes by provider........................................15

Figure 9: Frequency chart of MA wait times.................................................................................16

Figure 10: Percent of MA wait times greater than 5 minutes across time of day..........................16

Figure 11: Wait time for provider when providers were late to the appointment.........................17

Figure 12: Average wait time by provider.....................................................................................18

Figure 13: Percentage of time providers are late to appointment..................................................18

Figure 14: Provider indirect and direct care time by provider, 15 minute appointment...............19

Figure 15: Provider indirect and direct care time by provider, 30 minutes appointment..............20

Figure 16: Percentage of Time Patient Spends Waiting versus with a Staff Member..................21

Figure 17: Time Spent With Staff for 15 Minute Prep, Broken Down into RV and NP...............22

Figure 18: Time Spent With Staff for 30 Minute Prep, Broken Down into RV and NP...............23

Figure 19: Actual Prep Time by Procedure Performed.................................................................24

Figure 20: Actual 15 Min Prep Time by Time of Day..................................................................24

Figure 21: Actual 30 Min Prep Time by Time of Day..................................................................25

Figure 22: Histogram of Patient Late Times for Patients That Arrived Past Pre-Arrival Time....26

Figure 23: Percentage of late patient by stratification type...........................................................26

Appendix A-1: Time Study Data Collection Form.....................................................................A-1

Appendix A-2: Process Diagnostics Form..................................................................................A-2

Appendix A-3: Patient Time Study Form...................................................................................A-3

Appendix B-1: New Patient Value Stream Map..........................................................................B-1

Appendix B-2: Return Consultation Value Stream Map.............................................................B-2

Appendix B-3: Return Procedural Value Stream Map................................................................B-3

Appendix B-4: Nurse Visit Value Stream MapB-4 Appendix C-:1: Kruskal-Wallis test output on the time spent in clinic by diagnosis types..................................................................................C-1Appendix C- 2: Definition of timing related waste in the Pareto Chart Analysis.......................C-2Appendix C-3:Value stream map totals across day of the week.................................................C-3

Appendix C-4: Summary report on time patients spend in clinic excluding samples under 20 minutes.........................................................................................................................................C-4Appendix C-5: Summary report of MA wait times.....................................................................C-5Appendix C-6: Wait time for provider summary report..............................................................C-6Appendix C-7: Average actual consultation time for 15 minute consultation stratified by provider.....................................................................................................................................................C-7Appendix C-8: Average actual consultation time for 30 minute consultation stratified by provider.....................................................................................................................................................C-8Appendix C-9: Sample schedule of provider’s day.....................................................................C-9Appendix C-10: Summary Report of Samples with 15 Minutes Scheduled Prep Time...........C-10Appendix C-11: : Summary Report of Samples with 30 Minutes Scheduled Prep Time.........C-11

Executive Summary The Urology Clinic at the Livonia Center for Specialty Care performs consultations and minor procedures for patients experiencing urology related issues. Currently, the clinic staff have noticed a discrepancy between the scheduled time and actual time patients spend in the clinic. The variability between appointments has led to a backlog in the clinic. This backlog affects both patient and staff satisfaction. The clinic has asked a team of senior Industrial and Operations Engineering students at the University of Michigan to quantify the current state of the clinic and identify possible sources of process waste. The team collected data via observations, interviews, surveys, and a time study. This report details the methods, findings and conclusions, and recommendations of the team.

BackgroundThe clinic is staffed with 8 Medical Assistants (MA), 4 Registered Nurses (RN) and 1 to 5 providers depending on the day and has 11 rooms. A patient’s scheduled pre-arrival time varies between a new patient (NP) and returning patient (RV). NPs are told to arrive at the clinic 30 minutes before their scheduled appointment with the provider, while RVs are told to arrive 15 minutes before, unless a procedure is planned. If there is no procedure, the appointment duration is 15 minutes for RVs and 30 minutes for NPs. There are 3 types of RVs: consultation, procedural visit, and nurse visit. In the background section of this report, Figure 2 and 3 offer visual representations of the flow of each visit type.

Project Goals and ObjectivesThe primary goal of this project was to quantify the current patient flow process. The project aimed to collect timing information on each step of the patient flow process and display the information with Value Stream Maps to illustrate the clinic current process flow data clearly.

The secondary objectives of the project encompassed:● Identifying the most common forms of waste residing within the process● Identifying inefficiencies in the clinic patient flow process through observation ● Providing recommendations on the opportunities for improvement to reduce waste and

therefore, disparity between scheduled and actual times

MethodsTo collect data on the current patient flow, the team utilized the following data collection tools. Eighteen person-hours were spent observing the clinic to learn more about general clinic operations and process flow. A literature search was conducted to learn more about similar projects and obtain information that could be applied to the current project. Interviews were conducted after initial observations to obtain in-depth insights on patient flow and explain trends observed in the data. MiChart data for the past year was also obtained to gain insight on different patient diagnoses and their time spent in the clinic. Finally, a time study was conducted using the Combined Time Study Form (see Appendix A-3), which allowed the staff to indicate their activity and time spent during each stage of a patient visit. A total of 594 time study samples were collected. The data collected was used in value stream mapping and in the identification of the five most common forms of waste. Surveys were also distributed to providers to gather information on indirect patient care. Four provider responses were collected.

Findings and ConclusionsValue stream maps were created from the time study data (see Appendix B), which highlighted three areas for improvement. Firstly, RV procedural patients are experiencing the longest wait times per visit and the lowest percent value added time per visit (56 minutes and 38.95% respectively). Secondly, Mondays, Tuesdays, and Wednesdays tend to see the longest wait times for patients in the clinic (22.11 minutes versus 18.63 minute average). Lastly, the value stream maps revealed where patients are spending the most time waiting. See Table EX-1.

Table EX-1: Value Stream Map Summary Table for Steps in the Patient Flow Process in MinutesSource: Time Studies Data from 11/2/15 - 10/31/16, N = 548

A Kruskal-Wallis test performed on the MiChart data revealed that patients with elevated PSA spend the longest time in clinic. From the time study data, the team also discovered that the top 5 wastes in the clinic were: 1) Patients spending more than 60 minutes in clinic, 2) Waiting for more than 5 minutes for MAs, 3) Waiting for more than 5 minutes for roviders, 4) Actual Prep time exceeding scheduled prep time, and 5) Patients arriving late for their appointment.

The most common waste was patients spending more than 60 minutes in the clinic, which 54% of patients experienced. The overall average time spent in clinic across all providers is 67.04 minutes. Some providers had more than 50% of their patients exceeding 60 minutes in the clinic.

Secondly, 49% of patients experienced wait times greater than 5 minutes for an MA. The mean wait time for an MA is 11.2 minutes. Surprisingly, there was also a long wait time for MAs at the start of the day. This could be due to a lower MA staffing level or the additional tasks required at the start of the day. Waiting for a provider was the third most common form of waste and occurs during 48% of patient visits. There were significant differences in wait times among providers. Providers 2, 5, and 7 had higher than average wait times of 37.0 minutes, 11.2 minutes, and 12.0 minutes, respectively. Providers 4, 5, and 7 were late to a majority of their appointments, while provider 14 was never late, indicating a large variability between providers. The excess wait time is due to the current duration of an appointment, which does not include time for providers to perform indirect patient care tasks. All providers handle indirect patient care as well as add-on procedures differently, which may be additional sources of variability.

Exceeding the scheduled prep time occurs 38% of the time and is the fourth most common form of waste. The median prep time for samples with a 15 minute scheduled prep time and 30 minutes scheduled prep time was 22 minutes and 32 minutes, respectively. For both scheduled prep times, a patient spends over 50% of the time waiting. See Figures 17 and 18 for a detailed breakdown of prep time. The team also noticed that many procedures are scheduled for 15 minute prep times even though there are large variations in procedure prep times.

Finally, the fifth most common form of waste was patients arriving more than 5 minutes late. Overall, 27.5% of patients visiting the clinic were late. Patients arriving for an appointment regarding kidney stones or UTI have the highest percent of late patients. Kidney stone patients are late because they must have a scan performed at the walk-in radiology clinic immediately before their appointment at the urology clinic. There is currently is no standardized process in place for handling late patients.

RecommendationsGiven the findings mentioned above, the team developed the following recommendations for the clinic.

Look into the patient flow process for return procedural visit patients. Two possible concepts to consider are integration of tasks and parallelization.

Revise staffing levels or provider schedules on Mondays, Tuesdays, and Wednesdays to cope with the larger amount of patients.

Assign nurses to roles rather than providers. Perform a follow up study on PSA patients to identify the reason why they are spending

longer times in the clinic. Allow appointments to begin at 8:30 AM instead of 8:00 AM or reevaluate the

assignments and staffing levels of MAs in the morning. Increment and verify 15 minute appointment times by 5 minutes. Standardize indirect patient care such that it is completed immediately after each patient

is seen. Standardize add-on procedures. Conduct a study to investigate the effect of recommendations to reduce wait time on

patient prep time. Arrange for scheduled radiology scans for kidney stone patients rather than walk-ins to

reduce variability. Standardize handling of late patients by seeing them at the next available break in the

provider’s schedule rather than seeing them as the next patient.

Introduction

The Urology Clinic at the Livonia Center for Specialty Care performs diagnosis, consultation and minor procedures for urology-related medical issues. Staff at the clinic have noticed a disparity between the time patients are scheduled to spend in the clinic and the actual time patients spend in the clinic. Backlogs frequently arise due to this disparity. Clinic staff shared instances where the last patient was scheduled to leave at 3:15pm but left at 5:00pm instead because of the backlog. Both patients and staff are affected by the backlog in clinic schedule. Patients often spend more time at the clinic waiting for treatment while staff feel demoralized by the almost daily backlog of patients and the unpredictability of workload. This discrepancy has affected the satisfaction of both the patients and the staff. Therefore, the professor of urology and the ambulatory care manager would like to better understand the current patient process flow and identify waste residing in the process. They asked a team of senior students from the Industrial and Operations Engineering department (IOE) at the University of Michigan to conduct a study on the current patient process to produce quantifiable data on the current patient process flow and identify areas of waste within the process. The student team sought to understand the current state through conducting and analyzing data obtained through interviews, observations, surveys, and time studies. This report provides methods, findings, conclusions, and recommendations on the current state of the patient flow process and opportunities to reduce waste.

Background

The Urology Clinic at the Livonia Center for Specialty Care operates 5 days a week from 8:00am to 5:00pm. The clinic houses a rotating staff of providers who work at the clinic at varying frequencies while MAs and nurses are at the clinic daily. The clinic currently operates with 8 Medical Assistants (MA), 4 Registered Nurses (RN) and anywhere between 1 to 5 providers depending on the schedule. The clinic operates 11 exam rooms for consultations and procedures.

Patient types determine patient scheduling. New Patients (NP) are scheduled to arrive 30 minutes before their appointment times, and given 30 minute consultation times. Return Visit (RV) patients on the other hand are scheduled to arrive 15 minutes prior to their appointment times and given 15 minute consultation times, unless the RV is scheduled for a procedure. In the instance of a planned procedure, the pre-arrival time and appointment lengths vary. Figure 1 depicts the decision tree for patient scheduling.

Figure 1: Decision Tree for Patient Scheduling Timing

The general process flow at the clinic is classified into three broad groups: consultation, nurse visit and procedure. Figure 2 depicts the general process flow for a consultation and nurse visit appointment.

Figure 2: General Process Flow for Consultation Appointment/Nurse Visit

Upon arrival, the patient checks in at the front desk with the receptionist and receives forms to fill out depending on their provider’s requirements. Next, the patient waits in the lobby until called in by the MA for vitals. The MA then leads the patient into an exam room where the patient is interviewed about medication and medical history. The MA keys in the patient information into MiChart while in the exam room. Any tests ordered by the provider will be carried out during their interaction with the patient. The MA then leaves the room and the patient waits in the room until the provider arrives. After the consultation, the patient proceeds to the checkout counter for payment and scheduling of the next appointment. There are 6 opportunities for waste within the patient flow process, namely: wait times, missing medical history, lack of rooms, additional test, add-on procedures after consultation, and missing checkout instructions.

The general process flow for a procedure appointment follows the initial two steps of the consultation appointment but before the procedure can be performed, a nurse must first seek the patient’s consent on the procedure. After consent is sought, the MA then prepares the patient for the provider to perform the procedure before the provider finally arrives. After the procedure nurse teaching (nurse will educate patient on steps to follow at home) will be ordered depending on the procedure, and finally the patient can check out. This process is represented in Figure 3.

Figure 3: General Process Flow for Procedure Appointment

Patients visiting the clinic are identified by two factors: patient/visit type and diagnosis type. Figure 4 depicts the stratification of the patients by the two factors mentioned above. There are 4 patient/visit types and 8 diagnosis categories where patients can fall into.

Figure 4: Patient Stratification by Patient Type, Visit Type and Patient Diagnosis

There is currently no quantified measure of the patient flow process in the clinic. Since there is no quantifiable measure, the clinic is unable to definitively determine which step or steps in the process deviates from the scheduled timings. Without knowing which step or steps are problematic, the clients are unable to remedy the disparity between scheduled and actual timings. The disparity leads to lower patient satisfaction and staff morale at the clinic. The data collected on the current state of the patient flow process allows the team to identify wastes within the current clinic patient flow process and recommend these areas as opportunities for improvement.

Key Issues

To sum up the current state of the clinic patient flow, the key issues are highlighted below. ● No concrete measurement of clinic patient flow process● Unaware of where waste within the clinic resides● Need to reduce the disparity between actual and scheduled timings in the clinic

Project Goals and Objectives

The primary goal of this project was to quantify the current patient flow process. The project aimed to collect timing information on each step of the patient flow process, and display the

Nurse Visit

Others

Hematuria

Elevated Prostate-Specific Antigen

Erectile Dysfunction

Incontinence

Urinary Tract Infection

Benign Prostatic Hyperplasia

Kidney Stones

Procedural

Consultation

Return Visit New Patient

Patient DiagnosisPatient/Visit Type

Urology Clinic Patient

information on Value Stream Maps to illustrate the clinic current process flow data clearly.

The secondary objectives of the project encompassed:● Identifying the most common forms of waste residing within the process● Identifying inefficiencies in the clinic patient flow process through observation ● Providing recommendations on the opportunities for improvement to reduce waste and

therefore, disparity between scheduled and actual times

In achieving the project goals, the team hopes to provide the clients with a thorough understanding of the current patient flow process, improve patient satisfaction at the clinic, and improve staff morale.

Project Scope

The focus of this project was the on-site patient flow within the clinic. Surveys, observations, interviews and time studies were conducted to collect data on the on-site patient flow. The on-site patient process flow started at check-in, when patients reported to the front desk. All patient-related activities while the patient was at the clinic, up to the point when the patient left the checkout desk were considered to be within the scope of the student project.

Any tasks performed by the clinic prior to and after the arrival of the patient at the clinic were deemed out of the project scope. Call center scheduling and assignment of rules and priorities to various patient types are examples of out of scope activities that would not be covered in the project.

Data Collection and Analysis Methodology

The student team utilized five data collection tools to obtain information of the current state of the clinic. The data collections tools were surveys, observations, interviews, time studies and MiChart data dumps. The following section describes the data collection methods and analysis in detail. A literature search was also conducted to understand what other teams have performed in the past, helping the team better conduct the current project and provide good recommendations.

Observations

The team met with the ambulatory care manager and conducted preliminary observations on September 13th and September 20th from 1:00 PM to 4:00 PM. All three members of the student team were present at the clinic for observations, amounting to 18 person-hours of preliminary observation. In addition, a meeting was arranged with the coordinators and clients on September 16th to understand more about the clinic processes and the project expectations. During the meetings and observations, the team was looking to uncover the various steps within the patient flow process, understand the current patient flow process, understand staff roles, and gain useful information on how to conduct data collection at the clinic.

On October 27th, the team spent the afternoon shadowing three providers at the clinic as they interacted with patients. The shadowing of the providers helped the team better understand how time was being spent during patient interactions and how much time providers spent on indirect patient care after seeing the patient.

Literature Search

A literature search was performed by searching through past IOE 481 projects and electronic journal articles. Reports and electronic articles that were related the analyzing patient flows within clinics were highlighted to help the team develop its project methodology. In addition, electronic articles explaining case studies on the use of lean methodology in healthcare settings were also identified to assist the team with developing recommendations. The articles found will be cited in this report whenever applicable.

MiChart Data

The team requested MiChart data to analyze the time patient with different diagnosis spent at the clinic. The data pulled from MiChart was from November 2nd 2015 to October 31st 2016. The data for this period had 7,500 entries on the time the patient checked-in at the clinic to the time the patient checked-out of the clinic. The patient primary diagnosis was also stated in the records. The data retrieved had the patient names, medical record number and birth dates deleted to comply with HIPPA.

Time Study Form

After preliminary observations at the clinic and initial meetings with the clients, the team conducted a time study on the patient flow at the clinic. Time study forms were designed to collect timing and process information on patient flow. The patients were stratified according to patient/visit type and diagnosis (refer to Figure 4). The data from the time study form was condensed into value stream maps and analyzed by patient/visit type stratification.

Pilot PhaseThe team initially designed the two separate forms (Appendix A-1, A-2). The timing form was to be filled out by patients, recording the length of interaction with each staff encountered at the clinic. Tagged to each patient was a process diagnostics form to be filled out by staff to describe the interaction and record observed waste. The team decided to engage patients in collecting timing data as a past student project [1] and discussions with coordinators revealed that patients are enthusiastic about helping out in studies to improve wait times. The pilot phase occurred between October 21st and October 25th. The form completion rates were tabulated in Table 1.

Table 1: Statistics on form completion during pilot, broken down into daysSource: Pilot data collection from October 21st to October 25th, N = 56

Date Count % Time Study Complete

% Process Form Complete

% Complete

October 21st 13 46% 38% 8%

October 24th 26 50% 46% 27%

October 25th 17 24% 12% 6%

From Table 1, it is apparent that the percentage completion rate of the forms was very low (~15% completion in total). The team determined that a form completion percentage of <50% was insufficient for data analysis. The team spoke to staff members at the clinic and realized two key issues with the initial data collection forms:

● Contrary to literature research, a majority of patients were not filling out the time study forms. The team overlooked the fact that the clinic was a procedural clinic where patients were frequently undergoing minor procedures and therefore, were less likely to fill out forms on examination tables.

● Using two forms created confusion among the staff as they were frequently unable to locate the correct form to fill out.

Combined Time Study FormAfter collecting feedback on the initial time study forms, the team collapsed the two forms into one, requiring only staff to fill it out (refer to Appendix A-3). The new form collected the following data fields:

● Patient stratification (refer to Figure 4)● Provider Last Name● Gender● Time of each staff interaction● Planned and unplanned activity performed for each staff interaction● Waste observed

Data collection occurred from October 26th to November 15th with the new data collection form, a total of 14 work days. The team collected 594 samples.

Interviews

The team developed interview questions after initial observations to obtain in-depth insights on patient flow within the clinic. These initial interviews were focused on understanding the patient process flow, determining what metrics to collect, and how to design the data collection. The

client assisted in arranging for the initial interviews with the staff and these interviews occurred between September 13th and September 20th.

Secondary interviews with MAs, RNs, and providers were conducted after trends were revealed from analysis of the time study data. The secondary interviews were focused on explaining and understanding the trends observed in the data. The information obtained during the secondary interviews were used to shape recommendations provided to the client to improve the patient flow process.

Surveys

One important metric that the team was unable to collect was the time spent on indirect patient care (e.g. billing, dictation, primary care provider communication). Timing data was only collected on direct interaction with patients. Preliminary data analysis revealed that although providers were spending less than the allocated time on consultation, they were still frequently late to appointments. Interviews with providers revealed that activities performed by providers between patients were mostly related to indirect patient care activities. To estimate the time spent on indirect patient care, a survey was sent to all providers to obtain estimates on the time spent on indirect patient care for patients. The survey also asked providers to provide details on the loss of lunchtime due to the buildup of indirect patient care tasks. The survey was created on google forms and sent on November 8th. The team collected four responses.

Analysis of Data

The data collected from the time studies was inputted into Excel, with columns for timings and comments for each stage of the process. The data was analyzed to identify specific encounter times at the clinic and the types of waste occurring. Wastes in the form of wait time was determined by the team and identified through an analysis on excel. Frequency of key wastes were also identified using Excel. Most frequent forms of waste were studied further through statistical analysis in Minitab. The survey data was used to complement the time study data through incorporation of estimated indirect patient care times to direct consultation times. Interview and observation data were used to explain certain trends observed in the time study data and guide recommendations. The aim of the analysis was to quantify the current state of the patient process flow at the clinic and to identify the five most common forms of waste.

Findings and Conclusions

The goal of the project was to quantify the current state of the patient flow process and identify the most common forms of waste within the patient flow process. To quantify the current state, the team studied the time study data and generated value stream maps for the stratification by patient/visit type. Important findings from the value stream maps were highlighted. The MiChart data was also analyzed to determine if there was a significant difference in patient diagnosis and time spent in clinic. The team then tabulated the frequency of wastes found in the clinic and drilled down into the top five forms of waste. In-depth analysis was performed for these five

forms of waste. Data from interviews, surveys and observations were also discussed when they were relevant to the five forms of waste.

Value Stream Mapping

Value Stream Maps provide an excellent visualization for the clinic to brainstorm and discuss the current state of the clinic [2][3]. The team created four value stream maps based on the patient/visit type stratification: New Patients, Return Visit Consultations, Return Visit Procedural, and Nurse Visits. The process flows were discovered through the data collection from the time study data collection form (Appendix A-3) where patients in the four groups would usually go through a similar patient flow path in the clinic. The time study data collection forms also provided the timing data for the value stream maps (Appendix B).

Return Procedural Patient Flow Most InefficientThe team calculated patient waiting times and the time patients spent with their scheduled provider and the values are listed in Table 2.

Table 2: Value Stream Map Summary Table Stratified by Patient and Visit TypeSource: Time Studies Data from 11/2/15 - 10/31/16, N = 594

From Table 2, returning patients scheduled for a procedure spend the most time waiting, only 38.95% of their visit is spent with clinic staff, the lowest percentage across all visit types. The low percent value added time for return procedural patients can be attributed to the additional amount of staff encounters experienced by these patients. The extra encounters lead to longer wait times. For the other types of patients, the percent value added time falls around 57%. This is not an ideal value as well and the team will introduce recommendations later to reduce wait times.

Monday, Tuesday, and Wednesdays Experience Longer MA and Provider (Mondays and Tuesday) Wait TimesA table (Appendix C-3) was created to depict the wait and staff times for visits across different days of the week. The data analysis revealed Mondays, Tuesdays, and Wednesdays have the highest MA wait times, while provider wait times are highest on Mondays and Tuesdays. The

average MA wait time for these days is 13.21 minutes, compared to the average across all days of the week being 10.96 minutes. Additionally, Tuesday patients saw a 1.23 times increase for Vitals/Tests time. The average provider wait times on Mondays and Tuesdays are 11.65 minutes and 10.26 minutes, respectively, versus approximately 5 minutes for the rest of the days. Monday, Tuesday, and Wednesday are days when more providers and patients are scheduled.

Excessive Wait Time for MA, Nurse and Provider Table 3 displays the average, standard deviation and percentage of sampled visits for every step in the patient flow process. Denoted in the red rectangles in Table 3 are the 3 largest forms of wait times within the clinic: wait time for nurses, MAs, and providers.

Table 3: Value Stream Map Summary Table for Steps in the Patient Flow Process in MinutesSource: Time Studies Data from 11/2/15 - 10/31/16, N = 548

All three highlighted wait times exceed 5 minutes, the highest acceptable wait time for each member of the staff determined by the team. The high means for the three wait times lead to the disparity between the scheduled time and actual time. Take for example a procedure with a prep time of 30 minutes, typical of a procedural patient: the two wait times for an MA plus the wait time for a nurse would be 33 minutes, longer than the prep time allocated for the patient in the schedule without any value added work performed. The three wait times also have high standard deviations, indicating a large range of values for these wait times. The team attributed the high nurse wait times to nurses having both scheduled appointments and spontaneous tasks like consent, teaching and assisting providers. The long MA and provider wait times will be discussed under the Top 5 Wastes Section.

Patients with elevated PSA spend the longest times in the clinic

The data from MiChart was categorized into the seven diagnosis types used in the project (Figure 4). A Kruskal-Wallis test was performed using Minitab to determine if there is a statistical difference between the patient diagnosis types and the time spent in the clinic starting from appointment time.

The Kruskal-Wallis test output in Appendix C-1 returned a P-value of 0.00. This indicates there is a significant difference between the mean times a patient spends in the clinic starting from the appointment time. The team then drilled down into the diagnosis types by plotting the 95% confidence intervals of the various diagnoses. The plot is displayed in Figure 5.

Figure 5: MiChart data shows that 6 is significantly higher than 5, 3 and 1 Source: Michart Data from 11/2/15 - 10/31/16, N = 7500; 1 = Stones, 2 = Benign Prostatic Hyperplasia, 3 = Urinary Tract Infection and Cysts. 4 = Incontinence, 5 = Erectile Dysfunction, 6 = Elevated PSA, 7 = Hematuria

From Figure 5, it is evident that the largest mean times belong to patients with elevated PSA levels (category 6). The non-overlap of the interval of patients in 6 with patients in 1,3 and 5 indicate that there is a significant difference in means for patients in 6 compared to 1,3 and 5. The difference in patient times is a significant revelation because it indicates that scheduling should take diagnosis into account rather than just patient type, which is the current practice.

Top 5 Waste Identified in the Clinic

After analyzing the data for different stratifications collected by the team, wastes in the form of wait time and time spent in the clinic were identified by the team. These wastes were added to the 6 forms of waste introduced in the Background section. All forms of identified waste are listed below (definition of these waste are in Appendix C-2):

● Patient Waited >5 mins for MA● >60 minutes total time in clinic

● Wait time >5 minutes for provider● Exceed prep time by >5 minutes● Patient late by >5 minutes● Exceed scheduled consultation times● Wait time >5 minutes for nurse● ≥ 2 provider interactions per visit● Procedure added on

In addition to the nine sources of waste defined by the team, other sources of waste are listed in the time study data collection form (Appendix A-3). A Pareto Chart was created by the team after analyzing the time study data and is displayed in Figure 6.

Figure 6: Pareto chart of the frequency of waste within the clinic. Source: Time study data 10/21/16 - 11/15/16; N = 594

As highlighted in the Pareto chart in Figure 6, the top 5 forms of waste within the clinic are:1) >60 minutes in the clinic2) >5 minutes wait time for MA3) >5 minutes wait time for provider4) >5 minutes of scheduled preparation time5) Patients >5 minutes late

With the data from the Pareto Chart, further in-depth analysis was conducted and the results are presented in the following sections.

Patients Spend More Than 60 Minutes in the ClinicThe most common waste according to the Pareto Chart (Figure 6) is patients spending more than 60 minutes in the clinic. A weighted total of 321.5 patients spent more than 60 minutes at the clinic. This translates to 54% of patients spending more than 60 minutes at the clinic. Time spent is defined as the time between pre-arrival time to the time the patient checks out. For the purposes of this study, patients who spend less than 20 minutes in the clinic are excluded because these patients arrived excessively early and were seen early. The data is skewed right with large outliers. The median for patient time in clinic is 61 minutes with a mean of 67.04 minutes (Appendix C-3). Of the patients who spent more than 60 minutes in the clinic, the team performed a breakdown of the time spent in the clinic by frequency (Appendix C-4). Of note, 60% of patients who spend more than 60 minutes at the clinic spent up to 90 minutes at the clinic.

The team also compared time spent in clinic over 60 minutes across providers. Figure 7 plots the average visit time by provider while Figure 8 plots the percent of patients exceeding a 60 minute visit by provider.

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Figure 7: Average time in clinic by providerSource: Time study data 10/21/16 - 11/15/16; N = 240

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Figure 8: Percent of patient visits greater than 60 minutes by providerSource: Time study data 10/21/16 - 11/15/16; N = 240

From Figures 7 and 8, the team discovered that there are providers with more than 50% of their patients spending more than 60 minutes at the clinic. The same providers also have the highest average patient times in clinic. The median percentage of patients spending more than 60 minutes at the clinic is 41%. Since the clinic targets all patients to leave the clinic within 60 minutes, this is a large opportunity for improvement. Excess Wait Time for MAThe second most common form of waste during a patient’s visit is waiting over 5 minutes to see an MA after checking in. The weighted frequency for this process is 340 occurrences. This figure translates to 49% of patients experiencing greater than 5 minute wait time for the MAs. The MA wait time distribution is skewed right, with 41% of the wait times exceeding 10 minutes. The mean wait time for an MA is 11.2 minutes while the median wait time is 8 minutes (Appendix C-5). The difference in the two measures is attributed to large outliers to the right, indicating that there are instances where patients had to wait longer for a MA. For patients who waited more than 5 minutes for a MA, 42% experienced MA wait times of more than 15 minutes. The distribution of patient wait times for an MA is plotted in Figure 9.

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Figure 9: Frequency chart of MA wait times Source: Time study data 10/21/16 - 11/15/16; N = 519

The team then plotted the MA wait time against time of day and the results are displayed in Figure 10.

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Figure 10: Percent of MA wait times greater than 5 minutes across time of daySource: Time study data 10/21/16 - 11/15/16; N = 296

Long Wait Times for MA at Start of Day The result in Figure 10 indicates that MA wait times remain consistent throughout the day. This is an unexpected result since the clinic schedules its first patients at 8am and there should be

shorter wait times at the start of the day. The team investigated further and discovered that patients scheduled to see the providers at 8:00 AM were told to come in at either 7:45 AM or 7:30 AM depending on the patient type but had to wait on average 13.7 minutes before being brought in by the MA for vitals. This could also be due to a lower staffing level at the start of the day and the number of other tasks that are necessary to open the clinic at the beginning of the day. This long wait time for an MA at the start of the day causes the clinic to start the day off with a backlog of patients.

Excess Wait Time for ProviderWaiting over 5 minutes for a provider is the 3rd most common form of waste occurring in the clinic. The median wait time for provider is 3 minutes, which is acceptable for provider wait times, but since the data is skewed right, there are large outliers for provider wait times resulting in a mean of 8.1 minutes (Appendix C-6). The team discovered that 69% of patients who had to wait more than 5 minutes waited over 10 minutes for the provider from the time they were ready, and 45% of the patients waited over 15 minutes (Figure 11).

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Figure 11: Wait time for provider when providers were late to the appointmentSource: Time Study Data 10/21/16 - 11/15/16, N = 79

There were also significant differences between providers. Providers 2, 5 and 7 had higher than average wait times (37.0 minutes, 11.2 minutes and 12.0 minutes) while Providers 4, 12, and 15 (8.78 minutes, 3.4 minutes, and 7.2 minutes) had less than average patient wait times (refer to Figure 12). Only Provider 12 had an average patient wait time of less than 5 minutes.

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Figure 12: Average wait time by providerSource: Time study data 10/21/16 - 11/15/16; N = 79

Figure 13 shows the discrepancy between providers for frequency of being late. Only providers with a sample size of more than 5 patients were included. Provider 14 was never more than 5 minutes late to an appointment during this data collection phase whereas Providers 4, 5, and 7 were late to a majority of their appointments.

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Figure 13: Percentage of time providers are late to appointment(Source: Time study data 10/21/16 - 11/15/16; N = 79)

Scheduled 15 Minutes Appointment Insufficient for All Patient Care Tasks for a Single PatientThe team hypothesized that the excess wait time for provider is due to providers exceeding scheduled consultation times but the Pareto Chart (refer to Figure 6) only accounts for 5.8% of the frequency of waste. This is further supported by the plot of average consultation time vs

scheduled consultation time where the average time spent with patients is consistently lower than the scheduled time (Appendix C-7, C-8), except for Provider 12 (mainly attributed to the fact that most patients seeing Provider 12 are undergoing procedures). After observations at the clinic, the team discovered that other than direct patient care, the providers had to spend time on indirect patient care tasks like contacting the primary care providers, billing, dictation, and reviewing test results. These timings were not reflecting on the time study conducted since the time study only recorded face-to-face patient timings. The time required for indirect patient care was also not incorporated into the provider's schedule. The provider survey sent out was intended to obtain an estimate on the time required for indirect patient care and the results are detailed in Appendix E.

The least time spent on indirect patient care from the provider survey was 10 minutes for both NP and RV (Appendix E). Taking these timings as the most conservative estimates, two plots were created for 15 and 30 minute appointments respectively, where indirect patient care time was added to direct patient care time (Figure 14, Figure 15).

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Figure 14: Provider indirect and direct care time by provider, 15 minute appointmentSource: Time study data 10/21/16 - 11/15/16; N = 79

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Figure 15: Provider indirect and direct care time by provider, 30 minutes appointmentSource: Time study data 10/21/16 - 11/15/16; N = 79

The results revealed that the scheduled time for each patient was insufficient for providers to complete all necessary patient care tasks for 15 minute appointments. For 30 minute appointments, the time taken for patient care is sufficient for all providers except for two. The team would emphasize this as a conservative estimate. This was also reflected in the survey where most providers indicate that they spend a majority of their lunchtime catching up on indirect patient care tasks that they were unable to complete (Appendix E). The team then created a chart with a sample provider’s day to show a provider’s patterns throughout the day (Appendix C-9). As the figure shows, the provider spends more time on direct patient care at the beginning of the day and shortens the direct patient care time as the day proceeds. The team believes this is due to the fact providers have insufficient time for indirect patient care so this time eats into the direct patient care time.

Non-standardized Handling of Indirect Patient Care and Add-on Procedures another Source of VariabilityObservations at the clinic also revealed that there was no standardized method for the completion of indirect patient care. Some providers meticulously completed the required tasks before seeing the patient while others leave these tasks to breaks in their schedule. The team also observed that providers will add-on procedures for patients as well, performing the procedures immediately after the consult. The variability in the provider's methods and the practice of add-on procedures may lead to even greater discrepancies between the scheduled and actual timings.

Actual Prep Time Exceeds Scheduled Prep TimeExceeding the scheduled prep time was found to be the fourth most common cause of waste. For the team’s analysis methods, prep time was considered from the time the patient checked in at the front desk to the time the patient was ready to see the provider. If a patient arrived to the clinic early, the later time from when they arrived and when they were scheduled for pre-arrival

was used as the time patients first checked in. The team analyzed where an excess in prep time was occurring by scheduled prep time, patient type, and by the procedure performed.

For samples with 15 minute scheduled prep time, the median was 22 minutes, exceeding the allotted time. The data is also skewed right with large outliers resulting in a mean of 29.8 minutes (Appendix C-10). This is almost double the allotted time for prep. For samples with 30 minute scheduled prep time, the distribution is skewed right but less so than the 15 minutes samples. The median for this data is 32 minutes, which is very close to the allotted time but the mean is 37.6 minutes, which exceeds the allotted time by over 5 minutes.

Half of Prep Time for Both 15 Minutes and 30 Minutes is Spent WaitingA breakdown of patient prep time for each scheduled prep time was broken down into the amount of time a patient spends waiting and the amount of time the patient is interacting with a staff member. The results from this analysis are shown in Figure 16. Figure 16 reveals that regardless of how long the patient prep time was scheduled, a patient on average spends over half of that time waiting to be seen by a staff member.

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Figure 16: Percentage of Time Patient Spends Waiting versus with a Staff MemberSource: Time Study Data 10/21/16 - 11/15/16; N = 350

Wait Time for Longer for RV for 15 Minutes Prep Time but Longer for NP for 30 Minutes Prep Time. NP Takes Staff 1.5-2 Minutes More to Prep in Terms of Actual Staff Interaction TimeThe team was also interested in determining if there was a disparity between new patient prep times and return visit prep times. It was expected that a new patient would have a longer prep

time, but the data shows for a 15 minute scheduled prep time, return visits have an average total prep time of 31 minutes while new patients have an average prep time of 24 minutes. The actual staff interaction time for patient type revealed only a 1.5-minute difference which means this disparity is mostly due to higher waiting times for return visit patients (Figure 17).

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Figure 17: Time Spent With Staff for 15 Minute Prep, Broken Down into RV and NPSource: Time Study Data 10/21/16 - 11/15/16; N = 244

The opposite trend is apparent for 30 minute prep times (Figure 18) where even though NPs take the staff 2 more minutes to prep than RVs, NPs have on average a 38 minute prep time while RVs are on average under 20 minutes. In both cases, the actual prep time where a patient interacts with a provider is well under the scheduled time so any waste caused by exceeding the scheduled prep time is usually caused by having a patient wait between different staff interactions.

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Figure 18: Time Spent With Staff for 30 Minute Prep, Broken Down into RV and NPSource: Time Study Data 10/21/16 - 11/15/16; N = 106

Patients Arriving For Procedure Usually Scheduled For 15 Minutes Prep Time But Prep Time Varies By Procedure TypeThe clinic usually determines patient prep time as 30 minutes if they are a NP or 15 minutes for a RV even though very often, RVs are undergoing a procedure (Figure 1). These prep times take longer than average and are shown by procedure in Figure 19. One of the 8 procedures that data was collected had an average actual prep time (interaction with a staff member) under 15 minutes. All other procedure prep times require over 15 minutes of direct patient care. When wait times the patient experiences are considered, no procedure prep times remain under 15 minutes. The team believes the variability between different procedures and the amount of prep time that is actually needed for each procedure is something the clinic should consider when scheduling their patients. If this longer prep time is accounted for, the clinic would experience less build-up and run more smoothly.

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Figure 19: Actual Prep Time by Procedure Performed Source: Time Study Data 10/21/16 - 11/15/16; N = 106

The team categorized the data by the time of day to see if prep time varied throughout the day and this is shown in Figure 20 and Figure 21. This data is interesting because although the total prep time varies throughout the day, the actual time spent with staff is rather consistent. This shows that the variability is due to different wait times and not due to different preparatory tasks. This makes sense also because the only significant trend apparent from the data is a higher prep time from 11:00 AM - 15:00 PM. This could be explained by the fact that MA’s and nurses are on scattered lunch breaks during this time and there are less on staff to handle the prep of incoming patients.

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Figure 21: Actual 30 Min Prep Time by Time of DaySource: Time Study Data 10/21/16 - 11/15/16; N = 106

Late PatientsLate patients are the 5th most common form of waste occurring in the clinic. Late patients were defined as patients who arrived more than 5 minutes after their pre-arrival time. The team is unable to quantify the effect on late patients on subsequent patients due to the unavailability of data. Insufficient timing data was collected for instances where a patient was late and the subsequent patient was to see the provider immediately after (E.g. Patient late but no timing data collected for subsequent patient’s encounter with provider). Therefore, the team assumed the following effects of late patients - Late patients lead to higher variability for subsequent patients arriving at the clinic since providers would have to fit the late patient into their schedule. The busier the schedule of the provider, the larger the disparity between the actual and scheduled times, and subsequent patients would more than likely spend more time in the clinic.

Overall, 27.5% of the patients visiting the clinic were late. The team created a plot on how late patients were. Of the patients who were late, 70% were more than 10 minutes late (Refer to Figure 22).

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Figure 22: Histogram of Patient Late Times for Patients That Arrived Past Pre-Arrival TimeSource: Time Study Data 10/21/16 - 11/15/16; N = 63

Kidney Stones and UTI Patients Had Highest Percentage of Late PatientsPatients visiting the clinic for kidney stones and UTI had a significantly higher proportion of late arrivals than the other diagnosis (58.3% and 30.6% - Figure 23).

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Figure 23: Percentage of late patient by stratification typeSource: Time study data 10/21/16 - 11/15/16; N = 594

Interviews with the staff at the clinic revealed that kidney stones patients are told to arrive at the clinic earlier to undergo a walk-in radiology screening at an adjacent clinic in the Livonia Center before checking into the urology clinic. The need to first obtain a radiology scan before the appointment would contribute to the high percentage of late times for kidney stones patients.

No Standardized Management of Late PatientsObservations conducted at the clinic also revealed there is no standardized management system for late patients. There are no standardized rules on seeing late patients, this was mostly up to the individual provider discretion. The absence of standardization and efficient handling of late patients might lead to high variability of patient time in clinic as well as larger discrepancies between the actual and scheduled times.

Summary of Conclusions

The conclusions derived from all the findings in this report is summarized in this section.

Value Stream Mapping

The team created four value stream maps for the patient stratifications NP, RV consult, RV procedural and Nurse Visits. From the value stream map, the team drew the following conclusions

● RV procedurals spend the longest time in clinic. The procedural patients have the longest wait times as well, leading to the smallest percentage of value-added time at 38.95%. The team attributed the low percentage value added time to the extra staff interaction required for procedural patients (6 instead of 4) since every staff interaction would include wait time.

● Mondays, Tuesdays and Wednesdays see a higher average wait time for MAs and providers compared to Thursdays and Fridays. The mean wait time for Mondays, Tuesdays and Wednesdays is 13.21 minutes, compared to the average across all days of the week being 10.96 minutes. The longer wait time is attributed to the higher number of providers scheduled on the first 3 working days of the week

● Longest wait times occur while waiting for nurse, MA for vitals, and providers in that order. The nurses have the highest wait times because they are required to attend to both scheduled nurse visits and spontaneous tasks required by the providers such as consent and teaching. All three high wait times exceed the team’s acceptable limit of 5 minutes and have high standard deviations as well.

Patients with Elevated PSA Diagnosis Spend The Longest Times in Clinic

The analysis of MiChart data revealed that the patients visiting the clinic for elevated Prostate-Specific Antigens spend the longest time in the clinic. This result is supported by the Kruskal-Wallis statistical test indicating a significant difference. The 95% Confidence-Interval for

elevated PSA patients is from 66 to 72 minutes. The significant difference between diagnosis indicates that there may be a need to schedule patient timings by diagnosis as well.Top 5 Wastes in the Clinic

The top 5 waste in the clinic are as follows:

1) > 60 minutes spent in the clinic2) >5 minutes wait time for MA 3) >5 minutes wait time for provider4) >5 minutes of scheduled preparation time5) Patients >5 minutes late

More Than 60 Minutes at the Clinic54% of the patients visiting the clinic spend more than 60 minutes at the clinic. Of the 54% who spent more than 60 minutes, 40% of them spent more than 90 minutes at the clinic. When stratified by providers, large variations between different providers become apparent. The clinic standard for patient time spent in clinic is under 60 minutes, making the problem for spending excess times in the clinic a huge opportunity for improvement.

Excess Wait Time for MA49% of the patients experienced waiting more than 5 minutes for an MA to call them in to take their vitals. The median MA wait time is 8 minutes with the data skewed right with large outliers leading to a mean of 11.2 minutes. The team also discovered that the clinic starts the day with high MA wait times, an unexpected result for the start of the day.

Excess Wait Time for ProviderWait time for providers is heavily skewed right, with median of 3 minutes and mean of 8.1 minutes. Of the patients that had to wait more than 5 minutes for the provider, 69% had to wait more than 10 minutes. There are also large variations between providers with Provider 2 patients experiencing the largest patient wait times (37 mins) while Provider 12 is well within the 5 minute wait time (3.4 mins). The team also discovered that when indirect patient care times are included, all providers exceeded the time allotted for a 15 minute appointment while all but two providers remained within the 30 minute appointment allotted time. Providers exceeding the 15 minutes allotted time is identified as the main reason why patients have to wait more than 5 minutes for providers. Observations also revealed that there is no standardized procedure for indirect patient care tasks, with some providers completing the task immediately after consultation and others accumulating the tasks until the next available break. The absence of standardization may lead to more variability. Finally, the practice of adding on procedures to patients also adds to the variability in the schedule since the procedures are being performed immediately after the consult and create delays for subsequent patients.

Actual Prep Time Exceeds Scheduled Prep TimeFor patients with a scheduled prep time of 15 minutes, the median is 22 minutes and the mean is 29.8 minutes while for patients with a scheduled prep time of 30 minutes, the median is 32 minutes and the mean is 37 minutes. 50% of the actual prep time was spent waiting for staff for both 15 and 30 minute scheduled prep times. Variations also exists between different procedures types but most scheduled prep times are set at 15 minutes, regardless of procedure type.

Late Patients27.5% of the patients were more than 5 minutes late to their pre-arrival times, with 70% of the late patients more than 10 minutes late. When stratified by patient diagnosis, patients with kidney stones and UTI have the highest percentage of late patients. There is also no standardization of when to see patients who are late, the decision is left completely up to the provider’s discretion.

Recommendations

With the results of the findings, the team has generated the following list of recommendation on the areas of improvement to improve patient flow within the clinic.

RV Procedural Patients

To reduce the time spent in the clinic and improve the percentage value-added time, the team suggests looking into the patient flow process for this category of patients. Two possible concepts to consider are integration of tasks and parallelization.

For procedural patients, a lot of time is spent waiting for staff, since there are six interactions in total. By integrating tasks, it is possible to cut down the number of staff interaction and reduce the amount of wait time. One example of task integration could be training MAs to obtain consent for a procedure. With this improvement, there would only be four interactions instead of six.

Currently, many processes in the clinic are conducted serially, without overlap. A possible method to reduce wait time is for the MA to inform the nurse when they are about to bring the patient in for vitals. By allowing tasks to be conducted in parallel [4][5], nurses can enter the room while the MA is still present to seek consent for the procedure. This eliminates the wait time for nurse consent and MA prep for procedure since the MA will not leave the room.

Longer MA Wait Times on Mondays, Tuesdays and Wednesdays

The team advises the clinic to further investigate the longer wait times on Mondays, Tuesdays and Wednesdays. One way to approach the issue would be to revise staffing levels on the stated days to cope with the larger number of patients. Another approach would be to reassign the providers away from the first three days, to Thursday and Friday, to smoothen out the demand for MAs and therefore, reduce MA wait times.

Long Nurse Wait Times

Nurses at the urology clinic have to attend to both scheduled nurse visits and assist providers in procedures, obtaining consent and patient teaching. Currently the nurses are assigned to providers and assist whichever provider they are assigned to. One recommendation would be to assign nurses to roles rather than providers. By assigning a portion of nurses to assisting providers and another portion to nurse visits, the team hypothesizes that there would be less wait time for nurses. To confirm this hypothesis, a pilot study would have to be conducted after the change to verify the result.

PSA Patients Spend Longer Times at the Clinic

The team proposes a follow up study on PSA patients to clearly identify the reason why they are spending longer times in the clinic. Scheduling of PSA patients may have to be different from other diagnosis depending on the result of the follow-up study.

Excess Wait Times for MAs

The long wait time for MAs is a huge opportunity for improvement for the urology clinic. One of the more pertinent issues is the long MA wait times at the start of the clinic. The team recommends that the clinic either allow appointments to begin at 8:30 AM instead of 8:00 AM, to allow for more time to prepare the exam rooms at the start of the day, or adjust staffing at the start of the day to reduce wait times. The team also recommends looking into the assignment of MAs to patients for vitals and find out if there are any inefficiencies in the current MA assignment process.

Excess Wait Time for Providers

The team recommends increasing all 15 minute appointment times in steps of 5 minutes and verifying the wait-times as the scheduled consultation times increase. While increasing the consultation times, the clinic should also standardize the performance of indirect patient care tasks to be completed immediately after each patient is seen, possibility reducing variability among providers. Add-on procedures should also be allowed but standardized. Standardization

of add-on procedures should occur in the form of booking the patients for add-on procedures during breaks in the provider’s schedule rather than being performed immediately after consultation.

Actual Prep Time Exceeds Scheduled Prep Time

Since wait time for staff constitutes ~50% of the actual prep time, the team believes that the recommendations to reduce MA wait time and nurse wait times be implemented first. A study should then be conducted to investigate the effect of the recommendations on actual prep time. Should the recommendations be insufficient in reducing actual prep times, the team recommends extending prep times by steps of 5 minutes. Due to insufficient information on procedures performed, the team is unable to give an accurate estimate on the recommended prep time for each procedure. The team believes that there is enough variation in procedure prep times that an additional study is warranted to obtain an accurate prep time for each procedure performed at the clinic.

Late Patients

The team recommends that the clinic should try to arrange for scheduled radiology scans for kidney stone patients rather than walk-ins to reduce variability. To reduce the occurrence of late patients, the clinic must standardize handling of late patients and consequently, early patients. The clinic should see a patient at the scheduled pre-arrival and appointment time rather than taking a patient in whenever they arrive. When patients are late (arrive after the subsequent provider appointment), patients should be seen at the next available break in the provider’s schedule, instead of as the next patient. To facilitate this practice the clinic would also be disciplined in seeing early patients only at their scheduled appointment times. The delay experienced by late patients will act as a disincentive for future late arrivals [6].

Expected Impact and Outcome

The project conducted by the team is expected to benefit the clinic in two ways. The time study data, translated into value stream maps give the clinic a scientific and concrete understanding of the clinic process. The recommendations provided by the team will serve to improve the efficiency of the clinic and reduce disparity between the scheduled and actual times. The team hopes that the findings and recommendations in this project will enlighten the clinic on its current patient flow process, provide a clear visualization of the overall patient process, and to guide the clinic in its process improvement efforts.

Value Stream Mapping

The use of value stream maps provides an easy to understand visual of the current patient flow timings in the process. The data on the value stream map allows the clinic to quickly identify sources of waste in the clinic and where future improvement efforts should be focused to improve efficiency [2][7]. The involvement of all clinic staff in the data collection efforts also provides the staff with a foundation in scientific data collection for purposes of quantifying the clinic current state. Any future process flow study that the clinic hopes to pursue will be made smoother due to this project.

Recommendations

Recommendations provided by the team were aimed at identifying opportunities for improvement within the clinic in terms of patient wait times and reducing discrepancies between scheduled and actual times. Recommendations made to 1) standardize process and decision-making within the clinic and 2) re-evaluate scheduled timings were aimed at reducing variability in the clinic which ultimately reduces the discrepancy between actual and scheduled appointment times. Recommendations made to reduce wait times were made to reduce waste within the clinic and improve the process efficiency.

References

[1] Matt Bovberg et al., “Analyzing Patient Flow and Process Waste in the General Thoracic Surgery Clinic”, IOE 481 Senior Design Projects, Winter 2014, April 2014

[2] Altarium Institute, “Applying Lean to Improve the Patient Visit Process at Three Federally Qualified Health Centers”, July 2011

[3] Lori Rutman et al., “Improving Patient Flow Using Lean Methodology: an Emergency Medicine Experience”, Springer International Publishing, October 28th 2015.

[4] B. T. Denton and D. T. Brian, Handbook of healthcare operations management: Methods and applications. New York, NY: Springer New York, 2013, ch. 3, sec. 2.

[5] L. Jiang and R. E. Giachetti, "A queueing network model to analyze the impact of parallelization of care on patient cycle time," Health Care Management Science, vol. 11, no. 3, pp. 248–261, Dec. 2007.

[6] A. M. Association, "How to handle patients who are always late," 2009. [Online]. Available: http://www.amednews.com/article/20090413/business/304139998/5/. Accessed: Dec. 6, 2016.

[7] R. R. Lummus, R. J. Vokurka, and B. Rodeghiero, "Improving quality through value stream mapping: A case study of a physician’s clinic," Total Quality Management & Business Excellence, vol. 17, no. 8, pp. 1063–1075, Oct. 2006.

Appendix A: Time Study Forms

Appendix A-1: Time Study Data Collection Form

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Appendix A-2: Process Diagnostics Form

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Appendix A- 3: Combined Time Study Form

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Appendix B: Value Stream Maps

Appendix B-1: New Patient Value Stream Map

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Appendix B-2: Return Consultation Value Stream Map

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Appendix B-3

Appendix B-3: Return Procedural Value Stream Map

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Appendix B-4: Nurse Visit Value Stream Map

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Appendix C: Data Analysis Charts

Appendix C-:1: Kruskal-Wallis test output on the time spent in clinic by diagnosis types. Source: Michart Data from 11/2/15 - 10/31/16, N = 7500; 1 = Stones, 2 = Benign Prostatic Hyperplasia, 3 = Urinary Tract Infection and Cysts. 4 = Incontinence, 5 = Erectile Dysfunction, 6 = Elevated PSA, 7 = Hematuria

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● Patient Waited >5 mins for MA -Time difference between pre-arrival time and the time the patient left the front desk if patients were early (>5 minutes before pre-arrival). Time difference between the later of actual time patient left front desk and the time the patient was received by the MA for vitals if patients were punctual or late.

● >60 minutes total time in clinic - Time difference between pre-arrival time and actual time the patient left the clinic.

● Wait time >5 minutes for Provider - Time difference between time provider sees the patient and time of the last patient staff interaction. This metric only applies for instances when patients were ready for the provider at the scheduled appointment time (+/- 5 minutes of arrival time).

● Exceed prep time >5 minutes - Time difference between the later of pre-arrival and

actual arrival time, and the last staff patient interaction before the provider consultation. Instances where actual preparation time exceed the scheduled time by more than 5 minutes were recorded.

● Patient late by >5 minutes - Time difference between pre-arrival time and actual arrival time.

● Exceed scheduled consultation times - time difference between the actual amount of

time spent with patient by provider and the scheduled amount of time allocated to provider

● Wait time >5 minutes for Nurse - Time difference between start of Nurse interaction for consent or teaching and the last staff patient interaction

● >= 2 provider interaction per visit - When a provider enter and leave the room more than once per visit, it is considered to be a waste

● Added on - Added on procedures are considered to be a source of waste in this study

Appendix C- 2: Definition of timing related waste in the Pareto Chart Analysis

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Appendix C-3:Value stream map totals across day of the week Source: Time study data 10/21/16 - 11/15/16, N = 513

Appendix C-4: Summary report on time patients spend in clinic excluding samples under 20 minutes

Source: Time study data 10/21/16 - 11/15/16, N = 513

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Appendix C-5: Summary report of MA wait timesSource: Time study data 10/21/16 - 11/15/16; N = 519

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Appendix C-6: Wait time for provider summary reportSource: Time Study Data 10/21/16 - 11/15/16, N = 79

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2 4 5 6 7 9 10 12 13 14 150.0

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Appendix C-7: Average actual consultation time for 15 minute consultation stratified by providerSource: Time study data 10/21/16 - 11/15/16; N = 79

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2 4 5 6 9 12 14 150.0

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13.0

17.1 17.5 18.3 19.3

23.622.0

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E TA

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Appendix C-8: Average actual consultation time for 30 minute consultation stratified by providerSource: Time study data 10/21/16 - 11/15/16; N = 79

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7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:000

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Scheduled Time Actual Time Pt arrival

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Appendix C-9: Sample schedule of provider’s daySource: Time study data 11/2/16; N = 13

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Appendix C-10: Summary Report of Samples with 15 Minutes Scheduled Prep TimeSource: Time study data 10/21/16 - 11/15/16; N = 244

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Appendix C-11: : Summary Report of Samples with 30 Minutes Scheduled Prep TimeSource: Time study data 10/21/16 - 11/15/16; N = 106

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Appendix D: Provider Indirect Care Perception Survey

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Appendix E: Provider Indirect Care Perception Survey Responses

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