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Healthcare Operations Management An Integrated Approach to Improving Quality and Efficiency Chapter 13. Supply Healthcare Operations Management An Integrated Approach to Improving Quality and Efficiency Chapter 13. Supply Chain Management Daniel B. Mc. Laughlin Julie M. Hays

Chapter 13 Supply Chain Management • What is Supply Chain Management (SCM)? • Why Chapter 13 Supply Chain Management • What is Supply Chain Management (SCM)? • Why is SCM Important for Healthcare Organizations? • Tracking and Managing Inventory • Forecasting • Order Amount and Timing • Inventory Systems • Procurement and Vendor Relationship Management • Strategic SCM Copyright 2008 Health Administration Press. All rights reserved. 2

Supply Chain Management (SCM) • The management of all activities and processes related to Supply Chain Management (SCM) • The management of all activities and processes related to both upstream vendors and downstream customers in the value chain • Tracking and managing demand, inventory, and delivery • Procurement and vendor relationship management • Technology enabled Copyright 2008 Health Administration Press. All rights reserved. 3

SCM in Healthcare • In 2006, the United States will spend over $2 trillion SCM in Healthcare • In 2006, the United States will spend over $2 trillion on healthcare. • Annual cost/family for health insurance is forecasted to be $22, 000 by 2010. • By 2016, it is predicted that one dollar of every five dollars of the U. S. economy will be devoted to healthcare. Copyright 2008 Health Administration Press. All rights reserved. 4

SCM in Healthcare • Supply costs in hospitals account for 15– 25 percent of SCM in Healthcare • Supply costs in hospitals account for 15– 25 percent of operating costs (HFMA 2002; HFMA 2005). • Transaction costs are estimated at $150 per order for buyer and seller (HFMA 2001). • There is 35 percent inconsistency between hospital and supplier data, and it costs $15 to $50 to research and correct a single order discrepancy. Copyright 2008 Health Administration Press. All rights reserved. 5

Inventory • Inventory is the stock of items held to meet future demand. • Inventory • Inventory is the stock of items held to meet future demand. • Inventory management answers three questions: - How much to hold - How much to order - When to order Copyright 2008 Health Administration Press. All rights reserved. 6

Functions of Inventory • To meet anticipated demand • To level process flow • Functions of Inventory • To meet anticipated demand • To level process flow • To protect against stockouts • To take advantage of order cycles • To help hedge against price increases or to take advantage of quantity discounts • To decouple process steps Copyright 2008 Health Administration Press. All rights reserved. 7

Effective Inventory Management • • • Classification system Inventory tracking system Reliable forecast of Effective Inventory Management • • • Classification system Inventory tracking system Reliable forecast of demand Knowledge of lead times Reasonable estimates of: - Holding or carrying costs - Ordering or setup costs - Shortage or stockout costs Copyright 2008 Health Administration Press. All rights reserved. 8

ABC Classification System Classifying inventory according to some measure of importance and allocating control ABC Classification System Classifying inventory according to some measure of importance and allocating control efforts accordingly Pareto Principle -A very important -B moderately important -C least important High (80%) Annual $ volume of items A B C Low (5%) Few (20%) Many (50%) Number of Items Copyright 2008 Health Administration Press. All rights reserved. 9

Inventory Tracking • Track additions and removals - Bar-coding - Point of use or Inventory Tracking • Track additions and removals - Bar-coding - Point of use or point of sale (POS) - RFID • Physical count of items - Periodic intervals - Cycle count - Find and correct errors Copyright 2008 Health Administration Press. All rights reserved. 10

Forecasting • • • Exercise Averaging methods Trend, seasonal, and cyclical models Model development Forecasting • • • Exercise Averaging methods Trend, seasonal, and cyclical models Model development and evaluation VVH example Copyright 2008 Health Administration Press. All rights reserved. 11

Forecasting Exercise I • • Identify the pattern and construct a formula that will Forecasting Exercise I • • Identify the pattern and construct a formula that will “predict” successive numbers in the series. What is the next number in the series? (a) 3. 7, 3. 7 (b) 2. 5, 4. 5, 6. 5, 8. 5, 10. 5, 12. 5, 14. 5, 16. 5 (c) 5. 0, 7. 5, 6. 0, 4. 5, 7. 0, 9. 5, 8. 0, 6. 5 • What is the formula for the next number in the series? Copyright 2008 Health Administration Press. All rights reserved. 12

Exercise I—Graphs Series b Series a Series c Copyright 2008 Health Administration Press. All Exercise I—Graphs Series b Series a Series c Copyright 2008 Health Administration Press. All rights reserved. 13

Exercise I Solution a) 3. 7, 3. 7 - Constant - Next number is Exercise I Solution a) 3. 7, 3. 7 - Constant - Next number is 3. 7 b) 2. 5, 4. 5, 6. 5, 8. 5, 10. 5, 12. 5, 14. 5, 16. 5 - c) 0. 5 + 2 x, where x specifies the position (index) of the number in the series Next number is 18. 5 5. 0, 7. 5, 6. 0, 4. 5, 7. 0, 9. 5, 8. 0, 6. 5 - 4. 5 + 0. 5 x + Cs, where x specifies the position (index) of the number in the series Cs represents the seasonality factor C 1 = 0, C 2 = 2, C 3 = 0, C 4 = − 2 Next numbers: 9, 11. 5, 10, 8. 5 Copyright 2008 Health Administration Press. All rights reserved. 14

Exercise II • Identify the pattern and construct a formula that will “predict” successive Exercise II • Identify the pattern and construct a formula that will “predict” successive numbers in the series. • What is the next number in the series? (a) 4. 1, 3. 3, 4. 0, 3. 8, 3. 9, 3. 4, 3. 5, 3. 7 (b) 2. 9, 4. 7, 6. 8, 8. 2, 10. 3, 12. 7, 14. 2, 16. 3 (c) 5. 3, 7. 2, 6. 4, 4. 5, 6. 8, 9. 7, 8. 2, 6. 3 Copyright 2008 Health Administration Press. All rights reserved. 15

Exercise II Solution • Same as series above, but with a random component generated Exercise II Solution • Same as series above, but with a random component generated from normal random number generator with mean 0 (a) 4. 1, 3. 3, 4. 0, 3. 8, 3. 9, 3. 4, 3. 5, 3. 7 • 3. 7 + (b) 2. 9, 4. 7, 6. 8, 8. 2, 10. 3, 12. 7, 14. 2, 16. 3 • 0. 5 + 2 x + (c) 5. 3, 7. 2, 6. 4, 4. 5, 6. 8, 9. 7, 8. 2, 6. 3 • 4. 5 + 0. 5 x + Cs + Copyright 2008 Health Administration Press. All rights reserved. 16

Forecasting Methods • Qualitative methods - Based on expert opinion and intuition; often used Forecasting Methods • Qualitative methods - Based on expert opinion and intuition; often used when there are no data available • Quantitative methods - Time series methods, causal methods Copyright 2008 Health Administration Press. All rights reserved. 17

Demand Behavior • Trend - Gradual, long-term up or down movement • Cycle - Demand Behavior • Trend - Gradual, long-term up or down movement • Cycle - Up and down movement repeating over long time frame • Seasonal pattern - Periodic, repeating oscillation in demand • Random movements follow no pattern Copyright 2008 Health Administration Press. All rights reserved. 18

Trend Demand Forms of Forecast Movement Cycle Random movement Time Seasonal pattern Demand Time Trend Demand Forms of Forecast Movement Cycle Random movement Time Seasonal pattern Demand Time Copyright 2008 Health Administration Press. All rights reserved. Trend with seasonal pattern Time 19

Forecasting Averaging Methods • • Simple moving average Weighted moving average Exponential smoothing Averaging Forecasting Averaging Methods • • Simple moving average Weighted moving average Exponential smoothing Averaging methods all assume that the dependent variable is relatively constant over time; no trends or cycles Copyright 2008 Health Administration Press. All rights reserved. 20

Simple Moving Average over a given number of periods that is updated by replacing Simple Moving Average over a given number of periods that is updated by replacing the data in the oldest period with that in the most recent period Ft = Forecasted demand for the period Dt-1 = Actual demand in period t − 1 n = Number of periods in the moving average Copyright 2008 Health Administration Press. All rights reserved. 21

Weighted Moving Average Simple moving average where weights are assigned to each period in Weighted Moving Average Simple moving average where weights are assigned to each period in the average. The sum of all the weights must equal one. Ft = Forecasted demand for the period Dt-1 = Actual demand in period t − 1 wt-1 = Weight assigned to period t − 1 Copyright 2008 Health Administration Press. All rights reserved. 22

Exponential Smoothing Times series forecasting technique that does not require large amounts of historical Exponential Smoothing Times series forecasting technique that does not require large amounts of historical data Ft Ft-1 Dt-1 = = Exponentially smoothed forecast for period t Exponentially smoothed forecast for prior period Actual demand in the prior period Desired response rate, or smoothing constant Copyright 2008 Health Administration Press. All rights reserved. 23

Forecasting Trend, Seasonal, and Cyclical Models • Holt’s trend-adjusted exponential smoothing technique • Winter’s Forecasting Trend, Seasonal, and Cyclical Models • Holt’s trend-adjusted exponential smoothing technique • Winter’s triple exponential smoothed model • ARIMA models Copyright 2008 Health Administration Press. All rights reserved. 24

Holt’s Trend Adjusted Exponential Smoothing Exponentially smoothed forecast that accounts for a trend in Holt’s Trend Adjusted Exponential Smoothing Exponentially smoothed forecast that accounts for a trend in the data FITt = Forecast for period t including the trend Ft = Smoothed forecast for period t Tt = Smoothed trend for period t Dt− 1 = Value in the previous period 0 = smoothing constant 1; 0 = smoothing constant 1 Copyright 2008 Health Administration Press. All rights reserved. 25

Forecast Accuracy • • Error = Actual − Forecast Find a method that minimizes Forecast Accuracy • • Error = Actual − Forecast Find a method that minimizes error Mean absolute deviation (MAD) Mean squared error Copyright 2008 Health Administration Press. All rights reserved. 26

Forecasting Model Development and Evaluation • • Identify purpose of forecast Determine time horizon Forecasting Model Development and Evaluation • • Identify purpose of forecast Determine time horizon of forecast Collect relevant data Plot data and identify pattern Select forecasting model(s) Make forecast Evaluate quality of forecast Adjust forecast and monitor results Copyright 2008 Health Administration Press. All rights reserved. 27

VVH Diaper Example Copyright 2008 Health Administration Press. All rights reserved. 28 VVH Diaper Example Copyright 2008 Health Administration Press. All rights reserved. 28

VVH Simple Moving Average Copyright 2008 Health Administration Press. All rights reserved. 29 VVH Simple Moving Average Copyright 2008 Health Administration Press. All rights reserved. 29

VVH Weighted Moving Average Copyright 2008 Health Administration Press. All rights reserved. 30 VVH Weighted Moving Average Copyright 2008 Health Administration Press. All rights reserved. 30

VVH Exponential Smoothing Copyright 2008 Health Administration Press. All rights reserved. 31 VVH Exponential Smoothing Copyright 2008 Health Administration Press. All rights reserved. 31

VVH Comparison (from the Excel template) Copyright 2008 Health Administration Press. All rights reserved. VVH Comparison (from the Excel template) Copyright 2008 Health Administration Press. All rights reserved. 32

Realities of Forecasting • Forecasts are seldom perfect. • Most forecasting methods assume that Realities of Forecasting • Forecasts are seldom perfect. • Most forecasting methods assume that there is some underlying stability in the system. • Service family and aggregated service forecasts are more accurate I see that you will get an A this semester. than individual service forecasts. Copyright 2008 Health Administration Press. All rights reserved. 33

Order Amount and Timing How much to hold How much to order When to Order Amount and Timing How much to hold How much to order When to order • Basic economic order quantity (EOQ) • Fixed order quantity with safety stock • More models Copyright 2008 Health Administration Press. All rights reserved. 34

Definitions Lead time—time between placing an order and receiving the order Holding (or carrying) Definitions Lead time—time between placing an order and receiving the order Holding (or carrying) costs—costs associated with keeping goods in storage Ordering (or setup) costs—costs of ordering and receiving goods Shortage costs—costs of not having something in inventory when it is needed Back orders—unfilled orders Stockouts—occur when the desired good is not available Copyright 2008 Health Administration Press. All rights reserved. 35

Definitions Independent demand is demand that is generated by the customer and is not Definitions Independent demand is demand that is generated by the customer and is not a result of demand for another good or service. Dependent demand is demand that results from another demand. Demand for tires and steering wheels (dependent) is related to the demand for cars (independent). Copyright 2008 Health Administration Press. All rights reserved. 36

Assumptions of the Basic EOQ Model • Demand for the item in question is Assumptions of the Basic EOQ Model • Demand for the item in question is independent. • Demand is known and constant. • Lead time is known and constant. • Ordering costs are known and constant. • Back orders, stockouts, and quantity discounts are not allowed. Copyright 2008 Health Administration Press. All rights reserved. 37

Inventory Order Cycle Demand rate Order quantity, Q Average amount of inventory held = Inventory Order Cycle Demand rate Order quantity, Q Average amount of inventory held = Q/2 Inventory Level Reorder point, R 0 Time Lead time Order Placed Received Order Placed Copyright 2008 Health Administration Press. All rights reserved. Order Received 38

Reorder Point The point in time by which stock must be ordered to replenish Reorder Point The point in time by which stock must be ordered to replenish inventory before a stockout occurs R = Reorder point d = average demand period L = lead time (in the same units as above) Copyright 2008 Health Administration Press. All rights reserved. 39

EOQ Model Cost Curves Annual cost ($) Minimum Total Cost Holding Cost = h*Q/2 EOQ Model Cost Curves Annual cost ($) Minimum Total Cost Holding Cost = h*Q/2 Ordering Cost = o*D/Q Optimal Order Quantity Copyright 2008 Health Administration Press. All rights reserved. Order Quantity, Q 40

EOQ Model Insights • As holding costs increase, the optimal order quantity decreases. (Order EOQ Model Insights • As holding costs increase, the optimal order quantity decreases. (Order smaller amounts more often because inventory is expensive to hold. ) • As ordering costs increase, the optimal order quantity increases. (Order larger amounts less often because it is expensive to order. ) Copyright 2008 Health Administration Press. All rights reserved. 41

EOQ Model Implications Annual Cost ($) Total Cost Holding Cost Ordering Cost Q* Q* EOQ Model Implications Annual Cost ($) Total Cost Holding Cost Ordering Cost Q* Q* Order Quantity Copyright 2008 Health Administration Press. All rights reserved. 42

EOQ Model Implications Annual Cost ($) Total Cost Holding Cost Ordering Cost Q* Q* EOQ Model Implications Annual Cost ($) Total Cost Holding Cost Ordering Cost Q* Q* Order Quantity Copyright 2008 Health Administration Press. All rights reserved. 43

VVH Diaper Example • • • Cost $5/case Holding costs 33% or $1. 67/case-year VVH Diaper Example • • • Cost $5/case Holding costs 33% or $1. 67/case-year Ordering costs $100 Lead time 1 week She calculates annual demand as: Copyright 2008 Health Administration Press. All rights reserved. 44

VVH Diaper Example She calculates the reorder point as She calculates the EOQ as: VVH Diaper Example She calculates the reorder point as She calculates the EOQ as: Copyright 2008 Health Administration Press. All rights reserved. 45

VVH Diaper Example Annual demand Ordering cost per order (setup) Annual carrying cost per VVH Diaper Example Annual demand Ordering cost per order (setup) Annual carrying cost per unit Working days per year Economic order quantity D = S = H = = EOQ = 2, 782 100 1. 67 365 577. 21 Actual order quantity Q = 577 Increment DQ = 500 Number of orders per year D/Q = 4. 8 Length of order cycle (days) Q/D = 75. 7 Average inventory Q/2 = 288. 5 Annual carrying cost (Q/2) * H = $ 481. 80 Annual ordering cost (D/Q) * S = $ 482. 15 Total annual cost TC = $ 963. 94 Copyright 2008 Health Administration Press. All rights reserved. units/year $/order $/unit-year days/year units orders/year days units 46

Reorder Point with Safety Stock Order quantity (Q) Inventory level Reorder point (R) Safety Reorder Point with Safety Stock Order quantity (Q) Inventory level Reorder point (R) Safety stock (SS) 0 Lead time Copyright 2008 Health Administration Press. All rights reserved. Time Lead time 47

Reorder Point with Safety Stock Reorder point Safety stock where z is the z-score Reorder Point with Safety Stock Reorder point Safety stock where z is the z-score associated with the desired service level (number of standard deviations above the mean) L= standard deviation of demand during lead time Copyright 2008 Health Administration Press. All rights reserved. 48

Safety Stock Probability of meeting demand during lead time = service level = 84% Safety Stock Probability of meeting demand during lead time = service level = 84% Reorder point Probability of a stockout = 16% Example units 100 120 Average demand during Lead time = d. L Z 0 Copyright 2008 Health Administration Press. All rights reserved. 1 49

Model Insights • As the desired service level increases, the amount of safety stock Model Insights • As the desired service level increases, the amount of safety stock increases. (If fewer stockouts are desired, more inventory must be carried. ) • As the variation in demand during lead time increases, the amount of safety stock increases. (If demand variation or lead time can be decreased, less safety stock is needed. ) Copyright 2008 Health Administration Press. All rights reserved. 50

VVH Diaper Example • Desired service level = 95 percent - With five orders/year, VVH Diaper Example • Desired service level = 95 percent - With five orders/year, this means that the hospital would experience one stockout every four years • Standard deviation of demand during lead = σL = 11. 5 cases of diapers • Amount of safety stock needed: • New reorder point: Copyright 2008 Health Administration Press. All rights reserved. 51

VVH Diaper Example Average daily demand d = 7. 64 units Average lead time VVH Diaper Example Average daily demand d = 7. 64 units Average lead time L = 7 days Std dev demand during lead time s. L = 11. 5 units Service level SL = 0. 95 DSL = Stock out risk 0. 05 1. 64 Average demand during lead time d. L = 53. 48 units Safety stock SS = 18. 9 units Reorder point ROP = 72. 4 units Increment z associated with service level Copyright 2008 Health Administration Press. All rights reserved. 52

VVH Diaper Example Average demand = 53. 5 cases/week Order quantity (577) Inventory level VVH Diaper Example Average demand = 53. 5 cases/week Order quantity (577) Inventory level Safety stock (19) Reorder point (72) 0 Lead time = 1 week Copyright 2008 Health Administration Press. All rights reserved. Time Lead time 53

More Inventory Models • Fixed period with safety stock - Orders are bundled and/or More Inventory Models • Fixed period with safety stock - Orders are bundled and/or vendors deliver according to a set schedule • Quantity discounts • Price breaks • Etc. Copyright 2008 Health Administration Press. All rights reserved. 54

Inventory Systems • • Simple JIT MRP ERP Copyright 2008 Health Administration Press. All Inventory Systems • • Simple JIT MRP ERP Copyright 2008 Health Administration Press. All rights reserved. 55

Two-Bin System When the first bin is empty, stock is taken from the second Two-Bin System When the first bin is empty, stock is taken from the second bin and an order is placed. There should be enough stock in the second bin to last until more stock is delivered. Copyright 2008 Health Administration Press. All rights reserved. 56

JIT—Kanbans Microsoft Visio® screen shots reprinted with permission from Microsoft Corporation. Copyright 2008 Health JIT—Kanbans Microsoft Visio® screen shots reprinted with permission from Microsoft Corporation. Copyright 2008 Health Administration Press. All rights reserved. 57

Flow and Pull • Continuous or single piece flow—move items (jobs, patients, products) through Flow and Pull • Continuous or single piece flow—move items (jobs, patients, products) through the steps of the process one at a time without interuptions or waiting. • Pull or just-in-time (JIT)—products or services are not produced until the downstream customer demands them. • Heijunka (i. e. , “make flat and level”)—eliminate variation in volume and variety of production. - Level patient demand Copyright 2008 Health Administration Press. All rights reserved. 58

Enterprise Information Technology Trends E-Commerce E-Business Automation Collaborative Engineering Data Processing Computer Integrated Manufacturing Enterprise Information Technology Trends E-Commerce E-Business Automation Collaborative Engineering Data Processing Computer Integrated Manufacturing Concurrent Engineering ERP Business Webs SCM Appliances MRP II Handheld MRP I Microcomputer CAD/CAM Minicomputer Mainframe 1960 1970 Networks TCP/IP 1980 1990 Copyright 2008 Health Administration Press. All rights reserved. Mobile Networks 2000 2010 59

MRP Product Structure Table (end item) Lead time = 1 week Table top (1) MRP Product Structure Table (end item) Lead time = 1 week Table top (1) Lead time = 2 weeks Leg (4) Lead time = 3 weeks Copyright 2008 Health Administration Press. All rights reserved. 60

MRP Logic Order table tops Order table legs Week 1 2 3 Copyright 2008 MRP Logic Order table tops Order table legs Week 1 2 3 Copyright 2008 Health Administration Press. All rights reserved. 4 5 61

ERP Systems Link Functional Areas Copyright 2008 Health Administration Press. All rights reserved. 62 ERP Systems Link Functional Areas Copyright 2008 Health Administration Press. All rights reserved. 62

Procurement and Vendor Relationship Management • • E-procurement Value-based standardization Outsourcing Vendor managed inventory Procurement and Vendor Relationship Management • • E-procurement Value-based standardization Outsourcing Vendor managed inventory (VMI) Automated supply carts Group purchasing organizations (GPO) Disintermediation Copyright 2008 Health Administration Press. All rights reserved. 63

Strategic Supply Chain Management Many are the same as any other improvement/change initiative: • Strategic Supply Chain Management Many are the same as any other improvement/change initiative: • Top management support • Employee buy-in • Structure and staffing need to support the desired improvements • Process analysis and improvement • Need relevant, accurate data and metrics • Training Copyright 2008 Health Administration Press. All rights reserved. 64

Strategic Supply Chain Management • Need to evaluate cost and benefits of technology-enabled solutions Strategic Supply Chain Management • Need to evaluate cost and benefits of technology-enabled solutions • Need to highlight the necessity and benefits of strategic supply chain management • Improved inventory management through better understanding of the systems - Consequences of unofficial inventory - Just-in-time systems - Improved inventory tracking systems Copyright 2008 Health Administration Press. All rights reserved. 65

Strategic Supply Chain Management • Vendor partnerships - Information sharing - Investigation and determination Strategic Supply Chain Management • Vendor partnerships - Information sharing - Investigation and determination of mutually beneficial solutions - Performance tracking • Continually educate and support a systemwide view of the supply chain and seek improvement for the system rather than for individual departments or organizations in that system. Copyright 2008 Health Administration Press. All rights reserved. 66