While debated for over 30 years, productivity and staffing continue to be a challenging topic for the clinical engineering (CE) community. At the core of this challenge is the lack of reliable indicators substantiated by actual data. This article reports an attempt to evaluate some traditional and newer indicators using data collected from 2 distinct sources. Results confirm early concerns that worked hours self-entered by CE staff are subject to misuse and thus should be avoided. In contrast, good statistical correlation was found for staffing data with several hospital indicators that are consistently collected and widely available. Good correlation with CE department indicators was more difficult to find, apparently because of the lack of reliable records and consistent accounting of all CE resources and expenditures. Although no single, easy-to-measure and easy-to-understand indicator emerged as a replacement for the worked-to-paid-hours ratio, it is shown that a multidimensional model can be built to benchmark productivity and staffing. Calculations from such a model are accurate, but not precise, so the results need to be interpreted carefully. With proper precautions, such comparisons can be used as a good starting point for a more detailed analysis of the differences that could reveal substantive causes such as service scope and strategy, organizational characteristics, and geographical challenges as well as opportunities for major productivity improvements.

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Patient incidents involving medical equipment are fairly common, but it is unclear how many of them are actually caused by maintenance omissions, i.e., improper or lack of scheduled and unscheduled maintenance. This question is important because hospitals have been allowed by The Joint Commission (TJC) to develop their own maintenance practice instead of following manufacturers' recommended frequencies and procedures. This study reports an attempt to estimate the magnitude of such incidents using the sentinel events database collected by TJC. Using worst-case assumptions, the estimates ranged 0.14-0.74 in 2011, which translates into .00011-.0006 per million equipment uses. These extremely low values were confirmed by a survey conducted by AAMI in which 1,526 participants reported no known patient incidents traceable to maintenance practice. Therefore, it seems unwise to mandate clinical engineering (CE) professionals to refocus their attention to manufacturers' maintenance recommendations versus active involvement in technology management and, especially, user training and assistance, to address the most frequent root causes of sentinel events.

Almost since the beginning of clinical engineering as a profession, the need for scheduled maintenance (mostly safety and performance inspections) and its appropriate frequency have been debated extensively but could not be resolved conclusively because of the lack of comparable data. The combination of regulatory requirements typically based on manufacturers' recommendations and concern for patient safety discouraged experimentation by clinical engineering professionals and thus limited the possibility of comparisons within the same organization. Lateral comparisons among different hospitals have been difficult because of different computerized maintenance management systems, failure classification, and reluctance to share information. Using a small set of standardized failure codes, more than 62,000 work orders were classified by dozens of biomedical technicians at 8 hospitals for almost 2 years. These data were used to compare different maintenance strategies adopted for 7 types of medical equipment commonly encountered in acute-care hospitals. No prominent differences were found among the data collected from hospitals that adopted different maintenance frequencies, statistical sampling, and even run-to-failure strategies. Most of the small differences were comparable to the SDs calculated from the data for each maintenance strategy. These results suggest that it is justifiable to adopt a less resource-demanding maintenance strategy for most equipment types, except for the scheduled replacement of wearable parts that was outside the scope of this study.

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