Health Systems Engineering Instructor: Prof. Jingshan Li Dept. of Industrial and Systems Engineering University of Wisconsin - Madison Fall 2014 ISyE 417 1

Lean and Six Sigma in Health Care 2

3 What is Six Sigma? The roots of Six Sigma began with Deming, who promoted quality management in the US and Japan Motorola developed Six Sigma around 1985 Six Sigma is an integrated quality improvement framework, providing organizations with tools to improve the capability of their business processes Three key characteristics – A customer-centric management approach – Permanently changes how management functions – Yields major returns on investment from projects

4 What is Six Sigma? Measure of Quality Expresses how closely a process or service meets the expectations of the customers Method for Continuous Improvement Utilizes a formal framework for process improvement Mindset for Cultural Change If successful, changes the culture and operating philosophy of a company. The basic element of Six Sigma is a process improvement framework known as DMAIC (Define, Measure, Analyze, Implement, Control)

5 Why Six Sigma? Sigma Level Error RateErrors Per Million 230.8%308, %66, %6, % %3.4 Sigma level helps to show how good a process is. For example, Colonoscopy report turnaround time is at 2 sigma while biopsy report turnaround is 4 sigma.

6 Is 3 Sigma Enough? 99% Error-free (3.8 Sigma) % Error-free (6 Sigma) 200,000 wrong drug68 wrong drugprescriptions per year 5000 incorrect surgical2 incorrect surgical operations per weekoperations per week 50 newborn babies dropped1 newborn baby dropped at birth each dayevery month The difference between 3 Sigma and 6 Sigma is huge in health care – thousands times improvement

7 What makes Six Sigma Different? Process is measured by the patients’ expectations and specifications instead of internally established targets Analysis is rigorous and is data driven Statistically valid improvements Improvements are tested and proven Processes are controlled

8 customer spec target 6.6% defects  3 sigma process (Z = 3  ) … A Metric no defects  6 sigma process (Z = 6  ) … Reducing Variance is the Essence of Six Sigma

9 How to Make Six Sigma Successful? DEFINE MEASURE ANALYZE IMPROVE CONTROL OPPORTUNITY SYMPTOMS CAUSES SOLUTIONS SUSTAIN Methodology: DMAIC Philosophy: E =Q x A Effectiveness = Quality x Acceptance

10 How to Make Six Sigma Successful? Define: focuses on identifying project critical to quality (CTQ), defining the process map, and developing team charter. Measure: concentrates on defining performance standards for CTQs, collecting data, and verifying the adequacy of the measurement system to measuring the selected CTQ. Analyze: focuses on identifying the gap between the performance of the current process and the required performance, investigating variation sources, and identifying root causes.

11 How to Make Six Sigma Successful? Improve: focuses on generating ideas for removing or solving the problem. Control: concentrates on ensuring that key variables remain within acceptable limits under the modified process. This may include establishing new standards and procedures, training the workforce, and instituting control measures to ensure sustainability.

12 Can Six Sigma Work in Healthcare? Great Clinical & Financial Examples Today! Can Six Sigma Work in Healthcare? ‘98‘99‘00 Yes…It is Happening Now…With Impressive Results MD Anderson…CT Throughput Sick Childrens (Singapore)….Report Turnaround Bonsecours….Material Management Manipal (Bangalore, India)….Patient Registration Time Coney Island Hospital (NY)….Hospital Inventory Reduction

Lean and Six Sigma in Health Care (cont.) 13

14 The Main Idea of Lean Thinking It’s about adding value for customers (patients) by focusing on reducing or eliminating those things which are Non-Value-Added Improvement will be easier and more likely to succeed by focusing on & removing the non-value added activities (waste)

Lean Hospital Working to eliminate waste through: Goals and measures leading to accountability and driving improvement Areas organized and arranged Trained and empowered staff Smooth and consistent processes Problem solving and proactive failure mode analysis Working to promote the value stream Getting everyone involved 15

What Is Lean? Philosophy Produce only what is needed, when it is needed, with no waste Methodology Determination of value added in the process Tools 5S, kaizen event, standardized work, etc. 16

Six Sigma vs. Lean Lean Time variability Increase Speed Eliminate Waste Quick Fix Solutions Six Sigma Process variability Improve Quality Increase Yield Root Cause Solutions 17

Types of Waste Overtreatment and overdiagnosis Waiting Transportation Inventory of drugs, blood products, etc. Defects 18

Value Stream Mapping Process map of the value stream Includes information processing and transformational processing Value-added steps: “Would the patient/HMO be willing to pay for this activity?” Non-value-added steps 19

Throughput Time Time for an item to complete the entire process, which includes Waiting time Transport time Actual processing time 20

Clinic Cycle Time and Throughput 21

Clinic Cycle Time and Throughput Patient check-in cycle time = 3 minutes Nurse preliminary exam cycle time = 5 minutes Cycle time of the longest task = physician exam and consultation = 20 minutes Throughput time = = 70 minutes 22

Clinic - Value-Added Time Valued-added tasks: Nurse preliminary exam Physician exam and consultation Non-value-added steps: Patient waiting Value-added time = 5 minutes (nurse preliminary exam) + 20 minutes (physician exam and consultation) = 25 minutes Percentage value-added time = 25 minutes/70 minutes = 35 percent 23

Benefits of Lean in Health Care Reduced inventory Improved quality Lower costs Reduced space requirements Shorter lead time Increased productivity Better relations with suppliers Simplified scheduling and control activities Increased capacity Better use of human resources 24

Lean in Health Care Pros Cons 25

From Manufacturing to Health Care 26

Manufacturing to Healthcare Similarities Differences Challenges 27

Comparison: Areas in manufacturing: Machine tools; Production systems; Scheduling and planning; Quality assurance; Work systems; Information systems Corresponding areas in healthcare Clinical: diagnosis, treatment, medication, etc. Operations: workflow, patient flow, etc. Accessibility: capacity, staffing, etc. Safety: medication error, etc. Human factor: provider/patient behavior, team, etc. Health IT 28

Similarity: Parts flow  patient flow (or work flow, information flow) Performance Line throughput  Length of stay, decision time, discharge time, etc. Demand satisfaction (due-time performance)  Patient outcome (response-time performance, discharge-time performance, etc.) Bottlenecks/constraints Bottleneck machine  Bottleneck operation, bottleneck service, bottleneck department Bottleneck buffer  Bottleneck equipment, bottleneck resource 29

Lean Lean buffer  Lean workforce (doctors, nurses, etc.), lean equipment Improvability Work reallocation  Service reallocation Buffer reallocation  Capacity reallocation Layout Serial  Multiple procedures Assembly  Need multiple providers or resources Parallel  Multiple patient rooms Split/merge  Different routings Re-entrant  Multiple visits by providers 30

Products Multiple  Different patients, diseases, syndromes, providers Scheduling Sequencing  e.g., OR schedules Planning Product mix  Capacity design Quality SPC  Statistical analysis Work systems Incentives  Affordable care, insurance Rational behavior  Provider behavior, team, communicatins 31

From Manufacturing to Health Care 32

Difficulties in Healthcare Systems More variability Patients: syndrome, disease, age, gender, etc. Providers: levels, experiences, etc. Responses: predictable / unpredictable More complex layout Different routings Closed flow Reentrant operations 33

Resources constraints Limited number of providers, equipment, etc. Different policies, such as priority, pool, etc. Human behavior Patient Provider Dynamics Time dependent Transient 34

Einstein: The nature is complex, but not evil Production Systems Engineering The production system is complex, but not evil Healthcare systems The healthcare system is complex, is it evil? 35

Simplicities in Healthcare Systems Reliability Limited population 36

From Manufacturing to Health Care 37

Challenges Data collection Consistency / compatibility Action/Control Real time decision making Integration Patient status modeling Care provider behavior modeling Multiple disciplines 38

Should health care industry repeat the same mistakes manufacturing has made? 39