The value of obvious, especially when it's not
As clients learn more about what we do, the braver ones ask "Isn't this all kinda obvious"? A variant of this question is: "We know what our issues are, we don't need software to tell us what we already know". I'm reminded of the joke that a consultant is a person who borrows your watch and then charges you to tell you the time. When our analysis shows the ICU is crowded, how does it help if everyone already knows the ICU is crowded? Nobody needs to pay for a photo of an elephant if we all know one is in the room.
For example, our elective smoothing module shows that if hospitals do the same number of surgeries each day of the week instead of bunching them up on one or two days, peak inpatient bed census will usually go down. Furthermore, consider an orthopedic department that aggregates knee replacements as a "joint camp", where a cluster of elective patients all have surgery on Monday and then move through PACU, inpatient recovery, and then physical therapy. It doesn't take fancy math to see that doing two cases a day instead of ten in a single day will reduce peak demand on inpatient beds and other post-surgical resources.
The value of our software is the ability to quantify the opportunity by moving from joint camp to a smoother schedule. Given how disruptive it is to change around surgeon schedules, leadership must do everything possible to make sure that the benefits are worth the costs. It's not easy to make a cost - benefit decision if the costs and benefits are vague. We can model the savings and reduction in peak staff workload from a smooth schedule, and this can be weighed against the cost of adding weekend services and changes to surgeon schedules. This change may not make sense. Or the opportunity may be so big, even skeptics are forced to agree.
In any hospital, there may be at least half a dozen operational changes that could improve efficiency through OR optimization, re-assigning beds, or updating staff schedules. Which one is the biggest opportunity? Where does one start? Again, by quantifying the benefits of each scenario, leadership can use data to assist in the decision instead of guessing.
And the obvious is not always obvious. For example, we're often asked to study how moving cases to Saturday will affect inpatient bed crowding. If variation in length of stay is large, it turns out that moving cases to Saturday doesn't make much of a difference to peak census. This surprising result is a consequence of units with high unpredictability -- scheduling two days with no surgeries is statistically the same as one day without surgery. What's becomes obvious is not disrupting schedules for a change that won't yield operational improvements.
We can also show the value of incremental change spread over months or even years. For example, a service that crowds procedures to one or two days won't smooth overnight. In fact, we've found it's a counterproductive academic exercise to present an "ideal" schedule that disregards historical work patterns. Our simulations show how small changes produce small results and how over time this accumulation of small results winds up making a big difference. Every time a surgeon retires and a new surgeon is hired, there's an opportunity to design blocks that will create the smoothest schedule. We don't present a one-time analysis from a snapshot of data, we run continuously in the cloud so clients can always have the most updated view of their hospital.
The analogy is like a person on a diet. Everyone knows eating fewer calories leads to weight loss. It's calories in versus calories out. But telling someone to "eat less" rarely works. Hospital IQ is like the dietitian who says "You currently eat five doughnuts a week. Cut this down to two a week and you'll lose 1 pound every three weeks for the next six months". If this is too much of a sacrifice, the dieter can opt for a smaller reduction with smaller gains. If the dieter wants to see faster results, they can cut out more donuts to know what to expect in terms of results. Dieters know what they need to do to lose weight. But the goals are much more manageable if they're put on a plan that's backed up by data and allow the change to be incremental.
Finally, the obvious is what some clients are actually looking for. They have a good idea what they need to do, they just need data for the precision necessary to get to the finish line. We can turn a strategic vision into tactical steps that can be incrementally executed and adjusted to real-world feedback. By showing multiple scenarios with various degrees of cost and opportunity, leadership can build consensus around the best path forward.