armed with - ihi
TRANSCRIPT
• Improving patient flow through the hospital
increases patient safety, improves clinical
outcomes, positively impacts patient and staff
satisfaction, and increases revenue.
• Patient flow has been an area of focus for the
Institute for Healthcare Improvement (IHI),
particularly in the ED, ICU, and surgical units.
• Outpatient oncology clinics, however, have so
far eluded IHI publication in this field.
To study and test changes that will improve clinic
efficiency and decrease waiting times for patients
under the assigned care of an oncologist at the
Barbara Ann Karmanos Cancer Center by at least
20% for at least 50 patient visits over a 12-mo.
study period (Apr. 15, 2012 to Apr. 15, 2013),
without incurring extra cost or resource burden.
Kimberly Ku1, Natalja Stanski1, Andy Paranjpa1, Cameron Heilbronn1, Ashley Matusz1, Donghan Sohn1, Erin Ryan1, David Broome1, Brandon Twardy1, Elizabeth Perry1, Lance
Heilbrun, PhD, MPH2, Elisabeth Heath, MD2
1. Wayne State University School of Medicine, Detroit, MI
2. Division of Hematology/Oncology, Department of Internal Medicine, Karmanos Cancer Center, Wayne State University, Detroit, MI
• Data collection (See “Data Collection Form”) is
performed by trained medical students.
•Only non-infusion patient visits at Wertz Clinic
will be included in the study.
•Patients are made aware of study ahead of time
via clinic phone call.
•Statistical T-test will be used to analyze
significance of improvement measures.
•Baseline data (Cohort 0)completed and undergoing statistical analysis. •Cohort 1 and 2 possible interventions:
• Using flags outside of exam rooms to communicate among caretakers. • Lessen double booking load by increasing allotted patient encounter times for physician.
• Obstacles learned along the way:
• Soliciting buy-in from medical students and
clinic staff .
• Institutional paperwork guides our timeline.
All I’m
armed with
is
research..
Actual Arrival Time Scheduled Appointment Time
1. _ _ : _ _ am/pm Time patient signed in to Lab 1. _ _ : _ _ am/pm Lab appointment time
2. _ _ : _ _ am/pm Time patient registered with
Wertz Outpatient Clinic
3. _ _ : _ _ am/pm Time patient was called to enter clinic
4. _ _ : _ _ am/pm Time patient’s vital signs were obtained
5. _ _ : _ _ am/pm Time patient arrived in exam room
6. _ _ : _ _ am/pm Time nurse came into room
for routine questions
7. _ _ : _ _ am/pm Time provider #1 came into exam room
2. _ _ : _ _ am/pm Doctor appointment time
8. _ _ : _ _ am/pm Time provider #2 came into exam room
9. _ _ : _ _ am/pm Time provider #3 came into exam room
10. _ _ : _ _ am/pm Time patient started to schedule their
next appointment
11. _ _ : _ _ am/pm Time patient left the hospital
Apr
2012
May
2012
Jun
2012
July
2012
Aug
2012
Sept
2012
Oct
2012
Nov
2012
Dec
2012
Jan
2013
Feb
2013
Mar
2013
Apr
2013
Interventio
n Cohort 0
Intervention Cohort 1 Intervention
Cohort 2
Cycle 1 Cycles 2 Cycles 3 Cycles 4 No PDSA Cycles
Plan:
• Intervention Cohort 0
Establish baseline data to identify bottlenecks.
• Intervention Cohort 1
Suggest and test a change.
• Intervention Cohort 2
Plan for implementation.
Do:
• Intervention Cohort 0
-PDSA Cycle 1
Trained medical students use the Data Collection Form for at least 19 patient
visits under Dr. Heath or Dr. Shields on Wed and Thurs clinic days, which
eliminates both end-of-week and physician variability. Analyze wait times to
identify bottleneck.
• Intervention Cohort 1
-PDSA Cycles 2-4
Cycle 2 =Test a change on 19 patients. Medical students testing this change
will use Data Collection form to measure efficacy of change.
Cycle 3 = Regardless of results of Cycle 2, address another bottleneck or
possible change independently.
Cycle 4 = Address yet another possible change.
Study:
• Intervention Cohort 0
Question : What is the average total time spent waiting and time spent
between stations?
Prediction: Excess of 2-6 hours from expected appointment times.
Question : What is the bottleneck(s)?
Prediction : No system to alert physicians/staff when patient is ready to be
seen by them.
• Intervention Cohort 1
Question : How does the average total time spent waiting change with an
attempt at improvement?
Prediction : Waiting times decrease by 20%.
Act:
Test changes individually to analyze root-causes. Later try to build upon
changes and test consolidation as its own cycle under Intervention Cohort 1.