Please refer to the disclaimer for further information on data sources and copyright details.

Each dashboard includes a comparison feature, allowing you to compare data with another local area, the national average, or a different year. Colours are used to highlight areas of higher activity (e.g. hospital admissions) and differentiate between various data categories.

Some dashboards have navigation buttons along the top which you can use to navigate between different views of the data.

Tooltips are utilised across the dashboards to provide additional information when you hover over datapoints of interest.

In some dashboards, you can view the data in tables as well as charts, to see an overview of all data for your selected filter options.

Filters

To get the information you’re looking for, there are several common filters to choose from:

Organisation Type – use to select the organisation type you wish to view. Depending on the dashboard being viewed, this may include National, Region, Integrated Care Board (ICB), Trust and Primary Care Network (PCN).

When you select PCN you need to go to the other dropdown of organisation networks to select a chosen PCN – it does not automatically update to the first alphabetical PCN. If the other dropdown titles have brackets around the name it is a sign that they need to be checked to re-select the organisations and other variables.

Organisation Name – use to select the name of the organisation you wish to focus on. This will be of the type selected in the organisation type filter. You can search the organisation name filter using the filter search bar. On comparison dashboards, you will be able to select multiple organisations to compare; it is recommended that you select no more than 4 organisations.

Diagnosis – use to select which diagnoses you wish to view data for in the dashboard. The codes refer to the International Classification of Diseases (ICD) 10 clinical codes. Diagnoses available are: all respiratory disease, asthma, bronchiectasis, COPD (Chronic Obstructive Pulmonary Disease), influenza, interstitial lung disease and pneumonia.

Diagnosis Position – use to select the diagnosis position you wish to view data for in the dashboard. Each hospital admission is called a spell, and each spell is made up of episodes. All diagnosis position is where the selected diagnosis has been coded in any position within a hospital spell. Primary diagnosis is the diagnosis which brought a patient into hospital while secondary is an existing health condition that is not the main reason for the current healthcare (i.e. underlying chronic condition). Note that the figures for All may not match the sum of Primary and Secondary, as some patients may have the same diagnosis coded in different positions within the same spell.

Value Type – use to select the metric you wish to view in the dashboard, for example Patients or Cost. The value types available to view depend on the data source of the dashboard.

Normalisation
Normalisation allows the fair comparison of data between organisations. Most of the dashboards have the opportunity for you to normalise the data by 100,000 of the population. Only National, Region, ICB and PCN data can be normalised. Trust data cannot be normalised as they do not have a defined population.

Suppression
Data suppression is used to protect the privacy and confidentiality of patients. Numbers that could relate to a patient are suppressed in accordance with NHS England guidelines, with suppressed values rendered with a * or -1 on the dashboards. In some cases, e.g. bar charts, the suppression is shown as now bar, but the suppressed value of */-1 is present in the tooltip for you to view.

For HES data that could relate to a patient, values between 1 and 7 are suppressed; all other numbers that could relate to a patient are rounded to the nearest 5. Data is rounded based on the original figures, so some items such as totals may not sum correctly. The reference document gives further information on suppression, including test scenarios.

Normalisation – in most dashboards, data can be viewed as actual values (absolute), or normalised values (rate per 100,000 population). Note this is set to rate as default to allow for fair and accurate comparisons by standardising data across different areas, population sizes and demographics. Do not use absolute values for comparisons – they can be misleading because they do not account for differences in population size or demographics. For example, a larger area will naturally have a higher number of hospital admissions simply because there are more people. However, it does not necessarily mean that hospital admissions are more frequent in that area.

There are other filters present on some dashboards that allow you to further refine what you see and are specific to the dashboard selected.