armed with - ihi

1
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 Ku 1 , Natalja Stanski 1 , Andy Paranjpa 1 , Cameron Heilbronn 1 , Ashley Matusz 1 , Donghan Sohn 1 , Erin Ryan 1 , David Broome 1 , Brandon Twardy 1 , Elizabeth Perry 1 , Lance Heilbrun, PhD, MPH 2 , Elisabeth Heath, MD 2 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.

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Page 1: armed with - IHI

• 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.