Most healthcare imaging facilities are not able to report metrics on their diagnostics equipment usage. From my discussions with healthcare leaders, there seems to be a common thread unifying their concern – identifying and isolating bottlenecks that are deterring optimal utilization of the big iron machines.
Despite an array of monitoring systems from CMMS to EVMs, there are wide-ranging areas of pain points that are yet to be addressed, including optimal shift operations, profiling scheduling patterns, and segmenting examination throughput.
In this post, I have identified the three primary questions that leaders can have to create tremendous value from optimal equipment usage.
What are the Current utilization and additional capacity available?
Accommodating a few more exams per day per device could ramp up the share of the facilities' output and subsequently raise its profits. So, the first question to ask is what is my current utilization and how much additional capacity do I have per device or modality?
Knowing the current utilization and the free capacity would help you understand how much more you can stretch your existing investment without many optimizations. While this is a good start, the more important questions start coming up when device utilization increases and hits the over-utilization threshold prompting additional capital investment. So that leads us to the next important question.
What levers do I have to get more out of my existing investments and what is the cost/benefit ratio of tweaking these levers?
When you max out on the capacity in your diagnostic Centre, taking the capital investment route to add additional capacity is the most expensive option. To remain a viable player in the diagnostic services, imaging centers must maximize their existing investments and exhaust all optimization options before investing more.
Imaging leaders should be prepared to reevaluate their operating models to look for opportunities to increase the number of exams that could be accommodated on a particular day or during an entire week or month, by comparing the current utilization over a specific period for each modality.
The number of exams you can do on a given device is proportional to the exam duration and the change over time between patients, the two key levers that you can optimize. While decreasing the time it takes to perform exams or the change over time between patients has its own costs, doing a what-if analysis on possible increase in exam capacity by either reducing the time it takes to do an exam or by reducing the patient prep time (change over time) can significantly help in deciding the best way forward to further optimize your facility.
How are my exams scheduled? Should I optimize my operator shifts to match the patient volume? Or Should I incentivize patients to come at specific times of the day?
Looking at exams scheduled over a longer period can uncover some very interesting insights. Data collected over a period start showing insights that are lost in the day to day operations. Analyzing schedules will show up hotspots in your scheduling, help you decide if it would make sense to plan the lunch hour for the operators at different times or even schedule shifts in such a way that the maximum number of operators are available during the peak periods of operation.
Another option that can be explored based to reduce scheduling hotspots is to incentivize patients to come at specific times of the day when the utilization is low. While spreading the schedule doesn’t increase the daily throughput, it improves patient experience and operator utilization.
Routine reports are certainly not enough in assessing schedule delays; just knowing the number of exams from billing data does not paint the right picture of the current state of the operations either. We need to identify workflow improvement opportunities to gain visibility into more granular metrics such as the three questions I have described here.
Optimal utilization of the big iron machines ultimately requires a thorough understanding of the total duration of the interaction a patient has from one door to another at the healthcare facility. This means identifying the granular metrics to understand the difference in time spent in billing, scan, transport, examination, changeover, and system readiness. This will lead to deriving new value from the existing inventory and as a result, a more viable connected healthcare imaging institution.
Do you agree?
Are there other ideas that can be explored?
I am happy to hear if you have a different approach. Do reach out to me: firstname.lastname@example.org
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