Knowledge broker dyad

The intervention will involve the knowledge broker dyad implementing the Guiding Principles together with the RACF and MAC, with support from the MEGA-MAC collaborative. The knowledge broker dyad will act as a knowledge manager, capacity builder, and linking agent [15], with activities including:

Knowledge manager: Distributing and raising awareness about the Guiding Principles; embedding and applying the Guiding Principles into local contexts, policies and procedures; and assessing barriers and enablers to implementation in the local context.

Linkage agent: Facilitating collaboration between key onsite and off-site stakeholders (e.g. aged care provider management, quality improvement teams, medical practitioners, nurses, aged care workers, allied health, and community pharmacists); engaging with other knowledge broker dyads via the MEGA-MAC collaborative; and being a conduit between the Project Management Team and the RACF employed staff and visiting team members.

Capacity builder: Developing staff knowledge and skills to facilitate and enable improvements in medication management in line with the Guiding Principles; conducting audits and providing feedback on concordance with the Guiding Principles using the MEGA-MAC trial indicators to inform development of quality improvement initiatives; and evaluating effectiveness of those quality improvement initiatives.

The knowledge broker dyad will develop, implement, and evaluate RACF-specific local action plans quarterly based on each RACF's needs (Fig. 2). The local action plans will follow a systems approach using the United States Institute for Healthcare Improvement Model (IHI model) [34] and the Plan-Do-Study-Act (PDSA) cycle [35]. The knowledge broker dyad will use the three fundamental questions in the IHI model to identify why a change is needed, what improvement will look like and the changes that will result in improvement [34]. The PDSA cycle will be used as a systematic framework for continuous improvement in the real-world setting, including adapting planned actions according to ongoing feedback and monitoring [35]. The knowledge broker dyad will identify areas for improvement informed by a local context assessment, MEGA-MAC trial indicator results and with input from RACF staff, MAC members and the MEGA-MAC collaborative. Knowledge broker dyads will receive feedback on their local action plans from the Project Management Team, knowledge broker peers and the MEGA-MAC collaborative (Table 1).

Fig. 2

Description of the knowledge broker dyad intervention informed by the Institute of Health Improvement (IHI) model and the plan-do-study-act (PDSA) cycle. Abbreviations: KB, knowledge broker; MAC, medication advisory committee; RACF, residential aged care facility; SMART, specific, measurable, achievable, relevant, timely

Table 1 Knowledge broker dyad study activity requirementsMEGA-MAC collaborative

Knowledge broker dyads will be supported by the MEGA-MAC collaborative. This will be modelled on the national quality improvement collaborative for implementing Australia’s Clinical Practice Guidelines and Principles of Care for People Living with Dementia [20]. The MEGA-MAC collaborative will act as a real-time clinical network to enable sharing of experience and expertise between the knowledge broker dyads and support the knowledge broker dyads, RACFs, MACs and aged care provider organisations to implement the Guiding Principles and ensure quality use of medications.

The MEGA-MAC collaborative will support the knowledge broker dyads through the following activities (Fig. 3):

quarterly virtual ‘MEGA-MAC’ meetings (baseline, 3, 6 and 9 months);

quarterly ‘MEGA-MAC’ newsletters (baseline, 3, and 6 months) that include trial updates and sharing of learnings;

providing aggregate Guiding Principles concordance results from all participating RACFs that each knowledge broker dyad can use to benchmark against their RACF-level concordance;

expert and peer review feedback on the knowledge broker dyads’ local action plans (baseline, 3 months and at 6 months); and

ongoing ad-hoc expert and peer support via virtual meetings, and informal real-time peer support via SLACK (Searchable Log of All Communication and Knowledge) chat group.

Fig. 3

Visual representation of activities occurring during the MEGA-MAC study. Abbreviations: MAC, medication advisory committee; MEGA-MAC, national quality improvement collaborative

Ongoing fidelity of the intervention delivered by the knowledge broker dyads will be monitored using the local action plans, the MEGA-MAC meetings and regular meetings with the Project Management Team.

Data collection

Data will be collected from the participating RACFs at six timepoints (−6, −3, baseline, 3, 6, 9 months) by trained data collectors (aged care nurses, health or care professionals employed or contracted by each of the participating aged care provider organisations) (Table 2). Data collectors will attend an online training webinar on data collection led by the Project Management Team and will have access to data collection manuals and recorded training webinars to ensure consistency of data collection. Pre-intervention data (−6, −3, 0 months) will be collected retrospectively at or before baseline. Post-intervention data (+ 3, + 6, and + 9) will be collected prospectively. Trial data will be collected using a series of standard data collection forms and managed using Research Electronic Data Capture (REDCap), an electronic data capture tool hosted and managed by Helix (Monash University). REDCap is a secure, web-based software platform designed to support data capture for research studies [36, 37]. Trial data will be stored for a minimum of 15 years after publication of result in accordance with Australian National Health and Medical Research council (NHMRC) and Monash University guidance for medical research involving clinical trials. The final dataset will only be accessible to the investigators and statistician or epidemiologist.

Table 2 SPIRIT diagram – schedule of enrolment, intervention and assessment for the MEGA-MAC studyRACF-level concordance with Guiding Principles

The data collectors will assess RACF-level concordance with the Guideline Principles using a series of indicators developed for the MEGA-MAC trial by New South Wales Therapeutic Advisory Group (NSW TAG), in consultation with an expert advisory group and the Project Management Team [38]. The indicators will assess concordance with the Guiding Principles across four key domains: the RACF’s 1) MAC meeting; 2) policies, procedures and guidelines; 3) admission processes; and, 4) medication review processes (Tables 3, 4, 5, and 6). There will be 28 indicators across the four domains.

Table 3 Domain 1 Indicators and sub-indicators evaluating the RACF’s MAC meetingTable 4 Domain 2 Indicators and sub-indicators evaluating the RACF’s policies, procedures and guidelinesTable 5 Domain 3 Indicators and sub-indicators evaluating the RACF’s admission processTable 6 Domain 4 Indicators evaluating the RACF’s medication review processes

Data required for the indicators will be extracted from the RACF’s existing clinical information systems, including National Aged Care Mandatory Quality Indicator Program records, psychotropic medicines register, nursing progress notes, medical records, RACFs register of policies/procedures/guidelines, register of residents who have a completed comprehensive medication management review by a pharmacist, register of residents admitted to the RACF and MAC meeting agenda, minutes, and associated papers. The identifiable resident-level data required to complete the indicators will only be accessed by appropriate staff employed/contracted by the aged care provider organisation and by the knowledge broker dyad to assist with intervention delivery. Trial investigators will not have access to these data sources. Microsoft Excel-based ‘Guiding Principles Concordance’ data collection tools [38] were developed for the trial to assist data collectors in calculating RACF-level concordance for each trial indicator and sub-indicator. RACF-level concordance will be entered into REDCap. Aggregated data on Guiding Principles concordance for all participating RACFs will be reported at quarterly MEGA-MAC meetings and in the MEGA-MAC newsletters.

RACF-level proportions of hospitalisation, quality of life, consumer experience, and medication-related incidents

Data on RACF-level proportions of hospitalisation, quality of life, and consumer experience will be extracted from the mandatory National Aged Care Quality Indicator Program records [39]. The following definitions will be used in line with the National Aged Care Quality Indicator Program:

Hospitalisation: RACF-level proportion of residents hospitalised compared to the previous quarter. Hospitalisation will include emergency department presentations and hospital admissions within the last 3 months.

Quality of life: RACF-level proportion of residents who report ‘excellent’ or ‘good’ quality of life as assessed using The Quality of Life Aged Care Consumers (QOL-ACC) tool compared to the previous quarter [40].

Consumer experience: RACF-level proportion of residents who report ‘excellent’, or ‘good’ consumer experience using The Quality of Care Experience Aged Care Consumers (QCE-ACC) compared to the previous quarter.

Data on RACF-level prevalence of medication-related incidents will be extracted from each RACF’s electronic risk management system quarterly.

RACF and MAC characteristics

Data on RACF-level characteristics will include: location (e.g. State, Territory), region (e.g. metropolitan, regional, rural, remote), number of residents, number of beds, number of residents who are female, mean resident age, number of health and care professionals employed/contracted and the health professional disciplines that typically visit the RACF weekly. Data on MAC characteristics will include: number of RACFs and residents the MAC governs, number of MAC members, discipline of each MAC member (e.g. general practitioner, nurse, pharmacist) and the discipline of the MAC chair. RACF characteristics will be collected at baseline. MAC characteristics will be collected at baseline and 9 months.

Knowledge broker and MEGA-MAC Collaborative demographics

Demographic data will be collected from each knowledge broker dyad and MEGA-MAC collaborative panel member at time of recruitment. Knowledge broker demographics will include: gender, discipline (e.g. general practitioner, registered nurse, pharmacist), professional background (education, qualifications, practice experience, aged care experience) and length of time employed or contracted at the RACF. MEGA-MAC collaborative panel member demographics will include: gender, discipline (e.g. general practitioner, registered nurse, pharmacist), professional background (education, qualifications, practice experience, aged care experience, current role/s) and consumer roles.

Knowledge broker dyad activities

Data from local action plans (including goals, type of local activities implemented, resources used, timeline, actual implementation, reflections) and MEGA-MAC meetings will be collected throughout the trial. Semi-structured interviews with knowledge broker dyads will also be conducted at 3 months, 6 months and at the conclusion of the trial to understand the delivery of the intervention at each RACF. Semi-structured interviews may also be conducted with other stakeholders at the conclusion of the trial. Optional anonymous online surveys will be conducted at the conclusion of each MEGA-MAC meeting to understand attendees’ perspectives on the meeting (e.g. aspects of the meeting that were useful, aspects that could be improved).

Economic evaluation

Data for economic evaluation will include interventions costs (e.g. how much the intervention costs to be delivered), downstream costs (e.g. staff costs to attend MAC meetings), and costs of medication incidents and hospitalisations. Individual resident level data will not be collected, only RACF-level data. Economic data will be embedded within other trial data collection tools to minimise data collection burden where possible (refer to Appendix 2 for full details).