Public Health Outcomes Framework (2022)

NI = National Indicator

N/A = Not available

Unless otherwise stated, data presented are for Wales residents, and the geographies within health boards and local authorities.  Sub-local authority geographies include upper, middle and lower output areas and urban and rural classification.

National Survey for Wales:

Data presented in the tool is by financial year for the 2020-21 only.  Not all questions were asked during this survey period; therefore, data was unavailable for the following indicators:

• Mental well-being among adults NI
• The gap in mental well-being between the most and least deprived among adults
• People able to afford everyday goods and activities NI
• People who volunteer NI

In addition, direct comparisons over time are not possible due to the significant change in methodology each year.  The previous PHOF tool contains historic data. 

Useful links

• Terms and definitions
• Introduction and survey methodology
• Technical information
• 2020-21 data
• Results viewer

Patient Episode Database for Wales:

The Patient Episode Database for Wales (PEDW) comprises records of all episodes of inpatient and day case activity in NHS Wales hospitals. Hospital activity for Welsh residents treated in other UK nations (primarily England) is also included.  The data is collected and coded at each hospital. The records are then electronically transferred to Digital Health Care in Wales, who validate and merge into the main database.

Please note that there is an issue with diagnostic coding in several health boards. Table 1 illustrates how the missing codes are distributed by financial year and health board, as at August 2022. Counts of specific diagnoses will be underestimated, but to an unknown extent, therefore caution should be exercised when interpreting trends for these health boards.

Table 1 Missing diagnostic codes, emergency admissions (excluding transfers) by area and financial year

Useful links

ICD-10 codes

NHS Wales Data Dictionary

PEDW Publications Table

Life expectancy (LE)/ Healthy life expectancy (HLE) at birth:

The PHM is used to calculate Life expectancy (LE) at birth, it is an estimate of the average number of years that newborn babies could expect to live, assuming that current mortality rates for the area in which they were born applied throughout their lives.  It is calculated using the abridged life table method which is the preferred method of the ONS.  As all LE calculations are based on current mortality rates, average life expectancy will change over the course of a lifetime irrespective of other factors.  These should therefore be considered as comparative population measures of mortality during a period of time rather than as predictions of actual individual life expectancy.

Healthy life expectancy is an estimate of the average number of years that newborn babies could expect to live in good health, assuming that current mortality rates and levels of good health for the area in which they were born applied throughout their lives.  HLE is calculated using the Sullivan method which is the preferred method of the ONS for calculating healthy life expectancy at birth.  Its calculation involves combining health status data from the Annual Population Survey (APS) and Census with the mortality and population data used for LE.    ‘Healthy’ was judged to be a response of very good or good to the APS question asking those aged between 16 and 85 “How is your health in general; would you say it was … Very Good, Good, Fair, Bad, Very Bad”.

Adjustments are applied to prepare the APS data for the Sullivan method which use the Census health data, these include:

• • Imputation of health prevalence for age groups not available in the APS (children under 16 years and adults over the age of 85). 
  • Using regression analysis to smooth fluctuations in the subnational health prevalence.

Imputation is also needed where for a particular breakdown:

• • there was no valid response to the good health question in a breakdown.
  • the prevalence of good health was 0, regardless of how many respondents there were who weren’t in good health.

Statistical First Release, ONS

Percentages for people in education, employment or training were provided by the Statistical First Release (SFR) as it is the most robust source for young people not in education, employment or training (NEET) data.  The SFR uses the Annual population survey (APS), Higher Education Statistics Agency (HESA), Pupil Level Annual School Census (PLASC), Lifelong Learning Wales Record (LLWR) and ONS mid-year population estimates and forecasts as its data sources.

As the data comes from a survey, the results are sample-based estimates and are therefore subject to differing degrees of sampling variability, i.e. the true value for any measure lies in a differing range about the estimated value.

Data is published annually, 2020 data is provisional at this point.  The dataset can be accessed via stats wales.

Conception statistics (ONS)

The ONS conception data is used to help calculate teenage conceptions, alongside mid-year population estimates to produce rates per 1,000 females (15-17 year olds).

Quality and methodology information

User guide to conception statistics

Dataset

Public Health Mortality

Public Health Mortality (PHM) is a dataset containing each individual death of a resident that is registered in the particular year. Individual records for death registrations are sent on a weekly basis from the Registrars’ offices across England and Wales to the Office for National Statistics (ONS). The ONS collates and validates the data. The data are based on the underlying cause of death e.g. if an individual dies from pneumonia but had been made vulnerable to that disease by end-stage cancer, then cancer (rather than pneumonia) is recorded as the underlying cause of death.

There have been revisions to the manner in which the death certificates are translated by the ONS into International Classification of Diseases codes (10th revision). These changes mean that unrevised data are not comparable across years. The main change relates to the rules that govern which cause of death detailed on the death certificate is selected as the underlying cause. Comparability ratios have not been used in these analyses and therefore caution should be exercised when interpreting trends.

Cause of death is based on the medical certificate of cause of death. This is completed by the certifying doctor for about three quarters of deaths and by a coroner for the remainder. Most of the deaths certified by a coroner do not involve an inquest or any suspicion of violence, but are referred to the coroner because they were sudden and unexpected, or because there was no doctor in attendance during the deceased’s last illness. There will be a long delay in registering a small number of deaths for which a coroner’s ruling is required e.g. suicide, homicide, undetermined intent.

Please note that suicides have been counted by date of registration. There is a known delay between date of occurrence and the date of registration; further delays are likely as a result of the coronavirus pandemic. Please be aware that data is likely to be incomplete, particularly for the most recent periods.  See ONS for more information:

Impact of registration delays on mortality statistics in England and Wales - Office for National Statistics (ons.gov.uk)

Other key data sources:

Welsh Index of Multiple Deprivation 2019 (WIMD) (used to calculate fifths of deprivations).

ONS Mid-year estimates (MYE) (used as the denominator when calculating crude and age-standardised rates).

How to interpret:

• Confidence intervals

Confidence intervals are indications of the natural variation that would be expected around a rate and they should be considered when assessing or interpreting a rate. The size of the confidence interval is dependent on the number of events occurring and the size of the population from which the events came. Generally speaking, rates based on small numbers of events and small populations are likely to have wider confidence intervals. Conversely, rates based on large populations are likely to have narrower confidence intervals. In the PHOF reporting tool we use 95 per cent confidence intervals. This represents a range of values that we can be 95 per cent confident contains the ‘true’ underlying rate. Comparisons are often made between two or more estimates, for example between different areas or time periods (Figure 1). Sometimes in such cases statistical testing is undertaken by comparing the confidence intervals of the estimates to see if they overlap. Non-overlapping confidence intervals are considered as statistically significantly different (Figures 1a & 1b). Whilst it is safe to assume that non-overlapping confidence intervals indicate a statistically significant difference, it is not always the case that overlapping confidence intervals do not (Figure 1c). A more exact approach is to calculate the ratio of the two estimates, or the difference between them, and construct a test or confidence interval based on that statistic. Such methods are not covered in this technical guide, but can be found in a standard textbook.

Figure 1. Using confidence intervals for making comparisons a) & b) Non- overlapping confidence intervals are considered as statistically significant c) Overlapping confidence intervals do not always indicate a difference that is not statistically significant

• Local and national deprivation fifths have been used for national level analysis. For the health board and local authority level analysis, however, specific deprivation fifths within each area have been produced, as some areas do not have sufficient numbers of LSOAs in each national fifth. For example, Blaenau Gwent has no LSOAs that are nationally classed as least deprived. This approach is consistent with those used elsewhere in the UK.

• Revised European Standard Population 2013

• National Indicators (NI) represent the outcomes for Wales, demonstrating progress towards seven well-being goals. There are 50 NI's in total, ten are reported in the Public Health Outcomes Framework.

For supporting evidence, please refer to our Evidence service homepage.