An exploratory analysis into the likely accuracy of date of diagnosis by condition in the National Bridges to Health Segmentation Dataset. This can be used to help inform and interpret results of incidence analyses conducted on the National Segmentation Dataset.
Data Source: An existing local ICB Segmentation Dataset – derived from linked data from GP Practices and hospital admissions and outpatients appointments (SUS).
The column on the right combines the green and amber bars to produce an overall ‘incidence reliability score’ i.e. where a recording of a condition occurs in hospital data first or within 2 years of the condition being recorded in primary care. This indicates the likely accuracy of the ‘date of diagnosis’ in the National Bridges to Health Segmentation Dataset.
Conditions near the top of the chart have the highest reliability scores, and are typically those which present first in secondary care such as coronary heart disease and severe interstitial lung disease. Conditions towards the bottom of the chart such as asthma and chronic kidney disease have a less reliable date of diagnosis, as they are often diagnosed and managed in primary care in their early stages, in people with fewer long term conditions, who are less likely to have hospital admissions.
The National Diabetes Audit (NDA) data is one of the source datasets used to derive the National Segmentation Dataset. NDA data is extracted from primary care, and therefore the ‘date of diagnosis’ for diabetes in the National Segmentation Dataset is likely to be highly accurate.
A number of conditions available in the National Segmentation Dataset are not included in this analysis for different reasons including definitional differences, complexity and low volumes. These include: Cystic Fibrosis, Chronic Pain, Osteoporosis, Sarcoidosis, Sickle Cell Disease, Frailty, Incurable Cancer subsegments, as well as a number of subsegments in the Organ Failure segment.
Last Updated: 30th October 2023
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