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Measuring to improve management of demand and
capacity – how important is it?
Ruth Glassborow
Quality and Efficiency Support Team
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DCAQ Quick Revision
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Team No of Referrals
CMHT 20
Crisis Team 10
Average Contact Time Per Referral
10
25
Demand in Hours
200
250
Demand in Mental Health services
The amount of time needed to respond to those referrals that
chose to use your service
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Influence and manage the demand for your service by reducing created and failure demand
There are Different Types of Demand
Actual Demand Created Demand
Failure Demand Hidden Demand
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Capacity
How much work you can do in a given time period
Not the same as activity – what you actually do
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Ser
ver
Ser
ver
Ser
ver
Ser
ver
Ser
ver
Ser
ver
Ser
ver
Ser
ver
Queue type A Queue type B
Queue: people waiting to be seen
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Capacity= what we could
do
Activity = what we did
Demand = All requestsfor a service
= what we should do
Waiting list, queue= what we should have done
DCAQ Summary
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Ideally you want to effectively understand and manage
• Demand
• Capacity
• Activity
• Queue
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So how important is data to effectively manage demand and
capacity?
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Its really important but… there is lots you
can do without it
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DCAQ Work
Examples of things you can do without data
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Managing DCAQ without data
– Set specific treatment goals– Implement effective caseload management review
systems– Map your processes and take out un-necessary steps– Make effective use of group work– Effectively manage sickness– Ensure staff appropriately trained so have skills to do
work that presents– Manage meetings effectively
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Managing DCAQ without data
– Set clear eligibility criteria– Implement choice booking– Ensure admin staff have full access and booking
permission for clinic diaries– System in place for un-used appointment slots to
be filled quickly– Clear DNA and CNA policies– Make effective use of telephone contacts– Ensure systems to step-up and step-down
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Managing DCAQ without data
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DCAQ Work
Areas where data can help you make improvements
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At the most basic level
Unless you can measure your demand and you capacity you
have no way of showing if there is a mismatch
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New to follow/up rates – highlighting opportunities for improvement?
Average No of Sessions (Okiishi, 2006)
Most Effective Least Effective
5 126 127 9
12 135 10
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DNA Rates – highlighting opportunities for improvement?
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
New Follow up
Psychological Therapies
Psychology
Did Not Attend (DNA) East Lothian Psychology East Lothian Therapists
1st Assessment DNA rate 15.5% 19%Average hours lost per week due to 1st Ass. DNA 1.4 2.7Follow-up DNA rate 11% 12.2%Average hours lost per week due to follow-up DNA 3.3 4Average hours lost per week to DNAs 4.7 6.7
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Activity Audit - highlighting opportunities for improvement?
Percentage of average hours per week by activity - All Charge Nurses
1%
2%
5%
7%
14%
5%
6%
10%
24%
0%
1%
5%
6%
14%
0% 5% 10% 15% 20% 25%
Other
SupervisionTraining/CPD
Meetings (non-clinical)
TravelTelephone - other agency
Clinical Meeting AttendanceOther
Clinical AdminGroup Therapy
Case Review (inc. CPA)
AssessmentOther
Individual Follow-up
Role
Agen
cy
Tasks
Indire
ct
Clin
ical
Direct
Clin
ical
Acti
vit
y
Percentage of Hours
No
n
Cli
nic
al
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Clinical outcomes data – highlighting opportunities for improvement?
Outcome Most Effective Least Effective
Recovered 22% 11%
Improved 22% 17%
Deteriorated 5% 11%
Average Sessions per Client
8 11
Okiishi et al, 2006
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Referral analysis - highlighting opportunities for improvement?
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Summary
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We recommend
You start working your data so you can effectively measure
DCAQ but… parallel to this you make sure that you are addressing all of the things you can do without data.