Staff Benchmarking
Does this add value and should we
pursue this more widely?
Francis Thompson
West London Mental Health Trust
National context
 NHS Constitution, NHS Act and one of the six essential
CQC standards place a duty on Trusts to ensure that
staffing levels are adequate;
 Francis (no not me);
 Prime Minister’s commission;
 The Centre for Social Justice (2011) argue that all acute
inpatient wards should be seen as specialist areas and
staffed accordingly;
 Increasing acuity (HTT);
 The Royal College of Nursing (2007) survey RMN’s
showed that two thirds deemed inpatient staffing to be too
low and 42% felt that staffing levels compromised patient
care at least once per week.
Local Context
- Lack of easily identifiable information at a Trust
level and concerns re acute unit staffing;
- Concerns re differences in staffing between units;
- CQC concerns;
- Lack of clarity regarding safe staffing levels and
lack of a recognised way to measure staffing
needs;
- Context of financial savings.
What we did and some caveats
“Oh, people can come
up with statistics to
prove anything. 14%
of people know that.”
Trust data
Team
Wards (Ex PICU)
PICU
Male
admissions/HDU
Male rehab/long
term
Male Average
Female
Admission
Recovery
OPS
PICU
Average patient to
Range
staff ratio
High Secure
1.4
1.02-2.36
0.60
NA
Forensic services
3.6
3.5-3.8
4.67
4.5-5.2
4.26
1.85-4.70
2.63
1.8-4.05
Local services
4.55
3.72-5.0
5.21
4.65-5.69
3.16
2.9-4.1
2.0
NA
RMN:HCA ratio
1:0.82
1:0.73
1:0.89
1:0.80
1:0.83
1:0.95
1:0.78
1:0.67
NA
NA
Staffing data admission and
recovery wards
Recovery
wards
Ealing (2
wards)
RMN:HCA
ratio
H and F (2
wards)
RMN:HCA
ratio
Hounslow
(2 wards)
RMN:HCA
ratio
Overall
average
RMN/HCA
Average patients per
staff member
(RMN+HCA)
Day
Night Average
4
5.33
4.65
Admission
wards
1 ward
Average patients per staff
member (RMN+HCA)
Day
4
Night
6
1:1
1:0.33
4.4
5.5
1:0.66
1:1
3.3
4.13
1:1
1:0.5
1:0.75
4.2
6.33
5.26
1:0.5
1:0.5
1:0.5
4.88
6.5
5.69
1:1
1:0.5
1:0.75
1:0.66
1:1
Day
Night
Day
Night
4.36
1:0.83
6.05
1:0.5
Grand
average
5.21
1:0.67
3.9
1:0.77
5.21
1:0.78
1 ward
2 wards
Average
5
4.95
3.72
Grand
Average
4.55
1:0.78
Local comparisons recovery wards
Average Number of Patients to Staff Members (RMN and HCA)
WLMHT
Trust 1
Trust 2
Trust 3
Day
4.36
4.58
4.1
4.46
shifts
Night
6.05
6.07
5.6
6.43
Shifts
Total
5.21
5.35
4.85
5.44
Skill mix RMN:HCA
Days
1:0.83
1:0.95
1:0.73
1:0.63
Nights
1:0.5
1:0.5
1:0.62
1:0.5
Average
1:0.67
1:0.73
1:0.68
1:0.56
Points to note
 Disparities noted between wards inside Trusts in
both the areas I have carried out this work;
 Particular differences noted in availability of 9-5
staff;
 Need to include other available resources for a
robust comparison e.g. OT resource etc and this is
not easy to gather;
 It did enable a high level discussion on staffing
and noted some other local interesting points…..
Potential benefits
- Provides some assurance regarding staffing levels
locally and compared to other Trusts;
- Good intelligence to support workforce planning;
- Lever to raise quality issues and argue for budget
protection/enhancement;
- May improve patient care/experience if numbers
felt to be below par;
- Raises unit staffing to board level;
- Opportune time given national drivers.
Risks
 Biggest risk - no benchmark to measure against – what if
we are all too high or low??;
 May be inadvertently be used as quality measure;
 Crude - difficult to compare units in different contexts and
areas;
 If not done carefully may isolate nursing numbers from
other MDT input;
 Complexity of data collection and peripherals such as
bleep holders;
 Data may be felt to be sensitive by Trusts;
 Financial implications of having comparatively lower
staffing;
 Can the numbers influence change?
 Constant flux and change – this will only ever be a
snapshot.
Points for discussion
 Given the risk, benefits and complexity is
this worth pursuing?
 If so is this better done locally or more
broadly?
 What could be done with the outcomes?
Would this lead to rigidity?
 If this is pursued it would only be a snapshot
and timeframes and shared data tool would
need to be developed.
 Any more thoughts, comments or
questions?
 Any more?