Analysis of Lead Timefor

The Division of Nephrology

Project Coordinator

Elizabeth Othman

Student Project Team

Jonathan BrinksBrian Cross

Robert Larsen

April 22, 1996

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Table of Contents

Executive SummaryIntroduction 1Conclusions 1

Introduction 3

Approach and Methodology 3

ResultsEntire clinic results SIndividual clinic day results 8

Conclusions 11

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Executive Summary

Introduction

At the request of the Division of Nephrology, the new patient lead time for the Nephroiogy

clinic has been analyzed. This analysis has been completed by the student Project Team ofJonathan Brinks, Brian Cross, and Robert Larsen. The student project team has beenworking with Elizabeth Othman, Senior Analyst for the Program and Operations Analysis

department at the University of Michigan Hospital.

The purpose of this analysis is to provide the Division of Nephrology feedback on patient

lead times, to provide them with a reference point for future analysis and to aid them in

making improvements in the Nephrology clinic. The purpose of this report is to inform

you of the approach and methodology for this analysis and to provide the results of our

analysis.

The new patient lead time for the Division of Nephrology has been defined as the period of

time between the patient’s appointment date and the date when the patient called the hospital

to schedule the appointment. This scheduling is done by the Internal Medicine Scheduling

department at the University of Michigan Hospital.

Conclusions

The main conclusion from our analysis of the Nephrology clinic new patient lead time is

that the lead times is directly related to the number of slots the clinic closes. If the clinic

would like to reduce the new patient lead times,the most effective way may be to eliminate

the closings of new patient slots. As shown by Figure 5, the lead time in October dropped

alter the number of closings in September and October was very low.

The second conclusion from our analysis is that the number of no-shows is constant, at

about 7%, and is not related to the lead time. Combined with the cancellation and

rescheduling data, there is more than 30% of patients that don’t keep their scheduled

appointments. With this in mind you can overbook the clinic, unless your resources are

already maximized with four new patient sLots.

A third conclusion is that patients are more likely to keep an afternoon appointment. Based

on this fact, increasing the number of afternoon appointments would make the Nephrology

clinic more predictable. The data showed that the Tuesday clinic had a utilization of 81%.

This means that of the scheduled appointments for Tuesday, 81% of the patients showed

up for their appointments. Tuesday is the clinic day with afternoon appointments.

The final conclusion of our analysis is that there is a higher demand for Monday and

Tuesday appointments. If it is possible, increasing the number of slots available for use on

Monday and Tuesday would help meet the patient demand better, thereby reducing lead

time and lost business.

Finally, throughout our analysis of the Nephrolo clinic the charts that were most usefulin analyzing the data were:

• Number of appointments each month with lead time conthbudons (Figure 2)

• Average lead time by week vs. new patient slot closings by week (Figure 5)

Using these two charts to keep tack, week by week, of lead me the clinic will be able tonotice any tends in the lead time. The first chart (Figure 2) will keep tack of the lead thnecontributions for total appointments. The second chart (Figure 5) will keep tack of leadtime and new patient slot closings.

Introduction

At the request of the Division of Nephrology, the new patient lead time for the Nephrologyclinic has been analyzed. This analysis has been completed by the student Project Team ofJonathan Brinks, Brian Cross, and Robert Larsen. The student project team has beenworking with Elizabeth Othman, Senior Analyst for the Program and Operations Analysisdepartment at the University of Michigan Hospital.

The purpose of this analysis is to provide the Division of Nephroiogy feedback on patientlead times, to provide them with a reference point for future analysis and to aid them inmaking improvements in the Nephrology clinic. The purpose of this report is to informyou of the approach and methodology for this analysis and to provide the results of ouranalysis.

The new patient lead time for the Division of Nephrology has been defined as the period oftime between the patient’s appointment date and the date when the patient called the hospitalto schedule the appointment. This scheduling is done by the Internal Medicine Schedulingdepartment at the University of Michigan Hospital

For each day that the Nephrology clinic operates there are four new patient slots availablefor use. Whenever there are doctors absent from the clinic, some of these new patient slotsare closed. The reason for this is to make sure the clinic does not become overburdened.The Nephrology clinic informs the Internal Medicine Scheduling department of theseclosings so that patients are not scheduled for those slots. These closings are usuallyscheduled one to two months in advance.

This project focuses only on new patients for the Division of Nepbrology and does notinclude patients who have previously been seen within the Division of Nephrology. Thereason for this is that return patients lead times are affected by the length of time the doctorspecifies before the next appointment, and this variation cannot be accounted for in thedata.

Approach and Methodology

The first step in analyzing the lead times was to obtain the data for new patient schedulingfrom the University of Michigan Hospital. This step was facilitated by Elizabeth Othman.The data was originally in a Microsoft Word document with the data fields delimited bycomma’s. We imported this document into Microsoft Excel using Excel’s built in features.The data fields included in this document were as follows:

• Patient last name• Patient first name

• Patient home address

• Status of patient appointment

• Date patient scheduled the appointment

• Date of the appointment

• Date appointment was canceled (if it was canceled)

• Resource code (doctor or department seeing the patient)

Next, we talked with Bonnie Welliver, RN Case Manager, at the NeDhroloEy clinic to seewhat she thought of the project and to get some ideas of what she might expect out of thisanalysis. It was discovered that she was in the process of collecting data to analyze thenew patient lead times. She provided us with this data, which included the number of newpatient slots closed for each day of operation.

The next step in analyñng the data was to eliminate the data not needed for this analysis.The Division of Nephrology was only interested in recent patient lead times so the dataprior to July 14, 1995 was eliminated. This date was selected as the cutoff point becausethat is when the Nephrology clinic started keeping uack of the number of new patient slotsclosed.

After narrowing the data down to the specified dates, the next step was to eliminate dataoutliers. The first step was to calculate the lead time for each patient. This was a simpleprocess using Excel to find the difference between the patient’s appoinunent date and thepatient’s scheduling date. After this was completed the average and standard deviation forlead time was calculated with Excel. After these calculations any patient lead times thatwere outside of three standard deviations was eliminated from our analysis.

Next, we decided to analyze the data in two formats. The first format was to analyze thelead times for the entire clinic. The second format was to analyze the lead times for eachindividual clinic day. The Nephrology clinic is open only on Monday, Tuesday,Wednesday, and Friday.

The lead times for the entire clinic were analyzed in the following ways:

• Monthly average lead time

• Appointment status conthbudon to lead time

• Weekly lead time Vs. new patient slots closed

The lead times for the individual clinic days were analyzed in the following ways:

• Number of new patient slots closed

• Slot utilization

• Overall averages

• Monthly averages

• Appointment status conu-ibudon to lead time

There are four appointment status types for the Nephrology clinic and they are as follows:

• No-show - Patient does not show up or call

• Cancel - Patient calls in and cancels appointment (even after the scheduled time)

• Re-scheduled - Patient calls in and reschedules their appointment

• Appointment Kept - Patient shows up for the appointment

Results

4

Entire clinic results

These results are for the analysis of the data for the overall clinic operations. They showhow well the clinic is operating overall. The overall monthly averages for the new patientlead time are shown below in Figure 1. It appeared that there was a change in new patientlead times at the beginning of October, so we calculated the overall average for the threemonths prior to October, and the five months after October. -

Figure 1. Overall monthly average lead times. The line shows the overall average for thethree months prior to October (16.7) and the five months after October (11.83).The total number of patients seen each month is shown in parenthesis.

The number of appointments scheduled each month is fairly stable as shown in Figure 2 onthe following page. The number of appointments with a lead time of less than one weekvaried a lot. fri October, the number of appointments with a lead time of less than oneweek reached a peak. After October the number of appointments with less than a one weeklead rime fell, but to the levels before October. Also the number of appointments with alead time of eater than three weeks fell in October.

This shows once again that something that occuned in October drove the lead time down,and after October the lead times went up, but not to the previous levels.

Monthly Averages fortient Lead Times

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Figure 2. Number of Appointments by month, broken down into the length of lead time.

The number of cancellations increased dramatically as the length of lead time increased.Figure 3 below shows that with a lead time of less than one week, 74% of patients keeptheir scheduled appointment. As lead time increases to greater than three weeks, only 50%of the patients keep their scheduled appointments.

The number of no-show patients is fairly constant at approximately 7% of the scheduledappointments. As lead time increases the number of cancellations increase. What thisshows is that the longer the lead time, the more lost business (no-shows + cancellations)

Figure 3. Percentage of each type of appointment status for the different lead timeintervals.

Number of Appointments Each Monthwith Lead Time Contributions

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Figure 4 below shows the percentage breakdown of the lead times for new patients.

Almost 40% of new patients have to wait more than two weeks to get an appointment. If

the Nephrology clinic wants to improve customer satisfaction and decrease the amount of

lost business they will have to decrease the percentage of patients that have to wait more

than two weeks for an appointment.

Figure 4. Percentage breakdown of new patient lead times.

Figure 5. The relationship between average lead time and number of new patient slot

closings by each week.

Distribution of Appointment Lead Times

30.43%32.98%

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The relationship between lead time and the number of new patient slots closed is shown inFigure 5 on the previous page. This is one of the key findings of our analysis. This graphshows that when the number of new patient slot closings goes up the average lead timegoes up for the week or two after that increase. The same holds nue for a decrease in thenew patient slot closings.

This result is important in that it explains the decrease in average lead time during October.Looldng at the number of new patient slot closings during September and October wenoticed that there were very few closings and during this time the average lead time fell.

Individual clinic day results

This section of the results is for the analysis of the data for the individual Nephrology clinicdays. The overall average for each clinic day is show in Figure 6 below. Tnis chart showsthat from July 1995 to February 1996 the overall average lead time was 13.8. It alsoshows that Monday and Tuesday clinic patients had to wait two to three days longer thanthe patients with appointments on Wednesday or Friday. One possible reason for this isthat patients would rather have their appointments early in the week. Also, Tuesday is theonly clinic day that has afternoon appointment slots for new patients.

Figure 6. Average Lead time for each clinic day for July 95 to February 96.

As was mentioned earlier, during October the overall average lead time dropped almost 2days. Because of this change we decided to see if there was a difference in the individualclinic days from October to February. Figure 7 on the following page shows that theaverage lead time for each clinic day also dropped almost two days. It also shows that the

Wednesday and Friday clinic days still have a significantly lower lead time than theMonday and Tuesday clinic days.

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Average Lead Time for each CHnic Day(Jul 95 - Feb 96)

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Figure 7. Average Lead time for each clinic day for October 95 to February 96.

After seeing the higher lead times for Monday and Tuesday we thought that maybe thereason behind the higher lead time was that there were fewer appoinents available onMonday and Tuesday. If Monday and Tuesday had more slots closed then the lead time toget appoinients on those days would be higher. Figure 8 below shows that the oppositeis true. Wednesday and Friday actually had more new patient slot closings, and thereforefewer available slots than Monday or Tuesday.

Figure 8. Total number of new patient slots closed for July 95 to February 96.

Average Lead Time for Each Clinic Day(Oct 95 - Feb 96)

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The next thing we looked at was how many of the available new paent slots were actuallyused for each clinic day. To determine the number of slots used we found the number ofpatients that kept their appointments and divided by the total number of slots available forscheduling. To determine the total number of slots available we took the four new padentslots for each day and mui.dplied by the number of days the clinic was open. After doingthat we subtacted the total number of new patient slot closings. Figure 9 below shows thatTuesday had the highest slot utilization. This is probably because the Tuesday slots arescheduled in the afternoon and it is easier for people to make it to an afternoonappointment.

Figure 9. Slot utilization for each clinic day.

Finally as a test of the lead time to get an appointment for the Nephrology clinic, we calledthe Internal Medicine scheduling desk and asked to set up an appointment. When werequested an afternoon appointment we were told that the soonest available appointmentwas 22 days from when we called. When we requested a morning appointment we weretold that the soonest available appointment was 12 days from when we called. This showsthat the actual lead me to get an appointment is fairly long and not just related to patientpreference.

Slot Utilization by Clinic Day

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Conclusions and Recommendations

The main conclusion from our analysis of the Nephrology clinic new patient lead time isthat the lead times is directly related to the number of slots the clinic closes. If the clinicwould like to reduce the new patient lead ti.mes,the most effective way may be to eliminatethe closings of new patient slots. As shown by Figure 5, the lead time in October droppedafter the number of closings in September and October was very low.

The second conclusion from our analysis is that the number of no—shows is constant, atabout 7%, and is not related to the lead time. Combined with the cancellation andrescheduling data, there is more than 30% of patients that don’t keep their scheduledappointments. With this in mind you can overbook the clinic, unless your resources arealready maximized with four new patient slots.

A third conclusion is that patients are more likely to keep an afternoon appointment. Basedon this fact, increasing the number of afternoon appointments would make the Nephrologyclinic more predictable. The data showed that the Tuesday clinic had a utilization of 81%.This means that of the scheduled appointments for Tuesday, 81% of the patients showedup for their appointments. Tuesday is the clinic day with afternoon appointments.

The final conclusion of our analysis is that there is a higher demand for Monday andTuesday appointments. If it is possible, increasing the number of slots available for use onMonday and Tuesday would help meet the patient demand better, thereby reducing leadtime and lost business.

Finally, throughout our analysis of the Nephrology clinic the charts that were most usefulin analyzing the data were:

• Number of appointments each month with lead time contributions (Figure 2)

• Average lead time by week vs. new patient slot closings by week (Figure 5)

Using these two charts to keep track, week by week, of lead time the clinic will be able tonotice any n-ends in the lead time. The first chart (Figure 2) will keep track of the lead timeconthbutions for total appointments. The second chart (Figure 5) will keep track of leadtime and new patient slot closings.

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