Clinical Asset Optimization Research Proposal

Excerpt from Research Proposal :

service cost, Devices, and Cost per bed

Qualitative research design model

Secondary Data Collection

Research Validity and Reliability

Across the U.S., hospitals are overspending millions each year on mobile assets that are not utilized effectively. Despite more than adequate inventories, equipment often is not available when needed. As a result, more units are bought, leased, or rented. And those units, in turn, get lost in the system and therefore, underutilized. In fact, the number of mobile devices per U.S. hospital bed has increased 60% in the past 15 years while costs have doubled. Yet in most hospitals, the device utilization is approximately 45%. In the present study, the need for optimization and efficiency methods with clinical assets is investigated.


Hospitals in U.S. have to incur increased expenses for acquisition of medical equipment utilized for their normal operations. The cost of equipment purchased is high and hospitals are required to maintain a backup inventory of the equipment in order to efficiently carry out their daily operations. The hospitals utilize the equipment based on their needs and an increased number of equipment is either reported to be missing at times. The misuse, theft, wastage, and unavailability of medical equipment when required pose an economic challenge for these institutions. The result of all these issues can be interpreted in a huge annual loss, damaged reputation, and inefficacy in hospital operations.

The primary research objective is to perform detailed analysis of the elements concerning high cost of hospital operations and present a framework for optimization of clinical assets. The cost of operation is also increased through losses of clinical assets. The research will explore and identify the possible reasons for clinical asset losses.

The secondary objective of the research is to provide a framework for rectifying the possible cures of the situation. The research will also focus its attention in terms of providing the strategy that can facilitate in handling hospital operations, inventory management, and security of clinical assets. Finally the third objective of research is to propose recommendations for reduction of mishandling, theft, and misuse of the clinical resources. The usage of technology options will also be explored for clinical asset's traceability, allocation, and optimization (Pflaum, Meier, Muench, Fluegel, Gehrmann, Hupp, & Sedlmayr, 2010). The research will also be able to address clinical assets optimization issues in particularly in United States and generally in other parts of the world.

Literature Review

One common source of financial stress for hospital executives is equipment replacement. While new technology is paramount to providing remarkable patient care, its cost can often be measured in the millions of dollars. With most healthcare delivery systems already feeling pushed when it comes to operational costs, the common request to reduce spends simply part of the budget. Across the U.S., hospitals are overspending millions each year on mobile assets that are not utilized effectively. Despite more than adequate inventories, equipment often is not available when needed. As a result, more units are bought, leased, or rented. And those units, in turn, get lost in the system and therefore, underutilized. In the present paper, the need for optimization and efficiency methods with clinical assets are investigated.

In a research Kelly (2009) Thompson Reuters, it suggests that there is anywhere from $75 billion - $100 billion of waste in healthcare due to what is labels as "Provider Inefficiency and Errors." Of that category it specifically describes inefficiencies in the utilization of equipment. In the same article by R. Kelly, it referenced a May 2009 interview with NPR, Peter Orszag director of the White House Office of Management and Budget whom said, "Estimates suggest that the $700 billion a year in healthcare costs do not improve health outcomes. They occur because we pay for more care rather than better care. We need to be moving towards a system in which doctors and hospitals have incentives to provide the care that makes you better, rather than the care that just results in more tests and more days in [the] hospital."

According to Baretich (2004) the hospitals procure the devices and required clinical assets for usage in critical times. It is also noted that the procurement is made in advance and additional assets are kept in adequate amount in order to respond emergencies and smooth normal operations. However when required these assets are hard to locate and as a result the normal operations of hospital are disrupted (Nabelsi, 2012). The major issues found during the review of literature highlights that significant loop holes are identified for assets management and allocations. The three major issues entailing to non-availability of assets are theft, misplacement of the assets, and efficient retrieval from inventory. It is required to effectively handle these issues for eliminating the problems of non-availability at required times.

The operations management in hospital particularly with respect to inventory control allocation of resources is the major reason for hyped costs of clinical assets. The optimized usage of the clinical assets is the second stage after rectifying the issues of inventory management and allocation of required assets. The management of hospitals required to implement effective procedures with the help of technology to identify the required assets (Christe, Rogers, & Cooney, 2010; Castro, Lefebvre, & Lefebvre, 2013). It is also notable that issue, retrieval, and collection of clinical assets should be managed efficiently along with the regular stock take to eliminate the economic and operational damages caused due to inefficient handling of valuable clinical assets.

It has been reported that mobile equipment such as IV pumps, ventilators, and physiological patient monitors, typicallymake up more than 95% of a hospital's clinical assets and said inventory represents thousands of devices and aninvestmentworthtens ofmillions of dollars. Yet results of a recent study conducted by GE Healthcare disclose that the average utilizationofmobile devices is only 42%, meaning that more than half of the fleet is idle at any giventime. Despite the seeming oversupply, availability isinconsistent;for example, nursesspend anaverage of 21 minutes pershiftsearching forlost equipment.

According to the analysis in the article by Degraff (2013)the averagenumber ofmobile devices perstaffed bed increased62% onaverage between 1995 and 2010.Inthemid to late1990s,the typicalstaffed bedhad eight devices.Today, there are thirteen devices per bed.Thisfinding, coupledwithlowasset utilization, indicates a serious problem and need for asset intervention. With the number of devices increasing 62% over the 15-year period, the overall maintenance costs have risen even more, at a rate of 90%. Degraff (2013) suggests that an average 200-bed hospital had service and maintenance costs for the clinical devices increase from $331,200 to $628,800. However, the actual per unit cost to service the equipment only increased approximately 19%. Synthesizing this data indicates the aforementioned discovery that there has been an influx of technology over the 15-year period, therefore, driving up operational costs.

The attitude that manyhospitals believe, in erroris that it is lesscostly to address equipment availability issuesby leasing, renting, or buyingmore unitsratherthanoptimizinghowexisting devices aremanaged and distributed.This "purchase more" strategybackfires asthe additional equipmentsimplygets swallowed up in the system further drivingup costs. Therefore, when it comes to assets, most hospitals don't have a maintenance cost problem, they have an excess inventory problem.

This idea of an excess inventory problem can also be found in theHorblyuk (2013). In the graph below we can see that while the average cost of maintaining a device has seen a very moderate increase in cost, however the average number of devices per bed has increased significantly, driving the overall cost per bed to almost double in the last few years.

Figure: Average service cost, Devices, and Cost per bed

Source: Horblyuk (2013)

The data for the study on which the above graph is based were collected by the GE Healthcare Asset Management team in 1995-97 ("1995") and 2008-10 ("2010"), and included number of staffed beds and mobile device inventory count. In the article Yao (2012) on RFID benefits and barriers, it suggests another area for addressing the inefficiencies in clinical assets, that of theft loss. The article estimates that the theft of equipment and supplies cost hospitals $4,000 for bed each year, which represents a potential loss of $3.9 billion annually. The previous articles did not mention theft lost and its significant impact on overall costs.

In a study performed at Bon Secours Health System in Richmond, VA, the health system realized a savings of more than $5 million annually through reductions in equipment costs since adopting an RFID system. Eighty percent of Bon Secours' savings were attributed to better utilization, which resulted in a reduction in unnecessary equipment. For example, the St. Mary's campus was able to reduce its IV pump inventory from 520 to 392 - a 25% reduction. This reduction also improved the facility's utilization rate. Prior to its use of RFID technology, St. Mary's was at approximately 60% utilization of IV pumps. After the implementation, it was raised to 92%.

In order to address this excess inventory challenge hospital systems need an integrated strategy that drives productivity across the whole process.From making sure maintenances and repairs are performed efficiently and that every device…

Sources Used in Documents:


Baretich, M. (2004). Equipment Control and Asset Management. The Clinical Engineering Handbook, 1, 122.

Castro, L., Lefebvre, E., & Lefebvre, L.A. (2013). Adding Intelligence to Mobile Asset Management in Hospitals: The True Value of RFID. Journal of medical systems, 37(5), 1-17.

Christe, B., Rogers, R., & Cooney, E. (2010). Analysis of the impact of a radiofrequency identification asset-tracking system in the healthcare setting. Journal of Clinical Engineering, 35(1), 49-55.

DeGraff, B. (2013). As medical devices proliferate, asset management is key. Biomedical Instrumentation & Technology, 47(2), 123-7. Retrieved from

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