Flow is what we do

(The left to right, over and under concept)

Mike Ardagh

Professor of Emergency Medicine, University of Otago, Christchurch

Emergency Medicine Specialist, Canterbury District Health Board

National Clinical Director of ED Services, New Zealand, 2009-14

Observations and extrapolations regarding

‘best practice’ hospital operations

The problem

Demand exceeds capacity

The problem

Demand exceeds capacity

• Queues form

– For cubicles, nurses, doctors, CT scans, operating theatres, aged

care beds, etc etc

• A ‘backlog’ of work develops

• Now the same capacity needs to cope with;

– The ongoing demand, and;

– The backlog of work

So

• The queues get longer and the backlog gets bigger

• Now capacity needs to cope with;

– The continuing demand

– The bigger and bigger backlog

Worse still

• Queues introduce delays over and above the delays that

produced the queues

Recognisable consequences

• ED overcrowding

• Outliers (admission to the wrong ward)

– Cancelled elective surgery

• Safari ward rounds

– Delayed decision making

• Prolonged hospital LOS

– Further reduction in capacity

This is bad

• For patients

• For us

• For the health dollar

Queues are evil

demand

I’ve got

patients

I’ve got

beds

Average demand = 50

Capacity = 50

= demand exceeds capacity half the time

Peak demand = 100

Capacity = 100

= capacity exceeds demand all of the time

85th percentile or 85th

percentile plus a little,

or 85% occupancy

= popular conceptual capacity buffers

But - the key point is this:

When a patient needs ‘a bed,’ (or

whatever), it is available promptly

so a queue doesn’t form

But the reality is that demand tends to

match capacity and there usually isn’t a

‘capacity buffer’

So, how do we stop queues developing when

capacity and demand run so close?

We need a very responsive system

A very responsive system

1. Recognises early when demand is threatening capacity and

queues are developing

2. Responds quickly to modify demand and/or capacity so

that queues are avoided or cleared

A comprehensive model of a responsive

system

A comprehensive model

Left to right, over and under

Patient Journey

Governance

Operations

Patient Journey

Governance

Operations

Patient Journey

Patient Journey

Governance

Operations

• Structure

– Authority, representation, clinical governance,

operational leadership, street wisdom, project

grunt

• Method

– Informed, diagnostics, project methodology

• Plan

– Comprehensive, prioritised, planned

Governance

Patient Journey

Governance

Operations

• Forecasting demand in the future

– Days, weeks, months out

• Knowing demand now

– Daily operations

– Recognising when demand is threatening

capacity

• Matching capacity and demand

Operations

Matching capacity and demand

• Medium to long term

– Eg winter planning

• Short term

– Daily operations of all capacity (not just beds

and not just nurses)

• Crises

– Early recognition

– Early and aggressive response

Options if demand exceeds capacity

1. Reduce demand

2. Free up capacity by improving processes

(efficiency, productivity)

3. Better match demand and capacity in time

and space (smoothing)

4. Purchase more capacity

5. All of the above

Smoothing demand

Smoothing demand• Daily smoothing

• Discharge before the admission surge

• Weekly smoothing• Bring electives in when acute demand is least

• Discharge on the weekend before the busiest

admitting day of the week

• Seasonal smoothing• Increase elective activity over summer

• Decrease elective activity over winter

A comprehensive model

Left to right, over and under

Patient Journey

Governance

Operations

Michael.ardagh@cdhb.health.nz

Thank you,

come again