Employing Lean Flow to Streamline the Admission Process, Improve

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Presented by, Matthew Rusk, D.O.
Advisor: Khalid Qazi, M.D.
Objectives

Introduce a concept that augments the
admission process by improving:




Admission wait times
Patient satisfaction
Quality
Cost Effective Care
Explain how change was implemented
 Discuss results
 Compare results to current literature

Introduction—Lean Flow

Business concept that is well known and
implemented daily by successful
businesses

Often ignored in the healthcare industry

Gaining recognition in healthcare

Can make healthcare efficient and improve
quality
Introduction

ED overcrowding is associated with worse
quality of care and service delivery quality (1);

Recent studies have shown clearly that wait
time directly affects patient satisfaction (1-9);

Time to evaluation can also influence whether
or not a patient is seen at all (1, 2, 10).
Hypothesis

Utilizing lean flow will improve the admission
process at Sisters of Charity Hospital by:
 Decreasing the total admission process time
 Improving patient satisfaction
 Enhancing quality
 Improving Cost Effective Care
Methodology

Implementation of Lean Flow
 X32 Healthcare ‘Rapid Improvement 3-day
Program’
○ CHS Staff;
○ Four Residents;
○ Lean Flow Education;
○ ‘Front end’ Improvements;
○ Little focus on admission process
Methodology
Applied concepts to improve admission
process
Key Changes:
○ Admission Orders within 30 min;
○ ED Holding Orders in certain situations;
○ Earlier Bed Search;
○ Easier access to order sets, charts and labels
Methodology

Outcome measures
 Time
 Patient Satisfaction
 Quality and Safety
 Cost Effective Care
Methodology

Pre-intervention
 March 1 through October 31, 2008-2011

Intervention
 November 2011 – February 2012

Post-intervention
 March 1 through October 31, 2012
Methodology-Time Intervals
Arrival
ED Provider
TAPI
Admit Order
Departure
 Arrival to Departure (total admission time)
 Arrival to ED Provider
 ED Provider to Time Admitting Physician Informed
of admission (TAPI)
 TAPI to Admit Order
 Admit Order to Departure
Methodology-Patient Satisfaction

Questions:






Got help as soon as wanted
Quiet around room at night
Treated with courtesy and respect by doctors
Treated with courtesy and respect by nurses
Rate Hospital
Would recommend hospital to family

Answers 9 or 10 out of 10 defined as perfect score

8 or below defined as non-perfect (negative response)
Methodology-Quality Indicators
Inpatient Specific
ED Specific

Fall Rate

Left Without Being Seen
(LWBS)

Core Measure Compliance
 AMI, HF, PN, SCIP

ED Mortality

RRT calls

Inpatient Mortality
Methodology—Cost Effective Care
 Average
LOS

ED Volume

Total Admissions
Results—Time Variables

Summarized using means and standard
deviations.

An independent two-sample t-test using
assumption of equal variances was used to
test for differences in means.

A multiple regression model was used to
test for differences adjusted for baseline
variables (age, gender, race, Arr Method,
and Bed Type).
Time Interval Comparison
Time (minutes)
Time (minutes)
(Decrease of 78.8 minutes [417.8 – 339 = 78.8])
Statistically Significant, P-value <.0001
Time (minutes)
(Decrease of 35 minutes [168.5 – 133.5 = 35])
Statistically Significant, P-value <.0001
Time (minutes)
(Decrease of 36.2 minutes [61.9 – 25.7 = 36.2])
Statistically Significant, P-value 0.0015
Summary of Time Variables

Arrival to Departure (Total Admission Time)
 Decrease of 78.8 minutes
 19% reduction in total admission time
 Most of our overall improvement during TAPI to Dep

TAPI to Departure
 Decrease of 71.2 minutes
 31% reduction of this

TAPI to Admit Order
 Decrease of 36.2 minutes
 58.5% reduction of this interval

Admit Order to Departure
 Decrease of 35 minutes
 21% reduction of this interval
Results—Patient Satisfaction

Summarized using frequencies and
percentages.

A Pearson chi-square test was used to compare
the proportion of satisfaction between pre and
post.

Odds ratio and corresponding 95% confidence
interval was calculated.
Hospital Rating
Chi-square test:
Odds Ratio:
Statistic
Chi-Square
Type of Study
Case-Control
(Odds Ratio)
DF
1
Value
1.7981
Value
16.7623
Prob
<.0001
95% Confidence Limits
1.3561
2.3843
Would Recommend Hospital To Family
Chi-square test:
Odds Ratio:
Statistic
Chi-Square
Type of Study
Case-Control
(Odds Ratio)
DF
1
Value
1.6931
Value
12.5009
Prob
0.0004
95% Confidence Limits
1.2629
2.2698
Treated With Courtesy and Respect By Doctors
Chi-square test:
Odds Ratio:
Statistic
Chi-Square
Type of Study
Case-Control
(Odds Ratio)
DF
1
Value
1.7113
Value
10.0276
Prob
0.0015
95% Confidence Limits
1.2246
2.3914
Treated With Courtesy and Respect By Nurses
Chi-square test:
Odds Ratio:
Statistic
Chi-Square
Type of Study
Case-Control
(Odds Ratio)
DF
1
Value
1.7703
Value
11.0264
Prob
0.0009
95% Confidence Limits
1.2606
2.4861
Patient Satisfaction Results

All questions showed significant
improvement post-intervention.

Hospital Rating Scores improved to
70.2% (from 56.74%)

Recommend to Family Scores improved
to 74.94% (from 63.85%)
Results—Quality

Summarized using means and standard
deviations

An independent two-sample t-test using
assumption of equal variances was used
to test for differences in means.
Improved Inpatient Fall Rate
Falls significantly decreased (p-value < 0.0001)
Improved ED Left Without Being Seen (LWBS)
38% reduction in LWBS
p-value is < 0.0001
Improved Core Measure Compliance
Percentage of Perfect
Care
Pre (%) Post
(%)
P-value
AMI
91.41
100.00
0.0956
HF
84.35
100.00
<0.0001
PN
84.99
94.44
0.0293
SCIP
84.98
92.61
0.0006
Decreased Number of Rapid Response Team Calls
p-value = < 0.001
Statistically Significant
Mortality
Inpatient
p-value = 0.9053
No significant difference
ED
p-value = 0.6264
No significant difference
Quality Summary
Inpatient Specific
ED Specific

Improved Inpatient Fall Rate

Improved Left Without
Being Seen (LWBS)

Improved Core Measure Compliance
 AMI, HF, PN, SCIP

No change in ED
Mortality

Decreased RRT calls

No change in Inpatient Mortality
Results—Cost Effective Care

Summarized using means and standard
deviations

An independent two-sample t-test using
assumption of equal variances was used
to test for differences in means.
Improved Length of Stay
Average LOS decreased from 4.68 days to 4.36 days
(p-value < 0.0018)
Increased ED Volume and Admissions

ED Volume increased 13.5%:
 Pre Volume avg = 23,624
 Post Volume = 26,799


(March-Oct)
Admissions Increased 3.5%:
 Pre Admission Avg = 4,002
 Post Admission = 4,141

(March-Oct)
Cost Effective Care Summary

Improved Average Length of Stay

Increased ED Volume

Increased Admissions
Discussion

Yale-New Haven Hospital utilized lean and
reduced the time from decision to admit [TAPI] to
transfer to floor [departure] by 33% (11)
 Anecdotal recount
 We had a 31% reduction of this time frame.

Lack of studies focus on admitted patients.
 Lack of focus on admission times, affect of overall
hospital rating after admission
 Limited investigation on inpatient quality.
Conclusion

Our study fills void
○ focus on how lean affects the admission process and
subsequent hospital stay.

Implementing Lean Flow at Sisters Hospital




Significantly Improved Admission Times
Significantly Improved Patient Satisfaction
Significantly Enhanced Quality
Facilitated Cost Effective Care
Conclusion

Further improvements are possible
 Focus on specific time intervals
 Re-evaluate processes

Lean Flow works and is an essential tool
implement in healthcare.
Acknowledgements
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Marylin Boehler, RN, Director of ED and Critical Care
Julie Morgante, Quality Analyst, Quality & Patient Safety
Department
Terry Mashtare, PhD, UB Statistics Department
Jingjing Yin, UB Statistics Department
Entire Sisters Medical Records Department
Abid Hussain, MBBS, IM Resident
Sameer Waheed, MBBS, IM Resident
Mohammad Tantray, MBBS, IM Resident
Nancy Roder RN, BSN, Application Analyst, CHS Information
Technology
X32 Healthcare—Lean Consulting Firm

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
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Chuck Noon, PhD
Brian Livingston, MD, MBA
Jody Crane, MD, MBA
Kim Adams, RN
References
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1. Eitel DR, et al. Improving Service Quality by Understanding Emergency Department Flow: A White
Paper and Position Statement Prepared for the American Academy of Emergency Medicine. The
Journal of Emergency Medicine, Vol. 38, No.1, pp.70-79. 2010.
2. Schull MJ, Vermeulen M, Slaughter G, et al. Emergency department crowding and thrombolysis
delays in acute myocardial infarction. Ann Emerg Med 2004;11:577– 85.
3. Miro O, Antonio MT, Jimenez S, et al. Decreased healthcare quality associated with emergency
department overcrowding. Eur J Emerg Care 1999;6:105–7.
4. Pines JM, Hollander JE, Localio AR, Metlay JP. The association between ED crowding and hospital
performance on antibiotic timing for pneumonia and percutaneous intervention for myocardial
infarction. Acad Emerg Med 2006;13:873– 8.
5. Boudreaux ED, Ary RD, Mandry CV, McCabe B. Determinants of patient satisfaction in a large,
municipal ED: the role of demographic variables, visit characteristics, and patient perceptions. Am J
Emerg Med 2000;18:394 –400.
6. Kyriacou DN, Ricketts V, Dyne PL, McCollough MD, Talan DA. A 5-year time study analysis of
emergency department patient care efficiency. Ann Emerg Med 1999;34:326 –35.
7. Sun BC, Adams J, Orav EJ, Rucker DW, Brennan TA, Burstin HR. Determinants of patient
satisfaction and willingness to return with emergency care. Ann Emerg Med 2000;35:426 –34.
8. Bursch B, Beezy J, Shaw R. Emergency department satisfaction: what matters most? Ann Emerg
Med 1993;22:586 –91.
9. Watson WT, Marshall ES, Fosbinder D. Elderly patients’ perceptions of care in the emergency
department. J Emerg Nurs 1999; 25:88 –92.
10. Hobbs D, Kunzman SC, Tandberg D, Sklar D. Hospital factors associated with emergency center
patients leaving without being seen. Am J Emerg Med 2000;18:767–72.
11. Kulkarni RG. A reader and author respond to “Going Lean in the emergency department: a
strategy for addressing emergency department overcrowding.” Medscape J Med. 2008; 10:25.
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