<p>Modelled counts of patients registered at a GP practice by single year of age (0-95+), sex, and local authority of residence.</p>
<p>
<span style="color: rgb(63, 82, 95);">These modelled data contain information from NHS Digital, licenced under the current version of the Open Government Licence:</span>
</p>
<ol>
<li>Counts of patients by practice attended x sex x LSOA of residence - currently published quarterly</li>
<li>Counts of patients by practice attended x sex x single year of age - currently published monthly</li>
</ol>
<p>These data are published by NHS Digital here: <a href="https://digital.nhs.uk/data-and-information/publications/statistical/patients-registered-at-a-gp-practice" target="_blank">https://digital.nhs.uk/data-and-information/publications/statistical/patients-registered-at-a-gp-practice</a>
</p>
<p>Please refer to NHS DIgital documentation for full <a href="https://digital.nhs.uk/data-and-information/publications/statistical/patients-registered-at-a-gp-practice/data-quality-statement" target="_blank">data quality</a> and <a href="https://digital.nhs.uk/data-and-information/publications/statistical/patients-registered-at-a-gp-practice/metadata" target="_blank">metadata</a> information about the original data.</p>
<p>The GLA modelled counts of patients by age, sex, and local authority of residence are created by a simple process of apportioning the data for each GP practice in (2) by the distribution for each practice in (1). As residence data is only published quarterly, distributions for other months are interpolated.</p>
<p>A respository of the code used to generate the modelled counts is available on GitHub at: <a href="https://github.com/Greater-London-Authority/process-published-nhs-data" target="_blank">https://github.com/Greater-London-Authority/process-published-nhs-data</a>
</p>
<p>This data is used as an input to <a href="https://data.london.gov.uk/dataset/modelled-estimates-of-recent-births" target="_blank">Modelled estimates of recent births</a>
</p>
<p>
<strong>Notes on usage</strong>
</p>
<p>Patient register data can be used to provide frequent low-latency indicators of changing population trends. However, patient counts should not be interpreted as a direct proxy for population. Patient counts have been prone to compounding inflation in recent years, primarily as a result of failures to remove former patients that have since moved overseas (local inflation/deficits also occur due to delays in patients updating their records or registering with a new GP when moving within the UK).</p>
<p>The rate of inflation varies by area, sex, and age, being greatest for:</p>
<ul>
<li>areas with high volumes of international migration</li>
<li>adults age 20-30 (with the impact spreading to older groups over time)</li>
<li>males - due to typically lower levels of interaction with health services</li>
</ul>
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