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A Digitally Enabled, Pharmacist service to detecT medicine harms in residential aged care (nursing home) (ADEPT): protocol for a feasibility study

Por: Boord · M. S. · Brown · P. · Soriano · J. · Meola · T. · Dumuid · D. · Milte · R. · Roughead · E. E. · Lovell · N. H. · Stone · H. · Whitehouse · J. · Janetzki · J. L. · Gebreyohannes · E. A. · Lim · R.
Introduction

This feasibility study aims to develop and test a new model of practice in Australia using digital technologies to enable pharmacists to monitor early signs and symptoms of medicine-induced harms in residential aged care.

Methods and analysis

Thirty residents will be recruited from an aged care facility in South Australia. The study will be conducted in two phases. In phase I, the study team will work with aged care software providers and developers of digital technologies (a wearable activity tracker and a sleep tracking sensor) to gather physical activity and sleep data, as well as medication and clinical data from the electronic medication management system and aged care clinical software. Data will be centralised into a cloud-based monitoring platform (TeleClinical Care (TCC)). The TCC will be used to create dashboards that will include longitudinal visualisations of changes in residents’ health, function and medicine use over time. In phase II, the on-site pharmacist will use the centralised TCC platform to monitor each resident’s medicine, clinical, physical activity and sleep data to identify signs of medicine-induced harms over a 12-week period.

A mixed methods process evaluation applying the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) evaluation framework will be used to assess the feasibility of the service. Outcome measures include service reach, changes in resident symptom scores (measured using the Edmonton Symptom Assessment System), number of medication adverse events detected, changes in physical activity and sleep, number of pharmacist recommendations provided, cost analysis and proportion of all pharmacists’ recommendations implemented at 4-week, 8-week and 12-week postbaseline period.

Ethics and dissemination

Ethical approval has been obtained from the University of South Australia’s Human Research Ethics Committee (205098). Findings will be disseminated through published manuscripts, conference presentations and reporting to the study funder.

Trial registration number

ACTRN12623000506695.

Development and application of simulation modelling for orthopaedic elective resource planning in England

Por: Harper · A. · Monks · T. · Wilson · R. · Redaniel · M. T. · Eyles · E. · Jones · T. · Penfold · C. · Elliott · A. · Keen · T. · Pitt · M. · Blom · A. · Whitehouse · M. R. · Judge · A.
Objectives

This study aimed to develop a simulation model to support orthopaedic elective capacity planning.

Methods

An open-source, generalisable discrete-event simulation was developed, including a web-based application. The model used anonymised patient records between 2016 and 2019 of elective orthopaedic procedures from a National Health Service (NHS) Trust in England. In this paper, it is used to investigate scenarios including resourcing (beds and theatres) and productivity (lengths of stay, delayed discharges and theatre activity) to support planning for meeting new NHS targets aimed at reducing elective orthopaedic surgical backlogs in a proposed ring-fenced orthopaedic surgical facility. The simulation is interactive and intended for use by health service planners and clinicians.

Results

A higher number of beds (65–70) than the proposed number (40 beds) will be required if lengths of stay and delayed discharge rates remain unchanged. Reducing lengths of stay in line with national benchmarks reduces bed utilisation to an estimated 60%, allowing for additional theatre activity such as weekend working. Further, reducing the proportion of patients with a delayed discharge by 75% reduces bed utilisation to below 40%, even with weekend working. A range of other scenarios can also be investigated directly by NHS planners using the interactive web app.

Conclusions

The simulation model is intended to support capacity planning of orthopaedic elective services by identifying a balance of capacity across theatres and beds and predicting the impact of productivity measures on capacity requirements. It is applicable beyond the study site and can be adapted for other specialties.

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