Amanda J. Cross

Background: Effective implementation of guidelines into residential aged care facilities (RACFs) is important for high-quality care. The 12-month Evidence-based Medication knowledge Brokers in Residential Aged CarE (EMBRACE) helix–counterbalanced randomised controlled trial evaluated three strategies to implement Clinical Practice Guidelines for the Appropriate Use of Psychotropic Medications in People Living with Dementia and in Residential Aged Care: (i) passive distribution of Guideline material, (ii) pharmacist-led staff education and (iii) knowledge broker-led Guideline implementation. All three strategies reduced Guideline non-concordance over time, with no significant difference between strategies. This mixed-method process evaluation examined delivery of the implementation strategies, including contextual factors important for Guideline implementation. Methods: Semi-structured interviews conducted with 34 health and care professionals at 12 months were thematically analysed using a deductive approach informed by the Grant framework. Descriptive statistics summarised quantitative data from a post-trial survey completed by intervention pharmacists. Results: Distribution of Guideline materials occurred opportunistically with RACF staff preferring summary materials (e.g. one-page factsheets). Pharmacist-led staff education was tailored to be shorter, more frequent and delivered one-on-one or in small groups. Knowledge broker pharmacists spent a median 70% of time delivering quality improvement activities including audit and feedback and integrating psychotropic best practice into RACF procedures and digital systems. Facilitators of successful Guideline implementation included early engagement with aged care leadership and knowledge broker integration into the team. Conclusion: Guideline implementation efforts in RACFs may benefit from a multifaceted implementation approach involving early engagement with aged care leadership and contextualised delivery of implementation strategies according to staff preferences and needs.

Background: Medication-related problems (MRPs) place a substantial burden on the healthcare system, contributing to hospital admissions and significant healthcare costs. Quality prescribing indicators (QPIs) offer a way to evaluate and guide improvements in prescribing with the aim of improving medicine use. Objectives: This study aimed to establish an updated set of QPIs for Australian primary care. Method: Potential QPIs were identified from a scoping review and reviewed by clinical members of the research team. Potential QPIs (n=37) that were identified to be relevant, feasible and impactful by the research team were assessed by an expert panel using a two-round Delphi consensus-building approach. The panel (n=42) included experienced general practitioners, pharmacists and nurse practitioners from urban/regional settings across Victoria, New South Wales and Tasmania. Each QPI’s validity and importance were scored on a 5-point Likert scale. Participants could provide comments that were anonymously presented in round 2, along with other participants’ scores. A QPI was approved if >80% of participants scored it a 4 or 5 for both validity and importance. Results: A total of 23 of the 37 selected QPIs were approved, covering proton pump inhibitors, vaccinations, antihypertensives, anti-inflammatories, inhaled corticosteroids, mental health treatments and analgesics. The selected QPIs provide information on appropriate initiation, monitoring, deprescribing and the avoidance of high-risk prescribing. While mean scores and rate of acceptance were high, comments suggested perceived difficulties implementing some of the QPIs. Discussion: QPIs for primary care were developed after a rigorous review and consensus process. These should be progressed to field testing and implementation. If integrated into routine primary care practice through educational audit and feedback, the QPIs may improve the quality use of medicines.

Background: Knowledge brokers act as intermediaries to bridge evidence-to-practice gaps. Limited evidence describes how the knowledge broker role in health settings evolves over time. This study aimed to (a) examine the evolution of knowledge broker activities over a 12-month implementation trial and (b) identify enablers necessary to strengthen and support the role. Methods: This longitudinal multi-method study is nested within the 12-month Evidence-based Medication knowledge Brokers in Residential Aged CarE (EMBRACE) trial. The EMBRACE intervention involved knowledge brokers working in 19 residential aged care facilities (RACFs) to support implementation of Australia’s Clinical Practice Guidelines for the Appropriate Use of Psychotropic Medications in People Living with Dementia in Residential Aged Care. Seventy-six knowledge broker local action plans, representing 19 RACFs at four time points, were analysed to characterise core knowledge broker functions and the frequency of planned quality improvement activities targeting seven pre-defined sub-indicators of psychotropic appropriateness. The Consolidated Framework for Implementation Research informed thematic analysis of 76 separate quarterly written reflections and 28 semistructured interviews with knowledge brokers. Results: The number and breadth of knowledge broker activities increased over time. At baseline, six RACF local action plans included activities targeted towards at least one sub-indicator, increasing to all 19 local action plans from the 3-month timepoint onwards. Knowledge brokers enacted overlapping functions as knowledge managers, linkage agents and capacity builders, although the timing and extent of role progression varied across RACFs and individuals. Evolution of activities was shaped by individual (clinical leaders, implementation facilitators, peer support) organisational (culture, governance pathways, digital integration) and outer setting factors (COVID-19 disruptions, national policy directives). Conclusion: The knowledge broker role fundamentally evolved from assessing local context and establishing foundational rapport to driving systemic change. Effective translation of guidelines into practice requires future implementation programmes to support this role with a strong organisational culture, robust infrastructure and strategic alignment with RACFs and national priorities.

Glucagon‐like peptide‐1 receptor agonists (GLP‐1RAs) are increasingly prescribed for type 2 diabetes and weight management. However, conflicting evidence from preclinical, clinical, and pharmacovigilance studies suggests potential neuropsychiatric effects. This study examined associations between GLP‐1RA use and initiation of a range of neuropsychiatric medications using real‐world prescription data. A Prescription Sequence Symmetry Analysis was conducted using Australia's Pharmaceutical Benefits Scheme 10% random sample between July 1, 2013 and December 31, 2024. Individuals with an incident dispensing of both a GLP‐1RA and a neuropsychiatric medication were included. Outcomes comprised antidepressants, medication for substance use disorder (SUD), antipsychotics, psychostimulants, antidementia medications, antiparkinsonian medications, antiepileptics, and antimigraine agents. Adjusted sequence ratios (aSRs) with 95% confidence intervals (CIs) were calculated using a one‐year exposure window, with sensitivity analyses varying various time windows. Among 2,033 individuals, semaglutide was the most common GLP‐1RA (50.6%), followed by exenatide (27.5%) and dulaglutide (21.9%). GLP‐1RA initiation was inversely associated with initiation of antidepressants (aSR: 0.85; 95% CI: 0.76–0.94) and medications for SUD (aSR: 0.70; 95% CI: 0.51–0.88). No significant associations were observed for other neuropsychiatric outcomes. GLP‐1RA use was inversely associated with subsequent initiation of antidepressants and medications for SUD, while no associations were identified for other neuropsychiatric marker medications. These findings highlight the need for further studies to clarify the nature and magnitude of these potential neuropsychiatric associations with GLP‐1RAs.

Objectives: To systematically examine the prevalence of, and factors associated with, benzodiazepine, Z‐drug and melatonin use in Australian residential aged care facilities (RACFs). Methods: MEDLINE, Embase, CINAHL, PsycINFO, Scopus and International Pharmaceutical Abstracts were searched from January 2000 to February 2025 for studies reporting benzodiazepine, Z‐drug and/or melatonin prevalence in Australian RACFs. Overall, regular and pro re nata (PRN) medication use was considered. Screening, data extraction and quality assessment were performed independently by two authors. The primary outcome was overall prevalence (regular and PRN) of benzodiazepines, Z‐drugs and/or melatonin. Secondary outcomes included regular prevalence, PRN prevalence and medication class prevalence. Results: Fifty‐two studies ( n = 658,585 residents) were included. Overall prevalence of benzodiazepines and/or Z‐drugs was 33% (95% confidence interval [CI]: 30.4%–34.7%, 30 studies) when assessed over periods from point prevalence to one‐year prevalence. Prevalence was highest when assessed using prescribing (35%) rather than dispensing (32%) or administration (28%) data. Findings were similar when limited to studies published in the last 10 years (31%), studies of 100 or more residents (32%) and when excluding studies conducted in subsets of residents (33%). Benzodiazepine prevalence (35% [95% CI: 32.5%–36.9%], 24 studies) was higher than Z‐drug prevalence (0.4% [95% CI: 0.1%–1.1%], three studies). No published studies reported melatonin prevalence, and unpublished regular prevalence ranged 1%–9% (four studies). Conclusions: One in three Australian residents in RACFs use benzodiazepines and/or Z‐drugs. Targeted interventions are needed to ensure their use is consistent with evidence‐based practice and residents' clinical needs.

Background: Managing medications safely can be challenging for people with dementia and carers living in the community and medication errors can be a source of preventable harm. Resources to support people in medication management must address their information needs and prioritise these alongside those of broader stakeholders. Objective: We aimed to generate content statements for inclusion in tailored medication management literacy resources for people with dementia and carers. Design and Methods: Using a community-based participatory research approach, we established a Medication Management Guidance Partnership: collaboration between the research team, research advisory group, and partner organisations. A mixed-method approach generated 49 statements (Phase 1) then we conducted an online modified Delphi process to gain consensus (Rounds 1 and 2) and prioritise statement order (Round 3) for inclusion in resources (Phase 2). Primary criterion for consensus required ≥80% of participants rating statements as important (≥7 on 9-point Likert-type scale). Secondary criteria assessed response variability, and statements were required to meet all criteria for inclusion. Results: People with dementia (n = 5), carers (n = 5), healthcare professionals and/or national consumer organisation representatives (n = 13) reached consensus on 44 statements across six information domains. ‘Information about decision-making’ was ranked highest, followed by ‘general question prompts’, ‘information about common medications’, ‘addressing complexities,’ ‘getting guidance in different languages’ and ‘additional supports.’ Conclusion: Our ‘menu’ of statements about medication management priorities, endorsed by end-users, can be used to guide development of resources to improve medication management and potentially reduce medication-related harm in this population.

Introduction: High‐risk medications are medications associated with significant patient harm or death if misused or used in error. This study aimed to develop a national consensus high‐risk medication list for use in Australian residential aged care. Methods: A 3‐round modified Delphi study involving Australian healthcare professionals was conducted. In Round 1, participants indicated their level of agreement, on a 9‐point Likert scale, whether 60 medications/medication classes were considered high‐risk and should be included in a high‐risk medication list for Australian residential aged care. Round 2 included medications/medication classes that did not reach consensus and new medications identified by participants. Consensus was defined as 70% or more of participants responding at 7 or higher on the Likert scale. In Round 3, participants were asked to prioritise medications/medication classes that reached consensus in Round 1 or 2. Results: In total, 42 participants completed Round 1, and 35 (83%) completed all three rounds. Participants included pharmacists ( n = 21), prescribers ( n = 15), nurses ( n = 5) and a paramedic ( n = 1), with representation from all Australian states and mainland territories. Overall, 26 medications reached consensus (21 in Round 1, five in Round 2) and were categorised into 15 medications/medication classes for prioritisation in Round 3. The final prioritisation list was opioids, insulin, benzodiazepines, anticoagulants, z‐drugs, antipsychotics, lithium, sulfonylureas with high risk of hypoglycaemia, chemotherapeutic agents, methotrexate, digoxin, narrow therapeutic range antiepileptics, tricyclic antidepressants, immunosuppressants for transplant and sedating antihistamines. Discussion: This is the first, national consensus list of high‐risk medications developed specifically for Australian residential aged care. It can be used to implement targeted strategies to minimise medication‐related harm.

Recent regulatory changes in Australia have emphasised system-level approaches to ensure appropriate psychotropic medication use in residential aged care homes. This study explored quality improvement processes related to psychotropic medication use in Australian residential aged care homes. This qualitative study used in-depth semi-structured interviews with a maximum variation sample of key stakeholders involved in psychotropic medication use at organisations operating facilities in metropolitan and regional areas in four Australian states. The interviews were transcribed verbatim and thematically analysed using both inductive and deductive approaches by two researchers using a framework developed for learning health systems. Stakeholders (n = 33) included nurses, occupational therapists, pharmacists, medical practitioners, residents and caregivers. Identified themes were (i) regulation was driving change in organisational policies and procedures, and (ii) aged care organisations were enhancing quality improvement systems for psychotropic medications. Many of the requirements of successful healthcare quality improvement systems were present within the aged care organisations, including alignment of core values and presence of key ethical, legal and policy infrastructure. There are opportunities for better use of clinical data to improve care, especially in terms of learning from the data and implementing tailored change. The challenges identified by participants included navigating the perceived tension between compliance and quality, and aligning the goals and processes of all health professionals. Recent changes in policies, procedures and infrastructure have provided clearer oversight of psychotropic medication use. Individual and system approaches to psychotropic medication use in aged care have shifted. Key opportunities for improving use of psychotropic medications within aged care organisations include improving the capacity to use local data to improve care and building interdisciplinary teams to facilitate collaborative care.