New algorithms were developed to identify emergency admissions due to COPD. When compared with the national analysis, the NWC algorithm identified 58% more admissions for people with COPD currently being provided with NHS care.
COPD is the second most common cause of an acute medical admission, and NICE guidelines suggest many of these cases could be prevented or managed outside hospital. COPD is slowly progressive and most admissions are from people who are breathless during mild or minimal exertion, 60 or older, and come from more deprived backgrounds.
NWC CHC identified the COPD patients from the Secondary Uses Service (SUS)dataset with a new algorithm that made use of more than just the primary diagnosis. This improved the detection of COPD admissions. The NWC CHC team then characterised the admissions, examined their prior and later history and mapped them to locate ‘hotspots’ of admissions. The algorithm identified a total of 52,389 emergency admissions due to COPD over 3 years across the 12 NWC trusts, compared to just 33,233 spells if only the first diagnosis code was considered. Therefore the algorithm identifies 19,156 additional COPD admissions (a ‘missed’ population of 58%). This missed population is more severe, older and from deprived areas, with three times higher hospital mortality and has much higher use of resources (e.g. 81% more bed days).
Planning based on the official statistics (which take into account some of the issues around coding of COPD admission), when the exclusion of these additional more severe patients are omitted, will significantly underestimate the impact of COPD and the staffing required to manage it.
Some of the applications from the COPD NWC CHC project outputs:
Two CCGs in Central Lancashire have used the local area data to drive the early stages of their Elective Care Respiratory Quality Improvement Programme. This methodology enabled them to focus on the most challenged areas of their populations to improve the integrated care pathway for the biggest benefit at the lowest cost.
As part of the wider local respiratory strategy, data and methodologies from NWC CHC were used to contribute to data sets made available to CCGs and respiratory teams across the Cheshire and Merseyside Network, informing resource allocation across the regions. A Physician Associate Scheme in the area was set up to review COPD patients more efficiently and get them ‘winter-ready’ as well as supporting hospital A&E departments in the colder months. The Learning Health System can evaluate the effectiveness of this approach.
A COPD dashboard has been developed at Lancaster University so that healthcare professionals can access relevant information to improve service planning and delivery in their area.
Government bodies intend to make use of these new algorithms in the future and the Innovation Agency has developed a respiratory theme and is incorporating outputs from the COPD Pathway developed by NWC CHC.
Why we developed new algorithms to find more existing cases.
The North West Coast CHC project was concerned that many standard reports about clinical conditions were being disregarded by clinicians because the numbers within those reports did not match their clinical experience.
Most reports only use the first of many diagnostic codes recorded for each patient and so fail to take account of the additional information available. In each of the disease areas, NWC CHC has developed algorithms using the wider information available to identify the cases that physicians can recognise, and in doing so, has found more cases, as well as cases with greater severity, which provides a very different assessment of workload and patient pathways.
As this is based on a clinical rather than just a statistical approach, the response from the clinical community to our reports has been uniformly favourable and we believe this offers a better way forward for future planning of, and assessing the effectiveness of, clinical care. We describe the approach in three specific disease areas but the approach is taken equally applicable to many other areas within medicine.