Title: Development of the Medicines Optimisation Assessment Tool (MOAT) - Targeting hospital pharmacists' input to reduce risks and improve patient outcomes
Funder: Health Education England

Abstract: Study aim The aim of this research is to develop a prediction-tool, the Medicines Optimisation Assessment Tool (MOAT), to assist hospital pharmacists identify patients at highest risk of preventable Medication Related Problems (MRPs). Background The overall goal of clinical pharmacy is to promote the appropriate use of medicines in order to optimise medication-related outcomes. Hospital clinical pharmacists have been shown to improve the quality, safety and efficiency of patient care, but resources are finite and pharmacists often have to target their input to those patients perceived as being at highest risk'. Many potential risk factors have been identified (e.g. increasing age, renal impairment, high-risk medicines), but currently there is no evidence-based method to predict which factors, or combination of factors, convey the greatest risks. Predicting clinical risk is well established in medicine; examples include cardiac-risk calculators and the Waterlow score (which assesses the risk of pressure ulcers, see Optional Annex), both of which are in daily use across the NHS. Prediction-tools do not in themselves resolve problems, but they can identify patients who are likely to benefit most from an intervention, promote consistency in practice and improve efficiency. A clinical pharmacy prediction-tool for medication risk has the potential to permit pharmacists to identify and target the small number of patients (approximately 6%) who are likely to experience a significant MRP while in hospital. Plan of investigation A prospective cohort study of 2,000 patients across two hospitals will be used to develop the MOAT. I plan to collect data on risk factors (selected based on a review of published literature and expert opinion) for each patient, together with details of MRPs that occur. All MRPs will be reviewed by an expert panel who will grade for severity and preventability using recognised criteria. I will use univariate analyses to determine the strength of association between each risk factor and the outcome (patients who experience preventable, moderate to severe MRPs), followed by regression analyses to develop the prediction-tool. The objective will be to find the combination of risk factors (predictors for the regression calculations) that provide the greatest sensitivity for detecting moderate-severe MRPs (outcomes for the regression calculations) while achieving the maximum possible specificity. In order to make the MOAT simple and quick to apply it is proposed that it will contain as few variables as possible, and be presented in a way that does not require healthcare staff to use computerised or statistical aids. I will perform internal validation to assess the predictive performance of the MOAT (sensitivity, specificity, positive predictive value, and area under the receiver operating characteristic curve). In addition a bootstrapping technique will be used to predict performance in an independent dataset. The intention is to develop a tool with the potential to be adopted widely into clinical practice; therefore the content validity of the MOAT and simplicity of interpretation will be assessed using a nominal group technique. The potential workload impact (based on time taken to apply the MOAT and the specificity) will also be reviewed, together with an assessment of the potential clinical risk of false negative results. Further validation and implementation studies will be needed following completion of this research to determine whether the MOAT could be successfully employed in new settings (see career intentions). Potential benefits to patients/NHS Once fully validated, the MOAT has the potential to increase the efficiency of hospital pharmacy services, and thereby reduce NHS costs (linked to medicines wastage, preventable readmissions and prolonged hospitalisation). In terms of patient benefits, the identification and resolution of MRPs has the potential to improve health and wellbeing, improve patient experience and ultimately quality of life.

Lay abstract: By working with individual patients, pharmacists can improve prescribing and minimise the risk of harm. This research aims to develop and evaluate a method of targeting patients, the Medicines Optimisation Assessment Tool (MOAT), to help pharmacists target scarce resources to those patients who can benefit the most. The details of 2,000 patients across two hospitals will be reviewed to identify risk factors that lead to medication related problems (with new or existing medicines). These will be analysed to develop the MOAT.The anticipated benefits include improvements in the health and wellbeing of patients, and more efficient use of NHS resources.

Research activity codes: 6.1 PHARMACEUTICALS
Health categories: GENERIC HEALTH RELEVANCE