Understanding Persistent Pain Using a Decision Aid Tool in a Scottish Pharmacy Setting.
NCT ID: NCT05102578
Last Updated: 2023-12-06
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
NA
40 participants
INTERVENTIONAL
2022-01-01
2023-05-31
Brief Summary
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Detailed Description
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How the study will be implemented will be dependent on research restrictions due to the COVID-19 pandemic. If restrictions on research are in place, all study activities will be done remotely. If research restrictions are lifted the investigators will offer both remote and in person activities, depending on the participants preference.
Registered pharmacists in National Health Service (NHS) Grampian (see Section 5.1.) will be invited to take part in the study. As part of the assessment of feasibility for a future randomised control trial (RCT), a mixture of community and General Practitioner (GP)-surgery based pharmacists will be recruited. Recruited pharmacists will identify and invite patients living with persistent pain to a pain consultation. Pharmacists and patients will discuss current lifestyle and pain history, after which the pharmacist will recommend pain management plans that follow a person centred care (PCC) approach. Patients in the intervention group will receive the digital DAT - named UPP (Understanding Persistent Pain) - for self-completion with the help of the pharmacist. The DAT will generate a personalised report on the patient's preferences that can be used to discuss different PCC management plans. Management plans will be based on strategies routinely available in clinical practice4.
Heterogeneity in pharmacist-led pain consultations means that consultations are likely to differ across pharmacists. This study will allow the researchers to characterise different types of pharmacist-led pain consultations for a future larger study. As such, having a standardised control consultation falls beyond the scope of this feasibility study. Similarly, heterogeneity in current practice will cause agreed plans to differ across pharmacists and patients. These will also depend on the prescribing qualifications of the pharmacist.
The patient's GP will be informed of the person's participation and, in some cases, the recommendations/findings of the consultation. Where a prescription only medicine is deemed beneficial, pharmacists who are qualified independent prescribers will recommend this directly. Pharmacists without this qualification will, with the agreement of the patient, suggest to patients that they should book an appointment with the GP and send a referral letter to the GP with the recommendation for the prescription only medicine. Follow up consultations with the pharmacist will be arranged according to each pharmacist's current practice.
Parallel to the study, a testing event with patients living with persistent pain will be organised. Participants will be recruited using posters in GP Practices and using local patient networks. Participants will attend a half day event where they will get to use the digital DAT with the research team and provide feedback. Informed consent will be taken by the research team prior to the start of the event.
Conditions
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Study Design
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RANDOMIZED
PARALLEL
SUPPORTIVE_CARE
SINGLE
Study Groups
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Standard Care
Usual care. Consultation with pharmacist with no decision aid tool.
No interventions assigned to this group
Digital Decision Aid Tool
Consultation with pharmacist using the digital decision aid tool.
Digital Decision Aid Tool
The digital DAT will ask people about their current pain levels, medications and physical activity. Following this, it will include a Discrete Choice Experiment (DCE)-like component with a series of questions that ask users to choose between different pain management packages. Similar to a standard DCE, packages (or plans) are described by attributes and levels, which include broad categories of guideline-based pain management strategies routinely available in clinical practice. The descriptors used for the attributes and levels were informed by a previous qualitative research study and based on therapeutic options that are helpful and important to people with persistent pain .
Interventions
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Digital Decision Aid Tool
The digital DAT will ask people about their current pain levels, medications and physical activity. Following this, it will include a Discrete Choice Experiment (DCE)-like component with a series of questions that ask users to choose between different pain management packages. Similar to a standard DCE, packages (or plans) are described by attributes and levels, which include broad categories of guideline-based pain management strategies routinely available in clinical practice. The descriptors used for the attributes and levels were informed by a previous qualitative research study and based on therapeutic options that are helpful and important to people with persistent pain .
Eligibility Criteria
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Inclusion Criteria
* Suffer from non-malignant persistent pain (defined as pain lasting for more than three months).
* Managed entirely within a primary care setting.
Exclusion Criteria
* Have concomitant severe mental health problems or terminal illness.
* Suffer from pain caused by cancer or other malignancy.
* Not able to give informed consent (e.g. because of mental state)
* Takes part in another research study.
18 Years
ALL
Yes
Sponsors
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Pharmacy Research UK
UNKNOWN
University of Aberdeen
OTHER
Responsible Party
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Principal Investigators
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Mandy Prof Ryan
Role: PRINCIPAL_INVESTIGATOR
HERU Director
Locations
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NHS Grampian
Aberdeen, , United Kingdom
University of Aberdeen
Aberdeen, , United Kingdom
Countries
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References
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Loria-Rebolledo LE, Ryan M, Bond C, Porteous T, Murchie P, Adam R. Using a discrete choice experiment to develop a decision aid tool to inform the management of persistent pain in pharmacy: a protocol for a randomised feasibility study. BMJ Open. 2022 Sep 22;12(9):e066379. doi: 10.1136/bmjopen-2022-066379.
Other Identifiers
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2021UA003E-281537
Identifier Type: -
Identifier Source: org_study_id