All Indicators > Indicator SA1: Effective primary care
| Definition | A measure of the effectiveness of primary care |
| Dimension | Situation of health |
| Sector | Appropriate care (intermediate) |
| Components |
|
| Source | Various - see component details |
Component SA1_1: GP per capita
| Definition | The ratio of GPs to patients |
| Source Numerator | 2001 and 2001 Ethnic: General practioners 2001 (Prescribing Pricing Authority) |
| 2003: General practioners 2003 (Prescribing Pricing Authority) | |
| 2005: General practioners 2005 (Prescribing Pricing Authority) | |
| Source Denominator | 2001 and 2001 Ethnic: Practice list size 2001 (Department of Health) |
| 2003: Practice list size 2003 (Department of Health) | |
| 2005: Practice list size 2005 (Department of Health) |
Additional details
This measure was constructed with the assistance of Paul Dixon of the University of York. The measure is the number of GPs per (10000) head of registrations in each practise. It is based on the number of GPs per senior partner and the size of their combined list. (In cases where GPs had more than one senior partner, only the GP/SP combination with most registrations is used). A rate is computed for each practice (GPs/registrations) and a weighted average of these rates is used as the area figure. The weight was based on the number of the particular practice list living in a specific LAD. Given the available data sources, it is not possible to make any corrections for GPs who work part-time and the figures are based on the total numbers of GPs associated with each Senior Partner (SP), regardless of the hours they work.
Component SA1_2: Avoidable mortality < 75 years old
| Definition | Directly age and gender standardised rate of all avoidable mortality amenable to primary healthcare |
| Source Numerator | 2001: Deaths where the underlying cause of death was amenable to primary healthcare, Death Register, 1999, 2000, 2001, ONS |
| 2001 Ethnic: Deaths where the underlying cause of death was amenable to primary healthcare, Death Register, 1999, 2000, 2001, ONS | |
| 2003: Deaths where the underlying cause of death was amenable to primary healthcare, Death Register, 2001, 2002, 2003, ONS | |
| 2005: Deaths where the underlying cause of death was amenable to primary healthcare, Death Register, 2003, 2004, 2005, ONS | |
| Source Denominator | 2001, 2001 Ethnic: Mid year population estimate 2001, ONS |
| 2003: Mid year population estimate 2003, ONS | |
| 2005: Mid year population estimate 2003, ONS |
Additional details
This indicator measures the effectiveness of primary care at treating conditions which may lead to avoidable mortality.
The definition of avoidable deaths amenable to primary care are adapted from Nolte & McKee (2003) and Tobias & Jackson (2001) and are as follows:
Condition amenable to primary care |
Age |
ICD 9 |
ICD 10 |
|
|
|
|
| Intestinal infection | 0-14 | 001-9 | A00-9 |
| Tuberculosis | 0-74 | 010-8, 137 | A15-9, B90 |
| Other infections | 0-74 | 032, 037, 045 | A36, A35, A80 |
| Whooping cough | 0-14 | 033 | A37 |
| Measles | 1-14 | 055 | B05 |
| Colon or rectal cancer | 0-74 | 153-4 | C18-21 |
| Skin cancer | 0-74 | 173 | C44 |
| Breast cancer | 0-74 | 174 | C50 |
| Cervical cancer | 0-74 | 180 | C53 |
| Uterine cancer | 0-44 | 179, 182 | C54-5 |
| Diabetes | 0-49 | 250 | E10-4 |
| Epilepsy | 0-74 | 345 | G40-1 |
| Rheumatic heart disease | 0-74 | 393-8 | I05-9 |
| Hypertensive disease | 0-74 | 401-5 | I10-3 ,I15 |
| Cerebrovascular disease | 0-74 | 430-8 | I60-9 |
| All respiratory diseases | 1-14 | 460-79, 488-519 | J00-9, J20-99 |
| Influenza | 0-74 | 487 | J10-1 |
| Pneumonia | 0-74 | 480-6 | J12-8 |
| Maternal death | All | 630-76 | O00-99 |
| Perinatal deaths | All | 760-79 | P00-96, A33 |
| Ischemic heart disease | 0-74 | 410-4 | I20-5 |
To control for differences in the age and gender structure across small areas, direct standardisation was used. Direct standardisation involves the application of small area age and gender structures to a standard population, which in this instance is derived from the ONS mid year population estimates. This produces an expected number of events (avoidable deaths) in the standard population as if the risk profile of the individual areas was in place, which are then summed and divided by the total standard population to produce an age-sex standardised rate. An area with a low age-sex standardised rate of avoidable deaths reflects effective primary healthcare
References
Nolte & McKee (2003), Measuring the health of nations: analysis of mortality amenable to health care. British Medical Journal, 327: 1129+.
Tobias & Jackson (2001), Avoidable mortality in New Zealand, 1981-97 , Australian and New Zealand Journal of Public Health 25 (1): 12-20
Component SA1_3: Emergency admissions for chronic conditions
| Definition | Directly age and gender standardised rate of all emergency admissions to hospital for asthma and diabetes |
| Source Numerator | 2001: Admissions to hospital for asthma and diabetes coded as an emergency, Hospital Episode Statistics (HES), 1999/00, 2000/01, 2001/02, Department of Health |
| 2001 Ethnic: Ethnically coded admissions to hospital for asthma and diabetes coded as an emergency, Hospital Episode Statistics (HES), 1999/00, 2000/01, 2001/02, Department of Health | |
| 2003: Admissions to hospital for asthma and diabetes coded as an emergency, Hospital Episode Statistics (HES), 2000/01, 2001/02, 2002/03, Department of Health | |
| 2005: Admissions to hospital for asthma and diabetes coded as an emergency, Hospital Episode Statistics (HES), 2003/04, 2004/05, 2005/06, Department of Health | |
| Source Denominator | 2001, 2001 Ethnic: Mid year population estimate 2001, ONS |
| 2003: Mid year population estimate 2003, ONS | |
| 2005: Mid year population estimate 2005, ONS |
Additional details
Diabetes is a chronic, progressive disease that affects 1.3 million people in England. (2004, National Service Framework for Diabetes: One Year On). Many other people have the disease but are not aware of it and the number of people being diagnosed is increasing every year. Unless diabetes is managed effectively, it can lead to quite serious complications and is a major risk factor for coronary heart disease and stroke.
The cost of diabetes to the health service is significant, but the cost to people's quality of life - and their life expectancy - can be equally so. However, with appropriate support, in terms of drugs and treatments, and structured education and advice, people with diabetes can manage their condition so that the effect on their lifestyle is minimised.
Asthma is a very common long-term condition that currently affects approximately one child in 8 and about one adult in 13 in the UK (2004, NHS Direct Online). It can be mild and hardly noticeable, or sudden and severe, although most cases are somewhere in between. Asthma is a 'self-help' condition in which the affected person can do much to prevent attacks and, as with diabetes, reduce the impact on their lifestyle.
Services for people with diabetes and asthma are variable - excellent practice is demonstrated in some areas, but that excellence is not universal.
This indicator takes the number of emergency admissions for asthma and diabetes to be a proxy for the level of treatment provided to sufferers. In most instances these conditions should be managed in primary care, so an area where the service provided is good should not see as many emergency admissions as one where the service is relatively poor.
The International Classification of Diseases Version 10 (ICD-10) codes used to extract data on emergency admissions for chronic conditions from the HES dataset were:
- Asthma: J45 - J46
- Diabetes: E10 - E14
Cases were used if one or more of these codes were found in any of the fourteen diagnosis fields.
To control for differences in the age and gender structure across small areas, direct standardisation was used. Direct standardisation involves the application of small area age and gender structures to a standard population, which in this instance is derived from the HES data. This produces an expected number of events (emergency admissions for asthma and diabetes) in the standard population as if the risk profile of the individual areas was in place. This is contrasted with the actual number of observed events in the standard population to give a ratio. Thus a measure of higher or lower than expected occurrence of emergency admissions for asthma and diabetes is created.
For indicators derived from the Hospital Episode Statistics (HES) the estimates are based on the relationship between all hospital stays, and those recorded for a specific condition of interest. Detail is added from census data to depict the spatial distribution of individuals in ethnic groups. All estimates are statistically smoothed to reduce noise within the distribution, enabling the underlying trend to be highlighted. For more details see the discussion paper.