Intelligence update. CQC Board. May 2018

Transcription

1 Intelligence update CQC Board May 2018

2 Progress and plans Over the past 12 months the Intelligence team has made good progress in support of CQC s ambition to become more intelligence-driven This session will provide a progress update on the Intelligence plans previously shared with the board and a show and tell on some newer capability we are introducing, specifically: 1. Intelligence outputs: progress on data science since Feb update slide 4 2. Data & tech enablers: progress on improving data and tech slides Show and tell: Pilot identifying change in Registered Manager slides Show and tell: Proof of concept topic modelling slides Show and tell: Prototype of new area based analysis product slides Culture enablers: plans for wider staff engagement slide What next a high level view of the next 12 months slide 17 Our aim is that by the end of the session, the Board understands the progress made in recent months, sees the potential in the new capability showcased and is supportive of the work we will do next. 2

3 ENABLERS OUTPUTS Register Monitor Inspect & Rate Enforce Independent Voice Intelligence development framework 1. Intelligence Products & Services ASC Hospitals PMS Cross-sector 2. Data and technology 3. Intelligence team culture & capability 4. Org-wide culture and ways of working Integrated Intelligence products and services across the operating model and sectors 3

4 1. OUTPUTS: using data science to drive improved decision-making Expert systems Problem: Explore the use of AI to aid regulatory decision making by blending tacit operational knowledge with incoming data and generating easy to use outputs. Customer: Focus on ASC Output: Scoping report Impact: A successful outcome would lead to a larger project to develop an expert system. Delivery: Interviews & workshop complete Report to be delivered May 2018 Data science advice Problem: Provide training in cutting edge machine learning techniques. Customer: Intelligence Analysts Output: Training, and support in implementing the GP project. Impact: Greater capability in to deliver data science projects and greater confidence in quality. Delivery: Training & draft report delivered. GP modelling project at end of data phase, advice to be received through modelling phase (to end July 2018) Text severity Problem: Can we use natural language processing to identify patient experience comments of high concern? Customer: All Inspectorates Output: A tool to allow us to carry out ongoing screening. Impact: New intelligence to aid decisions, as we cannot manually screen this data. Delivery: Data passed to provider initial modelling has started, first results expected end May

5 2. ENABLERS: data & tech Qualitative / text data ihub single platform for data Aim: Enable use of data previously unavailable to analysts in order to stepchange understanding of risk and quality Future insights will be added to standard Intelligence products Aim: Bring all standard data in to one platform enabling significant efficiency in data access and improved data integrity Future: improved data loading and quality assurance processes Progress: 4/12 priority sources available to analysts Remaining 8 planned by end of June Exploring visualisation options to make this available to inspectors short-term Progress: PMS and Acute Hub developments complete and parallel testing in progress (to complete Q1 2018) All other sectors in development with data uploads and testing planned Q1-Q

6 2. ENABLERS: data & tech Automation of key Intelligence outputs Aim: Automate the most manually intensive Intelligence processes Free up analyst time to undertake more valueadd work Progress: MH evidence appendix by end June Automation of evidence appendices is a significant undertaking, particularly in the absence of digital platform for collecting PIR information. Analytic environment Aim: Create a scalable environment for processing analytical jobs removing reliance on laptops and poor network speeds Progress: Agreeing with DHSC to be part of their analytic environment proof of concept from July Proof of concept will allow us to shape future requirements for CQC (with possible options being to join DHSC, or take a copy of the test platform) 6

7 Show and tell: Registered Managers Problem trying to solve: We know the absence or change in Registered Manager can lead to risk in quality of care within ASC settings. How can we access information about changes to Registered Managers in ASC settings beyond notifications, to ensure we can identify any risk to the quality of care? Solution: Access recruitment data using web scraping techniques and combine the information with our notifications data. What does it enable? Allows us to better identify where changes to key personnel have occurred. Potential for ongoing monitoring including risk flags where CQC were not advised of changes in key staff. 7

8 Show and tell: Registered Managers Web scraping Cataloguing/processing Scenarios From a pilot set of recruitment sites all of which we have written to advising them Is the advert relevant (i.e. for a registered manager vacancy)? Is the advert useful (i.e. for an identifiable location which we regulate)? Does the advert/change in RM suggest a risk to the location? Current RM status Length of time without RM Current RM new in post Recent changes to RM 8

9 Show and tell: Topic modelling proof of concept Problem trying to solve: Can we identify what the public is talking about when they leave feedback on services for example via NHS Choices, Share Your Experience etc.? Solution: Machine learning algorithms that create topics based on properties of the data What does it enable? Automatic topic identification, greatly removing the demand for manual classification Automatic tagging of comments with specific topics, at provider, sector, regional or national level 9

10 Show and tell: Topic modelling of NHS Choices in NHS acute hospitals Automated analysis of topics identifying, for example, maternity services in free text NHS Choices comments 10

11 Show and tell: Local area portal Problem trying to solve: Support staff to work better across sectors in local areas Provide access to Intelligence products that support NCM and complex providers Solution: Automated, multi-functional map based tool Covers all sectors and links to existing Intelligence products (including CQC Insight and Local System Review data packs) 11

12 Show and tell: Local area portal The portal is an automated, multifunctional map based tool that provides CQC staff with multisector information, alongside links to existing Intelligence products. The Portal is intended to provide: Organisational mapping (details of relationship owners) to facilitate cross sector communication and working. Access to location, provider and area level analytical products to give a comprehensive view of the intelligence we can provide across an area, supporting an intelligence led model of regulation 12

13 Show and tell: Local area portal The portal is an automated, multifunctional map based tool that provides CQC staff with multisector information, alongside links to existing Intelligence products. The Portal is intended to provide: Organisational mapping (details of relationship owners) to facilitate cross sector communication and working. Access to location, provider and area level analytical products to give a comprehensive view of the intelligence we can provide across an area, supporting an intelligence led model of regulation 13

14 The portal also gives access to area level analytical products such as LSR 14

15 Local area portal: planned rollout Q1 Q2 Q3 Demo prototype to relevant engagement, digital, operations, intelligence groups Finalise refresh mechanism and ensure QA of product is robust Soft launch with small group of users over Q2 & evaluate Launch fully in Q3 and make available to all staff Ongoing iterate and improve following user feedback 15

16 4. WAYS OF WORKING AND CULTURE: Engaging all staff in intelligence-driven June month focused on the work of the Intelligence and Digital teams in delivering our strategic priorities: intelligence-driven, digitally-enabled Aim: to show what an intelligence-driven future looks like for staff across the organisation and how it will enable a more effective and efficient CQC. Key messages: Using intelligence is fundamental to our vision of a more targeted, responsive, and collaborative approach to regulation We will make it easier for staff to do their jobs by providing access to up to date and consistent information in easy to use tools and applications The biggest change will be the cultural shift required for all staff to behave and act differently and ask what does the data tell us? Delivered via: Cue articles yammer discussions question time with panel external speakers lunchtime learning sessions enhanced intranet content 16

17 What next? Some of the work to come: Q1 Q2 Q3 Q4 Start work on data strategy Plan and agree ASC data science programme Agree plan for next phase of external procurement. GP modelling work complete Initial testing of GP work, subject to viable model Begin ASC data science programme Text severity project reports Agree plan for next phase of text analytics work Test use of topic modelling Procurements out to tender and where possible projects start. Test analytic environment with DHSC Roll out of Local Area portal to all Inspectors Wider testing of GP work ASC data science work continues Next phase of external data science projects running Refining use of text analytics and incorporate in CQC Insight Intelligence Products & Services strategy and roadmap complete Data strategy complete Ongoing improvements to CQC Insight and ihub 17