Why hospital-based healthcare professionals do not report adverse drug reactions: a mixed methods study using the Theoretical Domains Framework

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Abstract

Purpose

Adverse drug reaction (ADR) underreporting is highly prevalent across the world. This study aimed to identify factors associated with ADR reporting and map these to a behavioural change framework to help inform future interventions designed to improve ADR underreporting.

Methods

A mixed methods survey was distributed to healthcare professionals at a tertiary hospital in Sydney, Australia. Quantitative data was analysed using logistic regression to identify factors that predict ADR reporting. Qualitative data was evaluated using content analysis. These were then integrated and mapped to the 14 domains within the Theoretical Domains Framework (TDF) to identify target areas relevant for improving ADR reporting.

Results

One hundred thirty-three healthcare professionals completed the survey. Knowing how to report ADRs (OR 4.56, 95%CI 1.95–10.7), having been trained on ADR reporting (OR 2.72, 95%CI 1.29–5.77), and encountering ADRs as part of clinical practice (OR 10.3, 95%CI 3.59–29.4) were significant predictors of reporting an ADR. Content analysis identified three categories: modifying the ADR reporting process, enabling clinicians to report ADRs, and creating a positive ADR reporting culture. After data integration, the three target TDF domains were knowledge, environmental context/resources, and beliefs about consequences.

Conclusion

Future interventions designed to improve ADR reporting should address these target domains to instigate behaviour change in healthcare professionals’ reporting of ADRs.

Supplementary information

The online version contains supplementary material available at 10.1007/s00228-022-03326-x.

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Most cited references 28

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Three approaches to qualitative content analysis.

Hsiu-Fang Hsieh, Sarah Shannon (2016)

Content analysis is a widely used qualitative research technique. Rather than being a single method, current applications of content analysis show three distinct approaches: conventional, directed, or summative. All three approaches are used to interpret meaning from the content of text data and, hence, adhere to the naturalistic paradigm. The major differences among the approaches are coding schemes, origins of codes, and threats to trustworthiness. In conventional content analysis, coding categories are derived directly from the text data. With a directed approach, analysis starts with a theory or relevant research findings as guidance for initial codes. A summative content analysis involves counting and comparisons, usually of keywords or content, followed by the interpretation of the underlying context. The authors delineate analytic procedures specific to each approach and techniques addressing trustworthiness with hypothetical examples drawn from the area of end-of-life care.

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Information bias in health research: definition, pitfalls, and adjustment methods

Alaa Althubaiti (2016)

As with other fields, medical sciences are subject to different sources of bias. While understanding sources of bias is a key element for drawing valid conclusions, bias in health research continues to be a very sensitive issue that can affect the focus and outcome of investigations. Information bias, otherwise known as misclassification, is one of the most common sources of bias that affects the validity of health research. It originates from the approach that is utilized to obtain or confirm study measurements. This paper seeks to raise awareness of information bias in observational and experimental research study designs as well as to enrich discussions concerning bias problems. Specifying the types of bias can be essential to limit its effects and, the use of adjustment methods might serve to improve clinical evaluation and health care practice.

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A guide to using the Theoretical Domains Framework of behaviour change to investigate implementation problems.

Lou Atkins, Jill Francis, Rafat Islam … (2017)

Implementing new practices requires changes in the behaviour of relevant actors, and this is facilitated by understanding of the determinants of current and desired behaviours. The Theoretical Domains Framework (TDF) was developed by a collaboration of behavioural scientists and implementation researchers who identified theories relevant to implementation and grouped constructs from these theories into domains. The collaboration aimed to provide a comprehensive, theory-informed approach to identify determinants of behaviour. The first version was published in 2005, and a subsequent version following a validation exercise was published in 2012. This guide offers practical guidance for those who wish to apply the TDF to assess implementation problems and support intervention design. It presents a brief rationale for using a theoretical approach to investigate and address implementation problems, summarises the TDF and its development, and describes how to apply the TDF to achieve implementation objectives. Examples from the implementation research literature are presented to illustrate relevant methods and practical considerations.

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Author and article information

Contributors

Raymond Li:

ORCID: http://orcid.org/0000-0002-8040-4296

rali3062@uni.sydney.edu.au

Kate Curtis:

ORCID: http://orcid.org/0000-0002-3746-0348

kate.curtis@sydney.edu.au

Connie Van:

ORCID: http://orcid.org/0000-0002-9114-9622

connie.van@sydney.edu.au

Syed Tabish Razi Zaidi:

ORCID: http://orcid.org/0000-0002-2031-1055

s.t.r.zaidi@leeds.ac.uk

Chin Yen Yeo: chinyen.yeo@health.nsw.gov.au

Christina Arun Kali: christina.kali@health.nsw.gov.au

Mithila Zaheen: Mithila.zaheen@health.nsw.gov.au

Grace Therese Moujalli: grace.moujalli@health.nsw.gov.au

Ronald Castelino:

ORCID: http://orcid.org/0000-0002-5128-7115

Ronald.castelino@sydney.edu.au

Journal

Journal ID (nlm-ta): Eur J Clin Pharmacol

Journal ID (iso-abbrev): Eur J Clin Pharmacol

Title: European Journal of Clinical Pharmacology

Publisher: Springer Berlin Heidelberg (Berlin/Heidelberg )

ISSN (Print): 0031-6970

ISSN (Electronic): 1432-1041

Publication date (Electronic): 27 April 2022

Publication date PMC-release: 27 April 2022

Pages: 1-11

Affiliations

[1 ]GRID grid.1013.3, ISNI 0000 0004 1936 834X, Faculty of Medicine and Health, , University of Sydney, ; Parramatta Rd, Camperdown NSW 2006, Sydney, Australia

[2 ]GRID grid.9909.9, ISNI 0000 0004 1936 8403, Faculty of Medicine and Health, , University of Leeds, ; Leeds, England

[3 ]GRID grid.482212.f, ISNI 0000 0004 0495 2383, Western Sydney Local Health District, Blacktown and Mt Druitt Hospital, ; Mt Druitt, Australia

Author information

Raymond Li http://orcid.org/0000-0002-8040-4296

Kate Curtis http://orcid.org/0000-0002-3746-0348

Connie Van http://orcid.org/0000-0002-9114-9622

Syed Tabish Razi Zaidi http://orcid.org/0000-0002-2031-1055

Ronald Castelino http://orcid.org/0000-0002-5128-7115

Article

Publisher ID: 3326

DOI: 10.1007/s00228-022-03326-x

PMC ID: 9043508

PubMed ID: 35476123

SO-VID: bbcfce0e-86e6-4308-846b-90cfd629ae41

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 21 January 2022

Date accepted : 18 April 2022

Funding

Funded by: University of Sydney

Open Access :

Open Access funding enabled and organized by CAUL and its Member Institutions

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Why hospital-based healthcare professionals do not report adverse drug reactions: a mixed methods study using the Theoretical Domains Framework

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Abstract

Purpose

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Conclusion

Supplementary information

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Herbal Medicines Journal (Herb Med J)

Most cited references 28

Three approaches to qualitative content analysis.

Information bias in health research: definition, pitfalls, and adjustment methods

A guide to using the Theoretical Domains Framework of behaviour change to investigate implementation problems.

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