Optimization of Medical Services: The Supply Chain and Ethical Implications by Daniel J. Miori and Virginia M. Miori
As an alternative to the current medical supply chain model, where patients are viewed as customers, it could be possible to view them (carefully) as inventory (pg 30). Other areas where humans are viewed as inventory include student tracking, resource utilization, staffing models and in censuses (pg 30).
Health Maintenance Organizations (HMOs) connect patients with health care providers in return for a fixed fee (regardless of the number or type of procedures required). Members must select “a primary physician who, when not faced with a medical emergency, may then refer the patient to other physicians as needed” (pg 33).
Traditionally, HCPs are service organizations. The service cycle begins when patients enter the system (pg 34). The patient moves through stages of outpatient/inpatient care, consuming the necessary resources (doctors, equipment, beds…), until they are no longer in need of care (pg 35).
Alternatively, HCPs can be viewed as “production operations”, with the patient being the most important sub-part of the final product (pg 36).
Ethical Considerations: Beneficence (do good things), Non-malfeasance (don’t harm), Autonomy (keeping patients fully informed), and Justice (care for all equally) (pg 37).
Service vs. Production Supply Chain:
Service supply chains “follow the movement of a customer through a series of processes” (pg 37). Quality is subjective, based on the experience of hospital staff and the patients themselves.
Production supply chains “focus on the processes that must be performed to yield a finished product” (pg 37). Measurements are objective, quantitative and qualitative.
Efficiency vs. Responsiveness: Industries that have a singular, easily repeatable final product (such as a steel mill, fast-food chain, or clothing business) are considered efficient. Responsive industries, healthcare especially, have to provide a wide range of ‘final products’ (pg 38).
Push vs. Pull processes: Push processes add products to inventory, pull processes move things from inventory to a final product (pg 39). In healthcare, paperwork and triage are push processes, since they add patients to the ‘inventory’. Everything that follows (out-/in-patient care, rehabilitation, etc…) is a pull process.
A Determination of the Optimal Level of Collaboration between
a Contractor and Its Suppliers under Demand Uncertainty by Seong-Hyun Nam, John Vitton, and Hisashi Kurata
To increase supply chain performance, suppliers and contractors need to collaborate, instead of each individually optimizing their own operations, as the later leads to reduced perforce. This is especially key for products with a short shelf-life, as suppliers can struggle to meet demand (pg 98). It is important to match supply with demand.
- The levels of collaboration:
- 1st level: ” … achieved when supply chain members share information relating to demand, inventory, capacity positions, and suppliers’ data—across the supply chain” (pg 99).
- 2nd level: “achieved when supply chain members exchange knowledge… a joint decision-making model for assortment planning, forecasting, inventory management, and replenishment to create competitive advantage from the customers’ point of view” (pg 100).
- 3rd level: “Supply chain members coordinate by exchanging decision rights, work, and resources” (pg 100). This includes Vendor-Management Inventory and Continuous Replenishment Plans.
- 4th level: “based on the best interest of the overall supply chain.” (pg 100).
Sharing demand information along the supply chain will reduce the bullwhip effect, and it will reduce the deviation D(t)-F(r,t), where D(t) is actual demand as a function of time, and F(r,t) is the forecasted demand as a function of time and collaboration r(t) (pg 101).
See pages 101– 112 for the derivation of Lemma 6.1
“Lemma 6.1 implies that the optimal level of collaboration with n suppliers can be chosen based on the marginal return with respect to the level of collaboration. If the marginal return with respect to the level of collaboration is positive, the maximum level of collaboration is the optimal solution. If the marginal return is negative then the minimum level of collaboration can be the optimal solution. Otherwise, contractors need to choose between the maximum and minimum level of collaboration required.” (pg 112).
See pages 115–117 for a numerical example of the collaboration model.
Inventory Optimization of Small Business Supply Chains with Stochastic Demand by Kathleen Campbell, Gerard Campagna, Anthony Costanzo, and Christopher Matthews
“Demand planning is the first step in a successful supply chain simulation.” (pg 153).
If seasonal increases in demand are know and readily predictable, inventory can be increased right before the demand increase, reducing the costs of holding inventory up until that point (pg 156).
Variability throughout the supply chain needs to be considered to optimize inventory investments (pg 158)
See pgs 164–171 for details on using Extend LT
There is now a comparison of types of materials and how to they are ordered at an ice cream shop, which maybe able to serve as examples to consider when thinking about medical supplies:
Hard ice cream (pgs 171-172): Deliverable twice a week; 24 tub capacity; Variable demand; Minimum order amount; Does not quickly expire. Can be ordered every couple of weeks.
Soft ice cream (pgs 172-173): Deliverable twice a week; 6 case capacity; Higher variable demand; Minimum order amount; Expires quickly (higher inventory cost). Must be ordered twice a week.
Other supplies (pgs 173-174): Deliverable once a week; Higher minimum order amount; Order can be triggered by shortages in many different things. Will be ordered as needed.
Applying Data Envelopment Analysis and Multiple Objective Data Envelopment Analysis to Identify Successful Pharmaceutical Companies by Ronald K. Klimberg, George P. Sillup, George Webster, Harold Rahmlow, and Kenneth D. Lawrence
“TQM (Total Quality Management) is a philosophy that advocates four basic principles: (1) an intense focus on customer satisfaction, (2) accurate measurement of activities, (3) continuous improvement of products and processes, and (4) empowerment of people” (pg 278)
“Efficiency can be defined as the ratio of weighted outputs to weighted inputs (pg 280)”
Data Envelopment Analysis combines the efficiency measures from many decision-making-units (DMUs) into a single metric (pg 280).
The DEA model maximizes the efficiency of each DMU by selecting determining weights for the output and input (pg 281).
Regression Forecasting Model (pgs 285-286):
- Define Objective(s)
- Stepwise Regression
- DEA or Multiple-Objective DEA (MODEA)
- Stepwise Regression