A medication assessment tool to evaluate adherence to medication guideline criteria in cancer pain management

Abstract

Abstract Objective The medication assessment tool for cancer pain management (MAT-CP) is a novel tool for measuring quality of drug use in chronic pain management in relation to guideline standards, and has been developed and tested in Norway with UK collaboration. The present paper describes the revision of the assessment tool for use in the UK, and its subsequent validation. Setting Three hospitals and one hospice in Scotland, UK. Method The MAT-CP was field-tested to produce preliminary data on its applicability in a UK clinical setting. The tool was then modified by peer review among clinical specialists before and after a pilot. The revised tool was further validated by wider application to a study sample of cancer inpatients. The outcome was the evaluation of the tool's utility in relation to clinical documentation in terms of applicability, clarity, reliability and perceived relevance of each criterion. The findings also included a quantification of adherence to the guideline criteria. Key findings The revised tool comprised 37 criteria covering six different aspects of cancer pain management. The field testing and pilot informed the modification of the MAT-CP to optimise its clarity and utility when applied to patients' clinical documentation. The revised tool was tested on 101 cancer patients experiencing pain (56 males), mean (standard deviation) age 68.9 (13.5) years. Overall guideline adherence was 68% (n = 1850 applicable criteria). Good inter-rater reliability (Cohen's kappa κ = 0.92) was demonstrated in the application. The preliminary application of the tool during validation and field-testing has highlighted several issues for further study. Conclusion A clinical tool to examine prescribing in cancer pain management that was designed for use in Norway has been revised for use in UK clinical settings. Reliability, face and content validity have been informed by applying the tool to patient data in clinical settings.