Measuring to improve management of demand and capacity – how important is it? Ruth Glassborow Quality and Efficiency Support Team

DCAQ Quick Revision

TeamNo of Referrals CMHT20 Crisis Team10 Average Contact Time Per Referral Demand in Hours 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

Server Queue type AQueue type B Queue: people waiting to be seen

Capacity = what we could do Activity = what we did Demand = All requests for 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 EffectiveLeast Effective

DNA Rates – highlighting opportunities for improvement? Did Not Attend (DNA)East Lothian PsychologyEast Lothian Therapists 1 st Assessment DNA rate 15.5%19% Average hours lost per week due to 1 st Ass. DNA Follow-up DNA rate 11%12.2% Average hours lost per week due to follow-up DNA 3.34 Average hours lost per week to DNAs

Activity Audit - highlighting opportunities for improvement? Non Clinical

Clinical outcomes data – highlighting opportunities for improvement? OutcomeMost EffectiveLeast Effective Recovered22%11% Improved22%17% Deteriorated5%11% Average Sessions per Client 811 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.