Measuring to improve management of demand and

capacity – how important is it?

Ruth Glassborow

Quality and Efficiency Support Team

DCAQ Quick Revision

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

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

Capacity

How much work you can do in a given time period

Not the same as activity – what you actually do

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

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

Ideally you want to effectively understand and manage

• Demand

• Capacity

• Activity

• Queue

So how important is data to effectively manage demand and

capacity?

Its really important but… there is lots you

can do without it

DCAQ Work

Examples of things you can do without data

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

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

Managing DCAQ without data

DCAQ Work

Areas where data can help you make improvements

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

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

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

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

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

Referral analysis - highlighting opportunities for improvement?

Summary

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.