Cited by 58Pharmaceutical Practices and Patient OutcomesHealthcare cost, quality, practicesChronic Disease Management Strategies

Addressing potentially inappropriate prescribing in older patients: development and pilot study of an intervention in primary care (the OPTI-SCRIPT study)

Open access
Clyne, Barbara, Bradley, Marie C, Hughes, Carmel M, Clear, Daniel, McDonnell, Ronan, Williams, David, Fahey, Tom, Smith, Susan M·2013·BMC Health Services Research

Abstract

BACKGROUND: Potentially inappropriate prescribing (PIP) in older people is common in primary care and can result in increased morbidity, adverse drug events, hospitalizations and mortality. The prevalence of PIP in Ireland is estimated at 36% with an associated expenditure of over €45 million in 2007. The aim of this paper is to describe the application of the Medical Research Council (MRC) framework to the development of an intervention to decrease PIP in Irish primary care. METHODS: The MRC framework for the design and evaluation of complex interventions guided the development of the study intervention. In the development stage, literature was reviewed and combined with information obtained from experts in the field using a consensus based methodology and patient cases to define the main components of the intervention. In the pilot stage, five GPs tested the proposed intervention. Qualitative interviews were conducted with the GPs to inform the development and implementation of the intervention for the main randomised controlled trial. RESULTS: The literature review identified PIP criteria for inclusion in the study and two initial intervention components - academic detailing and medicines review supported by therapeutic treatment algorithms. Through patient case studies and a focus group with a group of 8 GPs, these components were refined and a third component of the intervention identified - patient information leaflets. The intervention was tested in a pilot study. In total, eight medicine reviews were conducted across five GP practices. These reviews addressed ten instances of PIP, nine of which were addressed in the form of either a dose reduction or a discontinuation of a targeted medication. Qualitative interviews highlighted that GPs were receptive to the intervention but patient preference and time needed both to prepare for and conduct the medicines review, emerged as potential barriers. Findings from the pilot study allowed further refinement to produce the finalised intervention of academic detailing with a pharmacist, medicines review with web-based therapeutic treatment algorithms and tailored patient information leaflets. CONCLUSIONS: The MRC framework was used in the development of the OPTI-SCRIPT intervention to decrease the level of PIP in primary care in Ireland. Its application ensured that the intervention was developed using the best available evidence, was acceptable to GPs and feasible to deliver in the clinical setting. The effectiveness of this intervention is currently being tested in a pragmatic cluster randomised controlled trial. TRIAL REGISTRATION: Current controlled trials ISRCTN41694007.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/1472-6963-13-307

Cites

48 of 48 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Clyne, B., Bradley, M. C., Hughes, C. M., Clear, D., McDonnell, R., Williams, D., Fahey, T., & Smith, S. M.
Affiliations
  • Royal College of Surgeons in Ireland (IE)
  • Queen's University Belfast (GB)
Corresponding author
Clyne, Barbara
Venue
BMC Health Services Research
Published
2013-08-14
Volume
13
Issue
1
Pages
307-307
ISSN
1472-6963 (ISSN-L)
OpenAlex
W2149239442
Cited by
58
References
47
Citations by year
2026: 2 · 2025: 3 · 2024: 1 · 2023: 4 · 2022: 2 · 2021: 3 · 2020: 8 · 2019: 6 · 2018: 3 · 2017: 7 · 2016: 9 · 2015: 8 · 2014: 2
FWCI
2.95
Type
journal article
Language
en
Open access
Locations
  • BMC Health Services Research (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Research Portal (Queen's University Belfast) (acceptedVersion, other-oa)
  • Royal College of Surgeons in Ireland (submittedVersion)
  • Figshare (submittedVersion, cc-by-nc-nd)
  • Lenus, The Irish Health Repository (Dr Steevens Hospital Library) (submittedVersion)
Funders
  • Health Research Board (HRC/2007/1, PHD/2007/16)
  • Royal College of Surgeons in Ireland
Topics
  • Health Sciences › Medicine › Geriatrics and Gerontology › Pharmaceutical Practices and Patient Outcomes
  • Health Sciences › Health Professions › General Health Professions › Healthcare cost, quality, practices
  • Health Sciences › Medicine › Epidemiology › Chronic Disease Management Strategies
Keywords
potentially inappropriate prescribing, elderly patients, primary care, academic detailing, patient information leaflets, pharmacist involvement, complex intervention development, MRC framework, dose reduction, drug discontinuation
MeSH terms
Aged, Algorithms, Humans, Ireland, Pilot Projects, Primary Health Care, Focus Groups, Consensus, Qualitative Research, Inappropriate Prescribing, General Practice

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review