Understanding patient flow in hospitals

21 Understanding patient flow in hospitals
Figure 6: Example flow scenario over the course of a day
12.0%
10.0%
Cumulative queue
8.0%
Proportion of daily patient moves
6.0%
4.0%
2.0%
0.0%
Flow rate per hour
Queue dependent
on clean/transfer
rate
-2.0%
-4.0%
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Time of day (24-hour clock)
Queuing is occurring where numbers are negative. Source: HES (2016)
hotel services budgets, moves to 12-hour shifts and an underinvestment in logistics
support to deal with higher patient volumes.
The challenge of achieving early discharge
In theory, discharging patients early in the day makes sense: it ought to be possible to
plan discharge between 8am and 12 noon with some reliability. In practice, however,
it is much harder to achieve, as shown by Figure 7. One reason for this is that only
10% of patients stay more than 7 days – but that same 10% use 65% of the beds. The
average length of stay for patients staying over 7 days was 18.8 days in 2014/15. In a
32-bed ward caring only for this group of patients, this translates in to less than two
discharges per day.
Figure 7: The challenge of achieving early discharge
Proportion of hospital
stays (spells) by
duration of stay
0 days
58%
1-6 days
32%
7+ days
10%
Proportion of beds occupied
by duration of stay
0 days
10%
1-6 days
25%
7+ days
65%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Source: HES (2016)