Working with Sollis, NHS South East CSU helped several CCGs in London and the south-east to implement new reporting and service planning initiatives. Here we summarise how the CCGs used the insights provided by Sollis Clarity Health Analytics and ACG® System analysis for service planning and transformation.
Falls, Bone Health
A clinically-led team in Croydon used the Sollis Cube Viewer and Clinical Code Listener to examine cohorts of patients who had either fallen or were at risk of falling. Criteria for these groups came from the clinical lead of the team. These criteria were then interpreted by South East CSU and given to Sollis for configuration. Surfacing this information as a collection of Care Programmes within the Activity Cube and Cube Viewer gave the Croydon team quick and easy access to the data, along with the ability to triangulate this information with Secondary Care data.
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Serious Mental Illness
Another team requested data on patients with Serious Mental Illness in relation to local and national reporting requirements, as well as in support of their own service planning and Public Health initiatives. South East CSU were able to interpret their requirements as a collection of bespoke searches in Primary Care data, and provide support in interpreting the data. Sollis configured these reports and made them available to the Croydon team via the Activity Cube, enabling the team to view their results over the last rolling year by practice. The team could share this information directly with practices in a patient-identifiable format, and with Public Health colleagues in an anonymised, aggregated format.
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Croydon planned to use Sollis Clarity Health Analytics in order to understand their population better and work out the potential size of the pressure ulcer management service they will commission. They also sought clinical leadership to help to identify signs that would indicate where patients are at risk of pressure ulcers, and use Sollis Clarity Health Analytics to report that back to GPs for proactive intervention.
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Primary Care Variation
Using Sollis Clarity Health Analytics for population health management helped Croydon’s Primary Care Variation team understand the provision of care across the Primary Care landscape. At time of writing, they were using Sollis Clarity Health Analytics to construct reports to inform commissioning intentions and service planning in future.
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There was an urgent need to identify patients with dementia in Croydon according to the QOF definition of dementia. This was created by Sollis and released ahead of schedule as a bespoke extract, before being included in the final release of Clarity Patients 3.4.
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A team at Croydon planned to use Sollis Clarity Health Analytics to help monitor primary and secondary care activity for patients resident in care and nursing homes. The CSU worked with the team and Sollis to develop a bespoke dataset to identify patients resident in care and nursing homes from primary care data. This enabled their service usage in both primary and secondary care can be measured.
East Surrey CCG
Higher Cost Patients
A clinically-led team in East Surrey used the Sollis Activity Cube, Cube Viewer and Multi-practice Case Management reports to examine where they might have opportunities to reduce costs and increase the efficiency of their services. With the support of the CSU they were able to identify a ‘bulge’ of cost that appeared to show patients who were not catastrophically ill, but rather had consistently higher-than-average costs. This information was combined with a high number of attendances (more than five A&E attendances in the last 12 months) to identify where inappropriate use of the system was to blame for the higher cost. A list of these patients was then shared with the GP practice via Sollis Clarity Health Analytics for follow up.
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Unplanned Care Locally Commissioned Service
Following the initial work done on higher costing patients (above), East Surrey CCG wanted to identify three distinct groups of patients; frequent attenders to A&E (more than 5 attendances in the last 12 months), patients with COPD ranked by probability of emergency hospitalisation and patients without COPD ranked in the same way. This information was then shared with GP practices via Sollis Clarity Health Analytics for follow up, and was used at an aggregated level for service monitoring by the CCG.
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Community care workers form part of the rapid reaction team that helps GPs to manage higher risk patients. As a result, they use Sollis Clarity Health Analytics to have more up‑to‑date access to the patients’ notes, and to be able to manage their caseload.
Asthma, COPD and Frequent Attenders
Sollis Clarity Health Analytics and the ACG System have helped a business-led team in Merton to analyse information on the number of patients by practice that were attending A&E, along with their conditions, risk score data and the reason for attendance. South East CSU used a combination of Sollis Clarity Health Analytics and standard BI reports from SUS to create a combined report, showing reason for admission as well as risk scores and primary care diagnoses. Based on this work, Merton CCG’s analysts determined that the most common reason for admission was exacerbation of COPD symptoms. This data was subsequently triangulated with practice records of MRC breathless scores of 4 or more.
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AUA, Community, Continuing Care and Secondary Care Admission
Merton CCG are using Sollis Clarity Health Analytics and the ACG System to help them triangulate information across a number of patient cohorts:
- Patients within the top 2% probability of emergency hospitalisation across Merton
- Patients in community care (over the last year)
- patients in the continuing care programme (over the last year)
- Secondary care admission HRGs (over the last year)
A master patient index was created based on the three main datasets (top 2%, community and continuing care), then checked to identify which patients were common to which groups. Secondary care information was used from Sollis Clarity Health Analytics to identify where events had occurred, and again mapped to patients in the other datasets. The latest piece of work is now to find the HRGs that those patients attended with, to enable a service to be identified to fill in the gaps between community, continuing care and secondary care and better support the patient.
Surrey Downs CCG
Identifying High Cost Patients
Following training in the use of Sollis Clarity Health Analytics at a CCG level, Surrey Downs CCG incorporated high cost user information into their routine reporting. This has led to a general acceptance of ACG scoring as a valid metric in the CCG.
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Health Economy Radar Charts for Locality Meetings
Following the introduction of the health economy radar charts in Sollis Clarity Health Analytics, Surrey Downs CCG began to use them to facilitate discussions with GP practices — both individually and at locality level — to understand their performance across five key metrics:
- Prescriptions issued (which can be used as a proxy for whether a condition is being managed in primary care or not)
- Outpatient first attendance
- A&E attendances
- Emergency admissions
- Elective admissions
Surrey Downs CCG has included Sollis Clarity Health Analytics and the ACG System’s metrics as business as usual within the CCG. This means that future work using them will be easier to communicate.
Diabetes Risk Finding
Sollis Clarity Health Analytics and the ACG System were used to support diabetes case finding at Sutton CCG, assisting with long-term condition management and helping the CCG to reduce overall costs.
Sutton CCG’s analysts created a series of cohorts that they wanted to examine, based on primary care data, that Sollis Clarity Health Analytics can identify to the user. They split patients into groups of high, medium and low risk of diabetes to enable a better identification of patients who may be undiagnosed and therefore not managing the condition.
This information can then be fed back to GPs for action, and support the implementation of a service to manage patients with diabetes across primary care.
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Cohort Identification Work
Sutton CCG planned to identify a further cohort of patients that might lead to savings in secondary care within the CCG. This is based on increasing the savings realised by the Avoiding Unplanned Admissions cohort (top 2% by probability of emergency admission). As a result, the CCG is looking to identify where they might be able to use predictive risk to identify patients whose conditions have not yet become critical, and where early intervention might enable more efficient and more cost effective care.
The ACG System’s predictive models and risk stratification capability, combined with Sollis Clarity Health Analytics reporting, will enable Sutton to target patients lower down the risk pyramid where interventions can be more effective.
Planning All Care Together (PACT)
Wandsworth CCG used data from Sollis Clarity Health Analytics to help identify several new care programmes they wished to commission (their PACT locally commissioned service) and the candidate patients for those programmes. Sollis Clarity enabled the CCG to monitor the adoption of the programmes in GP practices and also to measure the effectiveness of the clinical interventions. They are now planning the use of community data alongside the core GP and acute information to identify candidates for more intensive multi-disciplinary team (MDT) support.