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Current Smoker (P18)

S Jill Stocks, Evangelos Kontopantelis, Artur Akbarov, Sarah Rodgers, Anthony J Avery, Darren M Aschroft

Type
Biomarker
ID
PH676
Version ID
1352
Data Sources
Valid event data range
Start - 01/02/2013
Sex
Female, Male
Agreement Date
2015-11-03
Coding system
Read codes v2
Tags /Collections
ClinicalCodes Repository Phenotype Library

Definition

Study question:

What is the prevalence of different types of potentially hazardous prescribing in general practice in the United Kingdom, and what is the variation between practices?

Methods:

A cross sectional study included all adult patients potentially at risk of a prescribing or monitoring error defined by a combination of diagnoses and prescriptions in 526 general practices contributing to the Clinical Practice Research Datalink (CPRD) up to 1 April 2013. Primary outcomes were the prevalence of potentially hazardous prescriptions of anticoagulants, anti-platelets, NSAIDs, β blockers, glitazones, metformin, digoxin, antipsychotics, combined hormonal contraceptives, and oestrogens and monitoring by blood test less frequently than recommended for patients with repeated prescriptions of angiotensin converting enzyme inhibitors and loop diuretics, amiodarone, methotrexate, lithium, or warfarin.

Study answer and limitations:

49 927 of 949 552 patients at risk triggered at least one prescribing indicator (5.26%, 95% confidence interval 5.21% to 5.30%) and 21 501 of 182 721 (11.8%, 11.6% to 11.9%) triggered at least one monitoring indicator. The prevalence of different types of potentially hazardous prescribing ranged from almost zero to 10.2%, and for inadequate monitoring ranged from 10.4% to 41.9%. Older patients and those prescribed multiple repeat medications had significantly higher risks of triggering a prescribing indicator whereas younger patients with fewer repeat prescriptions had significantly higher risk of triggering a monitoring indicator. There was high variation between practices for some indicators. Though prescribing safety indicators describe prescribing patterns that can increase the risk of harm to the patient and should generally be avoided, there will always be exceptions where the indicator is clinically justified. Furthermore there is the possibility that some information is not captured by CPRD for some practices—for example, INR results in patients receiving warfarin.

What this study adds:

The high prevalence for certain indicators emphasises existing prescribing risks and the need for their appropriate consideration within primary care, particularly for older patients and those taking multiple medications. The high variation between practices indicates potential for improvement through targeted practice level intervention.

Publications

  • S Jill Stocks, Evangelos Kontopantelis, Artur Akbarov, Sarah Rodgers, Anthony J Avery, Darren M Ashcroft, Examining variations in prescribing safety in UK general practice cross sectional study using the Clinical Practice Research Datalink. BMJ, 351(h5501), 2015.

Clinical Code List

Rows: 27
Code Description Entity type Category Coding System (Read)
137..11 Smoker - amount smoked res25: P18_current_smoker diagnostic Read
1372 Trivial smoker - < 1 cig/day res25: P18_current_smoker diagnostic Read
1372.11 Occasional smoker res25: P18_current_smoker diagnostic Read
1373 Light smoker - 1-9 cigs/day res25: P18_current_smoker diagnostic Read
1374 Moderate smoker - 10-19 cigs/d res25: P18_current_smoker diagnostic Read
1375 Heavy smoker - 20-39 cigs/day res25: P18_current_smoker diagnostic Read
1376 Very heavy smoker - 40+cigs/d res25: P18_current_smoker diagnostic Read
137C.00 Keeps trying to stop smoking res25: P18_current_smoker diagnostic Read
137D.00 Admitted tobacco cons untrue ? res25: P18_current_smoker diagnostic Read
137G.00 Trying to give up smoking res25: P18_current_smoker diagnostic Read
137H.00 Pipe smoker res25: P18_current_smoker diagnostic Read
137J.00 Cigar smoker res25: P18_current_smoker diagnostic Read
137M.00 Rolls own cigarettes res25: P18_current_smoker diagnostic Read
137P.00 Cigarette smoker res25: P18_current_smoker diagnostic Read
137P.11 Smoker res25: P18_current_smoker diagnostic Read
137Q.00 Smoking started res25: P18_current_smoker diagnostic Read
137Q.11 Smoking restarted res25: P18_current_smoker diagnostic Read
137R.00 Current smoker res25: P18_current_smoker diagnostic Read
137V.00 Smoking reduced res25: P18_current_smoker diagnostic Read
137X.00 Cigarette consumption res25: P18_current_smoker diagnostic Read
137Y.00 Cigar consumption res25: P18_current_smoker diagnostic Read
137Z.00 Tobacco consumption NOS res25: P18_current_smoker diagnostic Read
137b.00 Ready to stop smoking res25: P18_current_smoker diagnostic Read
137c.00 Thinking about stopping smoking res25: P18_current_smoker diagnostic Read
137e.00 Smoking restarted res25: P18_current_smoker diagnostic Read
137h.00 Minutes from waking to first tobacco consumption res25: P18_current_smoker diagnostic Read
137m.00 Failed attempt to stop smoking res25: P18_current_smoker diagnostic Read

API

To Export Phenotype Details:

Format API
XML site_root/api/v1/public/phenotypes/PH676/version/1352/detail/?format=xml
JSON site_root/api/v1/public/phenotypes/PH676/version/1352/detail/?format=json
R Package

# Download here

library(ConceptLibraryClient)


# Connect to API

client = connect_to_API(public=TRUE)


# Get details of phenotype

details = get_phenotype_detail_by_version('PH676', '1352', api_client=client)

To Export Phenotype Code List:

Format API
XML site_root/api/v1/public/phenotypes/PH676/version/1352/export/codes/?format=xml
JSON site_root/api/v1/public/phenotypes/PH676/version/1352/export/codes/?format=json
CSV site_root/phenotypes/PH676/version/1352/export/codes/
R Package

# Download here

library(ConceptLibraryClient)


# Connect to API

client = connect_to_API(public=TRUE)


# Get codelists of phenotype

codelists = get_phenotype_code_list('PH676', '1352', api_client=client)

Version History

Version
ID
Name Owner Publish date
1352 Current Smoker (P18) ieuan.scanlon 2021-10-06 currently shown

Export - export all codes into a csv file/JSON/XML for the current phenotype version.

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