General Practice

Characteristics of general practices that prescribe appropriately for asthma

BMJ 1995; 311 doi: https://doi.org/10.1136/bmj.311.7019.1547 (Published 09 December 1995) Cite this as: BMJ 1995;311:1547
  1. Patricia Sturdy, research officera,
  2. Jeannette Naish, general practitionera,
  3. Filomena Pereira, lecturer in medical statistics Make Chambers lecturer in urban and regional health Department of Primary Health Care and General Practice, St Mary's Hospital Medical School, Norfolk Place, London W2 1PGa,
  4. Chris Griffiths, general practitionera,
  5. Susan Dolan, research analysta,
  6. Peter Toon, general practitioner Department of Epidemiology and Medical Statistics, The London Hospital Medical College at Queen Mary and Westfield Collegea,
  7. Mike Chambers
  1. City and East London General Practice Database Project, Department of General Practice and Primary Care, Medical College of St Bartholomew's and the London Hospitals, Medical Sciences, Queen Mary and Westfield College, London E1 4NS
  1. Correspondence to: Dr Naish.
  • Accepted 16 August 1995

We have previously found that the ratio of prophylactic to bronchodilator prescriptions is a crude indicator of appropriate prescribing for asthma.1 In this study we explored the possible influence of the general practitioner, the practice, and the practice population on this ratio.

Methods

and results

Complete data sets were obtained for 150 of the 163 practices in east London for April 1992 to March 1993. Their asthma prescribing patterns have been described elsewhere.1 The 23 predictor variables selected for the analyses are listed in the table; detailed descriptions are available from the authors. The outcome variables were the ratio of prophylactic drugs to bronchodilators prescribed measured as both items and net ingredient cost (logarithm of ratio). Two models were constructed by stepwise multiple linear regression analysis with backward elimination of variables. A significance level of 0.05 was used to determine variables staying in the model. The resulting regression models (see table) show that 31% of the variability in the prescribing ratio measured as items was accounted for by average age of the principals, the presence of a trainer, and the proportion of the list aged over 65, while 33% of the variability in the ratio when measured as net ingredient cost was accounted for by average age of the principals, nursing hours available in the practice, and the presence of a practice manager.

Regression models 1 and 2: outcome variables were the ratios of prophylaxis to bronchodilator prescribing

View this table:

Comment

Our underlying assumption is that the prophylaxis to bronchodilator prescribing ratio represents a useful marker of appropriate prescribing; its limitations have been discussed.1 2 We are currently trying to validate these ratios by linking them with asthma admission rates as a measure of morbidity.

The average age of the principals had the strongest association with the ratio, practices with younger practitioners having higher prescribing ratios. The finding that practices with a trainer prescribed more appropriately accords with our previous analysis.1 Possibly younger practitioners, who received their training after inhaled corticosteroids became available in the early 1970s, are more likely to treat asthma with inhaled prophylaxis. Nevertheless, an age variable which broadly divided practices into those where practitioners qualified before or after 1973 explained less variation, as did a variable for year of General Medical Council registration. Our results cannot determine why these practices prescribe more appropriately, but they suggest that educational resources might most profitably be directed at older general practitioners and non-training practices.

As expected, increased staff resources were related to more “appropriate” prescribing, possibly because they improved practice organisation or because they released the doctor for more consultation time. A case can thus be made for helping practices with poorer resources to improve their staffing levels.

The only demographic variable related to the prescribing ratio was the proportion of the list size aged over 65. This result is consistent with the widespread use of corticosteroids in elderly people with chronic obstructive pulmonary disease. We found no correlations with selected sociodemographic variables. Others have failed to show an association between deprivation and prescribing volume but have noted a relation with standardised mortality ratios.3 Overall, our findings suggest that appropriate prescribing could be fostered through targeted education and by increased staffing in some practices.

Acknowledgments

We thank Kath Moser for the construction and management of the general practice database and the City and East London Family Health Services Authority for providing data. We are grateful to the Prescribing Pricing Authority for their information which was obtained by JN in her capacity as medical adviser to the family health services authority.

Footnotes

  • Funding The project, originally supported by the City and East London Family Health Services Authority and the former North East Thames Regional Health Authority, is now funded by the Wellcome Trust. The sociodemographic aspect of the work was funded by the North East Thames Regional Health Authority locally organised research scheme.

  • Conflict of interest None.

References

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