Six Sigma at The Urology Group

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					Six Sigma at The Urology Group
             W. Charles Slaven PMP CSSBB CMC
      www.maxtrain.com 513.382.3511 charlie@maxtrain.com
                         James Rapp
  www.theurologygroup.cc 513.366.3400 jrapp@theurologygroup.cc

          ASQ Meeting May 20, 2008
  Welcome
• Welcome and Introductions
  – Your Facilitators
        • Charlie Slaven MBA PMP CSSBB CMC
              – Vice President, MAX Solutions, LLC
        • Jim Rapp
              – Project Analyst, The Urology Group
  – Please Introduce yourselves




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Agenda

•   Background
•   The Vision and The Plan
•   The Process of Education and Mentoring
•   The Project’s Performance
•   Work in Process
•   Implications for the Health Care Industry
•   Thank You and Closing Remarks


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Six Sigma and Dilbert




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Background

• The Urology Group, a leader in Group Practice
  Management decides to implement Six Sigma
      – “We selected and pursued Six Sigma because Six
        Sigma is statistical based and performance
        measured. Six Sigma has tremendous opportunity
        and potential in the healthcare industry.”
            • Earl Walz, COO




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Background
“The urology group believes that Six Sigma is one of the
  best ways to quantify quality in the work place.
  Implementing six sigma in a health care business
  requires a change in mind set that we are just now
  appreciating. Making it part of our work routine,
  rather than an addition to the work routine is a work
  in progress.”

  Dr. William B. Monnig, CEO
The Vision and The Plan

• The Vision
      – To improve financial performance by orders of magnitude
        in an industry that is having margins collapse quickly due
        to many industry reasons and drivers
• The Plan
      –     Find a consultant and Implement the training
      –     Identify projects to implement improvements
      –     Get Certified as Black Belts
      –     Show results and build momentum


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DMAIC Process Improvement




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The Process
• Education
   – White Belt – one half a day for many of those on staff
   – Yellow Belt – 3 days for the core team
   – Green Belt - 7 days with Minitab, a simulation, an exam and
     two projects for the core team
   – Black Belt – 10 days with an exam and two more projects for
     the core team
• Mentoring
   – Every month, a read-out session was practiced
   – To prepare, the core team obtained just-in-time consultation

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Project Qualifications
We met them!
• There is a gap between current and desired
  performance.
• The cause of the problem is not clearly
  understood.
• The solution is not predetermined.




                       10
    Critical Success Factors
    We had them!
•   Dedicated Black Belts
•   Champion phase reviews
•   Black Belt has knowledge of processes to be improved
•   Historic data and repeated processes
•   Clearly defined deliverables
•   Committed process owners with the authority to
    modify the process



                            11
 Why Six Sigma was Different;
 Why it Worked in this Case!

• More rigorous and             • Used statistical data to drive
  statistically based than        improvements
  previous quality initiatives.    • Cost of poor quality
• Provides bottom line             • Measurement and analysis
  results                            of defects
• Senior Management was            • Rigorous business analysis
  involved                      • Uses the voice of the
• Organizational support          customer, voice of the
• Short cycle time 2 - 4          process, and voice of the
  months                          employees
• Clearly defined outcomes • Infrastructure of trained
  and measures of success         individuals – the Belts
                                                            12
A Project’s Business Case
 From Jan 2005 to Dec 2006 we
  experienced an average grade of
  75% in coding. With a target grade
  of 100%, this gap of 25% leads to a
  Cost of Poor Quality of $xxx,xxx
Sample Scope Statement
 Identify and evaluate CPC’s in the coding
  process. Identify and evaluate doctors on E &
  M coding process. Identify methods to
  improve the coding process for both doctors
  and coders. Identify and evaluate
  communication methods, such as audit tools
  and templates, to improve coding and
  documentation. Identify and evaluated doctor
  – coder relationship to improve training and
  communication of errors and questions.
Voice of the Customer (VOC)
•   CPCs
•   Don’t have time to review coding accuracy or doctor’s charts.
•   Doing audits, however, is a way to learn coding better (learning by doing).
•   Insurance Companies
•   Correct payments for services performed.
•   Over-utilization of higher level codes.
•   Physicians
•   Decrease risk of outside audits as well as fines.
•   Money collection increases with higher correct coding.
•   Decrease worrying that coding is done right the first time.
•   Patients
•   Does not want over-billing of treatment.
•   Better/correct medical record.
•   Divisional Managers
•   Heavy oversight from Corporate Management.
•   Heavy oversight would decrease when CM sees progress of audits being done correctly and timely.
•   Billers
•   Less refilling of “wrong” claims with insurance companies.
•   Correct coding would decrease days in A/R by decreasing rework.
•   Group Malpractice Insurance Company
•   Monthly audits reduce chance of fraud claims against doctors and corporation.
•   Ohio State Medical Association
•   Monthly audits reduce chance of fraud claims.
  Scores
                                           Summary for Grade
                                                                         A nderson-D arling N ormality Test
                                                                             A -S quared         9.92
                                                                             P -V alue <        0.005
                                                                             M ean              74.930
                                                                             S tD ev             9.938
                                                                             V ariance          98.768
                                                                             S kew ness      -0.576435
                                                                             Kurtosis         0.405434
                                                                             N                     801
                                                                             M inimum          40.000
                                                                             1st Q uartile     70.000
                                                                             M edian           77.000
                                                                             3rd Q uartile     81.000
         40   48        56       64         72      80       88    96
                                                                             M aximum          96.000
                                                                        95% C onfidence Interv al for M ean
                                                                             74.241            75.619
                                                                        95% C onfidence Interv al for M edian
                                                                             76.000            78.000
                                                                        95% C onfidence Interv al for S tD ev
                         9 5 % C onfidence Inter vals
                                                                             9.474             10.450
 Mean


Median

         74        75                 76                77        78
FMEA
                          Pareto Chart of Potential Failure Modes
                                                2000
                                                                                                                                              100
                                                1500                                                                                          80




                                                                                                                                                    Percent
 Count




                                                                                                                                              60
                                                1000
                                                                                                                                              40
                                                   500
                                                                                                                                              20

                                                       0                                                                                      0
         Potential Failure Modes                                      n                                 e          s          ts       er
                                                                 ig           DM x am                od         isy         ar      th
                                                              rs            M          e           c          M          ch       O
                                                             y
                                                               o
                                                                        eck      ic al        ng         t in          k
                                                            r         h         s          ro                       ic
                                                      ist
                                                          o
                                                                   tc         hy                      pu          p
                                                    h          n '          p            W
                                                                                                  fo        n ot
                                                  k                       k                    in
                                               ec           Do he c                         o           es
                                             h                      c                     N          do
                                        ' tc                   n 't                                C
                                     on                    Do                                 CP
                                   D
                                              Count                  405 405 405 320 180                                       30        78
                                           Percent                  22.2 22.2 22.2 17.6 9.9 1.6                                         4.3
                                           Cum %                    22.2 44.4 66.6 84.2 94.1 95.7 100.0
COPQ: Financial Impact
      Before
      Before:    After:
                 After

        EF      $58,922    Improvement
                Savings
                  EF

                   IF
        IF




                   A
        A
        P          P


     $684,080   $625,158
Project II Business Case

•   For January 1 through June 30, 2006, we experienced 21 days that our receivables
    sat in collections. With a target of 19 days, this gap of 2 days led to a Cost of Poor
    Quality of $XXX,XXX. While there are several divisions that make up this total, this
    project will focus on Division 8, which had 23 days in receivables. With the target
    of 19 days, this gap of 4 days led to a Cost of Poor Quality of $XX,XXX.

•   From January 1 through June 30, 2006, TUG experienced a gap of 2 days in
    collections. Of this gap, incorrect demographic entry and the collection of
    insurance cards in Division 8 represented 10.4% of the overall problem. This 10.4%
    leads to a Cost of Poor Quality of $XX,XXX.

•   The goal of this project is to reduce the days in collections in Division 8 from 23 to
    19 days by the end of 2006 by collecting and copying insurance cards and having
    correctly completed demographic forms to increase our cash flow by $XX,XXX. We
    will focus on the preparation of the demographic sheet and its entry into the
    MISYS system. The resources used will be the Division 8 front office staff, office
    manager, and the Norwood business office staff. For this case, the clinical process
    is out of scope
Sample Scope Statement
• Who – Josh, Norwood business office staff
• What – Presence of correct name, insurance company, insurance plan, and
  correct entry into MISYS will be tested via phone contact with new
  patients
• Where – After patient visit
• When – Random monthly sampling
• How – Division 8 front desk staff will copy registration forms and insurance
  cards as they are received. These forms will be given to Josh, who will take
  a sample of the patients and verify that the information is correct by
  calling the patient. Correct entry into MISYS will be verified by checking
  the information in the system against the form.
• Frequency – 10% of the patients will be selected at random
Voice of the Customer
• Patient
- Insurance not filed in timely manner
- Received a bill stating no insurance coverage

• Business Office
- There is no insurance company listed
- Claims refused because of incorrect data

• Insurance Companies
- There is no patient listed by that name
Scores
                           Summary for Correct Rate
                                                                         A nderson-D arling N ormality Test
                                                                              A -S quared        1.76
                                                                              P -V alue <       0.005
                                                                              M ean            0.87372
                                                                              S tD ev          0.11393
                                                                              V ariance        0.01298
                                                                              S kew ness      -1.49519
                                                                              Kurtosis         3.00654
                                                                              N                     54
                                                                              M inimum        0.44828
                                                                              1st Q uartile   0.82069
                                                                              M edian         0.90000
                                                                              3rd Q uartile   0.95000
            0.5   0.6        0.7           0.8      0.9   1.0
                                                                              M aximum        1.00000
                                                                        95% C onfidence Interv al for M ean
                                                                              0.84263         0.90482
                                                                        95% C onfidence Interv al for M edian
                                                                              0.86207         0.94323
                                                                        95% C onfidence Interv al for S tD ev
                   9 5 % C onfidence Inter vals
                                                                              0.09577         0.14064
 Mean


Median

         0.850     0.875           0.900          0.925         0.950
FMEA
                                                                             Division 8 Registration Project
                                    3500
                                                                                                                                                                                                                                                                                                                     100
                                    3000

                                    2500                                                                                                                                                                                                                                                                             80




                                                                                                                                                                                                                                                                                                                           Percent
                                    2000
Count




                                                                                                                                                                                                                                                                                                                     60
                                    1500
                                                                                                                                                                                                                                                                                                                     40
                                    1000
                                                                                                                                                                                                                                                                                                                     20
                                         500

                                                        0                                                                                                                                                                                                                                                            0
        Process Steps                                                         o.                       fo                    ta                   r   d                      rd                         g
                                                                                                                                                                                                                              bl
                                                                                                                                                                                                                                e                        s                    nt                   pa
                                                                                                                                                                                                                                                                                                      y
                                                                                                                                                                                                                                                                                                            he
                                                                                                                                                                                                                                                                                                                 r
                                                                            nf                      in                    da                   ca                          ca                       ul
                                                                                                                                                                                                      in
                                                                                                                                                                                                                            gi                      rm                      se
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                                               or
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                                                                                                                  .d                        do                         te                                                                      Re                       oe
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                                                                                                                Pt                       t.                         en                                              .d
                                                                                                                                                                                                                       o
                                                                                                                                                                                                                                                                 .d
                                             tc                  .t                     pt                                             p                                                                          Pt                                           Pt
                                        no                     Pt                ce                                               ce                     i   nf
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                                                                              Re                                               Re                     ct
                             .d                                                                                                                r   re
                        Pt                                                                                                                   co
                                                                                                                                        In

                                             Count                          500                      500                    500                    400                        320                     300                     240                   200                      120                     48      124
                                        Percent                             15.4                    15.4                   15.4                    12.3                     9.8                       9.2                     7.4                    6.2                     3.7                   1.5       3.8
                                        Cum %                               15.4                    30.8                   46.1                    58.4                    68.3                      77.5                    84.9                   91.0                    94.7                  96.2     100.0
Executive Summary

• The Days in A/R calculation has been reduced
  from 23 to 21 days thus far through collection
  and correct entry of patient demographics.
• There has been a total savings of $XX,XXX to
  date.
• There are still potential savings through the
  data collection process. These will be
  explored.
Work In Process

•   Copays, insurance cards, copay letters.
•   A/R processes.
•   Collection process.
•   Medication reconciliation.
•   Division demographics.
•   No Show/Cancellations.
•   Prostate Biopsy Protocal.
•   Scheduling
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Implications for Health Care

• Healthcare is decentralized and poorly integrated.
• Lack of standardization – different approach to common
  problems.
• Forces that make healthcare delivery more complex and
  difficult include: aging baby boomers, scarce financing,
  staffing shortages, as well as litigation.
• Overburdened by inefficiencies.




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Thank You & Closing Remarks

     • Comments
     • Questions


    What are your lessons learned from today’s session?




                    Thank You!

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