Inventory of various types is present in almost every organization, and I believe that it is essential to have the skills to handle the work and storage space in a given area successfully. It is especially true for hospitals, which use various tools and auxiliary equipment. I believe poor inventory management is a source of considerable problems, especially financial ones. It is relevant to the US healthcare system, which is growing dynamically, and healthcare expenditure is growing faster than GDP (Ahmadi, et. al., 2018). The easiest way to look at the effects of poor equipment management is with the example of a surgical department. Operating rooms are considered a significant source of revenue but also a major source of waste and operating costs (60 percent of all charges).
I am confident that the negative effects of poorly organized operating spaces are clear, and several pieces of evidence support this. The first source of cost overruns is the lack of a standardized approach to materials management. The amount and cost of consumables are determined based on the surgeon’s preoperative wishes. Based on observations, it was found by the researchers that the price of performing a laparoscopic cholecystectomy could be as high as $637 with a required cheque of $333 (Ahmadi, et. al., 2018). This fact demonstrates an obvious flaw in inventory management as overheads are unnecessarily increased.
In addition, the availability of materials is achieved not through quality accounting but by filling warehouses with consumables and equipment on reserve. Employees often accumulate excessive stocks of expensive consumables and tools, fearing future supply disruptions. Epidemics, natural disasters, and other unforeseen events can impact such logistical problems. Another problem that significantly affects hospital overhead is that the inventory of medical offices and attached storage areas is not tracked through information systems and databases (Farrokh, et. al., 2017). It makes it even more difficult to monitor medical facility inventory, not just that of surgery, creating a large information gap. The above evidence presents quite a serious problem for the financial situation of health care institutions, so it is necessary to provide possible options to improve the situation. Based on the research done by other scientists, I think that three approaches should be introduced in this case.
First, it is necessary to develop a model to account for possible risks to organizing the launches with anticipation of potential unnecessary expenditures. The models developed will better reflect the real problems. Hospitals also need the main storage facility and have some tools for the most popular surgeries or medical procedures directly in the wards (Ahmadi, et. al., 2018). People in emergencies tend to increase the demand for certain materials artificially, and spending increases accordingly. By having the right equipment on hand at once, doctors will spend fewer resources without worrying about the problem of possible shortages.
The last solution, which is expensive but pays for itself in the foreseeable future, is the introduction of modern technology. Data should be collected on cash instruments and supplies and their use, filling information gaps and systematizing reports on spending. Barcodes and RFID can be usefully used in this case (Farrokh, et. al., 2017). By and large, healthcare spending that is a consequence of poor inventory management significantly affects hospital revenues. In the case of private institutions, it also harms staff income and the quality of medical services. I believe implementing the abovementioned approaches can positively influence the solution to this urgent problem.
References
Ahmadi, E., Masel, D. T., Metcalf, A. Y., & Schuller, K. (2018). Inventory management of surgical supplies and sterile instruments in hospitals: a literature review. Health Systems, 1(1), 1–18. Web.
Farrokh, M., Azar, A., Jandaghi, G., & Ahmadi, E. (2017). A novel robust fuzzy stochastic programming for closed loop supply chain network design under hybrid uncertainty. Fuzzy Sets and Systems, 341, 69-91. Web.