Evidence map›Paper›PMID 37303488›Full record

ArticleBMJ medicine2023

Changes in medication safety indicators in England throughout the covid-19 pandemic using OpenSAFELY: population based, retrospective cohort study of 57 million patients using federated analytics.

Louis Fisher, Lisa Em Hopcroft, Sarah Rodgers, James Barrett, Kerry Oliver, Anthony J Avery, Dai Evans, Helen Curtis, Richard Croker, Orla Macdonald and 29 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMJ medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.1field-weighted citation impact, top 12% of its field
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

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. Observational
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

39 authors at 3 institutions in 1 country.

Louis FisherBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.ORCID 0000-0002-0295-3812
Lisa Em HopcroftBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.ORCID 0000-0002-7022-1322
Sarah RodgersPRIMIS, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK.ORCID 0000-0003-1676-1982
James BarrettPRIMIS, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK.
Kerry OliverPRIMIS, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK.ORCID 0000-0002-9384-301X
Anthony J AveryCentre for Academic Primary Care, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK.ORCID 0000-0001-7591-4438
Dai EvansPRIMIS, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK.ORCID 0000-0001-9272-3203
Helen CurtisBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.ORCID 0000-0003-3429-9576
Richard CrokerBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.ORCID 0000-0002-8114-9186
Orla MacdonaldBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.
Jessica MorleyBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.ORCID 0000-0001-5221-4770
Amir MehrkarBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.ORCID 0000-0002-2098-1278
Sebastian BaconBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.ORCID 0000-0002-6354-3454
Simon DavyBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.ORCID 0000-0001-9890-3619
Iain DillinghamBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.
David EvansBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.ORCID 0000-0002-1100-079X
George HickmanBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.ORCID 0000-0002-6691-4046
Peter InglesbyBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.
Caroline E MortonBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.ORCID 0000-0003-0783-0042
Becky SmithBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.
Tom WardBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.
William HulmeBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.ORCID 0000-0002-9162-4999
Amelia GreenBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.ORCID 0000-0002-7246-2074
Jon MasseyBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.ORCID 0000-0002-2497-4040
Alex J WalkerBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.ORCID 0000-0003-4932-6135
Christopher BatesTPP, Leeds, UK.ORCID 0000-0003-0113-2593
Jonathan CockburnTPP, Leeds, UK.ORCID 0000-0002-4681-4873
John ParryTPP, Leeds, UK.
Frank HesterTPP, Leeds, UK.
Sam HarperTPP, Leeds, UK.
Shaun O'HanlonEMIS Health, Leeds, UK.
Alex EavisEMIS Health, Leeds, UK.
Richard JarvisEMIS Health, Leeds, UK.
Dima AvramovEMIS Health, Leeds, UK.
Paul GriffithsEMIS Health, Leeds, UK.
Aaron FowlesEMIS Health, Leeds, UK.ORCID 0000-0003-2090-785X
Nasreen ParkesEMIS Health, Leeds, UK.
Ben GoldacreBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.ORCID 0000-0002-5127-4728
Brian MacKennaBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.ORCID 0000-0002-3786-9063
University of Oxford · GBUniversity of Nottingham · GBWPP (United Kingdom) · GB

Funding

Medical Research Council MC_PC_20058
6 · The paper itself

Abstract

Objective: To implement complex, PINCER (pharmacist led information technology intervention) prescribing indicators, on a national scale with general practice data to describe the impact of the covid-19 pandemic on safe prescribing. Design: Population based, retrospective cohort study using federated analytics. Setting: Electronic general practice health record data from 56.8 million NHS patients by use of the OpenSAFELY platform, with the approval of the National Health Service (NHS) England. Participants: NHS patients (aged 18-120 years) who were alive and registered at a general practice that used TPP or EMIS computer systems and were recorded as at risk of at least one potentially hazardous PINCER indicator. Main outcome measure: Between 1 September 2019 and 1 September 2021, monthly trends and between practice variation for compliance with 13 PINCER indicators, as calculated on the first of every month, were reported. Prescriptions that do not adhere to these indicators are potentially hazardous and can cause gastrointestinal bleeds; are cautioned against in specific conditions (specifically heart failure, asthma, and chronic renal failure); or require blood test monitoring. The percentage for each indicator is formed of a numerator of patients deemed to be at risk of a potentially hazardous prescribing event and the denominator is of patients for which assessment of the indicator is clinically meaningful. Higher indicator percentages represent potentially poorer performance on medication safety. Results: The PINCER indicators were successfully implemented across general practice data for 56.8 million patient records from 6367 practices in OpenSAFELY. Hazardous prescribing remained largely unchanged during the covid-19 pandemic, with no evidence of increases in indicators of harm as captured by the PINCER indicators. The percentage of patients at risk of potentially hazardous prescribing, as defined by each PINCER indicator, at mean quarter 1 (Q1) 2020 (representing before the pandemic) ranged from 1.11% (age ≥65 years and non-steroidal anti-inflammatory drugs) to 36.20% (amiodarone and no thyroid function test), while Q1 2021 (representing after the pandemic) percentages ranged from 0.75% (age ≥65 years and non-steroidal anti-inflammatory drugs) to 39.23% (amiodarone and no thyroid function test). Transient delays occurred in blood test monitoring for some medications, particularly angiotensin-converting enzyme inhibitors (where blood monitoring worsened from a mean of 5.16% in Q1 2020 to 12.14% in Q1 2021, and began to recover in June 2021). All indicators substantially recovered by September 2021. We identified 1 813 058 patients (3.1%) at risk of at least one potentially hazardous prescribing event. Conclusion: NHS data from general practices can be analysed at national scale to generate insights into service delivery. Potentially hazardous prescribing was largely unaffected by the covid-19 pandemic in primary care health records in England.

Indexed as

COVID-19Medical informaticsPrimary health care

Identifiers

PMID37303488
PMCPMC10254692
OpenAlexW4377140076

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.