ArticleBMJ (Clinical research ed.)2008
A model based on age, sex, and morbidity to explain variation in UK general practice prescribing: cohort study.
Article in BMJ (Clinical research ed.), 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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.
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.
Who cites it
11 citing papers in PubMed.
- [Validity of adjusted morbidity groups with respect to clinical risk groups in the field of primary care].Atencion primaria · 2019Observational
- Visualizing nationwide variation in medicare Part D prescribing patterns.BMC medical informatics and decision making · 2018Article
- Factors associated with prescribing costs: analysis of a nationwide administrative database.Cost effectiveness and resource allocation : C/E · 2018Article
- Pharmaceutical cost management in an ambulatory setting using a risk adjustment tool.BMC health services research · 2014Article
- Keep it simple? Predicting primary health care costs with clinical morbidity measures.Journal of health economics · 2014Article
- Relationship between efficiency and clinical effectiveness indicators in an adjusted model of resource consumption: a cross-sectional study.BMC health services research · 2013Article
- Adverse events recorded in English primary care: observational study using the General Practice Research Database.The British journal of general practice : the journal of the Royal College of General Practitioners · 2013Observational
- Geographical differences in the prevalence of chronic polypharmacy in older people: eleven years of the EPIFARM-Elderly Project.European journal of clinical pharmacology · 2013Article
- Variability of antibiotic prescribing in patients with chronic obstructive pulmonary disease exacerbations: a cohort study.BMC pulmonary medicine · 2013Article
- [Do we need to improve how we measure prescription quality in primary care?].Atencion primaria · 2011Article
- Temporal and within practice variability in the health improvement network.Pharmacoepidemiology and drug safety · 2011Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
objectiveTo examine whether patient level morbidity based measure of clinical case mix explains variations in prescribing in general practice.
designRetrospective study of a cohort of patients followed for one year.
settingUK General Practice Research Database.
participants129 general practices, with a total list size of 1 032 072.
main outcome measuresEach patient was assigned a morbidity group on the bases of diagnoses, age, and sex using the Johns Hopkins adjusted clinical group case mix system. Multilevel regression models were used to explain variability in prescribing, with age, sex, and morbidity as predictors.
resultsThe median number of prescriptions issued annually to a patient is 2 (90% range 0 to 18). The number of prescriptions issued to a patient increases with age and morbidity. Age and sex explained only 10% of the total variation in prescribing compared with 80% after including morbidity. When variation in prescribing was split between practices and within practices, most of the variation was at the practice level. Morbidity explained both variations well.
conclusionsInclusion of a diagnosis based patient morbidity measure in prescribing models can explain a large amount of variability, both between practices and within practices. The use of patient based case mix systems may prove useful in allocation of budgets and therefore should be investigated further when examining prescribing patterns in general practices in the UK, particularly for specific therapeutic areas.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.