Literature DB >> 1653065

Explaining outputs of primary health care: population and practice factors.

D Baker1, R Klein.   

Abstract

OBJECTIVE: To examine whether variations in the activities of general practice among family health service authorities can be explained by the populations characteristics and the organisation and resourcing of general practice.
DESIGN: The family health services authorities were treated as discrete primary health care systems. Nineteen performance indicators reflecting the size, distribution, and characteristics of the population served; the organisation of general practice (inputs); and the activities generated by general practitioners and their staff (output) were analysed by stepwise regression.
SETTING: 90 family health services authorities in England. MAIN OUTCOME MEASURES: Rates of cervical smear testing, immunisation, prescribing, and night visiting.
RESULTS: 53% of the variation in uptake of cervical cytology was accounted for by Jarman score (t = -3.3), list inflation (-0.41), the proportion of practitioners over 65 (-0.64), the number of ancillary staff per practitioner (2.5), and 70% of the variation in immunisation rates by standardised mortality ratios (-6.6), the proportion of practitioners aged over 65 (-4.8), and the number of practice nurses per practitioner (3.5). Standardised mortality ratios (8.4), the number of practitioners (2.3), and the proportion over 65 (2.2), and the number of ancillary staff per practitioner (-3.1) accounted for 69% of variation in prescribing rates. 54% of the variation in night visiting was explained by standardised mortality ratios (7.1), the proportion of practitioners with lists sizes below 1000 (-2.2), the proportion aged over 65 (-0.4), and the number of practice nurses per practitioner (-2.5).
CONCLUSIONS: Family health services authorities are appropriate systems for studying output of general practice. Their performance indicators need to be refined and to be linked to other relevant factors, notably the performance of hospital, community, and social services.

Mesh:

Year:  1991        PMID: 1653065      PMCID: PMC1670540          DOI: 10.1136/bmj.303.6796.225

Source DB:  PubMed          Journal:  BMJ        ISSN: 0959-8138


  5 in total

1.  Second thoughts on the Jarman index.

Authors:  G D Smith
Journal:  BMJ       Date:  1991-02-16

2.  Designing a deprivation payment for general practitioners: the UPA(8) wonderland.

Authors:  R A Carr-Hill; T Sheldon
Journal:  BMJ       Date:  1991-02-16

3.  Underprivileged areas and health care planning: implications of use of Jarman indicators of urban deprivation.

Authors:  R J Talbot
Journal:  BMJ       Date:  1991-02-16

4.  Correlates of physician utilization: why do major multivariate studies of physician utilization find trivial psychosocial and organizational effects?

Authors:  D Mechanic
Journal:  J Health Soc Behav       Date:  1979-12

5.  Underprivileged areas: validation and distribution of scores.

Authors:  B Jarman
Journal:  Br Med J (Clin Res Ed)       Date:  1984-12-08
  5 in total
  23 in total

1.  Measuring quality of care with routine data: avoiding confusion between performance indicators and health outcomes.

Authors:  A Giuffrida; H Gravelle; M Roland
Journal:  BMJ       Date:  1999-07-10

2.  Association between teenage pregnancy rates and the age and sex of general practitioners: cross sectional survey in Trent 1994-7.

Authors:  J Hippisley-Cox; J Allen; M Pringle; D Ebdon; M McPhearson; D Churchill; S Bradley
Journal:  BMJ       Date:  2000-03-25

3.  Polypharmacy in general practice: differences between practitioners.

Authors:  L Bjerrum; J Søgaard; J Hallas; J Kragstrup
Journal:  Br J Gen Pract       Date:  1999-03       Impact factor: 5.386

4.  Performance indicators for general practice.

Authors:  F A Majeed; S Voss
Journal:  BMJ       Date:  1995-07-22

5.  Impact of the 1990 contract for general practitioners on night visiting.

Authors:  D Baker; R Klein; R Carter
Journal:  Br J Gen Pract       Date:  1994-02       Impact factor: 5.386

6.  Using unemployment rates to predict prescribing trends in England.

Authors:  M Pringle; A Morton-Jones
Journal:  Br J Gen Pract       Date:  1994-02       Impact factor: 5.386

7.  Attitudes and behaviour of general practitioners and their prescribing costs: a national cross sectional survey.

Authors:  C Watkins; I Harvey; P Carthy; L Moore; E Robinson; R Brawn
Journal:  Qual Saf Health Care       Date:  2003-02

8.  Using patient and general practice characteristics to explain variations in cervical smear uptake rates.

Authors:  F A Majeed; D G Cook; H R Anderson; S Hilton; S Bunn; C Stones
Journal:  BMJ       Date:  1994-05-14

9.  Cervical screening and health inequality in England in the 1990s.

Authors:  D Baker; E Middleton
Journal:  J Epidemiol Community Health       Date:  2003-06       Impact factor: 3.710

10.  Practice characteristics and prescribing of cardiovascular drugs in areas with higher risk of CHD in Scotland: cross-sectional study.

Authors:  Gary McLean
Journal:  Int J Equity Health       Date:  2008-07-15
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