1 Using data to improve access to treatment: managing speciality performance and efficiencyMark Norwood – Associate Director of IM&T Rich Butterfield – Head of Information Credentials Mark Norwood – Associate Director of IM&T at Derby Hospitals. I have X amount of experience in health informatics I provide challenge and direction for the information team and ensure their message is understood across the trust. Rich Butterfield – Head of information at Derby Hospitals managing information extraction, processing analysis and data quality. We are going to show how we at Derby have built a reporting structure which is applicable to your trust and a good foundation achieve you national RTT targets but more importantly put you in a position where you have a working system to help ensure patients health is not adversely effected by waiting longer than is necessary for treatment.
2 Presentation Topics What Why Trust Detail Who is involvedUtilising Technology Information Processing Data Accuracy Reporting Scalability Ownership & Governance System Configuration Confidence in data Confidence in decisions Making the Problem Visible After giving your some context we are going to show you 6 elements that enable you to build a reporting set up which underpins business decisions and ultimately service development. I am constantly frustrated by presentation that don’t tell you how they have done what they have done. So here you have the “What” we are going to present and more importantly for you, the “Why” we are telling you this We tell you the trusts detail because this is very scalable and works for a single department link audiology all the way up to the whole trust. Who is involved because the success of this is around everyone owning their element How we have utilised technology – You have to be relentless in pushing for the perfect solution and this isn't just our ideas it is the work off all trusts on Lorenzo making it better How to process information – this shouldn’t be a black box it should be on an agreed set of rules which everyone signs up to The importance of data accuracy – Providing an answer with data quality concerns is a lot better than leaving someone to have a guess Reporting – The right measurements to make a problem visible
3 Trust Detail 1 million hospital events in a year 250,000 Referrals31,000 Incomplete Pathways 8,000 Inpatient Waiting List Up to 10,000 Lorenzo transactions effecting RTT on a weekday. Some headline Stats. We have 1 million hospital events in a year with two hundred and fifty thousand referrals. Currently we have about 31,000 RTT pathways and 8,000 on our inpatient waiting list This all adds up to having 10,000 record transition on any working day the margin for error is significant. So you cant manage these numbers without meaningful reporting.
4 RTT Incomplete Performance HistoryRegression issue Lorenzo Go Live Dashboard Launch To provide you with a bit of a potted history this is our Incomplete performance. Derby Hospitals Shown Against the National Level and the 92% Incomplete Target. We took Lorenzo 3 years ago. Prior to Lorenzo we had a PAS system that had RTT bolted on. Lorenzo automatically started an RTT clock for all patients based on a referral set up. So we no longer had to worry about starting clocks. We did however have to worry about stopping them We went Live with Lorenzo in Feb 14 and failed to report in Feb & March. We were unable to report because of one very simple problem – a linking process which finished historic RTT pathways to restarted pathways was not switched on. The blame can go down to we didn’t explain in a meaningful way to our software supplier what we were doing with the data or they fully understand the impact of this process. Either way we didn’t report for two months and when we the lack of visibility of patients on pathways took effect and we started to breach. Another points to note are that we had a regression issue after a go live because our software supplier was making rapid improvements to the RTT functionality and we didn’t have a robust testing process in place Then in May 15 we released the RTT dashboard. Now we are not saying that you will achieve what you need to with a dashboard or report but you will make your problems visible for action to be taken. Prior to this the following situation was the norm:
5 Problem This Rich Picture is a summarised take on the problemEveryone booking patients knows exactly how long they have waited for their area but not on an RTT pathway But they were bombarded with reports on finance, waiting times, efficiency, quality of patient care. So they couldn’t see the wood from the trees because they were proverbially blasted by the information services reporting cannon each week. The information team were a group of reporting squirrels though we had the vision of cultivating analytical ninjas. I know we have missed out cancer waiting times but the approach we go through can be applied to all areas it just made the presentation confusing.
6 All the pieces of the JigsawData Accuracy Problem Visibility Governance Reporting Structure Information Processing Systems Configuration So we needed a reporting structure to show a clear consistent message and assist instead of confusing. As we were not achieving the national target we were receiving assistance from IMAS but we were questioning the service on what we could do to give people confidence that the data reported matched the system and provide them with a solution that made the problems visible. We had a new starter in the information department and he was lucky enough to land the role of owning all waiting times. You will notice owning is said a lot in this presentation and that’s because that best sums up what I as the information manager wanted him to do. This is the reporting jigsaw which we have created with data accuracy, systems configuration and information processing (automation & business rules) being the foundation for making the problem visible, have ownership for the area and having a governance structure. I plan to demonstrate to you these 6 simple steps which will help you use data to positively effect how long a patient waits to be seen at your organisation and by doing that you will most certainly improve patient experience but also reduce the risk of patient care being adversely effected by long waiting times. Ownership
7 Building a reporting foundationTo make data trustworthily we needed to build a reporting foundation So you will have a system or group of systems that contains all of these types of data flows and more. The first task is to put a boundary around that so you can now measure everyone waiting which is a huge number of patients but you have everyone. Click 1: Then you can start to break down that total into manageable elements. Which can continue down to specialty level and clinician level but all of your parts add up to the total patient waiting. Click 2: Then you need to turn your boundaries into solid lines with a data accuracy process which addresses errors Click 3: And finally you can start to work out which patients are on RTT pathways or not.
8 Data Accuracy & Systems ConfigurationWe set a baseline and monitor using a RAG rating Data Quality Dashboard Transactional data – days work in a day Backlog Data – Reducing the error Adjust the System Configuration to support accurate recording So I explained the fence but as we pointed out in the beginning we have 10,000 daily systems transaction just effecting RTT. We know from a medical risk James Reason wrote about successful organisations planning for error putting processes in place to mitigate. So that’s exactly what we have done with our data quality dashboard. It is able to count everything that changes in the system so we focussed on every gap in the fence around RTT. So we had a Cymbio dashboard but it initially just a tool to help us upon go live. This became the second fence around the data to tackle where an error was made or a metaphorical gate was left open by the system. We all know good accuracy is key for making good business decisions. But more importantly good accuracy makes sure we do not drop a ball and adversely effect a patients outcome. From analysing the common DQ issues we then set about addressing where the system could help in proving improving accuracy but reducing unnecessary options or keeping the system tidy. Tis wasn’t just Derby, but every Lorenzo trust has done a lot to ensure that the system is configured in the correct way. Before stopping the clocks when patients were discharged we were adding 200 pathways a week to our validators workload. Some examples of this are: Stopping the RTT clock when the patient had been discharged and the referral closed. Or not allowing an RTT clock to be started for obstetric patients. Systems Config Data Accuracy
9 Insightful InformationValue Added Approach Assist in spotting problems early Assist in uncovering the cause Assist in reducing variation Assist in Booking in Order Assist in Understanding Backlog and Sustainability Assist in Understand Capacity Assist in Efficiency Gains Problem Visibility
10 Spotting problems earlyChristmas Impact Christmas Impact Christmas Impact We also show moving trends. This shows humps in the data passing through the system. This shows the reduction in referrals for Christmas but we have very similar ones for specialties where other providers have reduced their capacity or there has been a NHS awareness programme pushing people to see their GPs. As with all reports we split the incomplete profile into its constituent parts. Inpatient Waiting List Outpatient Waiting List Middle Phase – We uncover this by having an endoscopy tab and a separate diagnostic dashboard
11 Cause: Individual Waiting Lists DissectedDQ Issues Booking over 18 weeks No TCI at 20 Weeks plus As well as showing trends over time the dashboards allow the user to cut the waiting list into problem areas. How many long waiters do you have without TCIs – Do they belong to one clinician – Can they be shared or have some of his OP clinics switched off. By the way this is fake data to emphasise the point if you were getting concerned
12 Cause: Individual Waiting Lists Dissected Cont.Diagnostic Waiting list Imaging at modality level Endoscopy split by waiting list type (Cancer/Urgent/Routine/Planned) Our attempt to fluidly link information together allows users to uncover the diagnostic phase of a pathway and see that at a granular enough level to be able to spot hotspots and When I speak to trusts they tend to tell me that they cant link their pathways together to show how long someone has waited on an RTT pathway when they have entered the diagnostic phase. We have the same problems but we get around it by focussing on hitting the 6 week target, though ideally 4 weeks and assume the patient has entered the list at around 6 weeks.
13 Backlog and SustainabilityBreaches 4499 Target Breaches 2,541 Achievement of Target 1958 Sustainability: 29,795 Waiting List Size Ideal Waiting List Size Sustainable Waiting List 26,500 3,295 As providers we plan to remove the backlog and to do this most people look at what they need to achieve to the national target. This is usually all that you can get the CCGs to fund and as far as your capacity will stretch. But you need the waiting list to be sustainable. By sustainable I mean that you are treating the same that you add and you have enough leeway to come with Christmas, Easter, & Summer Holidays. Once that waiting list is sustainable you need to ensure it stays at the sustainable level by monitoring your additions and removals from each pathway stage or waiting list. Although this looks like I am advocating doing a lot of additional clinics and theatre sessions a lot of this can be achieved by switching patients on clinicians lists or efficiency gains. Then if you are doing all of this and still not achieving the target I would suggest you are booking out of order. Its normally that point when I loose everyone but you all seem to be with me still. Now you know what I mean when I say sustainable.
14 Utilisation of CapacityTheatres Trust to clinician level Outpatient clinic utilisation Trust to clinic level So as part of annual planning I would have hoped this has been converted roughly into required theatre sessions and clinics. I know of information departments that spend 6 months doing this and it turns out to be no more accurate than working out how many Inpatient and Outpatient sessions your consultants should run in a year, multiplying that by average throughput and adding on last years WLIs. Then next step is to monitor this activity and we do that at a clinician level in theatres and clinic level for clinics. This level of granularity is helpful to get to the route of the problem but doesn’t help for trust reporting so it is about chunking up at the right point. You will also see that we monitor WLI, we struggle with in-week but we can do weekend.
15 Reducing Variation with League TablesClinician Average Theatre Throughput Rank Clinician 6 3.48 1 Clinician 2 3.43 2 Clinician 1 2.73 3 Clinician 5 2.6 4 Clinician 10 2.25 5 Clinician 4 2.03 6 Clinician 3 1.98 7 Clinician 9 1.83 8 Clinician 8 1.77 9 Clinician 7 1.66 10 Specialty Average 2.52 Outpatient Utilisation Long Waiters Picking Order I am not a fan of league tables but I have not found a better way to start the variation conversation. Our theatre dashboard was hated at first because of the league tables. We had some consultant advocates and we answered every concern on the accuracy of data and sat with clinicians to show them what had been recorded against them. If this isn't feasible then we have chosen to show the top 3 performing clinicians and anonymise the rest which the promotes the question what do I need to do to be in the top 3. Which usually come down to start on time, and finish on time, reduce turnaround time, but ultimately get more patients on your theatre lists but this has to be in the realms of what is safe. Where possible we add in the national benchmark or 75 percentile but you will know as well as I that the national figure can sometimes be misleading. Late Starts & Early finished
16 Late Starts/Early FinishesEfficiency Gains Theatre Throughput Late Starts/Early Finishes DNAs & Cancellations Another strand to our information is to reduce cancellations and DNAs. We like every hospital has a high DNA rate for endoscopy and we tend to find when we look breaches a substantial proportion have had a DNA or cancellation at some point on their pathway. We know we have around 2-3 thousand DNAs on active RTT clocks just in the outpatient follow up phase which on average adds 3-4 weeks onto an RTT clock. We will never get tis down to 0 but if we could take a 500 off that could mean 500 less breaches. Get an extra 150 patients through theatres in a month and that’s 150 less WLIs, or take a day off our inpatient waiting times, or even make that waiting list sustainable. Reduce follow ups by 1,000 in a month and that capacity could be used to take a week off our new outpatient waiting list or a few days off our non admitted waiting list. Follow up Ratio
17 Cancelled Operations on the day Diagnostic Waiting TimesReporting Hierarchy Planned Care Dashboard Outpatient Dashboard RTT Dashboard Cancelled Operations Theatre Dashboard Diagnostic Dashboard Referrals DNAs Activity Patient Level (Daily) Cancelled Operations on the day Theatre Log books Diagnostic Waiting Times The purpose of this slide is to show that we had a vision for how the reporting structure would look. As we said previously we had all of these reporting in some guise and most trusts are the same as you have to report a lot of these measures to the board but the challenge was to navigate around this. Until a year ago we did have a reporting gap with diagnostics in that we didn’t have a diagnostic dashboard but this has been brought into our hierarchy. The daily patient level data is the only excel element we have and this is saved securely to SharePoint with folder level restricted access
18 Ownership Owners: Trust RTT Owner – Board LevelReporting Owner – Information Manager RTT Manager & Service Managers RTT Analyst Data Quality Support RTT Trainers RTT Validators I'm sure you have all heard Rudyard Kipling quote For the strength of the pack is the wolf, and the strength of the wolf is the Pack. Well that is a good premise to take in owning a problem and this is why we have had successes in this area. Everyone has a part to play in improving waiting times from a board level who ultimately own the trust performance and where to invest, what to prioritise, how to organise But they are confident that information team will make the problems visible, the data quality team monitor and look for ways to improve accuracy and the validation team clean up the errors. All three of these support team help the RTT trainers prioritise their workload. RTT trainers – who we are a little light on currently but Ownership
19 Governance Meetings: Governance Waiting Times Weekly MeetingMonthly RTT board Governance Documented Governance and Signoff process. Now you have your ownership you need a governance structure to ensure that this is managed. We have a weekly waiting times meeting where specialties come and deliver and update on current waiting times and progress report on plans. Then escalations are provided to the monthly RTT board which has oversight of the area. The information department has a documented process for how we treat the data which has been signed off by the trust RTT lead and validated through audit. We then make all interested individuals aware at the end of the month what the figures show and this is formally signed off. Governance
20 Take Away Points Information without action is wasted effortVisible problems are easier to fix Data Accuracy is vital to make good decisions but… Utalise technology to assist your goals It’s a lot easier when everyone owns the problem The take away points we want you to have got from this are: Visibility is key - You can go running without running shoes but they certain help. Think of information in that way… it will help effective decision making. But if nobody is acting it could be because you are bombarding them with too many messages or they are not confident enough in the numbers to make a decision. Data accuracy is vital for making good decisions but in my experience some data is better than no data. Some data accompanied by the tacit knowledge of the service makes a solid basis for decisions. If you system doesn’t have validation rules, or assist users in getting something right it needs to be amended. The 200 pathways we saved is a validator that can be redeployed as an RTT trainer/educator. Ownership of the problem at every level – I haven't mentioned the communication and that’s because if you own the problem you are already communicating. If you think that looks like a lot of work I have to say it was at the start but its progressive and once set up you start to free up time. The questions on the data reduce as the problem becomes visible.
21 Foresight: predictive analytics Information ProvisionStep 5 What next Step 4 Foresight: predictive analytics Knowledge Step 3 Step 2 Information Provision Insight Step 1- Facts & Data - Providing a number that helps the running of the business e.g. you have X many patient waiting for hip surgery. You cant move out of this stage without confidence in data processing and confidence in accuracy. Step 2- Information Provision - Measuring and monitoring the business – looking at efficiency, trends. Step 3 - Insight: This is about integrating performance management and insight which is the outcome from our weekly RTT meeting. So understanding the peeks and troughs. We have been at this level for a while now. This comes about through trust wide ownership. Step 3 – Knowledge: Business specific analytics embedded into business processes. This is about mapping the pathway and being able to monitor fluctuations. We have done this in parts but as you can imagine it is very tricky to do this well. This comes about through building a knowledge and skills base across the trust because it is the understanding and action that mean you as an organisation are achieving this level. Step 5 – Foresight: Predictive Analytics – Modelling the impact of decisions like changes to referral trends or other providers stopping services. This is the holy grail of an analyst function. Step 1 Facts & Data:
22 Thanks you for your attentionAny Questions? Thank you for listening. We have given you our framework for improving waiting times which you be used to validate your approach or replicated if you don’t have an approach. Do you have any questions?
23 Additional Slides
24 Our Vision What we wantedInformation to aid decision making As I had said earlier we had just had a report back from Peter Hyland at IMAS which talked around the information team working to give people confidence that the data reported matched the system and make the problems visible. We wanted information that aided in decision making and we had problems with our solution being available when needed and then when they were available being trustworthily. But we knew that once we resolved these issues we needed the information to tell the user something they didn’t know, or back up their knowledge so it needed to be insightful. All three of these things require a good relationship with the services to be able to ask questions. What can the information team do to make you feel more confident in the accuracy of the data? When do you need the data and in what format Once we have shown you the compliance against target what questions do you need the information to support with? Then you can create a project outline and start delivering on the agreed actions. Timely Trustworthily Insightful
25 Visible The reporting storyThis slide is how we linked it all together to tell a story or help get to attributing factors of a problem. We went from no reports the day after go live to too many reports which make decision making even harder for the trust managers. This is a reporting map and I have drilled into the inpatient waiting list to show all the measure that support that area. I could have done the same for Outpatient, Diagnostics or clock starts. We had 60+ separate reports and we assessed how they fit together and where the gaps are. We already had a very good theatre dashboard and to keep things slick we created a separate dashboard for waiting times Cancelled Operations was its own beast so we decided to create its own reporting structure. The waiting times dashboard picked up the rest but had to link to the other reporting products. This was our gap analysis and accompanies the reporting hierarchy.
26 How can System Configuration HelpAutomatically stopping clocks when referrals are closed Not starting RTT clocks for non RTT activity Putting the RTT breach date in clear view when dating a patient Closing historic unused referrals to de-clutter the system Not just Derby, but every Lorenzo trust has done a lot to ensure that the system is configured in the correct way. These are some of the things the system didn’t do and we have altered the configuration or put change requests in to make the system work for us. Systems Configuration
27 Outpatient Clinic Utilisation ExampleTrust Specialty Clinician Clinic Our outpatient dashboard looks at a trust level all the way down to a clinic level. So a clinician can look at their clinic utilisation and work out which clinic it relates to. It doesn’t resolve the problem but it starts the questioning on how the problem came about and how to resolve.
28 How to Calculate SustainabilityIn (additions) & Out (removals) Balance 6 Week Waiting List 6 * 100 = 600 In 100 Now is the pint when you all start to think I am a nutter. Well that horse has probably bolted and im now worried you will remember me as the bathtub bloke. Essentially you don’t want to flood your services so you need to balance ins and outs and the residual level cant be too high. You add on 100 patients in a week into this system So firstly you need to treat what you put in so 100 patients treated or removed from the waiting list Now you can set your residual level e.g. we want a 6 week waiting list. So 100 * 6 = 600 and that is your maximum waiting level but if you always stay below that you will sustainable treat patient within 6 weeks unless you book out of order or have differential clinician waiting times. Then you can breakdown further for cancer and urgent patients but it follows the same principal. 600 Patients Out 100