Patent Application
20090281867
The invention relates generally to the field of service delivery and, more specifically, to a system and method to facilitate efficient management of such service delivery.
In a variety of industrial, commercial, medical, and research contexts, various pieces of equipment may be employed on a day-to-day basis to accomplish or facilitate the work being performed at a facility. In many instances, the facility may rely upon a third party to provide service for some or all of the equipment at the site to ensure that the equipment remains operational and available. For example, in an industrial setting, production equipment or computer resources that are in operation in a continuous or near-continuous manner may be serviced by an off-site party that provides servicing as needed or requested. Similarly, hospitals, clinics, and research facilities may utilize another party to service some or all of the diagnostic, monitoring, and/or imaging equipment at a site so that the equipment remains available where and when it is needed.
Such an arrangement, however, may impose burdens on the service provider that are difficult to overcome in an efficient and cost-effective manner. For example, a service provider may utilize a combination of remote personnel and field personnel to provide service to a variety of clients. Additionally, a service provider or a supplier may often maintain a broad inventory of parts to allow replacement of malfunctioning components of serviced systems. While maintaining relatively high resource levels, including staffing levels, inventory levels, and the like, may allow a service provider to more quickly meet service needs as they arise, it will be appreciated that the maintaining of higher levels of resources may generally result in higher costs for the service provider. Thus, the allocation of resources at levels in excess of that actually needed to service a given system or, more generally, to provide service expected by a client, may be inefficient and unnecessarily add to the operating expenses of a service provider. Conversely, maintaining an insufficient level of resources may prevent timely service delivery and could lead to client dissatisfaction with the service provider.
There is a need for a system and method to efficiently manage service delivery that accounts for, among other things, variation in device reliability. The subject matter described herein is operable to address the needs and concerns described above. Certain aspects commensurate in scope with the originally claimed invention are set forth below. It should be understood that these aspects are presented merely to provide the reader with a brief summary of certain forms the invention might take and that these aspects are not intended to limit the scope of the invention. Indeed, the invention may encompass a variety of aspects that may not be set forth below.
An embodiment of the present invention includes a system including a memory device having a plurality of routines stored therein. The system may also include a processor configured to execute the plurality of routines stored in the one or more memory devices. In one embodiment, the plurality of routines may include a routine to collect service event data corresponding to one or more failure modes from a population of medical devices disposed at one or more healthcare facilities, and a routine to analyze the service event data in accordance with a reliability growth model to detect a trend in occurrences of the one or more failure modes. The plurality of routines may also include a routine to output a report including at least one of the following: an indication of the detected trend, an indication of a predicted future client demand for service of the population of devices attributable to the one or more failure modes based at least in part on the detected trend, or a recommended resource allocation based at least in part on the predicted future client demand.
According to another embodiment, a method may include collecting service event data corresponding to one or more failure modes from a population of devices disposed at one or more client locations. The method may also include analyzing the service event data, via a computer, in accordance with a reliability growth model to detect a trend in occurrences of the one or more failure modes, and predicting future client demand for service of the population of devices attributable to the one or more failure modes based at least in part on the detected trend. Additionally, the method may include outputting a report including at least one of an indication of the detected trend or an indication of the predicted future client demand.
According to yet another embodiment, a manufacture may include a computer-readable medium having executable instructions stored thereon. The executable instructions may include instructions to collect data from one or more medical facilities, as well as instructions to analyze the data in accordance with a reliability growth model to detect a trend in the data. Further, the executable instructions may also include instructions adapted to output a report including at least one of the following: an indication of the detected trend, an indication of predicted future service demand based at least in part on the detected trend, or a suggested resource allocation based at least in part on the predicted future service demand.
Various refinements of the features noted above may exist in relation to various aspects of the subject matter described herein. Further features may also be incorporated in these various aspects as well. These refinements and additional features may exist individually or in any combination. For instance, various features discussed below in relation to one or more of the illustrated embodiments may be incorporated into any of the above-described aspects of the subject matter of the application alone or in any combination. Again, the brief summary presented above is intended only to familiarize the reader with certain aspects and contexts of the present subject matter without limitation to the claimed subject matter.
These and other features, aspects, and advantages of the present invention will become better understood when the following detailed description is read with reference to the accompanying drawings in which like characters represent like parts throughout the drawings, wherein:
One or more specific embodiments of the subject matter will be described below. In an effort to provide a concise description of these embodiments, all features of an actual implementation may not be described in the specification. It should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions must be made to achieve the developers' specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another. Moreover, it should be appreciated that such a development effort might be complex and time consuming, but would nevertheless be a routine undertaking of design, fabrication, and manufacture for those of ordinary skill having the benefit of this disclosure.
When introducing elements of various embodiments of the present invention, the articles “a,” “an,” “the,” and “said” are intended to mean that there are one or more of the elements. The terms “comprising,” “including,” and “having” are intended to be inclusive and mean that there may be additional elements other than the listed elements. Moreover, while the term “exemplary” may be used herein in connection to certain examples of aspects or embodiments of the presently disclosed subject matter, it will be appreciated that these examples are illustrative in nature and that the term “exemplary” is not used herein to denote any preference or requirement with respect to a disclosed aspect or embodiment. Further, any use of the terms “top,” “bottom,” “above,” “below,” other positional terms, and variations of these terms is made for convenience, but does not require any particular orientation of the described components.
As generally noted above, certain embodiments of the presently disclosed subject matter may include a system and a method that facilitate efficient management of service delivery to a client. In some embodiments, the method includes collecting service event data and analyzing such data to detect a data trend. In various embodiments, the service event data may include any data capable of being analyzed for trends that may, in turn, be used for providing service to a client, including, but not limited to, system failure data, failure mode data, service records, patient data, or the like. In one exemplary embodiment, the data trend is a reliability trend with respect to a device, which may indicate an increase or decrease in reliability of the device or an associated component over a given time period. Based on such a trend, future client demand for servicing of the device or the component may be predicted, and resources may be allocated based on the prediction, as discussed in greater detail below.
Turning now to the drawings, and referring first to
Referring to
Such data may be stored in, or provided by, the memory 14 or mass storage device 16. Alternatively, such data may be provided to the microprocessor 12 via one or more input devices 18. The input devices 18 may include manual input devices, such as a keyboard, a mouse, or the like. In addition, the input devices 18 may include a network device, such as a wired or wireless Ethernet card, a wireless network adapter, or any of various ports or devices configured to facilitate communication with other devices via any suitable communications network, such as a local area network or the Internet. Through such a network device, the system 10 may exchange data and communicate with other networked electronic systems, whether proximate to or remote from the system 10.
Results generated by the microprocessor 12, such as the results obtained by processing data in accordance with one or more stored routines, may be provided to an operator via one or more output devices, such as a display 20 and/or a printer 22. Based on the displayed or printed output, an operator may request additional or alternative processing or provide additional or alternative data, such as via the input device 18. Communication between the various components of the processor-based system 10 may typically be accomplished via a chipset and one or more busses or interconnects which electrically connect the components of the system 10. In one embodiment the exemplary processor-based system 10 can be configured to facilitate service delivery for one or more systems, such as medical systems, as discussed in greater detail below with respect to
As also discussed in greater detail below, the processor based-system 10 may be configured to facilitate analysis of service event data and the performance of service rules associated with functional systems, as well as management of service delivery with respect to such systems. Embodiments of such functional systems may include a medical system (e.g., an imaging system, a diagnostic system, a monitoring system, or the like), although data and rules pertaining to non-medical systems (e.g., security systems, industrial systems, etc.) may also or instead be analyzed in full accordance with the present techniques.
An embodiment of the medical devices 36 may include imaging systems of one or more modalities, such as magnetic resonance (MR), computed tomography (CT), positron emission tomography (PET), X-ray, tomosynthesis, or the like. It should be appreciated, however, that the presently disclosed technique may also or instead be used in association with patient monitors, diagnostic devices, other medical resources, or some combination of these devices and systems. Such other medical resources may include, among other things, data storage or processing systems, such as computer workstations, servers, picture archiving and communication systems (PACS), radiological information systems (RIS), and so forth. While the embodiment of the system 10 can be described in combination with a plurality of medical devices, the system 10 can be in combination with non-medical devices.
As illustrated in
An embodiment of the method 40 includes a step 42 of collecting service event data from a plurality of devices, such as the medical devices 36. The service event data may be collected in various ways. For example, in one embodiment, the data processing system 34 may receive the service event data from medical devices 36 configured to automatically transmit such data to the data processing system 34 via the network 38. In other embodiments, the data processing system 34 may be configured to request service event data from the medical devices 36 via the network 38, an operator may manually input the service event data into the data processing system 34 based on information from a client or service technician, or the data may be collected in any other suitable fashion.
The service event data may include a wide array of data relevant to service delivery for a device or client, such as a medical device or healthcare institution. For example, the service event data may include occurrences of failure modes with respect to one or more medical devices 36 used by a client, such as medical devices deployed in a healthcare facility or in the field. In some embodiments, service rules may be generated and deployed in conjunction with the medical devices 36 and may be configured to detect failure mode occurrences and to provide an indication of such an occurrence to facilitate servicing of the medical devices 36. Device failures may, of course, be associated with particular failure modes without such service rules based on information received via input from a client or service technician. It should also be noted that, while certain service rules may be triggered upon the occurrence of a failure mode, other service rules may be adapted to detect and indicate a predicted device failure that is likely to occur in the future unless the device is serviced. Such predictive indications allow pre-emptive servicing of the device by a service provider before device failure, thus minimizing downtime of the device and inconvenience to the owner of the device. Accordingly, the service event data may also include data pertaining to predictions of future failure mode occurrences.
The embodiment of the method 40 may also include a step 44 of analyzing the service event data. In some embodiments, the service event data may be treated as a reliability growth problem and analyzed via any suitable mathematical model, such as a Duane model or a Crow-AMSAA model. By analyzing the service event data via such models, the data processing system 34 may detect changes in reliability of the medical devices 36, or an associated component, over time.
For example, performance of a medical device or a component, such as an X-ray tube or intravenous (IV) pump, may be analyzed in accordance with a Crow-AMSAA non-homogeneous Poisson process (N.H.P.P.) model. It will be appreciated that such a model includes various assumptions, including that failure arrival times are independent from one another and are identical within a time segment, and that reliability of the device or component may change during testing. In one embodiment, the failure intensity of the device or component may be approximated by a Weibull function:
f(t)=λβTβ−1,
where λ is a scale parameter and β equals one minus the reliability growth rate of the device or component. Consequently, a value of β greater than one can suggest a negative reliability growth rate or trend (i.e., reliability of the device or component is declining over time), while a value of β less than one may indicates improved reliability of the device or component over time.
Using this model, the cumulative number of failures over time may be considered to derive the value of β. For example, and as shown in
Consider such modeling with respect to a particular component, such as an IV pump common to a population of medical treatment devices. Such a population may include any number of devices, although it will be appreciated that a greater number of devices may result in increased confidence levels and lower margins of error with respect to interpolations or estimates derived from the analyzed data. As shown in
Assuming the plotted time can be measured in days, graph 60 illustrates that the first IV pump failure for the modeled time sample can occur at approximately 400 days of cumulative device operational time, while other IV pump failures can occur at approximately 3,200 days, 6,000 days, 7,000 days, 12,000 days, 13,000 days, and 15,000 days. A linear best-fit curve 70 may be interpolated from the data points 66 and used for various purposes, including to calculate the value of β, to calculate the frequency of future pump failures, or to compare the failure rates of a device or component over the given time sample relative to that of another time sample, for instance. As generally noted above, a value of β greater than one can indicate a reliability of the IV pump (or other component or system) can be declining over time, while a value of β less than one can indicate improved reliability of the IV pump or component over time. Consequently as illustrated in
Returning to
Additionally, based on the data analysis described above, the method 40 may include predicting a future client demand for servicing of the analyzed component or system. For example, with respect to the IV pump example provided above, the data processing system 34 or a user thereof may calculate an increase or decrease in reliability of the IV pump in proportion to a change in future servicing needs of the IV pump. Particularly, an increase in trend in the reliability of the IV pump may suggest that demand for future servicing of the IV pump will decrease, while a decrease in trend in reliability may be suggest increased demand for servicing of the IV pump in the future. On at least this basis, the data processing system 34 or a user may, as generally indicated in step 52, generate and recommend a certain future resource allocation, such as the number of IV pumps needed in the service provider's inventory, the level of staffing associated with servicing of such a component, or the like.
In one embodiment, the method 40 may also include a step 54 of outputting a report 56 that includes one or more of the following: a trend in the analyzed service event data, a predicted future client demand, and a recommended resource allocation. For instance, one embodiment the report 56 may include an illustration of a recommended resource allocation to implement. Another embodiment of the report 56 may include an illustration of a reliability trend of a device or component. The method 40 may also include predicting a future client demand and allocation of resources dependent on the reported trend generated by the system 10. An embodiment of the step 54 of outputting the report 56 may also include one or more of the following: displaying the report 56 on a display of a computer system, printing the report 56, storing the report 56 for future retrieval, and any other suitable manner that facilitates present or future communication of the information contained in the report 56 to a user.
A technical effect of the subject matter described herein may include, among others, facilitating optimization of service delivery, allowing better prediction of future client needs, and enhancing an efficiency of a client to meet those needs. Additionally, while certain examples are generally discussed above with respect to particular devices or systems, it will be appreciated that the present technique may also find applicability in modeling and predicting service needs on a broader scale, such as for entire departments, facilities, institutions, or even regions. For instance, using the technique described above, one may collect data from one or more healthcare facilities and model trends in the data to predict future demand for one or more resources and to efficiently allocate resources for such demand. More particularly, in one embodiment, patient data may be obtained and modeled to detect a nosocomial outbreak trend in a hospital or region, providing a service provider with an early indication of the outbreak and allowing the provider to allocate resources in a desired manner, based on the detected trend, to treat the outbreak. Additionally, in another embodiment, data related to service delivery quality (e.g., customer complaints) may be analyzed as generally discussed above to detect trends in the quality of service delivery and desired changes (e.g., to resource allocations, training, policies, or the like) may be implemented based on such analysis.
This written description uses examples to disclose the invention, including the best mode, and also to enable any person skilled in the art to practice the invention, including making and using any devices or systems and performing any incorporated methods. The patentable scope of the invention is defined by the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements with insubstantial differences from the literal languages of the claims.
