Clinical trial NCT02582463: Development of the Medicines Optimisation Assessment Tool
Official title: Development of the Medicines Optimisation Assessment Tool (MOAT) - Targeting Hospital Pharmacists' Input to Reduce Risks and Improve Patient Outcomes
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Medicines Optimisation
Keywords: Risk Assessment
Hospitals
Pharmacists
Medication Systems
Patient Selection
Prognosis research
Lead sponsor: University College, London
Sponsor class: OTHER
Collaborators: name: National Institute for Health Research, United Kingdom
First posted: 2015-10-21
Enrollment: 1552
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Patients admitted to the Medical Division (General, Emergency, and Elderly Medicine) at the Luton and Dunstable University Hospital and Watford General Hospital

Brief summary: The purpose of this study 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). This has the potential to permit pharmacists to identify and focus on the small number of patients (approximately 6%) who are likely to experience a significant MRP while in hospital.

Detailed description: The purpose of this study 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).

The MOAT will be developed following recommendations of the PROGnosis RESearch Strategy (PROGRESS) partnership. A prospective cohort study of 1,500 patients will be used to develop the MOAT from the medical wards of two UK hospitals. Data will be collected on prognostic 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. Multivariable logistic regression models will be used to determine the relationship between potential risk factors such as polypharmacy, renal impairment, and the use of 'high risk' medicines, and the study outcome of preventable medication related problems that are at least moderate in severity. Bootstrapping will be used to adjust the MOAT for optimism, and predictive performance will be assessed using calibration and discrimination. A simplified scoring system will also be developed, which will be assessed for sensitivity and specificity.

The intention of this research is to develop a prediction-tool (the MOAT), which has the potential to be adopted widely into clinical practice. If the initial research is successful in producing a prediction-tool with good predictive performance further research will be carried out to assess how feasible it would be to use the MOAT in practice, the potential efficiency savings, and an assessment of clinical risk to patients through use of the MOAT.

Eligibility criteria: Inclusion Criteria:

* subject admitted to the Medical Division (General, Emergency, and Elderly Medicine) at the study sites

Exclusion Criteria:

* subject admitted for investigation-only
* subject not prescribed medication
* subject both admitted and subsequently discharged outside of core pharmacy working hours

Primary outcomes:
measure: Number of MRPs experienced by study participants
timeFrame: Through study completion (discharge from hospital), an average of 6 days
Secondary outcomes:
measure: Feasibility of using the MOAT (content validity and ease of use)
timeFrame: 18 months
measure: Potential efficiency savings
timeFrame: 18 months
measure: Potential clinical risk to patients through use of the MOAT
timeFrame: 18 months
Other outcomes:
Locations:
city: Luton
country: United Kingdom
facility: Luton and Dunstable University Hospital
state: Bedfordshire
Study officials:
affiliation: University College, London
name: Cathy Geeson
role: PRINCIPAL_INVESTIGATOR
References:
citation: Geeson C, Wei L, Franklin BD. Medicines Optimisation Assessment Tool (MOAT): a prognostic model to target hospital pharmacists' input to improve patient outcomes. Protocol for an observational study. BMJ Open. 2017 Jun 14;7(6):e017509. doi: 10.1136/bmjopen-2017-017509.