Evidence map›Paper›PMID 38531661›Full record

ArticleBritish journal of clinical pharmacology2024

The impact of COVID-19 on medication reviews in English primary care. An OpenSAFELY-TPP analysis of 20 million adult electronic health records.

OpenSAFELY Collaborative, Christopher Wood, Victoria Speed, Louis Fisher, Helen J Curtis, Andrea L Schaffer, Alex J Walker, Richard Croker, Andrew D Brown, Christine Cunningham and 22 more

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

Article in British journal of clinical pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.0field-weighted citation impact, top 26% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Impact of structured medication reviews on prescribing in English primary care: a retrospective observational cohort study.The British journal of general practice : the journal of the Royal College of General Practitioners · 2026
    Observational
  2. 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

32 authors at 2 institutions in 1 country.

OpenSAFELY Collaborative
Christopher WoodBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0001-5184-0606
Victoria SpeedBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0001-5064-9375
Louis FisherBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0002-0295-3812
Helen J CurtisBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0003-3429-9576
Andrea L SchafferBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0002-3701-4997
Alex J WalkerBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0003-4932-6135
Richard CrokerBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0002-8114-9186
Andrew D BrownBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0002-3688-8393
Christine CunninghamBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0001-6802-7355
William J HulmeBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0002-9162-4999
Colm D AndrewsBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0003-2715-0562
Ben F C Butler-ColeBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
David EvansBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0002-1100-079X
Peter InglesbyBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0002-7784-1719
Iain DillinghamBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Sebastian C J BaconBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0002-6354-3454
Simon DavyBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0001-9890-3619
Tom WardBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0003-3743-1456
George HickmanBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0002-6691-4046
Lucy BridgesBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0002-4407-9596
Thomas O'DwyerBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0002-4373-1597
Steven MaudeBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0002-6112-5101
Rebecca M SmithBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Amir MehrkarBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0002-2098-1278
Chris BatesTPP, Leeds, Horsforth, UK.ORCID https://orcid.org/0000-0003-0113-2593
Jonathan CockburnTPP, Leeds, Horsforth, UK.ORCID https://orcid.org/0000-0002-4681-4873
John ParryTPP, Leeds, Horsforth, UK.
Frank HesterTPP, Leeds, Horsforth, UK.
Sam HarperTPP, Leeds, Horsforth, UK.
Ben GoldacreBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0002-5127-4728
Brian MacKennaBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0002-3786-9063
University of Oxford · GBLeeds City College · GB

Funding

Department of Health COV-LT-0009Department of Health COV-LT2-0073Health Data Research UK 2021.0157Health Data Research UK HDRUK2021.000Medical Research Council MC_PC_20030Medical Research Council MC_PC_20058Medical Research Council MC_PC_20059Medical Research Council MR/V015737/1Medical Research Council MR/W016729/1NIHR funded CONVALESCENCE programme COV-LT-0009NIHR funded CONVALESCENCE programme COV-LT2-0073NIHR funded CONVALESCENCE programme NIHR135559UK National Core Studies Programme MC_PC_20030UK Research and Innovation MC_PC_20058Wellcome Trust 222097Wellcome Trust 222097/Z/20/Z
6 · The paper itself

Abstract

aimsThe COVID-19 pandemic caused significant disruption to routine activity in primary care. Medication reviews are an important primary care activity ensuring safety and appropriateness of prescribing. A disruption could have significant negative implications for patient care. Using routinely collected data, our aim was first to describe codes used to record medication review activity and then to report the impact of COVID-19 on the rates of medication reviews.

methodsWith the approval of NHS England, we conducted a cohort study of 20 million adult patient records in general practice, in-situ using the OpenSAFELY platform. For each month, between April 2019 and March 2022, we report the percentage of patients with a medication review coded monthly and in the previous 12 months with breakdowns by regional, clinical and demographic subgroups and those prescribed high-risk medications.

resultsIn April 2019, 32.3% of patients had a medication review coded in the previous 12 months. During the first COVID-19 lockdown, monthly activity decreased (-21.1% April 2020), but the 12-month rate was not substantially impacted (-10.5% March 2021). The rate of structured medication review in the last 12 months reached 2.9% by March 2022, with higher percentages in high-risk groups (care home residents 34.1%, age 90+ years 13.1%, high-risk medications 10.2%). The most used medication review code was Medication review done 314530002 (59.5%).

conclusionsThere was a substantial reduction in the monthly rate of medication reviews during the pandemic but rates recovered by the end of the study period. Structured medication reviews were prioritized for high-risk patients.

Indexed as

COVID-19Electronic Health RecordsPrimary Health CareAdultAgedAged, 80 and overCohort StudiesEnglandFemaleHumansMaleMiddle AgedSARS-CoV-2State MedicineYoung Adultgeneral practiceprescribingprimary care

Identifiers

PMID38531661
PMCPMC7616229
OpenAlexW4394766525

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.