using six sigma to improve cardiac medication ... · using six sigma to improve cardiac medication...

Using Six Sigma to Improve Cardiac Medication Administration and CAT

Scan Capacity

Using Six Sigma to Improve Cardiac Medication Administration and CAT

Scan Capacity

Susan McGann RN, BSNAdrienne Elberfeld

Harvard Quality ColloquiumAugust 22, 2005

Virtua Health….TodayFour hospital system in Southern New JerseyTwo Long Term Care FacilitiesTwo Home Health AgenciesTwo Free Standing Surgical CentersAmbulatory Care - CamdenFitness Center8000 employees + 2000 physicians7,000 deliveries$650 million in revenuesSTAR Culture

Virtua Facilities

The Virtua STAR

CaringCulture

ExcellentService

Clinical Quality

& Safety

ResourceStewardship

BestPeople

Outstanding Patient

Experience

Virtua Health…. The Future

Change in HR Structure and ProcessFocus on Programs of ExcellenceBuilding a Greenfield site

Potential consolidation of multiple sitesAmbulatory StrategyGrowth in the North Additional Strategic Partnerships

R0 Cardiac Medication Indicators

Project Title: Cardiac Medication: Indicators Six Sigma ProjectSponsors: Jim Dwyer, Ann Campbell, Ellen Guarnieri, Adrienne Kirby, Mike KotzenChampions: Pat Orchard & Jane SlaterbeckMaster BB: Mark Van KooyBlack Belt: Adrienne ElberfeldGreen Belt: Ted GallFinance Approver: Gerry LoweProject Start Date: July 22, 2002

Team Members: Jay Brewin, Darlene Euler, Christine Gerber, Val Torres, Kathy Halstead, Kathy Plumb, Cindy D’Esterre, Lori Edell, Heather Scheckner, Angie Smolskis, Pat Quackenbush, Ronald Kieft, Michelle Weaks, Robert Singer, Vince Spagnuolo, Steve Fox

Project Description:Increase quality of patient care by use/non-use and appropriate documentation of aspirin, beta-blockers, and ACE inhibitors in CHF or AMI patients to achieve or exceed Virtua benchmark goals.

Project Scope:To have all four acute care facilities, within all medical disciplines, meet the standards of Core/JCAHO guidelines

Potential Benefits:To achieve improved outcomes for patients with AMI/CHF diagnosis by adhering to evidence based practice through education, documentation, and compliance while meeting regulatory standards and enhancing quality of patient care at Virtua.

Alignment with Strategic Plan:IIA-Cardiology; Global MICP Goals for Virtua.

Define

Each Appraiser vs Standard

Assessment Agreement

Appraiser # Inspected # Matched Percent (%) 95.0% CIAppraiser A 12 4 33.3 ( 9.9, 65.1)Appraiser B 12 11 91.7 ( 61.5, 99.8)Appraiser C 12 9 75.0 ( 42.8, 94.5)Appraiser D 12 10 83.3 ( 51.6, 97.9)

# Matched: Appraiser's assessment across trials agrees with standard.

Assessment Disagreement

Appraiser # 1/0 Percent (%) # 0/1 Percent (%) # Mixed Percent (%)Appraiser A 0 * 8 66.7 0 0.0Appraiser B 0 * 1 8.3 0 0.0Appraiser C 0 * 3 25.0 0 0.0Appraiser D 0 * 2 16.7 0 0.0

# 1/0: Assessments across trials = 1 / standard = 0.# 0/1: Assessments across trials = 0 / standard = 1.# Mixed: Assessments across trials are not identical.

Between Appraisers

Assessment Agreement

# Inspected # Matched Percent (%) 95.0% CI 12 5 41.7 ( 15.2, 72.3)

# Matched: All appraisers' assessments agree with each other.

QRA Chart Review Gage R&R Measure

Percentage of time QRA’s agreed on assessment

• During this gage, it was determined that there was variation between the QRA’sreview of charts

• A Workout was held on September 18th with the QRA’s and Case Management Directors to develop SOP’s in reviewing of all CHF and AMI patients for core indicators

Root Cause Analysis Identified through Containment

IssueConcurrent reviews of AMI & CHF patients

Ongoing information needed for medical staff and nursing staff of the core indicators

Cardiac POE needs real time access to Clinical Care Advisor to review data

ConclusionBetween Case Management, Quality & Nursing charts needed to coordinate efforts in reviewing charts

Have team members develop a storyboard template with pathways and indicators to be available at key areas throughout the facility

Coordinate with IS accessibility to system

SolutionMet with CCM’s, Case Management & Quality to educate on core indicators

Identified key areas, (physician lounges, Cardiac specific units, nursing specific areas), and posted storyboards that are the same throughout the system

Cardiac POE Director, AVP, and Black Belt access to system; able to review ongoing and provide feedback to Case Management

WhoTeam members specific to campus, J. Slaterbeck, A.Elberfeld

Team members specific to campus

C. Mullin, J. Slaterbeck, B. Rodin

Analyze

IssueWho is going to perform the task of daily chart reviews concurrent with care?

Communication with physicians per need for documentation

Coordination of ongoing chart reviews, documentation completion, and data information

ConclusionNursing, case management and quality are all reviewing charts; need to coordinate efforts in regard to the indicators

Need one point person to communicate directly with physicians in a timely manner

Need to appoint point people within the facility to ensure that activities are being completed and coordinated

SolutionCase Management to take the lead on chart reviews for patients with AMI, CHF & related diagnosis. Support from quality & nursing

If nursing and/or case mgt has direct contact with physician, they give necessary feedback. Next step is the facility QRA and physician champion

Case Management to coordinate with nursing & quality; all paperwork forwarded to Black Belt & VP Quality

WhoCase MtgDirectors, Quality Directors, CCM’s

Case Mgt, QRA’s, B. Singer, V. Spagnuolo, S. Fox

Case Mgt, QRA’s, C. Mullin, A. Elberfeld

AnalyzeRoot Cause Analysis Identified through Containment

(continued)

Root Cause Analysis

Factor MICU run sheets not available on charts

Root Cause Medics unable to complete; shortened documentation not part of permanent chart

Proposed Solutions Sponsor to work with Ambulatory Quality Director to have MICU run sheets completed & submitted concurrent with care

Inconsistent availability of patient census with diagnosis for Nursing and Case Management

IS integration with Canopy system; initial information input by ICD-9 code, not description

Work order placed with Information Services with actual cases to research and advise on proper input process

Physician compliance in completion of discharge instructions

Inconsistent follow-through

Directive from Medical Staff leadership to complete discharge instructions; two week trial period in April, 2003 by HIM to tag all charts without discharge instructions

Consistent practice of multi-disciplinary care of the patient across Virtua

Need for champion at each campus to lead initiatives of the Cardiac Programs of Excellence

Appointment of Nurse Leader within each facility to coordinateactivities of Cardiac Programs of Excellence at local level

Improve

MICU run sheets on patient charts within 24 hours of admission

Increased compliance for aspirin given with 24 hours

Compliance with PRO indicators for aspirin given within 24 hours of admission; DOH regulations for transfer of patient care

Physician completion of written discharge instructions specific to medications for cardiac patients

Compliance and proper documentation of care for discharge medication indicators

Quality of care documented

Standard Operating Procedures by Nursing and Case Management in chart review, stickie reminders for physicians, and availability of discharge instructions

Increased compliance in care and documentation for all indicators

Coordination of care for the cardiac patient by the multi-disciplinary team

Consistent education of nursing per cardiac medication indicators

Increased compliance for medications given within time frames

Increased knowledge base of the nursing staff of the cardiac medications for AMI and CHF patients

Accurate daily census with diagnosis available through OAS Gold and Canopy

Increased compliance in care and documentation for all indicators

Timeliness of care improved

Appointment of a Process Owner at each hospital to coordinate care with directives from Cardiac Programs of Excellence

Sustained improvement in all indicators

Sustained results maintained and reported to CMS and public; appropriate recognition and reporting of quality of care

Realized Results of Implemented Solutions

Improvement Y Benefit Quality Benefit

Control

0 10 20

0.00

0.05

0.10

Sample Number

Prop

ortio

n

Virtua Health Control Chart for Aspirin Within 24 Hrs

P=0.02861

UCL=0.09429

LCL=0

Project Started June 03

Feb 05

Goal=95% Compliance

P ChartControl

DefineR0 CT Scan Capacity

Project Title: CT Scan Six Sigma ProjectSponsors: Ellen Master BB: Adrienne ElberfeldBlack Belt: Kathy EichlinGreen Belt: John Graydon, Wendy SeilerFinance Approver: Rex RueblingerProject Start Date: July 28, 2004

Project Description:Increase capacity by reducing in and out of room times for the CT Scan to adhere to GE industry benchmarks of 15 minutes without contrast and 25 minutes of with contrast.

Project Scope:Marlton CT Scan department

Potential Benefits:A more efficient process will lead to increased capacity thereby increasing opportunities for increased volumes.

Alignment with Strategic Plan:Resource StewardshipPatient Satisfaction

Team Members: Beverly Crawford, Melody DeLaurentis, JoAnnDomingo, Audrey Fley, Darryl Fussell, Cynthia Koller, Jo Nast, Heather Pierce, Donna Rapp, Elizabeth Zadsielski

Y1

•Mean = 13.6333

•Standard Deviation = 6.6993

•Z Score = 2.78

•Mode = 9

•Percent of Defects = 11.1%

0 8 16 24 32 40

95% Confidence Interval for Mu

10 11 12 13 14 15

95% Confidence Interval for Median

Variable: Avg Time

A-Squared:P-Value:

MeanStDevVarianceSkew nessKurtosisN

Minimum1st QuartileMedian3rd QuartileMaximum

11.2994

5.2348

10.0000

2.4500.000

13.0385 6.246439.01811.994535.98253

52

1.0000 9.000011.500015.000038.0000

14.7775

7.7464

13.4970

Anderson-Darling Normality Test


95% Confidence Interval for Sigma


Descriptive StatisticsY1-CT Abdomen/Pelvis Without ContrastUpdated 11/10/04

40353025201510


26.525.524.523.522.521.520.519.5


Variable: Avg Time

20.0000

5.6026

20.9492

Maximum3rd QuartileMedian1st QuartileMinimum

NKurtosisSkew nessVarianceStDevMean

P-Value:A-Squared:

26.0000

9.2909

25.9883

40.000028.500023.500018.500010.0000

32-1.4E-01

0.28013948.8377 6.988423.4688

0.9180.174





Descriptive StatisticsY2-Abdomen/Pelvis With Contrast

Y2

•Mean = 23.4688


•Z Score = 1.90

•Mode = 20, 21 and 24


MeasureDescriptive Statistics

2 6 10 14 18 22 26


10 11 12


Variable: Avg Time

A-Squared:P-Value:

MeanStDevVarianceSkew nessKurtosisN

Minimum1st QuartileMedian3rd QuartileMaximum

10.4046

3.7159

10.0000

1.1660.004

11.3671 4.297218.4661

0.8044130.843822

79

2.0000 8.000011.000014.000025.0000

12.3296

5.0959

12.0000





Descriptive StatisticsY3-CT Brain Without Contrast

Y3

•Mean = 11.3671


•Z Score = 2.58

•Mode = 7


The problem is too much standard deviation/ variation in the process!!

MeasureDescriptive Statistics

1917151311975

95% Confidence Intervals for Sigmas

P-Value : 0.006

Test Statistic: 5.287

Levene's Test

P-Value : 0.000

Test Statistic: 69.345

Bartlett's Test

Factor Levels

3 CT Techs

2 CT Techs

1 CT Tech

Test for Equal Variances for multiple Levene’s test –Test for equal variances for continuous data that is not normally distributed.

There is a statistical difference in the variance!

T Test for Equal VariancesAnalyze

A Pareto Chart shows where within the process the greatest opportunity exists for improvement. Here we see opportunities for the need for improvement with interruptions caused by the phone, door interruptions and assistance needed to move a patient resulting in 59 % of CAT Scan Delays. Use LEAN opportunities to streamline process.

Others

Pt Uncooperative

Equipment Failure

Pt Rescan

Radiologist Delay

MD Interuption

Other

IV Started in CT Rm

Patient Delays

Tech Delays

Assistance for pt

Door interruptions

Phone

24 8 10 13 17 18 21 25 47 48 93103129 4 1 2 2 3 3 4 4 8 9171923

100 96 94 92 90 87 84 80 76 67 58 42 23

500

400

300

200

100

0

100

80

60

40

20

0

DefectCount

PercentCum %

Perce

nt

Coun

t

CAT Scan Delays

Pareto ChartAnalyze

Before-A After-Av

0

10

20

30

40

50

60

Boxplots of Before-A and After-Av(means are indicated by solid circles)

Y1-CAT Scan of Abdomen/Pelvis Without Contrast

Two-sample T for Before-Avg. Time vs After-Avg. Time

N Mean StDev SE MeanBefore-A 62 14.95 9.87 1.3After-Av 106 11.65 5.21 0.51

Difference = mu Before-Avg. Time - mu After-Avg. TimeEstimate for difference: 3.3095% CI for difference: (0.61, 5.99)T-Test of difference = 0 (vs not =): T-Value = 2.44 P-Value = 0.017 DF = 81

P-value was less than .05, therefore, there is a statistical difference!

Y1-Abdomen-Pelvis Without ContrastOne-way ANOVA: Before-Avg. Time, After-Avg. Time

Analysis of VarianceSource DF SS MS F PFactor 1 426.2 426.2 8.04 0.005Error 166 8794.9 53.0Total 167 9221.1

Individual 95% CIs For MeanBased on Pooled StDev

Level N Mean StDev ---------+---------+---------+-------Before-A 62 14.952 9.869 (--------*--------) After-Av 106 11.651 5.214 (------*------)

---------+---------+---------+-------Pooled StDev = 7.279 12.0 14.0 16.0

2 Sample T Test & ANOVA Y1Improve

Before-A After-Av

10

20

30

40

Boxplots of Before-A and After-Av(means are indicated by solid circles)

Y2-CAT Scan of Abdomen/Pelvis With Contrast

Two-sample T for Before-Avg. Time vs After-Avg. Time

N Mean StDev SE MeanBefore-A 32 23.47 6.99 1.2After-Av 20 18.05 4.93 1.1

Difference = mu Before-Avg. Time - mu After-Avg. TimeEstimate for difference: 5.4295% CI for difference: (2.09, 8.74)T-Test of difference = 0 (vs not =): T-Value = 3.27 P-Value = 0.002 DF = 49

Y2-Abdomen-Pelvis With ContrastOne-way ANOVA: Before-Avg. Time, After-Avg. Time

Analysis of VarianceSource DF SS MS F PFactor 1 361.4 361.4 9.15 0.004Error 50 1974.9 39.5Total 51 2336.3

Individual 95% CIs For MeanBased on Pooled StDev

Level N Mean StDev ----------+---------+---------+------Before-A 32 23.469 6.988 (------*-------) After-Av 20 18.050 4.925 (--------*---------)

----------+---------+---------+------Pooled StDev = 6.285 18.0 21.0 24.0


2 Sample T Test & ANOVA Y1Improve

Mood median test for CT Scan Chi-Square = 16.76 DF = 1 P = 0.000 Individual 95.0% CIs Subscrip N<= N> Median Q3-Q1 ----+---------+---------+---------+-- After - 33 10 8.00 2.00 (-----+------) Before-A 30 49 11.00 6.00 (-----+------) ----+---------+---------+---------+-- 7.5 9.0 10.5 12.0 Overall median = 9.00 A 95.0% CI for median(After -) - median(Before-A): (-3.12,-1.00)


Mood’s Median/Non-Normal Data

Improve

I & MR Control ChartCan we see the improvement on the chart post SOP implementation?

Can we see the improvement on the chart post SOP implementation?

Take away: Process is capable and in control.Take away: Process is capable and in control.

0Subgroup 50 100 150-10

010203040506070

Indivi

dual

Value

1

11

1 11

Mean=12.87

UCL=29.70

LCL=-3.964

0

10

20

30

40

50

Mov

ing R

ange

1

1

1

11

11 1

R=6.329

UCL=20.68

LCL=0

I and MR Chart for Y1-Avg Time

Y1-CT Scan Abdomen-Pelvis Without Contrast

Control

I & MR Control ChartCan we see the improvement on the chart post SOP implementation?


0Subgroup 10 20 30 40 50

0

10

20

30

40

Indivi

dual

Value

1

Mean=21.38

UCL=36.04

LCL=6.731

0

10

20

Mov

ing R

ange

R=5.510

UCL=18.00

LCL=0

I and MR Chart for Y2 Avg TimeY2-CAT Scan of Abdomen-Pelvis With Contrast

Control


I & MR Control Chart




0Subgroup 50 100

0

10

20

Indivi

dual

Value

11

1

Mean=10.43

UCL=20.19

LCL=0.6671

0

10

20

Mov

ing R

ange 11

11

R=3.669

UCL=11.99

LCL=0

I and MR Chart for CT Scan TimeY3-CT Brain Without Contrast

Control

The “other results”

Ahead of the ‘hospital’ curveData driven organizationThe dots are connected:

Strategy, Operations, Quality, Finance, PeopleFinancial up-spinLeadership Development

The Results Go Well Beyond the Project!

using six sigma to improve cardiac medication ... · using six sigma to improve cardiac medication...

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