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Facing the NHS Winter Pressures with Analytics

Monday 5 October 2015

As we enter the Autumnal months and start to think about beginning our Christmas shopping, the NHS brace themselves for unprecedented patient demand, particularly in their Accident and Emergency departments over the winter period. It is widely known that each NHS organisation faces a daily challenge to balance patient care and growing waiting lists with long term financial constraints – so any initiative that proactively tackles a seasonal trend such as this should be whole heartedly embraced.

With the cold wet British weather comes an increased number of hospital admissions particularly via the A&E departments. So, is it possible to predict this demand and proactively manage it? Well, many NHS organisations are already planning for this and have been for a number of years. But can Business Intelligence influence the success of these initiatives?

The NHS has a whole host of systems that are capturing data across primary, community and secondary care, so surely there must be some answers in there somewhere. NHS organisations are using this data to identify patients at risk – by analysing historic data and capturing the specific cohort of patients that did result in a hospital admission. Trusts can then use this information to target patients with similar criteria and conditions to define and deliver proactive care plans.

There are a number of community care streams that have been identified for delivering this care, such as District Nursing, Anticipatory Care and Out of Hours.

Increasing District Care availability by scheduling it on a 24/7 basis involves a financial investment. However, if this additional care means that patients are treated proactively and their conditions are managed to avoid any unnecessary A&E attendances and subsequent admissions, then the value to the patients involved coupled with the saving in bed days is an investment well spent.

GPs have an understanding of their patients and their conditions, all of which are captured electronically. Applying risk stratification to this patient data will more effectively identify patients that are at risk of an unplanned admission during the winter period. Having identified these patients, Anticipatory Care Plans can be defined and delivered.

Out of hours services can provide valuable insight into treatments provided to patients that contributed to an admission avoidance.

As technology advances, it no longer takes massive effort to collate data and analyse it. It is possible to bring data from multiple data sources, across primary, community and secondary care organisations in varying formats and present it in one place quickly and easily. The data can be combined into searchable indexes to form a rapid integrated search engine that can be used to explore, discover and gain insight out of the data, providing a super-fast analysis platform that can be used to generate report outputs that can be used to measure hospital admission avoidance. Unlike traditional BI, new state of the art technology provides the user with the ability to perform ad-hoc analysis over any combination of data fields without the need to design and implement a fixed set of dimensions or measures.

Now the data is available measuring the success of the winter initiatives has never been so easy. Metrics can be put in place to identify the patients that require additional care to avoid hospital admissions over the winter period. Once identified, the data can be analysed to report what actually happened to the patients at risk. The value of each community care strand can then be measured and where appropriate revision of plans can be made to learn from the process and make further improvements.

It is extremely difficult to predict the attendances in an Accident and Emergency department by the very nature that patients arrive as a consequence of an unforeseen event. Managing the department to ensure that patients with a real life threatening emergency are seen and treated effectively can be impacted by the unpredictability of attendance at any given time. Trusts are looking to technology to support this challenge. Patients are informed of the current capacity of each department through real-time A&E data capture. The patient can see the number of patients waiting and make an informed choice as to the hospital they decide to visit. In circumstances were the visit may not be critical, the patient may decide to seek alternative options and relieve the pressures on their local hospitals.

BI is being used to support the challenges faced by the NHS especially the increased pressures experienced during the winter period. The NHS strives every day to meet patient need – as technology advances, so do they. The age of number crunching has gone. The NHS can now use data to make informed decisions, support transformational change and deliver the most effective patient care.

For more information or to arrange a personal demonstration of CXAIR please contact info@connexica.com

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