NHS Digital Data Release Register - reformatted
Medeanalytics International Limited
Project 1 — DARS-NIC-25634-T2Z1Z
Opt outs honoured: N
Sensitive: Non Sensitive
When: 2016/09 — 2018/05.
Legal basis: Health and Social Care Act 2012
Categories: Anonymised - ICO code compliant
- Hospital Episode Statistics Accident and Emergency
- Hospital Episode Statistics Admitted Patient Care
- Hospital Episode Statistics Outpatients
The benefits of having the national comparators derived from the HES data available within the MedeAnalytics system are realised through the additional information they provide to support decision making by commissioners and providers in a range of activities. Commenting on the benefits of the UKMede platform, the chair of the East of England consortium of CCGs said “The challenges facing healthcare commissioners and providers are well documented, and are now demanding necessarily highly advanced and precise levels of insight to support the management and delivery of services. The CCGs need to know which areas to prioritise and what services interventions are likely to yield the greatest benefit for their populations. A self-service comparative platform allows them to do this in a wide range of service areas. The CCG consortium's commissioners are actively using HES derived insights delivered through the Mede platform to feed an enhanced analysis and understanding of provider activity. They are evaluating trends to be able to better focus on priorities and opportunities to improve demand management and patient outcomes. Delivered through this interface local health economy leaders are able to exploit fully the business intelligence benefits available from HES.” Often the HES-based work is used at a project initiation stage or for ongoing reporting of impact of a specific project. It is difficult to give a comprehensive list of benefits that have derived from the many different uses of the system but some illustrative examples are: Historical Benefits : 1. In Hertfordshire using the HES-based national comparison system, it was realised that the care of frail and elderly needed to be a priority in the area and this led to a highly regarded vanguard project being initiated, Home First, that looks to improve the care of patients who are resident in care homes. This has recently been shown to have led to a significant reduction in emergency admissions and A&E attendance. The health economics analysis of the project is currently being completed. Without the initial comparator work being done on the Medeanalytics system the project may not have been started. In September 2016, NHS England plan to use this example and apply it to other areas of the country by sharing the methodology and approach that was used by Hertfordshire including the original benchmarking work using the HES-based MedeAnalytics platform. 2. In West Essex, comparison work was done using the system as part of its success regime programme that identified that a priority area was ‘low value interventions’. This came from analysis of 1-day length of stay and an analysis of inappropriate condition attending A&E. This has led to further work by the CCG to give access to GPs more real time information on admissions and A&E attenders and an associated quality improvement programme. In addition analysis using the system was used to initiate the Integrated Frailty Programme under the West Essex Better Care Fund and the Urgent Care Strategy. These programmes are subject to evaluation in 2017 and 2018. Future Benefits: The specific benefits of shifting to an outcome-based contract are well documented in the Five Year Forward View. The East Staffordshire contract aims, through a lead provider contract, to target behaviours and service design activity to improve outcomes across a number of clinical domains including diabetes and frail and elderly. The outcomes are monitoring using the HES-based Medeanalytics platform. This contract was due to start in April 2016. MedeAnalytics are currently in discussions with other areas that are looking to adopt such an approach. - Opportunity Analysis for Service Reconfiguration & Stratification Hertfordshire Valleys CCG – Oct 2016 Purpose: to provide routine benchmarked analytics to commissioners to help target reconfiguration initiatives, specifically the Health, Social and Community hub (‘The Hub’) in Borehamwood, Hertsmere within the context of ‘Your Care Your Future’ (YCYF), the strategy for a healthier West Hertfordshire. Output: A suite of benchmarked indicators, aligned with the NHS Outcome Framework, that will support the targeting of geographies and populations for service redesign. For example, the users will evaluate standardised admission ratios by condition groups to best understand relative need in their population and allocate resources appropriately, with a supporting evidence base. Additionally, using the same metrics users can evaluate the efficacy of interventions as part of a baseline study. Benefit: The introduction of integrated hubs are still underway, but the selection of pilot sites was informed by these analyses, MedeAnalytics will be used to evaluate the ongoing benefits of the hubs. Users fed back that: “Showing the number of benchmarked A&E admissions (and A&E attendances – in the next analysis) from specific west Herts geographical locations in a heat map, will enable us and our providers to direct our finite health and social care (public health) resources more efficiently and effectively.” Director of Strategy, Planning & Delivery - Risk Adjustment and Stratification – Continual Development, Calibration and Application – All Clients Purpose: Mede/Analytics are continually being asked to develop new risk adjustment and stratification models against the national dataset for a variety of outcomes/events. The purpose of these include: o calibrate and update existing national models (e.g. PARR30) to reflect the most recent patterns of activity and coding practice – this is routinely carried this out for MedeAnalytics’ Acute clients o develop bespoke indirectly standardised hospital mortality rates based on unique risk models derived from the national dataset o apply risk models from the national dataset against local datasets to facilitate case finding and performance management o evaluate complex preventative interventions Output: routinely updated suite of condition specific and all cause risk adjustment models for a number of outcomes (e.g. admissions to hospital, readmissions, mortality, long lengths of stay etc.). These are applied through performance management reporting, evaluation and baseline study reports, and through case finding in an operational context. Benefit: Users can better understand variation in their system, and make comparisons between populations and organisations in a fair and meaningful way with a greater understanding of what ‘normal’ is. This will support routine ‘opportunity analyses’ that they carry out in order to best target resources and best understand which activities have had a genuine benefit, and helped reduce costs to the system. In addition, the platform provides access to comprehensive supporting information that commissioning organisations such as Clinical Commissioning Groups use to ensure that the services they commission are: * deliver the best outcomes for their patients * designed to cater for and meet the needs of the population they are responsible for; * monitor condition prevalence within the population * identify health inequalities and work with local organisations and agencies to remove them Also for Acute Trusts and other care providers it provides access to comprehensive supporting information that helps to: * ensure that the services they provide are of high quality, efficient and effective; * plan and re-engineer services to meet the changing requirements and developments in technology; Direct measurement of the benefits associated with an enabling self-service system such as this is challenging, however, proxies can be provided through use metrics (number of individual users and frequency of use) as well as examples of decisions made by customers in the management and delivery of their services that have been supported by reports / information from the Mede tool.
The MedeAnalytics system provides information to a range of NHS and Social Care staff (including commissioners, service managers and clinicians, with responsibilities for operational, financial and clinical activities). The MedeAnalytics UK Mede system is a platform that is run on HES to produce graphs, charts, reports and dashboards specifically geared to the needs of each user. The outputs of the system are at a summary level ie aggregated data , users do not have access to event level or person level data. Where analysis produces small numbers these are suppressed in line with the ICO anonymisation standard . The outputs derived from HES data allow comparisons between the customer’s organisation or population and others nationally for a range of performance metrics such as lengths of stay , emergency admissions , A&E attendance etc. These National comparators are used by NHS organisations to improve the quality of care delivered by comparing their performance as set out by a specific range of care quality and performance measures, detailed activity and cost reports. The comparators are also used in service redesign and Health Needs Assessment (identifying underlying disease prevalence within the local population compared with the national picture). A customer typically looks at areas of activity that they are outliers for and use these as a way of prioritising service redesign activity and to target areas of deeper analysis and service improvement using more detailed data sources. As the platform allows for self service analytics MedeAnalytics cannot give a comprehensive list of all the commissioning purposes the system is used for however some examples of how the system is being used are included. Usage of the MedeAnalytics Solution is governed under the UK Data Protection Act and NHS regulations and guidance (including the Care Act) as well as the specific terms of the contracts entered into between MedeAnalytics and its clients. 1. Work done in Hertfordshire on different rates of admission for respiratory conditions by geographical area compared with national data which is informing service changes to the respiratory service in 2016. 2. On-going work looking at the number and rate of traffic accidents involving pedal cyclists that result in an admission to hospital (often under-reported to police) 3. East and North Hertfordshire CCG GPs have a report that allows them to see their referral rates and emergency admission rates compares with national averages for different conditions. This is an ongoing project. 4. The Hertfordshire Safeguarding from Children Board use an operational report on under 18 admission rates for mental health conditions, self-harm, substance misuse, and injuries due for relaunch in September 2016 5. Gloucestershire CCG use of Right Care Peers comparators looking at 10 core HES based metrics derived from UK Mede including: follow up to first outpatient ratio, percentage elective conversions , readmissions in 30 days, and inappropriate admissions. Most of these have specific targets to reduce in the Gloucestershire CCG area . In addition, the data is used to produce comparative baselines of outcomes and will enable commissioners and providers to identify clinical areas to prioritise and to take the first steps on the path to outcomes-based contracts. An example is the East Staffordshire CCG outcome-based contract that was due to go live in April 2016 and is currently subject to ministerial review. The HES based MedeAnalytics system will be used to set baselines in these contracts (often contracts of five or more years). Performance is measured against these historical baselines and the trends calculated to drive payment. Baseline trends used to set trajectories must be robust (i.e. avoiding spikes or dips in the data due to changes in coding practices for example). When creating a best-fit line (regression line) for trajectory setting, an absolute minimum of three complete years of baseline data are required to have a reasonable degree of confidence, although five years of baseline data are preferred to ensure accurate trend lines, to allow for evaluation of statistical significance of year-on-year changes, and associated confidence intervals. This is essential when setting outcomes-based contract trajectories as the extent to which true change is expected to occur must be determined. Outputs from the system are used by clinical, financial and operational staff, across all levels including management, and are frequently used in board papers. Live access to the MedeAnalytics system (primarily through mobile devices) is used during board meetings to support operational decisions and answer live questions. HES (or HES-derived) data presented via the tool complies with the ICO anonymisation standard. Access is limited to UK users by browser location controls. IP addresses not registered in the UK are blocked from accessing the system. Access to Isle of Man users will also be permitted under this agreement, as if the Isle of Man were part of the UK. The data items that users are able to access depend on each individual user's rights and the multi-dimensional role to which they are assigned. This means that users have access only to the relevant subset(s) of data contained in the tool.
The MedeAnalytics system provides information to a range of NHS and Social Care staff (including commissioners, service managers and clinicians, with responsibilities for operational, financial and clinical activities). The MedeAnalytics UK Mede system is a platform that is run on HES to produce graphs, charts, reports and dashboards specifically geared to the needs of each user. The outputs of the system are at a summary level ie aggregated data (with small numbers suppressed in line with the ICO anonymisation standard), users do not have access to event level or person level data. HES data is accepted into MedeAnalytics’ secure, FTP service (which is accessible from an N3 connection). On landing, initial data quality checks are undertaken (e.g.: to ensure that the correct number of records have been received, that it is not a duplicate transmission). Upon successful download of data, the ETL (Extract, Transform and Load) process is run against the data to receive, normalise and upload the Data into MedeAnalytics' central databases. ETL processing includes the following: • Extract (data receipt/collection, cleanse, parse and pre-processing) • Transform (aggregation, normalise, apply business rules) • Load (OLAP cube processing and database load) • Data integrity and reconciliation (pre and post ETL) • Performance tuning (DB indexing and data cache) • Trending archive and meta data repository and file back-up management • Production testing and QA During Transformation processing, algorithms are run to create derived data from the data stream. Derived fields are stored alongside the original data as additional fields that allow different levels of obfuscation based upon Roles Based Access Controls (RBAC). The retention period is the current NHS year plus five previous years for historical comparisons. At the end of the retention period, MedeAnalytics removes expired data and can provide appropriate destruction certificates. The reason that a longer period is needed is to provide a robust timeline with at least 4 data points to establish the baseline and trend for the management of outcome-based contracts. Three years would provide only 2 data points and the confidence limits are too wide to be useful. Our statisticians have advised us that 4 data points is the minimum. MedeAnalytics can confirm that it has complied with all previous data deletion requests. Please note: MedeAnalytics will only process data in the Back up/Disaster Recovery Centre in the event of a disaster that renders the primary data centre inoperable, and occasionally (no more than once per year) to test that the back-up/Disaster Recovery system is functional. Normal data processing is performed at the primary data centre.
The objective is to provide MedeAnalytics International Limited (“MedeAnalytics”) customers with national comparators for a range of quality and performance metrics that are derived within the MedeAnalytics UKMede system that uses HES data. The record level HES data is not linked with any other data. MedeAnalytics provides an online service to customers that are limited to clinical commissioning groups, care quality commission registered providers and public health departments, accepting data, storing it in the central repository, then providing online analytics and reporting services. Where a client of MedeAnalytics is an independent sector provider, data from NHS Digital can only be used in support of their NHS-commissioned work. In addition, the system is going to be used by customers in the Isle of Man (limited to the department of health, hospitals, community providers, and general practitioners). They are using the system to understand the performance of their health system and its relationship with the mainland NHS. The users on the Isle of Man are limited to those public organisations that come under the remit of the Isle of Man government Department of Health and Social Care. Use cases supported by the MedeAnalytics system include commissioning activities, operational and financial activities, comparators and indicators, case identification, data quality validation, and the informing of direct patient care support. By using HES data to compare activity from one region to another MedeAnalytics’ customers use the UK Mede platform to identify clinical domains where they are significant outliers. This enables them to prioritise their service redesign activities. HES is also used to produce baselines for a number of outcome metrics (eg amputations, acute kidney injury, or myocardial infarctions) that are derived from HES, these are then used for outcome based contracts. The platform based on HES is used by operational, clinical and financial staff, to inform the better use of services and resources, and ultimately better patient outcomes. In some circumstances the customers use third parties to analyse data on the system – they might include individual consultants, contracted staff or consultancy firms who have a contract with MedeAnalytics’ customer and are therefore acting as their agents. Any access to data by MedeAnalytics' customers is only ever access to aggregated data, with small numbers suppressed in line with the ICO anonymisation standard.