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The impact of COVID-19 on medication reviews in English primary care. An OpenSAFELY-TPP analysis of 20 million adult electronic health records.
Wood, Christopher; Speed, Victoria; Fisher, Louis; Curtis, Helen J; Schaffer, Andrea L; Walker, Alex J; Croker, Richard; Brown, Andrew D; Cunningham, Christine; Hulme, William J; Andrews, Colm D; Butler-Cole, Ben F C; Evans, David; Inglesby, Peter; Dillingham, Iain; Bacon, Sebastian C J; Davy, Simon; Ward, Tom; Hickman, George; Bridges, Lucy; O'Dwyer, Thomas; Maude, Steven; Smith, Rebecca M; Mehrkar, Amir; Bates, Chris; Cockburn, Jonathan; Parry, John; Hester, Frank; Harper, Sam; Goldacre, Ben; MacKenna, Brian.
Afiliação
  • Wood C; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Speed V; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Fisher L; Department of Thrombosis and Haemostasis, King's College Hospital, London, UK.
  • Curtis HJ; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Schaffer AL; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Walker AJ; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Croker R; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Brown AD; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Cunningham C; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Hulme WJ; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Andrews CD; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Butler-Cole BFC; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Evans D; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Inglesby P; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Dillingham I; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Bacon SCJ; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Davy S; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Ward T; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Hickman G; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Bridges L; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • O'Dwyer T; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Maude S; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Smith RM; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Mehrkar A; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Bates C; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
  • Cockburn J; TPP, Leeds, Horsforth, UK.
  • Parry J; TPP, Leeds, Horsforth, UK.
  • Hester F; TPP, Leeds, Horsforth, UK.
  • Harper S; TPP, Leeds, Horsforth, UK.
  • Goldacre B; TPP, Leeds, Horsforth, UK.
  • MacKenna B; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Br J Clin Pharmacol ; 90(7): 1600-1614, 2024 Jul.
Article em En | MEDLINE | ID: mdl-38531661
ABSTRACT

AIMS:

The 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.

METHODS:

With 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.

RESULTS:

In 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%).

CONCLUSIONS:

There 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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Atenção Primária à Saúde / Registros Eletrônicos de Saúde / COVID-19 Limite: Adult / Aged / Aged80 / Female / Humans / Male / Middle aged País/Região como assunto: Europa Idioma: En Revista: Br J Clin Pharmacol Ano de publicação: 2024 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Atenção Primária à Saúde / Registros Eletrônicos de Saúde / COVID-19 Limite: Adult / Aged / Aged80 / Female / Humans / Male / Middle aged País/Região como assunto: Europa Idioma: En Revista: Br J Clin Pharmacol Ano de publicação: 2024 Tipo de documento: Article