Evidence map›Paper›PMID 8305014›Full record

ArticleBMJ (Clinical research ed.)1993

Age, sex, and temporary resident originated prescribing units (ASTRO-PUs): new weightings for analysing prescribing of general practices in England.

S J Roberts, C M Harris

Abstract read
In one paragraph

Article in BMJ (Clinical research ed.), 1993. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

41 citing papers in PubMed.

  1. Controlled trial of pharmacist intervention in general practice: the effect on prescribing costs.The British journal of general practice : the journal of the Royal College of General Practitioners · 1999
    Trial
  2. Sharing resources to create a district drug formulary: a countywide controlled trial.The British journal of general practice : the journal of the Royal College of General Practitioners · 1996
    Trial
  3. Observational
  4. Gender Differences in Medication Use: A Drug Utilization Study Based on Real World Data.International journal of environmental research and public health · 2020
    Article
  5. The scale of repeat prescribing--time for an update.BMC health services research · 2014
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Do GPs working in practice with high or low prescribing costs have different views on prescribing cost issues?The British journal of general practice : the journal of the Royal College of General Practitioners · 2000
    Article
  13. Article
  14. Article
  15. Morbidity, deprivation, and antidepressant prescribing in general practice.The British journal of general practice : the journal of the Royal College of General Practitioners · 1999
    Article
  16. Therapeutic substitution and therapeutic conservatism as cost-containment strategies in primary care: a study of fundholders and non-fundholders.The British journal of general practice : the journal of the Royal College of General Practitioners · 1999
    Article
  17. Accrediting research practices.The British journal of general practice : the journal of the Royal College of General Practitioners · 1998
    Article
  18. A comparison of three methods of setting prescribing budgets, using data derived from defined daily dose analyses of historic patterns of use.The British journal of general practice : the journal of the Royal College of General Practitioners · 1998
    Article
  19. Prescribing allocations: theory into practices.The British journal of general practice : the journal of the Royal College of General Practitioners · 1998
    Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

S J RobertsPrescribing Research Unit, University of Leeds.
C M Harris

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo derive demographic weightings to replace the existing system of prescribing units used in analysing prescribing by general practitioners in England.

designThe prescribing data for one year from a sample of 90 practices in 80 family health service authority areas were used to calculate the relative frequency with which items were prescribed, for each sex, in nine age bands and for temporary residents. Data on the variation in cost per item by age and sex then allowed estimates to be made of the relative costs for these groups. Integer values for both the item based and cost based weightings were obtained by conversion to optimal integer scales.

main outcome measuresItem based and cost based weightings for each of the 18 age-sex groups and for temporary residents. The cost based weightings were considered more appropriate to the context in which the new system was to be used.

resultsPrescribing costs increased noticeably, for both sexes, in the middle years (ages 35-64). Compared with the existing system, the cost based weightings (ASTRO-PUs) gave greater weight to patients aged 45 and over, especially those in the 55-64 age band, at the expense of younger patients. Children under 5 received twice as many items as those aged 5-14, but the inexpensiveness of their drugs made the cost based weightings of the two groups equal. Similarly, women were generally given more items than men, but at a lower average cost per item, which reduced differences between the sexes in the cost based weightings. Costs for patients aged 75 and over, compared with those aged 65-74, were higher only for women.

conclusionsThe cost based weightings proposed are believed to reflect the present distribution of prescribing costs, in relation to age and sex, in English general practice. They are intended for use in analyses at practice level.

Indexed as

AdolescentAdultAgedAged, 80 and overAge FactorsChildChild, PreschoolDrug CostsDrug PrescriptionsDrug UtilizationDrug Utilization ReviewEnglandFamily PracticeFemaleHumansInfant

Identifiers

PMID8305014
PMCPMC1678776

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.