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Arden & GEM CSU > News & Insights > Why data analysis should be part of your practice DNA

Why data analysis should be part of your practice DNA

When it comes to providing more efficient and effective services, the quick wins have already been banked. So how do GP practices continue to improve services and save money – while grappling with an ageing population, exponential rise in long term conditions, tighter budgets, increasing vacancies and a heavier workload – asks Helen Seth, Associate Director of Business Intelligence at Arden & GEM.

While data analysis may not be the answer to all these challenges, using risk stratification does give clinicians a greater understanding of the likely behaviour and vulnerability of their patients and enables them to plan more effective services as a result. As more practices work together across localities or under new arrangements such as federations, the opportunities to use data to improve preventative care increase.

Risk stratification in practice

Risk stratification tools are used to identify and predict outcomes for particular cohorts of patients based on a range of algorithms. The Arden & GEM CSU risk stratification tool utilises the highly-regarded population profiling and risk markers developed by the Johns Hopkins Adjusted Clinical Group (ACG) System. Rather than focusing on specific diseases or episodes, this system encourages a holistic view of the patient, including co-morbidities that could affect commissioning and care management decisions.

Using primary and secondary care data on admissions, GPs and CCGs can use the tool to build registers of high-risk patients and drill down to view individual care pathways. The tool also shows patients attendances to A&E, hospital admissions and outpatient appointments. This gives primary care healthcare professionals essential insight into how they might consider modifying care plans and pathways to improve self-care, reduce GP appointments and hospital admissions, and support patients’ needs in the most cost effective way.

Unlike some legacy algorithms, the Johns Hopkins ACG system is updated monthly with both clinical and secondary care data. This enables us to create reports that offer insight into specific issues or treatment pathways, as well as identifying population trends to support future commissioning. Using filters such as age band, condition and frailty, cohorts of patients can be used to create bespoke lists for case management programmes. This approach is empowering health and social care organisations to deliver targeted care and health promotion strategies where their work will have the best impact.

Enhancing preventative care

Naturally, the temptation is to focus on using risk stratification to tackle the most immediate high cost issues. This work is certainly important and there is evidence that this approach is helping to reduce A&E attendances. But this is just the tip of the iceberg – and it’s also the toughest area to deliver sustainable results. Tackling top costing patients is always going to be challenging as the likelihood is they will have a complex combination of conditions which may already be reasonably advanced. While some proactive intervention may reduce A&E admissions, it may not be possible to make sustainable changes which deliver significant benefits.

As organisations become more familiar with risk stratification, we are starting to see exciting work being done to radically improve patient care before needs become too great. Where practices and other organisations work together, either through an alliance, across a CCG or across community services, risk stratification can be used more effectively to identify common conditions and lifestyle factors, understand the impact of different care pathways, and support future commissioning decisions.

Working in partnership with business intelligence analysts

One of the common concerns about using a tool like risk stratification is time. Against the backdrop of a fast-growing workload, how can you possibly justify practice time spent analysing data? Much depends, or course, on how you work with your analysts.

In our experience, the biggest gains to be had are when we work in partnership with customers to develop bespoke reports which provide the data needed to tackle specific priorities. This type of partnership working between expert analysts and customers not only helps practices with their immediate priorities but also enables business intelligence teams to identify new areas to investigate and to share best practice across the NHS.

Shared learning

Risk stratification is improving all the time as clinicians and analysts become more confident and conversant in how it can be used to improve patient care. By looking at data across comparable localities, variations in performance and approach between practices can be identified. This has already led to learning being shared across localities, helping to fast track improvements and deliver much needed efficiencies.

Data analysis may not immediately appear to go hand in hand with improving patient care, but as we work together to develop more creative and innovative ways to stratify patients and understand the triggers for health deterioration; analysts, clinicians and commissioners can work together to identify new and sustainable opportunities to improve quality and outcomes.

This is a summary of an article written for Management in Practice. To view the full article visit http://www.managementinpractice.com/asktheexpert-it/why-data-analysis-should-be-part-your-practice-dna

To learn more about Arden & GEM’s Risk Stratification tool, please click here.

Author: Helen Seth
author_helenseth

Helen is responsible for the operational management of our business intelligence service. A diagnostic radiographer by background, Helen has over 29 years’ experience in NHS provider organisations including service delivery, operations management , corporate strategy and system wide transformation.  Most recently she has been implementation lead for long term conditions as part of the Leicester, Leicestershire and Rutland Better Care Together programme.