Okay, so I realise it’s been a while but I’m hoping we can still make it work.

That’s me and the blog (not me and you, although it could be you and the blog). Turns out that spouting forth my opinions is really not my natural state, but hey – I’m at an improvement organisation so with the right will, ideas and execution even this blog will start rolling. We’ve all noticed the need for Pete to sort this out …I’m going to use the Model for Improvement to help me out.

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1) What am I trying to improve? > The AIM: There will be a quality blog post every week from 25th November until July

2) How will I know that a change an improvement  > The MEASURES:
1. Number of blogs per month
2. Blog ratings from blog users

3) What changes will result in an improvement? > The CHANGE ideas
1. “Interview myself”
2. Keep it brief (if possible!)
3. Think up topics in advance
4. Have a time and structure I can depend on
5. Stick a link and an image on each post

My first PDSA cycle:

    Plan: Complete my blog post on the train. Prediction: It will only take 20 minutes.
Do: It was kinda cramped on Monday night
Study: Its possible and feasible but editing and upload requires dragging it up at home – all in 40 minutes
Act: Do I adopt, adapt, abandon, test under new conditions or extend the test?
I’ll adapt. Select one fixed time in the week with internet access.

If the MODEL FOR IMPROVEMENT can be used to get my blog going then it can likely be used to fix the Obamacare website, and while we are at it the whole of the American Health Care system. Funnily enough that’s not far off the truth. There is of course a lot more to this than my drivel above. However for each blog I will aim to touch on one basic ‘improvement aspect’ for further consideration plus  reflection on what’s current on the fellowship journey.

 

What’s current?:  ‘Real Time Capacity and Demand Management’.

Last week I attended ‘Cracking the code to hospital wide patient flow’. The focus was essentially ‘Real Time Capacity and Demand Management’.

Patient flow is a major challenge that just about affects everyone in a local health care system in some way.  It’s easy to say “if only (so and so ) did this – everything would be okay”. RTCDM takes an institution out of this mindset to one that brings all hospital departments together with a common goal. No more ‘on red’, emails requesting ‘no more patients’.

The premise:

– Sort out the 8am-2pm window and one will prevent the ‘compression wave’ that causes havoc until the late evening
– You only need to release 1-2 beds per unit/day to go from the cliff edge to smooth riding
– Length of Stay: Move from managing from days to hours
– Accurate daily patient specific predictions in capacity and demand at the ward level combined with an integrative discharge planning meeting are required as the basis.

The challenge:

Flow needs to be strategic objective and high on the agenda executive.  Without that you can forget it.
Each ward 8am discharge huddle predicts:
1. Bed demand  from a) historical data b) known demand
2. Pre 2pm discharges (i.e. the specific patients) and puts together a specific (who, what, when) plan to maximize
Hospital wide bed meeting at 8.45.
1. Capacity is reported IN PERSON by every ward, ED, ITU at the hospital wide bed meeting which occurs daily at 8.45. Also in attendance is representation from theatres, pharmacy, cardio, radiology, cleaning/ environmental, social services etc. Attendance, punctuality and data is compulsory.
2. Those in the red are discussed in a standard manner and patient specific plans take shape across the hospital. Action on promised plans is vital.
– All data is collected in real time and prediction accuracy fed back to wards by email the next day

Case study – University of Colorado results

Post IHI seminar University Hospital Colorado applied RTCDM in 2010.
Since then:
– A&E left without being seen reduced 5.3% > 3.3%
– Average time on ‘divert’ 21 hours/ week > 7h/ week
– A&E ‘front door to floor’: 7 hours to 4.3 hours
– Clean to occupy in less than 45 minutes: 22% > 55%
– Median discharge time: 15:01 > 14:32
– Median Length of stay: 5.7 > 4.11 days

Balancing measures
Admissions/ year actually rose from 14000 to 16800
CMI index (measure of patient frailty) also rose

Bed occupancy currently runs at 87-97% med surg 65% crit care

 

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