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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: [email protected]
Mandy McKay, Quality & Compliance Project Manager
University of Michigan Home Care Services
2705 South Industrial, Suite #300
Ann Arbor, MI 48104
Email: [email protected]
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: [email protected]
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
2
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
4
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
5
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
6
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.
7
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
8
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.
9
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.
10
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:
11
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)
12
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.
18
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.
20
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.
21
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 [email protected] (734-975-7488), [email protected], [email protected], [email protected]
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 [email protected] (734-975-7488), [email protected], [email protected], [email protected]
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)