Anyone who has worked in a hospital imaging department, or outpatient center that utilizes diagnostic imaging, knows the impact of a system outage. It doesn’t matter if the cause of the downtime is a network issue, integration problem, or the application simply stopped working, the results are the same: frustration lost revenue and degraded patient care. In today’s digital world imaging is integrated into many clinical operations, when images are unavailable, be they new captures or priors for comparison, many clinical workflows stop. It may or may not surprise the reader that the most requested feature of any PACS during a selection process is proactive IT monitoring of the system (Joshi et al., 2014). In addition to the clinical impact there are revenue implications of system downtime. Due to imaging system outages alone, a medium-sized (200-bed) facility’s lost revenue can amount to almost $300k annually. (Basu, 2015; Becker, Goldszal, Detal, Gronlund-Jacob & Epstein, 2015; Becker’s Hospital Review, 2014). In addition to the direct impact of lost revenue, secondary impacts occur, which can include rescheduled procedures, delayed surgeries and postponed discharges. These secondary impacts, while important, are outside the scope of this paper and should be addressed in subsequent research.
Demand for Proactive Monitoring
According to Joshi et al. (2014), 32% of radiologists rated system continuity and functionality as the top priority. Subdivisions of this category include downtime prevention with a global weight of .179 and tools for continuous PACS performance monitoring weighted at .085 (Joshi et al., 2014). For comparison the highest rated image manipulation feature in PACS selection, convenience, and responsiveness in the manipulation of images with a global weight of .068 (Joshi et al., 2014). PACS administrators and IT professionals rated these sections even higher, with real-time monitoring being a focus for 47% of respondents. These results should not be overly surprising; if the system is not available, other features such as user-interface or image manipulation, become irrelevant. A key takeaway is that both the IT and clinical user communities place significant value on system uptime and monitoring.
Turning to the purely financial side of imaging-downtimes, it is important to note Basu (2015) and Jackson (2012) report that 37% of a hospital system’s revenue is derived from imaging sources. Additionally, an application of Becker’s CFO Report (2014) reveals that annual per-bed revenues, which are attributable to imaging, average $370,190. A further breakdown shows a per-bed imaging revenue of $189.54/hour. Armed with these figures the real impact on revenue, from a system outage, can be calculated. According to Becker et al. (2015) the average duration of a downtime is 3.5 hours, which, for the aforementioned medium-size facility, results in a lost revenue implication of $132,716. On the low end of estimates is Change Healthcare’s evaluation of downtime which indicates $15,833 per-hour of lost revenue *. This generates a facility cost of $55,415, for a single downtime incident. Averaging these two estimates yields a per-downtime-cost of over $94,000, and this is without factoring in the residual impacts of patient care or physician satisfaction.
While the lost revenue of a downtime incident is clearly significant, the frequency must also be taken into account. The expected number of (3.5 hour) downtime incidents range from 2.3 to 7 outages per year (Kolowitz et al., 2012; Becker et al., 2015). Assuming a lower end frequency of 3-4 incidents per year, the lost revenue consequences are compelling, residing somewhere between $282,197 and $376,260. Of course, the dollar amounts will increase as the number of downtime incidents or the number of beds increases.
Limitations and Future Research
Future research can expand on current findings by directly measuring facility imaging revenue instead of aggregating and assuming a percentage of overall hospital revenue. Additionally, future research could increase accuracy by measuring procedure volume as an indicator of size versus current aggregates utilizing the number of beds as a measure of facility size. Outpatient imaging volumes have a tremendous impact on revenue and are imperfectly measured by the number of beds. A final improvement in current research would be to expand the scope beyond the single imaging system of radiology PACS and encompass the ever-expanding role of enterprise imaging and centralized archives in discussions of downtime.
Given the data presented, it is clear the cost of imaging downtime is significant and that its effects on the organization can be far reaching. The financial implications are of a magnitude that demands attention and solutions that are relevant to operations. Fortunately, there are products in the marketplace that go above typical IT monitoring and are able to proactively monitor all aspects of the imaging ecosystem from a single dashboard, which can dramatically reduce the duration of a downtime. Facilities and health systems should invest in such resources to minimize the occurrence of imaging system downtimes and thereby also mitigating the financial impact of downtimes.
*note- The Change Healthcare estimate includes a moderator for % down, and did not specify the number of beds only a “medium” facility.
Basu, P. (2015, April 4). Health System Management. Retrieved from The Radiology Department: From Cost to Profit Center: http://health-system-management.advanceweb.com/the-radiology-department-from-cost-to-profit-center/
Becker, M., Goldszal, A., Detal, J., Gronlund-Jacob, J., & Epstein, R. (2015). Managing a Multisite Academic – Private Radiology Practice Reading Environment: Impact of IT Downtimes on Enterprise Efficiency. Journal of the American College of Radiology, 12(6), 630-637. doi:10.1016/j.jacr.2014.11.002
Becker’s Hospital Review. (2014, January 21). 12 Statistics on Hospital Profit and Revenue in 2012. Retrieved from Beckers Hospital CFO Report: https://www.beckershospitalreview.com/finance/12-statistics-on-hospital-profit-and-revenue-in-2012.html
Change Healthcare. (2017). Quantifying PACS Downtime. Vancouver, BC: Change Healthcare.
Jackson, W. L. (2012, March 13). The Value of In-House Radiology Departments. Retrieved from Diagnostic Imaging: http://www.diagnosticimaging.com/practice-management/value-house-radiology-departments
Joshi, V., Narra, V. R., Joshi, K., Lee, K., & Melson, D. (2014). PACS Administrators’ and Radiologists’ Perspective on the Importance of Features for PACS Selection. Journal of Digital Imaging, 27(4), 486-495. doi:10.1007/s10278-014-9682-3
Kolowitz, B. J., Lauro, G. R., Barkey, C., Black, H., Light, K., & Deible, C. (2012). Workflow Continuity- Moving Beyond Business Continuity in a Multisite 24-7 Healthcare Organization. Journal of Digital Imaging, 25(6), 744-750. doi:10.1007/s10278-012-9504-4