It is related to a previous post: The Unnoticed Crisis in Healthcare.
I was hoping you could tell me if there have been any discussions amongst Healthcare Professionals about an effect known in Aviation as "Region of Reverse Command" or "being behind the power curve".
Dr James talks about Systems Theory, IIRC, and I've had an interest in it (via Feedback & Control Theory) since my Uni days in the 1970's. But I've no idea if the concept is widely known/acknowledged within Healthcare.
[I've studied Queuing Theory a few times, including for my work in Telco software and for I.T. performance analysis. It's useful for modelling this problem.]
Here's a simple intro with a good graphs:
And a better technical description, though I found less understandable:
Here is someone trying to apply the concept to economics, to show it's a well-known effect:
[I didn't read this in full, just skimmed the intro :-)]
"Region of Reverse Command:" Consequences of the Industrialized Country Debt Explosion"
I hope you can find some time to read this long piece and that I'm not stating something already well known and understood.
Here's my theory or model and then a question...
The underlying cause of a "reversal of command" is two opposing system responses:
- one that starts low and increases along the x-axis, and
- another that starts high and decreases along the x-axis.
In "normal command", the first (increasing) response is clearly dominant with the other response negligible or zero.
First, why would you even want to change?
It's not about Patient Outcomes, effective use of Public Monies, it's far simpler:
Because of the "bath-tub" curve, spending the same amount of money can achieve two different outcomes: low or high throughput.
Professional Pride says you aim for the best outcomes for those who've trusted themselves to your care. (And, if you can, those who've entrusted you with their money.)
So where are these countervailing forces/effects in a Hospital or Healthcare System?
In hospitals and healthcare, we have two opposing effects along the axes of time and cost:
- average cost of service increases with staffing, because for service times and waiting times to decrease, queuing theory says that both more 'servers' are needed and that their utilisation (time busy serving/working) decreases. You can see this in every supermarket or bank, long queues result when the arrival and service rate are too close.
- so there is a 'cost vs total time' curve (total = service + wait time). Generally, you can reduce average costs by reducing staff, at the cost of increasing patient wait time.
- the average cost of patient treatment increases with very long wait times for treatment.
A breast-cancer case caught early in stage-1 may be treated for $30,000 with very good outcomes.
Each year the person has to wait for treatment, the cost of treatment increases and outcomes reduce.
An example from the USA was a woman who waited for 7-8 years until her breast cancer had become
stage-5. The treating oncologist estimated a treatment cost of $150,000 then and survival of only 12-24 months... At every level it was more expensive for treatment to have been delayed. [Source: Dr Otis Webb Brawley]
- Complication rates in known, untreated conditions, such as 'discretionary surgery', increases with wait-time. Patients 'jump the queue' (and delay others) when treatment becomes necessary due to an emergency admittance. There are no medical benefits, only downsides, from extending treatment times past the known treatment benchmarks. By pushing patients into this self-selection-by-emergency, total treatment costs are increased, presumably by a large margin.
- Long E.R. waits are documented as having a similar counter-productive effect.
"save money" by reducing staff costs.
This is without considering other feedback effects that reduce efficiency and effectiveness with increasing staff load/utilisation. Stressed staff have increased rates of sick leave and (much) higher
turnover. Being forced to act in haste causes staff to attempt short-cuts and to omit 'unnecessary' steps, such as cleaning-up, tidying up and replacing supplies. This creates inefficiency and increased service time later as necessary tools, equipment and supplies are not found or available.
From the aircraft "reverse command" model, we know two things:
- there is an optimum performance region, without clearly delineated boundaries [can slide into dysfunction without noticing]
- applying more "power" (or money) AND applying less "power"/money can not recover the situation.
In aircraft struggling "behind the power curve", applying more power decreases speed (the very definition of this 'reversal of command' region), so you can't power your way out.
Because the aircraft is very close to stall, decreasing power will force a stall, so cannot be used to recover the aircraft. Pilots can't fly their way out of this abnormal situation as they normally would...
The solution is to do two things (drop nose, increase power) and lose a significant amount of height until normal flying speed + attitude is regained. If the aircraft has entered the region of 'reverse command' on takeoff and is too low to recover, then a crash may be inevitable if the terrain is difficult and there is insufficient space to manoeuvre.
Trainee pilots are taught to identify "minimum controllable speed", not just stall speed, so that they may recognise an incipient transition into the region of reverse command and avoid it.
For a Hospital or Healthcare system that has fallen below minimum-safe staffing-levels and is locked into a rising cycle of longer-waits and higher average treatment cost, nothing can be done internally to
recover the situation: spending cuts (ie. reducing head counts), counter-intuitively, can only result in increased costs.
To recover the system back to minimum staffing-levels and optimal costs requires external actions that:
- fix long-term infrastructure problems exacerbating inefficiency and ineffectiveness problems,
- identify "critical paths" and both to remove impediments to efficiency (waste) and add systems and staff to increase their performance and effectiveness, and
- draft additional staff or services (even external) to clear the backlog ("lose height").
The total time to recovery must include restaffing, additional staff training in Process Improvement, the establishment and bedding down of the new improvement systems, and the redefinition and stable-operation of management processes, metrics and targets. Like an aircraft, during the transition back to "normal control", the Hospital/healthcare system is extremely susceptible to "inappropriate control inputs". Which is a euphemism for "you will crash if you don't stick to the plan" - if a pilot pulls out of the recovery dive too early, they will only re-enter the region of "reverse control". A complete waste of time and a precious resource - altitude.
The biggest challenge to system recovery is a failure of management or political will.
Demanding change in unrealistic timeframes and budgets is guaranteed to not just be counter-productive, but cause maximum damage.
Unless there is resolute, unflinching long-term support 'from above', like the small aircraft after take-off struggling to gain height whilst "behind the power curve", its far better to struggle on, than to attempt
change without sufficient "economic altitude". DO NOTHING if the situation isn't obviously safe.
An extreme view would be to replace all management because "they got us into this mess and won't get us out". Whilst this will be true for some individuals, it ignores the synergistic and performance multiplier effects of teams and breaks Deming's Rule: Drive out Fear.
A sudden, complete replacement of management will be counter-productive and as useful as ejecting the pilot of an aircraft struggling "behind the power curve". Changing those in control on the way to recovery has to be considered and careful.
A note on the optimum speed of aircraft and how that applies to other systems, like Hospitals and Healthcare.
There are many metrics that can be optimised, this effects the pilots (cf. managers) decision of attitude, speed and throttle settings. Do you want to go as far as you can, stay aloft as long as you can or limit
your loss of height ('sink rate')? These all require different, and quite precise, aircraft configurations.
Skilled and informed managers will need less support and intervention to achieve a whole-system turn-around by implementing focussed turn-around "trials".
Pick one small, significant area and increase funding and support while introducing Process Improvement (and metrics/performance analysis systems) training and processes. There will be an additional costs during the transition phase, but compared to a "Big Bang" project, well within normal budget fluctuations.
When that change has settled, the first area will be more efficient and effective, requiring a smaller budget, *and* because you've chosen an area that influences the costs and efficiency of other areas, realise savings throughout the rest of the system.
Then, rinse and repeat.
Find another "hot spot", preferably with wide-spread efficiency impacts, potential high internal payoffs and modest change costs and timeframe.
As adaptable staff see change, they will be more confident that every area can be turned-around and that there's hope: their individuals efforts and insight will be useful, even used, within the organisation.
Whilst this approach may take longer than a "Big Bang" approach, it has the least impact on yearly budgets and the staff aren't left feeling "it was done to us", but "we did this" - a much more robust and 'empowered' stance. They finish knowing they have the tools and capability to execute the next turn-around or address a problem when it arises.
Is this model/idea of 'region of reverse control' novel within the Hospital/Healthcare community?
If so, is there a good way for me, an interloper, to write something that will be given any credence or is there someone internal who would be the best person for me to approach?
This model is useful, especially if real measurements can be made of systems 'in the reverse region', to mediate a conversation with politicians and the public (taxpayer).
It suggests a Nirvana for Politicians, lowered Healthcare/Hospital System spending and better health outcomes, and that it is possible, plus a way to get there.
But it also says a) it won't be free and b) nor immediate, that the Politicians have to be both patient and resolute. And hold their top public servants accountable for progress. All of which might be challenging.
VC Design cruising speed, also known as the optimum cruise speed, is the most efficient speed in terms of distance, speed and fuel usage.
VNE Never exceed speed. [literally, the wings fall off if you go faster]
VBE Best endurance speed – the speed that gives the greatest airborne time for fuel consumed. This may be used when there is reason to remain aloft for an extended period, such as waiting for a forecast improvement in weather on the ground.
VBG Best power-off glide speed – the speed that provides maximum lift-to-drag ratio and thus the greatest gliding distance available.
[different to minimum 'sink rate', the speed to retain the most height. This may be necessary in a situation like the aircraft that landed in the Hudson, seconds after take-off they lost both engines they had minutes to fly. They were never going to get to another airport, couldn't benefit from extending their time aloft, but needed to maintain as much height as possible to clear all obstacles.]
The symptom and solution I'm addressing here is not unrelated to Dr Brent James' Quality Improvement work.
But it differs in its exact focus and implementation (not Patient Safety and Quality of Care, but System Efficiency/Effectiveness, then PS, Q-o-C.)
It also identifies a problem and its symptoms/causality that Dr James wasn't seemingly trying to address.