NHS Digital Data Release Register - reformatted
Lightfoot Solutions Uk Ltd projects
271 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).
HES data through the Signals From Noise (sfn) tool — DARS-NIC-359692-Q4X1C
Type of data: information not disclosed for TRE projects
Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant, No (Does not include the flow of confidential data)
Legal basis: Health and Social Care Act 2012, Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 s261(2)(b)(ii), Health and Social Care Act 2012 - s261 - 'Other dissemination of information', Health and Social Care Act 2012 s261(2)(a)
Purposes: Yes (SME)
Sensitive: Non Sensitive, and Non-Sensitive
When:DSA runs 2019-03-11 — 2020-03-10 2017.06 — 2023.07.
Access method: Ongoing, One-Off
Data-controller type: LIGHTFOOT SOLUTIONS UK LTD
Sublicensing allowed: No
Datasets:
- Hospital Episode Statistics Admitted Patient Care
- Hospital Episode Statistics Accident and Emergency
- Hospital Episode Statistics Outpatients
- Emergency Care Data Set (ECDS)
- HES-ID to MPS-ID HES Accident and Emergency
- HES-ID to MPS-ID HES Admitted Patient Care
- HES-ID to MPS-ID HES Outpatients
- Hospital Episode Statistics Accident and Emergency (HES A and E)
- Hospital Episode Statistics Admitted Patient Care (HES APC)
- Hospital Episode Statistics Outpatients (HES OP)
Objectives:
Lightfoot provide the Signals from Noise (sfn) statistical tool, which is used by or for (where Lightfoot are providing the service) the following non-commercial organisations: NHS (Providers, Commissioners), Exeter Medical School, NHS Professional Associations, or Academic Health Science Networks (AHSNs).
The sfn tool is used for the following purposes:
1. Providing access to summary and statistical analysis of patient data to customers with the objective of supporting a greater understanding of patient activity and flow to support the following activities in order to improve health provision:
a. Viewing current patient pathways to identify the key constraints and points for improvement, supporting the opportunities for sharing of best practice between clinicians and providers;
b. Agreeing with clinicians work plans to address the key constraints identified in the patient pathways causing delays to patients;
c. Monitoring and evaluating the impact of the improvement actions;
d. Identifying and embedding the improvements and realising the benefits.
2) Providing access to summary and statistical analysis of patient data to NHS commissioning organisations to support healthcare planning and service redesign, using the Statistical Process Control (SPC) view to:
a. Provide a view of current patient pathways and to identify key constraints, variation and bottlenecks in the various patient pathways;
b. Monitor and evaluate the impact of the improvement actions.
3) Providing access to summary and statistical analysis of patient data to Ambulance Trusts to support service improvement programmes.
4) Providing access to summary and statistical analysis of patient data to the Association of Ambulance Chief Executives (AACE) to enable and support national improvement programmes by using HES data to demonstrate outcomes of patient cohorts taken to hospital via the Urgent & Emergency Care pathway and conveyed by ambulance. Lightfoot also support AACE’s national objective of improved benchmarking between the 10 ambulance trusts in England. The aim being to identify, using HES data, areas of good clinical practice between the 10 ambulance trusts and provide comparison KPIs.
In addition the data is used to analyse variation across the region with the aim of identifying best practice and also areas of opportunity. Once the areas of best practice have been identified these can then be spread across the region to improve the health outcomes for the regional and national populations of the England.
Work streams are provided with Statistical Process Control (SPC) view of current pathways for patients and to identify key constraints, variation and bottlenecks in the various patient pathways which is used to monitor and evaluate the impact of the improvement actions and advise when necessary intervention should take place.
Data is used to review workforce planning with clinicians to address the key constraints identified in the pathways where there are patient queues due to a mismatch between demand and capacity. Statistical process control identifies and allows clinicians to embed improvements and monitor them in real time using metrics linked to patient quality.
In all cases data is for use by operational staff and clinicians to support their work by presenting HES data in a unique and highly visual manner through the Signals From Noise (sfn) tool.
The data is presented in dashboards, charts, mapping charts and in written reports as required by clients. In addition a client may use sfn SPC charts to demonstrate where improvements to service levels or patient experience can be made. In these cases the results analysed through sfn are used in reports and client case studies.
Lightfoot will also provide secure access for agreed analysts to complete their own analysis and prepare a range of reports including a summary dashboard. In all customer use cases statistical analysis and the drill down platform will automatically suppress small numbers before being presented the user. The user will be informed that some data has been restricted due to small numbers. Lightfoot confirm that no record level data will be provided to any third party customers or Lightfoot internal consultants and analysts.
In addition the data will not be used for sales or marketing purposes or in compiling tender responses.
Yielded Benefits:
A board of ambulance medical directors representing all trusts use the data dashboard and it informs improvement strategies by looking at the variation in acute trust HES data for arrival by ambulance, re-admissions, % that are admitted and acuity of patients conveyed by ambulance to A&E. The HES data is viewed along side ambulance data to form partial measures for patient outcomes. Some ambulance trusts have then gone on to apply SPC principles to local data and commission support for service improvement. The HES data has identified where there is an opportunity for an ambulance trusts to increase their “hear and treat” rate so patient are treated and remain in their home with community nurse support . Ambulance trusts are trying to move away from a target driven service to a patient centric service and they are reviewing the data collected to support this approach.
Expected Benefits:
The following are examples of benefits achieved through use of the sfn tools with Lightfoot clients. The maturity of current change projects makes it is difficult to quantify benefits and provide dates for all projects at the current time. In these cases a narrative around expected benefits has been provided and a metrics strategy to quantify benefits will be part of the work streams as the approach uses HES data with SPC for evidence based change to health services.
1) South West Academic Health Science Network with NIHR CLAHRC South West Peninsula on behalf of NHS England have used HES data within the Lightfoot platform to compare patient outcomes by comparing the Somerset Practice Quality Scheme (SPQS) with the national Quality & Outcomes Framework (QOF). This was testing a new approach to QOF findings which would allow clinical freedom to innovate while continuing to provide high quality care. Specifically the data were used to monitor non-elective emergency admission rates for SPQS practices for MI, Stoke, COPD, and diabetes as a partial indicator for patient outcomes to evaluate the two approaches. The paper has been published, “An evaluation of the Somerset Practice Quality Scheme” July 2015. The paper makes recommendations to expand the notion of quality in primary care and provide a way to capture what is happening systemically in a second evaluation of SPQS, this will help understanding to establish markers for improved patient outcomes.
http://www.swahsn.com/wp-content/uploads/2016/06/Evaluation-of-the-Somerset-Practice-Quality-Scheme-July-2015.pdf )
2) Exeter University supported the South West Cardiovascular Strategic Clinical network (SW SCN) in recommendations to reconfigure existing acute services to establish a network of emergency centres for heart attacks and strokes . The purpose of these centres is to maximise good outcomes though the provision of high quality specialist services that are resilient and sustainable. This work is likely to lead to more centralised care that is evidence based to improve patient outcomes. It is hoped the findings will inform thinking when developing the ambitions for the delivery of seven day services and access and treatment to specialist services within developing Sustainability and Transformation Plans (STPs). HES data was used as part of the modelling to develop a clinical benefit measures to look at the number of patients treated for time and volume sensitive conditions of ST elevated MI and stoke where time to treatment is a big factor in patient outcomes and maintaining function. This paper makes recommendations for service re-configuration across the South West of England that will deliver the highest clinical benefit in terms of time to emergency centre for the local population.
http://www.swscn.org.uk/delivering-five-year-forward-view-transforming-cardiovascular-disease-services-deliver-four-priority-clinical-standards-specialist-services/7939/
3) Pen chord (the Peninsula Collaboration for Health Operational Research and Development) part of SW Peninsula CLAHRC (Collaboration for Leadership in Applied Health Research and Care) are conducting research to look at number and location of neonatal and childbirth centres in England. The HES data for childbirth was used for the modelling. That is funded by a National Institute for Health Research (NIHR) grant: http://www.nets.nihr.ac.uk/projects/hsdr/141908. The aim of this proposed research is to understand national neonatal care demand and to investigate configurations of service that best meet the needs of both service providers and parents. The publication date is September 2017.
4) South West Academic Health Science Network have used the platform to assess the opportunity for social intervention bonds around diabetes activity and alcohol related activity for early intervention in terms of Emergency Department Care, Outpatient Care and Admitted Patient Care.
5) An NHS Clinical Commissioning organisation has identified patients attending A&E and subsequently admitted whose initial diagnoses were considered an ambulatory care sensitive condition. This allowed commissioners to identify patient pathways to be reviewed with secondary care providers. These are long term projects are currently been scoped and the CCG view the use of HES data through Lightfoot’s SPC tool as vital to been able to monitor and evidence the success of this work. The work streams have not been implemented yet so we are unable to quantify the patient benefits and provide dates.
The benefits of using HES with SPC methods include the timeliness of the findings. In many cases the length of time to undertake a full summative evaluation is simply too long so interim measures of progress that are statistically robust are needed. This will influence direction of travel to identify change in a way that allows clients to respond – reinforcing the good and reacting to the bad - within a shorter timeframe to optimise transformation activity. SPC methods make more use of the information available by looking not just at one point in time but considering the history of observations. They can be adapted to look at change against a variety of benchmarks, could set the expectations to be an improvement on historical patterns or to be better than elsewhere or to change faster than elsewhere. So, for example, it is possible to test first whether in a specific area there is an improvement over time, and then test to see if this change is greater or lesser than that seen elsewhere. (Nuffield 2016 “Monitoring change in health care through SPC methods.”)
The following work streams will start in the next couple of months. Lightfoot will agree a metric strategy with the work streams.
i) A review of outpatient pathways for cardiology, gastro and respiratory to improve DNA rates and reduce waiting times. SPC using HES will be used to track improvement over time and compare if change is greater or lesser than elsewhere.
ii) Work with the acute provider clinicians to look at frailty pathways and assess if HES data can be used to understand the impact of new frailty clinics in the community. Lightfoot expect the use of HES data to show an impact on outpatient activity and a reduction in acute admissions for the frail elderly. These metrics and timeline will be agreed as part of the project. SPC methods will aid commissioners to forecast the impact of initiatives on activity to assist with planning health provision.
6) Lightfoot have been commissioned to support several ambulance trusts in analysis of patient journey data with ambulance trusts to review clinical models in order to deliver the local urgent care strategy and develop a model to treat more people at home and refer to local community services where appropriate. Lightfoot is in discussion with a these ambulance services to support redesign of their clinical model to improve patient outcomes.
This work has progressed for one ambulance service which has used the HES data to demonstrate to stakeholders and commissioners the effectiveness of a new clinical model in a particular geographical area. The HES data quantified the new model of care in terms of the contribution of the ambulance service to the wider health system in order support the case for further pathway re-design through development of hear and treat and see and treat models of care.
HES data showed the deployment of paramedics practitioners in the new model of care had significant impact on reducing ambulance attendances by an annual reduction of 11,190, this model delivers a better quality of service to patients who are treated at home instead of conveyed to a hospital.
The trust is exploring a phased approach to establishing further initiatives for service redesign leading to reduced hospital transports and more care nearer the home in the community. The ambulance service views the on-going use of HES data as essential to monitor the success of these initiatives to provide evidence of change in discussions with commissioners and other providers.
7) Lightfoot continue to provide benchmarking data to the Association of Ambulance Chief Executives Association of Ambulance Chief Executives (AACE) that has allowed the membership of English ambulance trusts to explore the variation in outcomes for patients transported to hospital by ambulance to inform national policy.
A. Analysis of patient data with ambulance trusts identified regions across the country where ambulance trusts delivering an enhanced clinical model which allowed increased rates of See and Treat therefore significantly reducing the number of “avoidable attendances” to A&E departments of patients transported by ambulance. In one region (re point 7) this established better outcomes for patients but also significant financial savings to the health economy when patients were treated at scene rather than be transported to hospital. The SFN took allows ACCE to share evidence for best practice. This also helped commissioners to appropriately fund this level of service provided by the ambulance trust.
B. Providing benchmarking data to the AACE has allowed the member ambulance trusts to explore the variation in outcomes for patients transported to hospital by ambulance. The on-going benefit is that the trusts will be able to highlighted opportunities for knowledge share and the transfer of best practice to improve patient outcomes in regions that had the greatest variation.
C. Association of Ambulance Chief Executives (AACE): provision of nationwide benchmarking solution to ACCE and ten national ambulance trusts utilising HES data. Supporting strategic objectives in their National Programme. Completing evidence based research to support national commissioning discussions.
Outputs:
Lightfoot’s offering is designed to support and enable continuous improvement projects in the NHS and allied health care organisations to improve patient outcomes. Specific outputs include:
• Charts and graphical representations of data using statistical process control to highlight variation;
• Tabulations and summarised data;
• Statistical analysis;
• Written reports and recommendations for stakeholders based on findings from analysis and supported by Statistical Process Control (SPC) charts from the sfn tool;
• SPC signals and alerts indicating processes where behaviour has recently changed.
In all cases these are for Lightfoot’s clients to use with operational staff and clinicians to support service improvement work by presenting HES data in a unique and highly visual manner through the sfn tool. The data is presented in dashboards, charts and in written reports as required by clients. In addition a client may require use of sfn SPC charts to demonstrate to commissioners and other NHS organisations or members of the public where improvements to service levels or patient experience have resulted from their initiatives. In these cases the results analysed through sfn are used in reports and client case studies. All charts and reports included in the outputs use aggregate data (small numbers suppressed) in line with the HES Analysis Guide, derived from the HES data and presented via the sfn tool.
Processing:
All processing of record level data will take place on hardware and software wholly owned and controlled by Lightfoot. Processing of record level data takes place within the datacentre without data being transferred to or processed using laptops, desktops or networks outside of the datacentre.
C4L hosts Lightfoot’s secure rack, servers, power and internet connection within their facility.
All access by third parties is through the Signals from Noise (sfn) tool. The connections to this tool are encrypted over SSL and require the end user to authenticate. The sfn tool has a specific processing layer responsible for applying small numbers rules to all charts and tabulations prior to returning the results to the user/third party.
To summarise the process -
i) HES Data will be downloaded via SEFT to Lightfoot’s secure data centre facility. This data will then be processed on a server with controls specifically designed for processing of sensitive data. These controls include restricted access and physical security managed under ISO27001. The HES files will be processed and loaded into a SQL server database in a format suitable for Lightfoot’s OLAP tool – signals from noise (sfn). Once text based data has been loaded into the SQL database it will be stored on the secure area of the server encrypted using AES 256 bit encryption. Once the loaded database has been reconciled with trusted national reference sources it is promoted to the production server.
ii) Only third parties as specified above will be given access to the signals from noise (sfn) tool. Lightfoot’s clients benefit from viewing data through the sfn tool because this allows users to run immediate real time queries across several years of HES data. The sfn tool provides unique views of the data with functionality (not available in traditional reporting tools) that supports the use of statistical process control techniques which clients need for the measurement of process performance and provide greater understanding of patient flow and pathways.
The sfn tool provides unique views of the data with functionality (not available in traditional reporting tools) that support the use of statistical process control techniques which is needed by Lightfoot for the measurement of process performance and provide greater understanding of patient flow and pathways.
For some customers within the customer groups stated above, Lightfoot will provide secure access for analysts to complete their own analysis and prepare reports and summary dashboard using the sfn tool. The patient level data does not leave the Lightfoot secure hosting facility, and the clients’ analysts do not have access to record level data. All analysts may only access aggregated data with small number suppression. Lightfoot will maintain a user log and provide full training for all such users. All users must comply with NHS Digital's Hospital Episode Statistics (HES) Analysis Guide.
In all cases summary and statistical analysis will be automatically processed to suppress small numbers before being presented. Lightfoot confirm that no record level data will be provided to any third party.
The Lightfoot HES group over sees the governance for approving and on-boarding new clients with access to an SFN platform containing HES data. This group is accountable for ensuring new clients requirements are complying with the Health and Social care act 2012 as amended by the care act 2014. Clients are only approved if they are an NHS organisation, health provider or a not for profit academic organisations conducting health research using the data for the provision of health services or promotion of health.
Each client has an environment built to an agreed specification in line with their requirements and complying with HES data analysis guidance. Clients only have access to aggregated data with small number suppressions. Lightfoot agree a senior customer representative with each client to approve all client user requests. Lightfoot provide customers with a process for administration of users. All clients’ user access requests are authorised by the Lightfoot appointed account manager who is responsible for checking the user access is in accordance with license agreements and HES analysis guidelines. The process for user access management has been revised in line with the recommendations in the “HSCIC audit of data sharing activities” report 15/07/2016.
Lightfoot regularly meets with clients to review use of the data and compliance with license agreements.