ArticleBMJ (Clinical research ed.)1995
Specific therapeutic group age-sex related prescribing units (STAR-PUs): weightings for analysing general practices' prescribing in England.
Article in BMJ (Clinical research ed.), 1995. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed, 86 citations in OpenAlex.
- 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 · 1999Trial
- Observational study of antibiotic prescribing patterns by age and sex in primary care in England: why we need to take this variation into account to evaluate antibiotic stewardship and predict AMR variation.JAC-antimicrobial resistance · 2025Article
- Article
- Association between regulator inspection and ratings on primary care prescribing: an observational study in England 2014 to 2019.BMC health services research · 2024Observational
- The influence of age, gender and pharmacogenetic profiles on the perspective on medicines in the German EMPAR study.PloS one · 2024Observational
- The impact of the COVID-19 pandemic on the treatment of common infections in primary care and the change to antibiotic prescribing in England.Antimicrobial resistance and infection control · 2023Article
- Impact of COVID-19 on broad-spectrum antibiotic prescribing for common infections in primary care in England: a time-series analyses using OpenSAFELY and effects of predictors including deprivation.The Lancet regional health. Europe · 2023Article
- Gender Differences in Medication Use: A Drug Utilization Study Based on Real World Data.International journal of environmental research and public health · 2020Article
- Identifying English Practices that Are High Antibiotic Prescribers Accounting for Comorbidities and Other Legitimate Medical Reasons for Variation.EClinicalMedicine · 2018Article
- Explaining variation in antibiotic prescribing between general practices in the UK.The Journal of antimicrobial chemotherapy · 2018Article
- Factors associated with prescribing costs: analysis of a nationwide administrative database.Cost effectiveness and resource allocation : C/E · 2018Article
- Understanding the delayed prescribing of antibiotics for respiratory tract infection in primary care: a qualitative analysis.BMJ open · 2016Article
- Antibiotic prescribing and patient satisfaction in primary care in England: cross-sectional analysis of national patient survey data and prescribing data.The British journal of general practice : the journal of the Royal College of General Practitioners · 2016Article
- Achievement of cholesterol targets and prescribing of higher-cost statins: a cross-sectional study in general practice.The British journal of general practice : the journal of the Royal College of General Practitioners · 2012Article
- General practitioners' intentions and prescribing for asthma: using the theory of planned behavior to explain guideline implementation.International journal of preventive medicine · 2012Article
- [Do we need to improve how we measure prescription quality in primary care?].Atencion primaria · 2011Article
- Academic impact of a public electronic health database: bibliometric analysis of studies using the general practice research database.PloS one · 2011Article
- Influence of population and general practice characteristics on prescribing of minor tranquilisers in primary care.Pharmacy practice · 2010Article
- Which practices are high antibiotic prescribers? A cross-sectional analysis.The British journal of general practice : the journal of the Royal College of General Practitioners · 2009Article
- Variations in anxiolytic and hypnotic prescribing by GPs: a cross-sectional analysis using data from the UK Quality and Outcomes Framework.The British journal of general practice : the journal of the Royal College of General Practitioners · 2009Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo derive cost comparators for prescribing by English general practitioners in eight specific therapeutic groups, based on age-sex related weightings, and to confirm, from a new dataset, earlier age-sex weightings for overall prescribing (ASTRO-PUs).
designCalculations based on one year's prescribing data from selected practices using AAH Meditel software, held on MediPlus by Intercontinental Medical Statistics (IMS, UK and Ireland), and research practices using VAMP software, held on the General Practice Research Database.
setting112 English practices with 739,672 patients and 510 British practices with 3,126,570 patients.
main outcome measuresCost based weightings for 18 age-sex groups and for temporary residents for eight leading specific therapeutic groups and for prescribing overall.
resultsThe two datasets were similar in age distribution and in the way that prescription numbers were distributed by age-sex band in each therapeutic group. The cost based weightings for specific therapeutic groups showed great variation in the use of these groups for patients in different age-sex groups. When these weightings were applied to the prescribing of practices in two family health services authorities they differed in their power to predict prescribing costs: for cardiovascular and gastrointestinal drugs predictive power was particularly high; for drugs for infections it was particularly low, since these are widely used at all ages and for both sexes. Cost based weightings for overall prescribing derived from the IMS data were similar to those of the ASTRO-PU system even though they were derived by different methods from different datasets.
conclusionsThe weightings (STAR-PUs) offer a sound basis for cost comparisons at the therapeutic group level. Cost-based weightings for overall prescribing derived from the IMS data were reassuringly similar to those of the existing ASTRO-PU system.
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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.