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Healthcare Operations Management

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1 Healthcare Operations Management
Daniel B. McLaughlin Julie M. Hays

2 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.

3 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.

4 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.

5 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.

6 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.

7 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.

8 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.

9 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.

10 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.

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

12 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, 3.7, 3.7, 3.7, 3.7, 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.

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

14 Exercise I Solution 3.7, 3.7, 3.7, 3.7, 3.7, 3.7, 3.7, 3.7 Constant Next number is 3.7 2.5, 4.5, 6.5, 8.5, 10.5, 12.5, 14.5, 16.5 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 x + Cs, where x specifies the position (index) of the number in the series Cs represents the seasonality factor C1 = 0, C2 = 2, C3 = 0, C4 = −2 Next numbers: 9, 11.5, 10, 8.5 Copyright 2008 Health Administration Press. All rights reserved.

15 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.

16 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 x +  (c) 5.3, 7.2, 6.4, 4.5, 6.8, 9.7, 8.2, 6.3 x + Cs +  Copyright 2008 Health Administration Press. All rights reserved.

17 Forecasting Methods Qualitative methods Quantitative 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.

18 Demand Behavior Trend Cycle Seasonal pattern
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.

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

20 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.

21 Simple Moving Average 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.

22 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.

23 Exponential Smoothing
Times series forecasting technique that does not require large amounts of historical data Ft = Exponentially smoothed forecast for period t Ft-1 = Exponentially smoothed forecast for prior period Dt-1 = Actual demand in the prior period  = Desired response rate, or smoothing constant Exponential Smoothing Constant Alpha () A value between 0 and 1 that is used to minimize the error between historical demand and respective forecasts. Use small values for  if demand is stable, larger values for  if demand is fluctuating. Copyright 2008 Health Administration Press. All rights reserved.

24 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.

25 Holt’s Trend Adjusted Exponential Smoothing
Exponentially smoothed forecast that accounts for a trend in the data Exponential Smoothing Constant Alpha () A value between 0 and 1 that is used to minimize the error between historical demand and respective forecasts. Use small values for  if demand is stable, larger values for  if demand is fluctuating. 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.

26 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.

27 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.

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

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

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

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

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

33 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 than individual service forecasts. I see that you will get an A this semester. Copyright 2008 Health Administration Press. All rights reserved.

34 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.

35 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.

36 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.

37 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.

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

39 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 per period L = lead time (in the same units as above) Copyright 2008 Health Administration Press. All rights reserved.

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

41 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.

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

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

44 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.

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

46 VVH Diaper Example Annual demand D = 2,782 units/year
Ordering cost per order (setup) S = 100 $/order Annual carrying cost per unit H = 1.67 $/unit-year Working days per year = 365 days/year Economic order quantity EOQ = units Actual order quantity Q = 577 Increment DQ = 500 Number of orders per year D/Q = 4.8 orders/year Length of order cycle (days) Q/D = 75.7 days Average inventory Q/2 = units Annual carrying cost (Q/2) * H = $ Annual ordering cost (D/Q) * S = $ Total annual cost TC = $ Copyright 2008 Health Administration Press. All rights reserved.

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

48 Reorder Point with 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.

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

50 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.

51 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.

52 VVH Diaper Example Average daily demand d = 7.64 units Average lead time L = 7 days Std dev demand during lead time sL = 11.5 Service level SL = 0.95 Increment DSL = Stock out risk 0.05 z associated with service level 1.64 Average demand during lead time dL = 53.48 Safety stock SS = 18.9 Reorder point ROP = 72.4 Copyright 2008 Health Administration Press. All rights reserved.

53 Average demand = 53.5 cases/week
VVH Diaper Example Average demand = 53.5 cases/week Order quantity (577) Inventory level Reorder point (72) Safety stock (19) Lead time = 1 week Lead time Time Copyright 2008 Health Administration Press. All rights reserved.

54 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.

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

56 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.

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

58 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.

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

60 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.

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

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

63 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.

64 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.

65 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.

66 Strategic Supply Chain Management
Vendor partnerships Information sharing Investigation and determination of mutually beneficial solutions Performance tracking Continually educate and support a system-wide 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.


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