For decades, standards organizations and jurisdictional authorities have required that health care organizations maintain historical records on medical devices and ancillary equipment. Accurate equipment histories provide evidence that devices are routinely checked for proper performance by “experts,” incipient problems have been identified and resolved, and actual incidents are investigated so prevention protocols may be adopted.
Recording these equipment events provides a sound risk management approach to maintaining a safe and effective environment of care. Most health care organizations maintain service histories and many oganizations use computerized maintenance management systems (CMMS) to document this information.
Equipment support capabilities range from well-staffed clinical engineering departments at large facilities to completely outsourced programs at clinics and small hospitals. Whether outsourced programs are provided by manufacturers or independent organizations, the provider usually performs the task of documenting service history. While most adhere to professional standards, there is an inherent bias to portray the program in a positive light when the provider assumes the maintenance responsibility for a fixed fee. Detail can disclose profit margin. Regardless of the entity providing the service and documentation, a health care organization is still responsible for the accuracy of the records. In-house biomedical engineering departments hopefully track the service they deliver to prioritize their time according to the need expressed through trouble calls, incidents, and use errors. This same level of oversight should be applied to services provided by third parties.
Many organizations use available CMMS or custom applications for documenting service history. Software has sufficiently evolved to allow service events to be recorded quickly in reasonable detail. While many effective CMMS systems are available, they lack one important function: the ability to translate service history into an accurate maintenance forecast.
Maintenance management systems should contain the service records for each device in the inventory. The collection of service data should follow the format to be used to estimate maintenance budgets. Most service providers break down labor, travel, and parts by service type, hours, hourly rate, and component cost, and this provides a useful pattern to create tables that will house predicted and actual service values in the same format. The budget “calculator” uses these values to provide work effort and cost estimates. The budget should be broken down by scheduled inspections, labor rate, type of labor (preventive, corrective), travel, generic parts, glass and specialized components (x-ray tubes, detectors arrays, etc), calculated labor and travel costs, parts, and component costs.
Using the same table format for budget rating and service history allows “predicted and actual” work effort and cost to be compared. As the device population grows, the accuracy of the forecasts improves significantly. Using standard naming conventions for devices greatly enhance sorting and filtering capabilities. Predicted and actual service values are sequestered in similar table structures. Dynamic averages are maintained that form type-specific benchmarks within the budget calculator.
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Many might argue that this approach asks technicians and engineers to become underwriters, but who is in a better position to predict cost than those who perform the service? Equipment management programs must be priced for the devices they intend to cover. It will come as no shock that many program “underwriters” have far less equipment experience than the average service professional. What they do have is a disciplined approach to forecast service events in light of loss history.
I make the case that equipment maintenance costs can be accurately predicted by in-house engineering staff if the proper tools and instruction are provided. When maintenance management systems are equipped with appropriate rating and service history tables, a “rating engine” can be developed that allows the comparison of predicted versus actual performance. Budgeting is neither difficult nor time consuming. If the equipment and event populations are integrated in a shared repository, the statistical significance is greatly enhanced. A Web-based system protecting individual client and device identity would allow average rating and loss values to guide device maintenance budgeting with a high confidence level. Such a system does exist, and it is equipped with all of the “standard” tools of most CMMS systems. Whether organizations choose to upgrade their equipment management systems or utilize the system described, the skills to accurately predict equipment support costs are easily mastered. Accurate, device-based maintenance budgets greatly reduce the need for contracts and managed programs. Practice and the right tools will allow equipment maintenance to be managed within the operations budget with significant cost avoidance. When major risks are identified, contracts or “stop loss” insurance can be used to protect the budget.
Michael Dickerson, president and founder of SysMetrix Inc, Carmel, Ind, provides engineering solutions focused on health care, including equipment maintenance underwriting and acquisition and replacement planning. www.sys-metrix.com. For more information, contact .
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