University of Michigan Health System

Program and Operations Analysis

Home Care Referral Process Analysis at

University of Michigan Hospitals and Health Centers

Final Report

To: Jean Shlafer, Ancillary Care Services & Discharge Planning Director

University of Michigan Hospital - Nursing Administration

300 North Ingalls St. #5A25

Ann Arbor, MI 48109

Email: jshlafer@med.umich.edu

Mandy McKay, Quality & Compliance Project Manager

University of Michigan Home Care Services

2705 South Industrial, Suite #300

Ann Arbor, MI 48104

Email: mandym@umich.edu

Mark Van Oyen, Ph.D., Industrial and Operations Engineering Associate Professor

University of Michigan College of Engineering - Industrial and Operations Engineering

1205 Beal Ave.

Ann Arbor, MI 48109

Email: vanoyen@umich.edu

From: Industrial and Operations Engineering (IOE) 481 Project Team #5

Trisha Bailey, Senior IOE Student

Brian Harris, Senior IOE Student

Katharine Herrgesell, Senior IOE Student

Date of Submission: December 15, 2010

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Table of Contents

Executive Summary ………………………………………………………………… 6

Introduction ………………………………………………………………………… 9

Background ………………………………………………………………………… 9

Key Issues ………………………………………………………………………….. 10

Goals and Objectives ………………………………………………………………. 11

Project Scope ………………………………………………………………………. 11

Project Methodology ……………………………………………………………….. 12

Interviews and Observations ……………………………………………….. 12

Frequency Tests ……………………………………………………………. 12

Ladder Logs ………………………………………………………………… 13

Data Analysis ………………………………………………………………. 13

Findings ……………………………………………………………………………. 13

Interviews and Observations ……………………………………………….. 13

Frequency Tests ……………………………………………………………. 15

Ladder Logs ………………………………………………………………… 21

Conclusions ………………………………………………………………………… 29

Extensive Time for the Home Care Referral Process ……………………… 29

High Frequency of Communications with Home Care Providers …………. 29

Increased Work Volume at the Beginning of the Week …………………… 31

Recommendations ………………………………………………………………….. 34

3

Expected Outcomes ………………………………………………………………… 35

Decreased Overall Referral Processing Time ……………………………… 36

More Efficient Communication with Home Care Providers ………………. 36

More Evenly Distributed Work throughout Week per Discharge Planner … 36

Support Provided By Operating Entities …………………………………………… 38

Acknowledgments ………………………………………………………………….. 38

Works Cited ………………………………………………………………………… 38

Appendix A: Frequency Test Data Collection Form ………………………………. 39

Appendix B: Ladder Log Test Data Collection Form ……………………………… 40

Appendix C: Ladder Log Test Patient Identification Form ………………………… 41

Appendix D: Frequency of Detailed Tasks by High Level Tasks …………………. 42

Appendix E: Frequency of Detailed Tasks by Clinical Service …………………… 44

Appendix F: Frequency of High Level Tasks by Day of Week and Clinical Service 49

Appendix G: Percentage of Detailed Tasks by Discharge Planner ………………… 54

Appendix H: Time for High Level Tasks by Day of Week and Clinical Service …. 68

Appendix I: Proportion of Time for High Level Tasks by Discharge Planner …….. 73

Appendix J: Percentage of Time Spent Multi-Tasking by Discharge Planner …….. 87

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List of Figures and Tables

Figure 1: Discharge Planning Home Care Referral Process, Current State ………… 10

Figure 2: Frequency of Home Care Work by High Level Tasks …………………… 15

Figure 3: Frequency of Home Care Work by Detailed Tasks, Top 80% …………… 16

Figure 4: Frequency of High Level Tasks by Interaction Method …………………. 17

Figure 5: Proportion of High Level Tasks by Clinical Services …………………… 18

Figure 6: Frequency of High Level Task by Day of Week ………………………… 19

Figure 7: Frequency of High Level Tasks by Time of Day ………………………… 20

Figure 8: Number of Discharge Planners who Frequently Perform Detailed Tasks . 21

Figure 9: Time for Home Care Work vs. Non-Home Care Work …………………. 22

Figure 10: Time for Home Care Work by High Level Tasks ……………………… 22

Figure 11: Time for Home Care Work by Detailed Tasks, Top 80% ……………… 23

Figure 12: Proportion of Time for High Level Tasks by Clinical Service ………… 24

Figure 13: Time for High Level Tasks by Day of Week …………………………… 24

Figure 14: Time for High Level Tasks by Discharge Planner ……………………… 25

Figure 15: Percent of Time for Multi-Tasking vs. Not Multi-Tasking …………….. 26

Figure 16: Total Time for Home Care Work per Patient …………………………… 26

Figure 17: Number of Patients per Referral Processing Time Interval ……………. 27

Figure 18: Average Time for Home Care Work per Patient by Clinical Service ….. 27

Figure 19: Average Number of Home Care Referrals per Patient by Clinical Service 28

Figure 20: Average Time for Home Care Work per Patient by Discharge Planner .. 28

Figure 21: Incomplete vs. Complete Electronic Referrals …………………………. 30

Figure 22: Initial Screens by Admit Day of Week ………………………………… 32

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Figure 23: Initial Screens Performed by Day of Week …………………………...... 33

Figure 24: Length of Stay based on Days from Admit to Initial Screen …………… 33

Table 1: Home Care Referral Tasks by High Level Tasks and Detailed Tasks …… 14

Table 2: Number of Communications per Referral between Discharge Planning and

Home Care Providers: University of Michigan Affiliated v. Non-

University of Michigan Affiliated ……………………………………….. 31

Table 3: Practice Management & Discharge Planning Average Number of Staff

Scheduled Per Day of Week ……………………………………………… 35

Table 4: Time Spent on Tasks to be Reallocated to Non-Clinical Staff …………… 37

Table 5: Time Gained by Reallocating Work ……………………………………… 37

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Executive Summary

Introduction

During an inpatient stay at University of Michigan Hospitals and Health Centers (UMHHC), all

patients are assessed for post discharge needs including home care services. When a need for

these services is identified, the Practice Management Coordinator (discharge planner) creates a

referral that is sent to home care providers. This referral process plays a critical role in the patient

transition from the hospital to home.

Prior to this project, the tasks necessary to complete home care referrals were undocumented and

were assumed to vary between the 57 clinical services (Bone Marrow Transplant, Pulmonary

Medicine, Orthopedic Surgery, etc.) and among discharge planners at UMHHC. In addition, the

time required to complete a home care referral was unknown. Therefore, the Director of

Ancillary Services asked Industrial and Operations Engineering (IOE) 481 Team 5 to:

Define the current state of the home care referral process.

Identify the tasks necessary to complete the process.

Identify and provide recommendations to improve the time required to perform home

care referral tasks.

Identify the value added tasks that require the clinical skill level of discharge planners.

Provide recommendations to improve the first time quality of each referral.

Identify the amount of wait time that discharge planners experience for home care

provider responses.

Provide recommendations to improve the efficiency of communications between the

discharge planners and home care providers.

Maintain the safety and provide recommendations to improve the efficiency of the

discharge process.

Project Methodology

The team completed the following qualitative and quantitative data collection methods to gain a

better understanding of the home care referral process.

Interviews and Observations

The team interviewed 15 discharge planners to gather information on the tasks involved in the

discharge planning home care referral process. In addition, the team observed seven discharge

planners as they completed their daily work to document the home care referral process tasks, as

well as tasks that hinder, interfere with or delay the process.

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Frequency Tests

The team created and distributed frequency tests to be completed by 27 discharge planners

representing the clinical services included in the project. For these tests, the discharge planners

were given a form with 27 predetermined tasks. Each time a discharge planner completed a task,

they were asked to put a tally mark under the corresponding hour that the task was performed.

The team conducted the tests for a five day period (November 8 - November 12, 2010) and

collected the completed forms at the end of each day. An example of the frequency test form can

be found in Appendix A.

Ladder Logs

The team also created and distributed ladder logs to be completed by the same 27 discharge

planners. During these tests, the discharge planners were asked to record the length of time they

spent on certain, high level tasks throughout the day. Additionally, the discharge planners were

asked to record the patient for which the task was being performed. These tests were also

administered over a five day period (November 15 - November 19, 2010) and were collected at

the end of each day. An example of a ladder log test data collection form can be seen in

Appendix B, and an example of a ladder log test patient identification form can be seen in

Appendix C.

Qualitative Findings

With the qualitative data from the interviews and observations of discharge planners, the team

identified the tasks of discharge planners in the home care referral process. With the tasks

identified, the team divided the high level tasks into four categories with detailed level tasks

acting as sub-categories.

In addition, the team identified there was variation in the information included in home care

referrals by discharge planner and clinical service. The team also identified the opportunities for

improvement that were believed to exist among discharge planners, including: the existence of

wait time for home care provider responses, the capacity for text viewing on the discharge

planners’ pagers, and the repetitive entry of information across the three separate computer

systems (MCCM, CareWeb, ECIN/Allscripts) required for the discharge planning process.

Quantitative Findings

After analyzing the data from both the frequency tests and the ladder logs, a few common

findings were frequently noted. The first finding was that discharge planners only spend about

15-18% of their home care related work on patient interaction. The majority of the work

discharge planners do related to home care is on information gathering and on creating the actual

referral. Further analysis of this trend shows that a select group of detailed tasks are among the

most frequent tasks performed. These tasks include Updating Careweb, Accessing Careweb, and

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Updating MCCM. These tasks not only occur often, but they are also very repetitive and do not

require the clinical skill level the discharge planners possess.

Another finding from the data was that the home care referral process workload for discharge

planners on Monday and Tuesday is higher than during the other days of the week and this

additional workload on Monday and Tuesday is mainly concentrated on Information Gathering

tasks.

Also, after reviewing the data to identify instances when discharge planners were performing

tasks simultaneously, the team found that discharge planners multi-task approximately 7% of the

time. Lastly, it was found that for 75% of all patients in the study, the time it takes for the home

care process to be completed per patient is less than one hour with the average being about 24

minutes per patient. This information helps give baseline data to the home care referral process,

which can then be improved upon in the future.

Recommendations

The team recommends that the Discharge Planning Practice Management department do the

following to improve the technology that aides discharge planners in the home care referral

process:

Reconfigure the three computer systems (CareWeb, ECIN, MCCM) currently in place to

be more user-friendly which will help decrease the overall referral processing time.

Equip Discharge Planners with portable, high-functioning tools such as iPads or

Blackberries in order to more efficiently communicate with home care providers.

Improve collaboration with home care providers through ECIN to build relationships that

will ensure a smooth transition of patients from hospital to home.

Hold collaborative training workshops for both discharge planners and home care

providers in order to identify the key elements necessary to complete a home care referral

which will help decrease the amount of back-and-forth communication that currently

exists between discharge planners and home care providers as well as the waiting

associated with provider response times.

The team also recommends that the administrative work currently performed by discharge

planners be reallocated to non-clinical staff. The administrative tasks performed by discharge

planners are below the clinical skill level of discharge planners and reallocating these tasks

would allow more time for discharge planners to spend on value added tasks such as patient

interactions. Finally, the team recommends an increase in the number of staffs working at the

beginning of the week to help distribute work for each discharge planner more evenly throughout

the week.

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Introduction

During an inpatient stay at University of Michigan Hospitals and Health Centers (UMHHC), all

patients are assessed for post discharge needs including home care services. When a need for

these services is identified, the Practice Management Coordinator (discharge planner) creates a

referral that is sent to home care providers. This referral process plays a critical role in the patient

transition from the hospital to home.

Prior to this project, the tasks necessary to complete home care referrals were undocumented and

were assumed to vary between the 57 clinical services (Bone Marrow Transplant, Pulmonary

Medicine, Orthopedic Surgery, etc.) and among discharge planners at UMHHC. In addition, the

time required to complete a home care referral was unknown. Therefore, the Director of

Ancillary Services asked Industrial and Operations Engineering (IOE) 481 Team 5 to:

Define the current state of the home care referral process.

Identify the tasks necessary to complete the process.

Identify and provide recommendations to improve the time required to perform home

care referral tasks.

Identify the value added tasks that require the clinical skill level of discharge planners.

Provide recommendations to improve the first time quality of each referral.

Identify the amount of wait time that discharge planners experience for home care

provider responses.

Provide recommendations to improve the efficiency of communications between the

discharge planners and home care providers.

Maintain the safety and provide recommendations to improve the efficiency of the

discharge process.

The primary goal for this project was to define the current state of the referral process and

provide recommendations to improve the efficiency of the time required to complete a home care

referral and place a patient with an appropriate home care provider, prior to the patient’s

discharge from the hospital. To accomplish this goal, the team collected data on the home care

referral process, analyzed the data to identify any waste within the process, determined

productivity gains attained by standardizing and centralizing the process, and recommended

improvements to the current process. The purpose of this report is to summarize the current state

of the home care referral process, explain the methodology the team used to complete the

project, and to present recommendations for improving the process.

Background

Discharge planning is the process of determining patients’ needs to ensure the transition from the

hospital to home is smooth for patients and their families. Discharge planners ensure these

transitions are safe and efficient, and may identify the need for home care services within a

patient’s planning process. According to the University of Michigan Health System (UMHS)

Practice Management Discharge Planning (PMDP) Performance Dashboard, in FY 2009,

UMHHC had a total of 43,186 acute care discharges, 40% of which required post-acute care

service, such as home medical equipment, home infusion therapy, or home nursing care.

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Discharging patients from the hospital and continuing their care through home care providers can

save costs, as well as generate needed inpatient space in the hospital. On average, UMHHC

operates at greater than 90% capacity, making timely discharge critical.

According to the University of Michigan Hospital (UMH) Practice Management Discharge

Planning Manager, the referral process begins when the discharge planner or patient’s physician

identifies a patient’s need for home care services. When this need is identified, the discharge

planner meets with the patient and the patient’s family to discuss the patient’s options, regarding

potential home care service providers. Following the meeting, the discharge planner creates a

referral in ECIN/Allscripts (a web based electronic referral application), contacts the home care

provider, and awaits approval from the provider. When the approval is received, the discharge

planner documents the patient’s plan in CareWeb (an electronic medical record), and the patient

is prepared for discharge. A flowchart of this process can be seen in Figure 1. Prior to this

project, the time to complete the entire home care referral process was unknown and was

believed to have high variability between clinical services. Additionally, the lack of a

standardized process and the occurrence of multiple waiting periods led to unpredictable process

lead times, which delayed patient discharge from the hospital.

Start

Determine

Patient’s Need

for Home Care

Services

Home Care

Need

Identified?

Meet with

Patient and

Family to

Discuss Home

Care Options

Create Home

Care Referral in

ECIN/Allscripts

Contact Home

Care Vendor(s)

Note Patient’s

Final Plan in

CareWeb

End

Patient

Accepts

Home Care

Services?

Approval

Received

from Home

Care Vendor?

YES

YES NO

YES

NO

NO

Figure 1: Discharge Planning Home Care Referral Process - Current State

Key Issues

The following key issues resulted in the need for this project:

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The current state of the home care referral process lacked baseline data for discharge

planners.

Clinical services were believed to have variable referral processing times.

Discharge planners were believed to have variable referral processing times. Discharge planners were believed to spend time on work associated with discharging that

does not require their clinical skill level, which prevents them from focusing on

additional patients with discharge needs (Source: Weekend Services Initiative, 2007). The year-to-date (YTD, October 2010) overtime expense for Discharge Planning is

$95,000 (Source: Datamart).

Goals and Objectives

The primary goal for the Home Care project was to define the current state of the home care

referral process and provide recommendations to improve the efficiency of the time required to

complete a home care referral and place a patient with an appropriate home care provider, prior

to the patient’s discharge from the hospital. The activities of the discharge planners were

observed and measured to determine the time spent on each task of the process, as well as the

frequency of occurrences for each task. To make appropriate recommendations to centralize and

standardize the process, the previously mentioned information was analyzed and stratified to

accomplish the following objectives:

Define the current state of the home care referral process.

Identify and provide recommendations to improve the efficiency of the time required to

perform home care referral tasks.

Identify the value added tasks that require the clinical skill level of discharge planners.

Provide recommendations to improve the first time quality of each referral.

Identify and provide recommendations to improve the efficiency of the time that

discharge planners experience for home care provider responses.

Provide recommendations to improve the efficiency of communications between the

discharge planners and home care providers.

Provide recommendations to improve the safety and efficiency of the discharge process.

Project Scope

The project scope included:

Discharge planning home care referral process tasks and the time required to perform the

tasks.

The home care referral process, which begins when the discharge planner or a physician

identifies a need for home care and concludes when the discharge planner documents the

patient’s final plan in CareWeb.

The following clinical services with a high volume of home care referrals (≥145 referrals

over 6 months, 10 services):

o Bone Marrow Transplant (BMT)

o Medicine Faculty Hospitalists (MFH)

o General Medicine (MGen)

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Medicine Dock - Internal Medicine (MDD)

Medicine Hewlett - Internal Medicine (MH)

Medicine Francis - Internal Medicine (MF)

Medicine Newburgh - Internal Medicine (MN)

Medicine Sturgis - Internal Medicine (MS)

o Medicine Pulmonary (MP)

o Surgery Orthopedic (SO)

o Pediatric Cardiology (PCar)

o General Pediatric (PGen)

o General Surgery (SGen)

o Surgery Thoracic Cardiac (STC)

o Surgery Urology Adult (SUA)

The project scope excluded:

Discharge planning tasks unrelated to the home care referral process.

Discharge planning tasks that occur prior to identifying a patient’s need for home care.

Discharge planning tasks that occur after the patient’s final plan has been documented in

CareWeb.

Clinical services with a low volume of home care referrals (<145 referrals over 6

months).

Project Methodology

The team used qualitative and quantitative data collection methods to gain a better understanding

of the home care referral process. Following the data collection, the team analyzed the data and

provided recommendations for improvements to the current state of the home care referral

process, including formulating strategies for the improvements.

Interviews and Observations

The team members interviewed 15 discharge planners, with at least one representative from each

of the clinical services indicated in the project scope. During the interviews, the discharge

planners explained their job and described the tasks in the home care referral process. The team

members documented the tasks involved in the process, as described by the discharge planners,

and the problems or barriers that were believed to exist.

Following the interviews, the team observed seven discharge planners as they completed their

daily work. During these observations, the team members documented home care referral

process tasks, as well as tasks that hinder, interfere with or delay the process. For these

observations, the team allocated at least two hours with each discharge planner.

Frequency Tests

To determine the frequency of the home care referral tasks, the team developed and distributed

frequency tests to be completed by 27 discharge planners representing the clinical services

13

included in the project. For these tests, the discharge planners were given a form with 27

predetermined tasks necessary to complete a home care referral. Each time the discharge

planners completed a task, they were asked to put a tally mark under the corresponding hour that

the task was performed. An example of the frequency test data collection form can be seen in

Appendix A. The team conducted the tests for a five day period (November 8 - November 12,

2010) and collected the completed forms at the end of each day. To account for any absences, the

personnel responsible for completing the work of the absent discharge planners were also

responsible for completing the frequency test forms. In total, 85 frequency test data collection

forms were collected and recorded into a Microsoft Access database for further analysis.

Ladder Logs

To determine the time for the home care referral tasks, the team developed and distributed ladder

logs to be completed by the 27 discharge planners representing the clinical services include in

the project. During these tests, the discharge planners were asked to record the length of time that

they spent on certain, high level tasks throughout the day. Additionally, the discharge planners

were asked to record the patient for which the task was being performed. An example of the

ladder log test data collection form can be seen in Appendix B, and an example of the ladder log

test patient identification form can be seen in Appendix C. These tests were also administered

over a five day period (November 15 - November 19, 2010) and were collected at the end of

each day. As with the frequency tests, the personnel responsible for completing the work of

absent discharge planners were also responsible for completing the ladder log forms. In total, 76

ladder log data test collection forms were collected and recorded into a Microsoft Access

database for further analysis.

Data Analysis

The team input the quantitative data collected from the frequency tests and ladder logs into a

Microsoft Access database and stratified the data by key variables to support the quantitative

conclusions. With this data analysis, the team identified opportunities for improvement to the

current state of the home referral process and formulated strategies to implement the

improvements.

Findings

The team analyzed the data from the methods described above and concluded the following:

Interviews and Observations

With the qualitative data from the interviews and observations of discharge planners, the team

identified the tasks of discharge planners in the home care referral process. With the tasks

identified, the team divided the high level tasks into four categories with detailed level tasks

acting as sub-categories. The task divisions can be seen in Table 1.

14

Table 1: Home Care Referral Tasks by High Level Tasks and Detailed Tasks

In addition, the team identified that there was variation in the information included in home care

referrals by discharge planner and clinical service. The team also identified the opportunities for

improvement that were believed to exist among discharge planners, including the existence of

wait time for home care provider responses, the capacity for text viewing on the discharge

planners’ pagers, and the repetitive entry of information across the three separate computer

systems (MCCM, CareWeb, ECIN/Allscripts) required for the discharge planning process.

15

Frequency Tests

The findings from the frequency tests showed the following about the current state of home care

process.

Figure 2: Frequency of Home Care Work by High Level Tasks (N=4,831 occurrences)

In Figure 2, the graph shows the percentage of the frequency of home care work by the high

level tasks. From the data presented in the graph, Patient Interaction has the lowest frequency of

home care work at 18%, whereas Administrative and Referral Creation have the highest

frequencies at 24% and 27%, respectively. It is important to recognize that the latter two tasks’

percentages are high considering not all of the tasks within these two categories need be

performed by someone with the clinical skill level of a discharge planner. Also, some of the tasks

in these two categories require duplicating work and entering the same information into different

computer systems multiple times. For both of these reasons, these two portions of the work

provide an opportunity for efficiency gains within the process.

16

Figure 3: Frequency of Home Care Work by Detailed Tasks, Top 80% (N=3,906 occurrences)

The above graph shows the frequency of home care work by the detailed level tasks. To attempt

to obtain results that affect the majority of the home care work, only the top 80% is shown. In

Figure 3, it should be noted that the top tasks involve Updating Careweb, Accessing Careweb,

and Updating MCCM. These tasks involve computer systems that are not used for the home care

referral creation, but are instead used to gather or store information on patients. Also, it is

important to notice that some of the other tasks within the top 80% include having the Physician

Sign Forms and having to enter Referral Follow Up information. Having physicians sign forms

is time consuming if the discharge planner must track down the physician in the hospital and if

the discharge planner must locate multiple doctors for multiple patient documents needing

signatures.

The task of entering referral follow up information is important because it relates to the concept

of first time quality. If the referral is sent to the home care provider correct and complete the first

time, or if the home care provider is easily able to locate needed information within the referral,

the frequency of these requests for additional information would be reduced.

With further analysis done, the detailed level tasks were organized by the high level task

categories they correlated to. These graphs can be seen in Appendix D. The Patient Interaction

tasks follow an expected trend, as the tasks with the highest and similar number frequencies are

needed for the majority of patients. The Administrative tasks graph shows that highest frequency

of the work performed in this category is on updating Careweb and MCCM, and on having

physicians sign forms. The Referral Creation graph shows that requests for Referral Follow Up

17

information are high for both clinical and non clinical information. Lastly, the Information

Gathering graph shows that Accessing Careweb and Insurance Assessment/Validation are both

among the most frequently performed tasks.

After analyzing the general frequency of the detailed tasks, the team analyzed the interaction

method that was used by the discharge planners to complete the tasks, meaning that the discharge

planner could have performed the work on the computer, on the phone, or face-to-face.

Figure 4: Frequency of High Level Tasks by Interaction Method (N=4,831 occurrences)

Figure 4 validates the perception that most Patient Interaction is done via face-to-face

communication, and most of the Administrative and Referral Creation work will be done on the

computer. It can be noted that the frequency of tasks on the computer is relatively high. Since

discharge planners are not always in front of a computer throughout the course of the day,

locating a computer to perform tasks at different times throughout the day can be disruptive to

the process flow. Lastly, it is interesting to see that Referral Creation has such a high frequency

of tasks completed on the phone. The amount of phone interaction is supposed to be minimized

with the implementation and use of the computer systems (ECIN/Allscripts, CareWeb).

Understanding there are times when work must be completed on the phone, this frequency is still

larger than expected.

The following graph breaks down the high level tasks between the clinical services. The clinical

services are organized with the highest frequencies of home care work on the left.

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Figure 5: Proportion of High Level Tasks by Clinical Services (N=4,831 occurrences)

Figure 5 shows that little or no variation exists in the proportion of tasks the different clinical

services complete. The low values for Patient Interaction and the high values for Information

Gathering also exist for each individual clinical service. The detailed level tasks are also broken

down by clinical service and filter the top 80% of tasks. These graphs can be found in Appendix

E. One similarity found across all services is that the tasks of Updating Careweb, Updating

MCCM, and Accessing Careweb are all present in the top 80% for each service. This shows that

these tasks are not specific to individual services.

19

Figure 6: Frequency of High Level Task by Day of Week (N=4,831 occurrences)

The results of the frequency tests were next stratified by clinical service and day of week in order

to examine the frequency of high level tasks throughout the week. Figure 6 shows the frequency

of the high level tasks by day of the week for all services combined. The proportions of each

high level task are approximately the same for each day of the week. However, it should be

noted that there are more Information Gathering tasks occurring on Mondays then on other days.

Discharge planners must do more Information Gathering on Mondays in order to process

patients that were admitted over the weekend and for any work that was not completed on

Friday. This data was also broken down further to analyze the frequency of high level tasks by

clinical service and by day of week, and this data can be found in Appendix F.

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Figure 7: Frequency of High Level Tasks by Time of Day (N=4,831 occurrences)

Taking this last stratification one step further, the data was broken down by the time of day for

the home care tasks seen in Figure 7. As shown, discharge planners perform a majority of the

tasks related to home care referrals during the middle of the day. From the team’s observations,

most discharge planners meet with their teams and with patients in the morning. For the most

part, these meetings take a longer amount of time than other tasks which could explain why the

occurrences are less frequent in the mornings. In addition, most discharge planners’ return to

their office between 10:00am and noon and perform tasks on the computer or on the phone.

These tasks are generally shorter than the morning tasks explaining the higher frequencies of

tasks at these times.

The graph also shows that the proportion of tasks seems to be spent on Information Gathering in

the morning and on Administrative and Referral Creation in the afternoon. This depicts that

discharge planners gather information they need for referrals in the morning and then complete

any paperwork utilizing that information in the afternoon.

The last stratification for the frequency tests compares the work of the individual discharge

planners. A table of each discharge planner and the tasks they complete can be found in

Appendix G. Within these tables, the top 80% is highlighted; representing which tasks the

discharge planners do most often. To summarize this data, the tasks that fell within this 80% for

each discharge planner were recorded.

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Figure 8: Number of Discharge Planners who Frequently Perform Detailed Tasks

(N=27 discharge planners)

Figure 8 shows the amount of discharge planners that performed the detailed tasks in the top

80% of their work. For example, 25 of the 27 discharge planners who collected data perform the

Accessing Careweb task frequently. This graph confirms the previous findings that a high

frequency of tasks are performed on the two different systems, Careweb and MCCM, therefore,

the previous findings were not skewed by a high occurrence rate of just one of the discharge

planners, but is consistent from discharge planner to discharge planner.

Ladder Logs

Similarly to the frequency tests, the general proportion of time spent on different tasks was first

analyzed for the ladder log tests. The first graph, in Figure 9 below, shows the proportion of time

that discharge planners spend completing Home Care Related work. This graph is important in

understanding the current state of discharge planning and realizing how much of their work is

Home Care related. The 35% of Home Care Related work can then be broken down further to

analyze the proportion of time spent on the high level tasks.

22

Figure 9: Time for Home Care Work vs. Non-Home Care Work (N=36,000 minutes)

Figure 10: Time for Home Care Work by High Level Tasks (N=12,607 minutes)

Figure 10 shows similar results to those found in the frequency tests. Once again Patient

Interaction has the smallest proportion of time, 15%, while Referral Creation and Administrative

have higher proportions, 24% and 30% respectively. It can now be hypothesized that the time

spent on different tasks is proportional to the frequency that those tasks occur.

Using these proportions of time of the high level tasks and the frequency of the detailed tasks,

the team was able to approximate the time spent on the detailed tasks. The top 80% of detailed

23

tasks is shown in Figure 11. As with the frequency tests, the detailed tasks with the highest times

for the ladder log tests are Updating Careweb, Updating MCCM, and Accessing Careweb. Also,

like before, Referral Follow Up and Having Physicians Sign Forms are two of the top tasks.

Figure 11: Time for Home Care Work by Detailed Tasks, Top 80% (N=10,121 minutes)

Similar to the frequency tests, the first stratification to the ladder logs will be by clinical service

in order to examine the proportion of time spent on high level tasks.

24

Figure 12: Proportion of Time for High Level Tasks by Clinical Service (N=12,607 minutes)

Figure 12 shows the proportion of time spent on each of the high level tasks for each of the ten

clinical services. The proportion of time spent on each of the high level tasks is approximately

equal across all ten services. It is important to note that each of the ten services spends the

smallest proportion of their time on Patient Interaction tasks. Also it is important to note the

large Information Gathering times that exist across all services.

Figure 13: Time for High Level Tasks by Day of Week (N=12,607 minutes)

25

The ladder logs were next stratified by both clinical service and day of the week. Figure 13

shows the amount of time spent on each of high level tasks by day of the week. The proportion

of time spent on each of the high level tasks is approximately equal on each day of the week. The

discharge planners spend the least amount of their home care related work time on Patient

Interaction tasks. Also, the amount of time discharge planners spend on Tuesday on home care

work is higher than the other days. When compared with the results from the frequency test

stratification by day of the week, it is seen that Monday and Tuesday have the higher volume of

home care related work. The results showing the amount of time spent on high level tasks by day

of the week for each of the clinical services are shown in Appendix H.

Figure 14: Time for High Level Tasks by Discharge Planner (N=27 discharge planners)

Figure 14 shows the total time that each discharge planner spends on home care work. Once

again, it can be seen that the Patient Interaction is relatively low across all discharge planners.

Also, the Information Gathering for certain discharge planners is high comparatively to others.

For a more detailed breakdown of each discharge planner, refer to Appendix I.

26

Figure 15: Percent of Time for Multi-Tasking vs. Not Multi-Tasking (N=12,607 minutes)

Figure 15 shows the percentage of time discharge planners were multi-tasking. Multi-tasking

increases the chance for making errors and can reduce the efficiency of work that is done. 7% is

a percentage for multi-tasking that presents an opportunity for improvement regarding the quality

of the process. An analysis of multi-tasking by discharge planner was also performed and the

results can be found in Appendix J.

The graph in Figure 16 shows all patients in need of home care services during the data

collection period and the total time it took discharge planners to complete the home care referral

work. For 75% of the patients, the average time spent was 23.9 minutes with a standard deviation

of 15.2 minutes. These times are useful in establishing a baseline for the current state of the

home care referral processing time.

Figure 16: Total Time for Home Care Work per Patient (N=235 patients)

27

Figure 17: Number of Patients per Referral Processing Time Interval (N=235 patients)

Figure 17 is another way to view the same data. In this graph it is clear to see that for 75% of

patients, the home care processing times are less than 1 hour.

The graph in Figure 18 shows the average home care processing time per patient stratified by

clinical service. It is clear that some clinical services, such as Bone Marrow Transplant, have

longer processing times.

Figure 18: Average Time for Home Care Work per Patient by Clinical Service (N=235 patients)

28

For some services, however, there may be a correlation between the number of required referrals

and the time it takes to complete a patient’s work. For instance, if a patient needs both home

infusion and skilled nursing, then that patient would require two separate referrals. Figure 19

below shows the average number of referrals needed for patients by clinical service. From this

graph, a connection can be made between the processing time for BMT patients and the number

of referrals that are usually needed.

Figure 19: Average Number of Home Care Referrals per Patient by Clinical Service

(N=39 patients)

Figure 20: Average Time for Home Care Work per Patient by Discharge Planner (N=235 patients)

29

The final graph in this section is shown in Figure 20. It shows the average time per patient

stratified by discharge planner. Most of the discharge planners maintain an average time that is

below the 1 hour mark that represented 75% of the patients.

Conclusions

After examining the results from the data analysis, the team was able to develop the following

conclusions:

There is extensive time spent during the home care referral process.

There is a high frequency of communications between discharge planners and home care

providers.

There is an increase in work volume in the beginning of the week.

Extensive Time for the Home Care Referral Process

The results from the team’s data analysis indicated that extensive time is spent during the home

care referral process. As seen in the findings section, 75% of patients have a referral processing

time that is under 1 hour; however there are still points during the process where better use of

time can occur. As discussed earlier, there is a high amount of work discharge planners do that is

below their clinical skill level. Also, the amount of tasks that cause disruptions for the discharge

planners are high (i.e. entering data duplicate times).

High Frequency of Communications with Home Care Providers

After the initial interviews with 15 of the discharge planners, the team noted that many discharge

planners reported frequent back-and-forth communication with home care providers. These

communications were often regarding details of the referral or the patient’s needs that was either

left blank or needed clarification in the initial referral. Many discharge planners reported that

home care providers often requested a piece of information that was already included in the

referral. It appeared to the discharge planners that the home care providers didn’t know where to

look within the referral for needed information.

During observations, the team confirmed that frequent communication occurred. This frequent

back-and-forth communication often occurred when a patient’s home care needs changed or if

there were difficulties obtaining insurance verification or approval. However, the team also noted

that frequent communication occurred when key elements of the home care referral were

missing. The discharge planners appear to play a “guessing game” when trying to determine

which elements of the referral are necessary to include for the home care provider. This

“guessing game” is played for a variety of different reasons. Often, discharge planners have

30

processed similar referrals in the past and believe to know which pieces of information are

necessary. Sometimes, discharge planners will leave out some of these key elements if they

create the referral before some information is known (i.e. date of discharge is unknown).

Using data collected from the IOE 481 Winter 2010 University of Michigan Home Care Services

Intake Workload Project, the team was able to examine the number of electronic referrals that

were determined to be incomplete after the first pass. As shown in Figure 21, 47% of electronic

referrals that were sent to home care providers were incomplete. Incomplete referrals require the

need for additional communication between home care providers and discharge planners.

Figure 21: Incomplete vs. Complete Electronic Referrals (N=133 referrals)

After collecting and analyzing the data from the frequency test and ladder log tests, the team was

able to see that a high frequency of communication with home care providers existed. As

mentioned earlier, Referral Follow Up for both clinical and non-clinical information was a

frequently occurring task.

The team also examined the number of communications per referral between discharge planners

and home care providers. These results are shown in Table 2. The response times in Table 2

include all communications, not just the initial response after sending the referral. As seen in the

table, the average number of back-and-forth communications is 5.9 and the average total

provider response time is 58.1 minutes. These communications can be caused by a variety of

reasons including incomplete referrals or the needs of the patient being changed. However,

regardless of the reason for the communication, frequent communication is occuring, which

31

includes waiting for provider responses which in turn leads to long home care referral process

times.

Table 2: Number of Communications per Referral between Discharge Planning and Home Care

Providers: University of Michigan Affiliated v. Non-University of Michigan Affiliated

(N=24 referrals)

Increased Work Volume at the Beginning of the Week

The results from the team’s data analysis indicate that there is an increased work volume for the

home care referral process occurring in the beginning of the week. As seen in the findings

section, the frequency and proportion of time spent on information gathering tasks is greater on

Mondays and Tuesdays.

The team looked at data from the 2007 Weekend Services Initiative conducted by Kate Bombach

at the University of Michigan Hospitals and Health Centers to help better understand the

increased workload in the beginning of the week. When a patient is admitted to the University of

Michigan hospital, an initial screen is administered by a discharge planner. Often when a patient

is admitted to the hospital at the end of the week, the initial screen is not performed within 24

hours of the patient being admitted. Figure 22 shows the number of patients admitted, who had

an initial screen performed after 24 hours of being admitted to the hospital, by day of week.

32

Figure 22: Initial Screens by Admit Day of Week (N=3,881 patients)

As seen in the figure, the highest number of patients receiving initial screens after 24 hours of

being admitted to the hospital occurs on Friday and Saturday. These patients who are admitted

on Friday or Saturday and don’t have initial screens performed within 24 hours of being

admitted, then need to have an initial screen performed in the beginning of the week. Figure 23

shows the number of initial screens performed by day of week. The figure shows that the highest

number of initial screens occurs on Mondays. This high number of initial screens needing to be

performed relates directly to the increased workload for discharge planners in the beginning of

the week.

33

Figure 23: Initial Screens Performed by Day of Week (N= 9,617 patients)

In addition to an increased workload for the discharge planners, the high number of patients who

receive an initial screen after 24 hours also leads to an increased length of stay. Figure 24 shows

length of stay based on how many days it took from admittance to the initial screen. As seen in

the figure, the length of stay for a patient increases as the number of days between the admittance

and initial screen increases.

Figure 24: Length of Stay based on Days from Admit to Initial Screen (N=3,881 patients)

34

Recommendations

The following are the team’s recommendations for process improvements for the home care

referral process. It has been communicated that the future state of discharge planning will

include a centralized intake process for managing home care referrals. This process plans to align

work with the appropriate resources, improve the length of stay for patients requiring home care

services, and improve the quality and efficiency of patient discharges. However, before this

process can be implemented there are improvements that must be made to ensure an efficient and

successful transition.

The team recommends that improvements in the technology that aide discharge planners be

made. Currently, there are three different computer systems (CareWeb, ECIN, and MCCM) that

are used in completing the home care referral process. During the team’s interviews and

observations of the discharge planners, it was noted that repetitive information entry occurs in

the different computer systems. It was also noted that Update Careweb, Accessing Careweb, and

Update MCCM were the three most frequently occurring tasks of discharge planners. Therefore,

the team recommends that these computer systems be reconfigured to be more user-friendly.

Auto-populate and auto-transfer options linking the three computer systems should be considered

to reduce the amount of repetitive information entry as well as the time associated with those

repetitive entries. The team also recommends that reducing the number of total computer systems

used in the home care referral process be considered.

It was also noted in the data analysis process, as well as the conclusions section of this report,

that there is a high frequency of communication between discharge planners and home care

providers. During the team’s interviews and observations of discharge planners, the team noted

issues regarding the pagers currently used to receive notifications of communication from home

care providers. When a home care provider sends any sort of communication regarding the home

care referral, discharge planners receive a page on their pagers. However, these pagers are

limited to viewing 160 text characters and often a significant amount of these 160 characters are

used up by timestamp information. If discharge planners are unable to read the entirety of the

message sent, they must log on to the nearest computer to read the rest of the message. If a

discharge planner is attending to patients or not at their desk, this lack of capacity can slow down

their response time, which in turn leads to a longer overall processing time. Therefore, the team

recommends equipping discharge planners with portable high-function tools such as iPads,

Blackberries, or iPhones. These tools will allow discharge planners to read an entire message

sent by a home care provider without having to locate and log in to the closest computer. All of

these portable high-functioning tools have internet capabilities and have the potential to be used

by discharge planners to respond back to home care providers.

Collaboration with home care providers also must be improved. The team recommends

conducting collaborative training workshops between discharge planners and home care

35

providers where the key elements of referrals are identified. Creation of templates for categories

such as patient type or insurance provider should be considered to help ensure that key referral

elements are included. Reformatting home care referrals in an ordered fashion to provide easier

identification of necessary information should also be considered. The need for timely responses

to home care providers should be emphasized. The team recommends establishing a position for

monitoring communication between discharge planners and home care providers as well as

response times. These recommendations will help decrease the amount of back-and-forth

communications between discharge planners and home care providers, which should also

decrease the time spent waiting for provider responses.

Certain administrative work performed by discharge planners has been identified to be below

their clinical skill level and can be reallocated to administrative staff. Reallocation of

administrative tasks will provide more time for discharge planners to spend on patient

interaction.

Finally, the team recommends increasing the number of staff working at the beginning of week

to help process the work that accumulates at the end of the week and over the weekend. The

current staffing levels are shown in Table 3.

Table 3: Practice Management & Discharge Planning Average Number of Staff Scheduled Per

Day of Week

Expected Outcomes

If the team’s recommendations are implemented, the following outcomes are expected:

Decreased overall referral processing time.

More efficient communication with home care providers.

More evenly distributed work throughout week per discharge planner.

36

Decreased overtime hours and associated expenses.

Decreased Overall Referral Processing Time

By implementing the team’s recommendations regarding improving the technology in the home

care referral process, discharge planners can expect to see a decreased overall referral processing

time. Reconfiguring the computer systems to be more user-friendly and using auto-populate or

auto-transfer options to link the three computer systems will reduce the amount of repetitive

entries by discharge planners. Decreasing the overall referral processing time will increase the

amount of time discharge planners have to spend on patient interaction. It will also free up more

time in their day to perform more initial screens for patients being admitted to the hospital.

More Efficient Communication with Home Care Providers

Improved collaboration with home care providers will allow for better communication between

discharge planners and home care providers. By equipping discharge planners with portable tools

such as iPads or Blackberries, discharge planners will be able to read messages in their entirety

and respond in a timely fashion. This will reduce response time to home care providers by

eliminating the need for discharge planners to find and log onto a computer to respond.

Working with home care providers to identify key referral elements will help improve the first

time quality of referrals. In turn, improved first time quality will help decrease the frequency of

back-and-forth communication and minimize the frequency of referral follow up requests.

Improvements in the efficiency of communication with home care providers will allow for more

timely patient discharge which results in decreased time spent on home care work per patient.

More Evenly Distributed Work throughout Week per Discharge Planner

Reallocating administrative work to non-clinical staff as well as increasing the number of staff

working at the beginning of the week will allow for a more evenly distributed workload for each

discharge planner. The team identified tasks that do not require the clinical skill level of

discharge planners and examined the impact of reallocating these tasks to non-clinical staff.

Table 4 shows the time spent on tasks that could be reallocated to non-clinical staff.

37

Table 4: Time Spent on Tasks that were Identified to be Reallocated to Non-Clinical Staff

As seen in Table 4, 3,922 minutes were recorded on these tasks over a one week period by ten

clinical services. A total of 12,607 minutes of work was recorded which corresponds to 210.117

hours or 5.253 full time equivalents (FTE’s). Table 5 shows the time gained by reallocating the

tasks in Table 4.

Table 5: Time Gained by Reallocating Work

As shown in Table 5, by reallocating those tasks to that are below the clinical skill level of

discharge planners to non-clinical staff, the tasks left to be performed by discharge planners

require 8,685 minutes which is equivalent to 3.619 FTE’s. This reallocation of tasks allows for a

gain in 1.6 FTE’s to perform value added work.

38

Support Provided By Operating Entities

The Director of Ancillary Care Services and Discharge Planning, the project client, provided

details of the home care referral process, staff contact information, and assistance in attaining

cooperation from the discharge planning staff.

The Home Care Services Quality and Compliance Project Manager, the project coordinator,

acted as a mentor and advisor to the project team. She helped maintain analytical quality and

positive relationships between the project team, the client, and the discharge planning staff. She

provided the team with previously collected data and research that was relevant to the project, as

well as tools that assisted the team in data collection. In addition, the project coordinator gave the

team feedback on the project progress and helped the team to develop their professional skills.

Acknowledgments

The team would like to thank the following people for all of their hard work and contribution to

the project:

Jean Shlafer, Director - Ancillary Care Services and Discharge Planning

Mandy McKay, Project Manager - Home Care Services Quality and Compliance

Amanda Mezger, Supervisor - Clinical Nursing and UMH Practice Management

Discharge Planning

Priscilla Mazurek, Manager - Clinical Nursing and UMH Practice Management

Discharge Planning

University of Michigan Hospital Practice Management and Discharge Planning Staff

Mark Van Oyen Ph.D., Associate Professor - Industrial and Operations Engineering 481

Austin Chrzanowski, Graduate Student Instructor - Industrial and Operations Engineering

481

Mary Lind, Lecturer in Technical Communication - UM College of Engineering

The support, technical expertise and practical advice of these people were integral to the

progression of the project and helped it to succeed.

Works Cited

Bombach, Kate. Weekend Services Initiative. University of Michigan Hospitals and Health

Centers, 2007.

Gutting, Andrew, Jing Ma, Nikita Vardya, and Ilir Xholi. Analysis of the Central Intake Process

at University of Michigan Home Care Services. University of Michigan Health System, 23 April,

2010.

39

Appendix A: Frequency Test Data Collection Form

Part 1: PMPD Frequency Study Staff Member Name: Department/Service: Date: Are you a Float today? Yes No

With any questions, contact mandym@umich.edu (734-975-7488), briansh@umich.edu, trishann@umich.edu, klherrge@umich.edu

Tasks: 7:00-8:00 AM 8:00-9:00 AM 9:00-10:00 AM 10:00-11:00 AM 11:00-12:00 PM 12:00-1:00 PM 1:00-2:00 PM 2:00-3:00 PM 3:00-4:00 PM 4:00-5:00 PM

Patient/Family Interaction

Home Care Need Identified / Initial Visit

Discuss Vendor Preference

Gather/Verify Patient Info (Address, Phone #, etc.)

Discuss Discharge Plan Status w/ Patient/Family

Discuss Final Discharge Plan w/ Patient/Family

Perform Caregiver Assessment (Home support?)

Patient Refused Home Care

Unable to see Patient/Family

Assessment/Information Gathering

(Not Patient/Family Interaction)

Home Care Need Identified

Team Meetings

Physician Interaction

Other Team Member Interaction

Insurance Assessment/Validation

Accessing Careweb to Gather Patient Information

Referral Creation

Update Facesheet

Search for Recipients/Vendors

Send Referral (First Time)

Resend Referral to Different Vendor(s)

Fill Out Configurables Sections

Referral Follow Up-Add Non Clinical Information

Referral Follow Up-Add Clinical Information

Referral Rejected (For Any Reason)

Paperwork/Administrative Work

Fill Out LOC Form

Have Physician Sign LOC Form

Fax Attach Forms to ECIN

Update MCCM with Patient Status

Update Careweb with Patient Status

Start Shift Time: ___________ Lunch: __________ - ___________ End Shift Time: ___________

Do you have additional coverage today? Yes No

Directions: Begin marking tasks once home care need is identified. Included tasks are those only related to Home Infusion, DME, or Home Health Care need patients.

1) Upon completion of a listed task, put a single tick mark next to that task for the current block of time under the correct "On Phone", "On Computer", or "Face to Face" category, every time it is performed within the hour. 2) If you complete a task that relates to home care referral but is not listed please put it in the blank spots provided.

40

Appendix B: Ladder Log Test Data Collection Form

Name: Date: Shift Start Time: Shift End Time:

P#Multi

P#P#

Multi

P#P#

Multi

P#P#

Multi

P#

7:00 00 10:00 00 1:00 00 4:00 00

02 02 02 02

04 04 04 04

06 06 06 06

08 08 08 08

7:10 10 10:10 10 1:10 10 4:10 10

12 12 12 12

14 14 14 14

16 16 16 16

18 18 18 18

7:20 20 10:20 20 1:20 20 4:20 20

22 22 22 22

24 24 24 24

26 26 26 26

28 28 28 28

7:30 30 10:30 30 1:30 30 4:30 30

32 32 32 32

34 34 34 34

36 36 36 36

38 38 38 38

7:40 40 10:40 40 1:40 40 4:40 40

42 42 42 42

44 44 44 44

46 46 46 46

48 48 48 48

7:50 50 10:50 50 1:50 50 4:50 50

52 52 52 52

54 54 54 54

56 56 56 56

58 58 58 58

60 60 60 60

8:00 0 11:00 0 2:00 0 5:00 0

2 2 2 2

4 4 4 4

6 6 6 6

8 8 8 8

8:10 10 11:10 10 2:10 10 5:10 10

12 12 12 12

14 14 14 14

16 16 16 16

18 18 18 18

8:20 20 11:20 20 2:20 20 5:20 20

22 22 22 22

24 24 24 24

26 26 26 26

28 28 28 28

8:30 30 11:30 30 2:30 30 5:30 30

32 32 32 32

34 34 34 34

36 36 36 36

38 38 38 38

8:40 40 11:40 40 2:40 40 5:40 40

42 42 42 42

44 44 44 44

46 46 46 46

48 48 48 48

8:50 50 11:50 50 2:50 50 5:50 50

52 52 52 52

54 54 54 54

56 56 56 56

58 58 58 58

60 60 60 60

9:00 0 12:00 0 3:00 0 6:00 0

2 2 2 2

4 4 4 4

6 6 6 6

8 8 8 8

9:10 10 12:10 10 3:10 10 6:10 10

12 12 12 12

14 14 14 14

16 16 16 16

18 18 18 18

9:20 20 12:20 20 3:20 20 6:20 20

22 22 22 22

24 24 24 24

26 26 26 26

28 28 28 28

9:30 30 12:30 30 3:30 30 6:30 30

32 32 32 32

34 34 34 34

36 36 36 36

38 38 38 38

9:40 40 12:40 40 3:40 40 6:40 40

42 42 42 42

44 44 44 44

46 46 46 46

48 48 48 48

9:50 50 12:50 50 3:50 50 6:50 50

52 52 52 52

54 54 54 54

56 56 56 56

58 58 58 58

60 60 60 60

10:00 0 1:00 0 4:00 0 7:00 0

Task

Type

Multi-

Task

Type

Task

Type

Multi-

Task

Type

Task

Type

Multi-

Task

Type

Task

Type

Multi-

Task

Type

Ladder Log: Task Time Data Collection SheetWith any questions, contact mandym@umich.edu (734-975-7488), briansh@umich.edu, trishann@umich.edu, klherrge@umich.edu

Time Time Time Time

Directions: Begin marking tasks and patients once home care need is identified. Included tasks are those only related to Home

Infusion, DME, or Home Health Care need patients.

Are you a float today?: Yes No Do you have additional coverage today? Yes No

41

Appendix C: Ladder Log Test Patient Identification Form

Patient Info:

Ex.

P1

P2

P3

P4

P5

P6

P7

P8

P9

P10

P11

P12

P13

P14

P15

P16

P17

P18

P19

P20

P21

P22

P23

P24

P25

P26

P27

P28

P29

P30

P31

P32

P33

P34

P35

P36

P37

P38

P39

P40

P41

P42

P43

P44

P45

P46

P47

P48

P49

P50

Example:

P#Multi

P#

7:00 00

02

04

06

08

7:10 10

12

14 P1

16

18

7:20 20

22

24

26

28

7:30 30

X 1 minutes or less InterruptionInterruptions - Mark an X at the time you experience a minute or less interuption during your current task

T4

Instructions For Using This Ladder Log:

Date of Discharge11/20/2010

This Log is intended to show when and how long it takes to perform tasks related to patients needing

some type of home care service for specific patients. On the sheet you will see 2 major columns, 1 for

the task length, 1 for the patient number.

Date Home Care Need IdentifiedPatient Name/Identifier11/16/2010Susan B. Anthony

P# Patient Number - to track the time spent on work performed for the same patient

Home Care Service Need(s)Infusion and Home Nursing

Patient/Family Interaction - Initial Visit, Discussing vendor preference, Gathering/verifying personal

information (address, phone number, living arrangements, etc., Informing patient/family of status of D/C

plan, Informing patient of final D/C plan, Unable to see patient/family (Patient getting tests, Family not

there, etc)

T1

Information Gathering (No patient/family interaction) - Team meetings, Physician interaction,

Other team member interaction, Accessing Careweb to gather patient information.T2

Referral Creation - Update facesheet, Search for recipients/vendors, Send referral (first time),

Resend referral to different vendor(s), Fill out configurables sections, Referral follow up-add non clinical

information, Referral follow up- add clinical information, Referral Rejected (For Any Reason) P3T1 X

P2T2

T2

T3

Paperwork/Administrative Work - Fill out LOC form, Have physician sign LOC form, Fax attach

forms to ECIN, Check with nurses and other team members that discharge needs are known, Update

MCCM with patient status, Update CareWeb with patient status

P1

T4

TimeTask

Type

Multi-Task

Type

T1 P1

This is a patient log to assist you in tracking your patients. Only mark the name of the patient on one line. This will be their number (P#) on the log each time you

perform a task for that patient (i.e. you could create multiple referrals for the same patient.)

Keeping Track of Patients:

42

Appendix D: Frequency of Detailed Tasks by High Level Tasks

Figure D.1: Frequency of Detailed Patient Interaction Tasks (N=866 occurrences)

Figure D.2: Frequency of Detailed Administrative Tasks (N=1,508 occurrences)

43

Figure D.3: Frequency of Referral Creation Tasks (N=951 occurrences)

Figure D.4: Frequency of Detailed Information Gathering Tasks (N=1,506 occurrences)

44

Appendix E: Frequency of Detailed Tasks by Clinical Service

Figure E.1: Frequency of Detailed Tasks for BMT (N=587 occurrences)

Figure E.2: Frequency of Detailed Tasks for SUA (N=529 occurrences)

45

Figure E.3: Frequency of Detailed Tasks for MFH (N=577 occurrences)

Figure E.4: Frequency of Detailed Tasks for STC (N=577 occurrences)

46

Figure E.5: Frequency of Detailed Tasks for PGEN (N=618 occurrences)

Figure E.6: Frequency of Detailed Tasks for PCAR (N=265 occurrences)

47

Figure E.7: Frequency of Detailed Tasks for MGEN (N=469 occurrences)

Figure E.8: Frequency of Detailed Tasks for SGEN (N=544 occurrences)

48

Figure E.9: Frequency of Detailed Tasks for SO (N=462 occurrences)

Figure E.10: Frequency of Detailed Tasks for MP (N=203 occurrences)

49

Appendix F: Frequency of High Level Tasks by Day of Week and Clinical

Service

Figure F.1: Frequency of High Level Tasks by Day of Week for BMT (N=587 occurrences)

Figure F.2: Frequency of High Level Tasks by Day of Week for SUA (N=529 occurrences)

50

Figure F.3: Frequency of High Level Tasks by Day of Week for MFH (N=577 occurrences)

Figure F.4: Frequency of High Level Tasks by Day of Week for STC (N=577 occurrences)

51

Figure F.5: Frequency of High Level Tasks by Day of Week for PGEN

(N=618 occurrences)

Figure F.6: Frequency of High Level Tasks by Day of Week for PCAR

(N=265 occurrences)

52

Figure F.7: Frequency of High Level Tasks by Day of Week for MGEN (N=469 occurrences)

Figure F.8: Frequency of High Level Tasks by Day of Week for SGEN

(N=544 occurrences)

53

Figure F.9: Frequency of High Level Tasks by Day of Week for SO (N=462 occurrences)

Figure F.10: Frequency of High Level Tasks by Day of Week for MP (N=203 occurrences)

54

Appendix G: Percentage of Detailed Tasks by Discharge Planner

Table G.1: Frequency of Detailed Tasks for Alison Wilson (N=180 occurrences)

Table G.2: Frequency of Detailed Tasks for Andrea Stec (N=163 occurrences)

55

Table G.3: Frequency of Detailed Tasks for Ann Dowling (N=254 occurrences)

Table G.4: Frequency of Detailed Tasks for Anna Silvenis (N=254 occurrences)

56

Table G.5: Frequency of Detailed Tasks for Brian Kobylarz (N=315 occurrences)

Table G.6: Frequency of Detailed Tasks for Deb Sgroi (N=50 occurrences)

57

Table G.7: Frequency of Detailed Tasks for Deb Stoll (N=110 occurrences)

Table G.8: Frequency of Detailed Tasks for Denice Raciti (N=95 occurrences)

58

Table G.9: Frequency of Detailed Tasks for Diane Noack (N=126 occurrences)

Table G.10: Frequency of Detailed Tasks for Elizabeth Stevens (N=265 occurrences)

59

Table G.11: Frequency of Detailed Tasks for Gina Bergmoore (N=116 occurrences)

Table G.12: Frequency of Detailed Tasks for Jane Antosiak (N=70 occurrences)

60

Table G.13: Frequency of Detailed Tasks for Judy Benkesser (N=54 occurrences)

Table G.14: Frequency of Detailed Tasks for Karen LaRue (N=209 occurrences)

61

Table G.15: Frequency of Detailed Tasks for Kathleen Baker (N=433 occurrences)

Table G.16: Frequency of Detailed Tasks for Kathy Soloy (N=287 occurrences)

62

Table G.17: Frequency of Detailed Tasks for Kelly Krawcke (N=205 occurrences)

Table G.18: Frequency of Detailed Tasks for Linda Lentz (N=76 occurrences)

63

Table G.19: Frequency of Detailed Tasks for Liz Johnson (N=295 occurrences)

Table G.20: Frequency of Detailed Tasks for Marietta Brooks (N=225 occurrences)

64

Table G.21: Frequency of Detailed Tasks for MaryKay Downs (N=159 occurrences)

Table G.22: Frequency of Detailed Tasks for Nancy Montange (N=229 occurrences)

65

Table G.23: Frequency of Detailed Tasks for Patty Brink (N=186 occurrences)

Table G.24: Frequency of Detailed Tasks for Penny Cates (N=101 occurrences)

66

Table G.25: Frequency of Detailed Tasks for Rachel Wilken (N=203 occurrences)

Table G.26: Frequency of Detailed Tasks for Robin Edwards (N=111 occurrences)

67

Table G.27: Frequency of Detailed Tasks for Vicki Edwards (N=60 occurrences)

68

Appendix H: Time for High Level Tasks by Day of Week and Clinical Service

Figure H.1: Time for High Level Tasks by Day of Week for PGEN (N=1,074 minutes)

Figure H.2: Time for High Level Tasks by Day of Week for BMT (N=2,965 minutes)

69

Figure H.3: Time for High Level Tasks by Day of Week for MFH (N=1,676 minutes)

Figure H.4: Time for High Level Tasks by Day of Week for STC (N=1,350 minutes)

70

Figure H.5: Time for High Level Tasks by Day of Week for SGEN (N=943 minutes)

Figure H.6: Time for High Level Tasks by Day of Week for SUA (N=1,870 minutes)

71

Figure H.7: Time for High Level Tasks by Day of Week for MGEN (N=952 minutes)

Figure H.8: Time for High Level Tasks by Day of Week for SO (N=689 minutes)

72

Figure H.9: Time for High Level Tasks by Day of Week for PCAR (N=956 minutes)

Figure H.10: Time for High Level Tasks by Day of Week for MP (N=132 minutes)

73

Appendix I: Proportion of Time for High Level Tasks by Discharge Planner

Figure I.1: Proportion of Time for High Level Tasks of Alison Wilson (N=577 minutes)

Figure I.2: Proportion of Time for High Level Tasks of Andrea Stec (N=194 minutes)

74

Figure I.3: Proportion of Time for High Level Tasks of Ann Dowling (N=458 minutes)

Figure I.4: Proportion of Time for High Level Tasks of Anna Silvenis (N=946 minutes)

75

Figure I.5: Proportion of Time for High Level Tasks of Brian Kobylarz (N=474 minutes)

Figure I.6: Proportion of Time for High Level Tasks of Dawna Innis (N=81 minutes)

76

Figure I.7: Proportion of Time for High Level Tasks of Deb Sgroi (N=89 minutes)

Figure I.8: Proportion of Time for High Level Tasks of Deb Stoll (N=698 minutes)

77

Figure I.9: Proportion of Time for High Level Tasks of Diane Noack (N=1,231 minutes)

Figure I.10: Proportion of Time for High Level Tasks of Elizabeth Stevens (N=956 minutes)

78

Figure I.11: Proportion of Time for High Level Tasks of Jane Antosiak (N=284 minutes)

Figure I.12: Proportion of Time for High Level Tasks of Jill Haas (N=25 minutes)

79

Figure I.13: Proportion of Time for High Level Tasks of Judy Benkesser (N=239 minutes)

Figure I.14: Proportion of Time for High Level Tasks of Karen LaRue (N=155 minutes)

80

Figure I.15: Proportion of Time for High Level Tasks of Kathleen Baker (N=526 minutes)

Figure I.16: Proportion of Time for High Level Tasks of Kathy Soloy (N=689 minutes)

81

Figure I.17: Proportion of Time for High Level Tasks of Kelly Krawcke (N=89 minutes)

Figure I.18: Proportion of Time for High Level Tasks of Liz Johnson (N=1,540 minutes)

82

Figure I.19: Proportion of Time for High Level Tasks of Marietta Brooks (N=790 minutes)

Figure I.20: Proportion of Time for High Level Tasks of MaryKay Downs (N=924 minutes)

83

Figure I.21: Proportion of Time for High Level Tasks of Nancy Montange (N=476 minutes)

Figure I.22: Proportion of Time for High Level Tasks of Patty Brink (N=477 minutes)

84

Figure I.23: Proportion of Time for High Level Tasks of Penny Cates (N=123 minutes)

Figure I.24: Proportion of Time for High Level Tasks of Rachel Wilken (N=132 minutes)

85

Figure I.25: Proportion of Time for High Level Tasks of Robin Edwards (N=348 minutes)

Figure I.26: Proportion of Time for High Level Tasks of Susan Jones (N=43 minutes)

86

Figure I.27: Proportion of Time for High Level Tasks of Vicki Edwards (N=43 minutes)

87

Appendix J: Percentage of Time Spent Multi-Tasking by Discharge Planner

Figure J.1: Percentage of Time Spent Multi-Tasking for Alison Wilson (N=577 minutes)

Figure J.2: Percentage of Time Spent Multi-Tasking for Andrea Stec (N=194 minutes)

88

Figure J.3: Percentage of Time Spent Multi-Tasking for Ann Dowling (N=458 minutes)

Figure J.4: Percentage of Time Spent Multi-Tasking for Anna Silvenis (N=946 minutes)

89

Figure J.5: Percentage of Time Spent Multi-Tasking for Diane Noack (N=1,231 minutes)

Figure J.6: Percentage of Time Spent Multi-Tasking for Elizabeth Stevens (N=956 minutes)

90

Figure J.7: Percentage of Time Spent Multi-Tasking for Jane Antosiak (N=284 minutes)

Figure J.8: Percentage of Time Spent Multi-Tasking for Liz Johnson (N=1,540 minutes)

91

Figure J.9: Percentage of Time Spent Multi-Tasking for Marietta Brooks (N=790 minutes)

Figure J.10: Percentage of Time Spent Multi-Tasking for MaryKay Downs (N=924 minutes)

92

Figure J.11: Percentage of Time Spent Multi-Tasking for Nancy Montange (N=476 minutes)

Figure J.12: Percentage of Time Spent Multi-Tasking for Robin Edwards (N=348 minutes)

93

Figure J.13: Percentage of Time Spent Multi-Tasking for Vicki Edwards (N=43 minutes)