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Trial registered on ANZCTR

Registration number

ACTRN12622000508774

Ethics application status

Approved

Date submitted

4/03/2022

Date registered

30/03/2022

Date last updated

30/03/2022

Date data sharing statement initially provided

30/03/2022

Type of registration

Prospectively registered

Titles & IDs

Public title

A controlled trial to evaluate a pharmacy prioritisation tool in an older adult inpatient setting

Scientific title

Evaluation of the Modified Adverse Inpatient Medication Event (AIME-FRAIL) Model on the incidence of medication-related harms or drug adverse events in Older Hospitalised Adults: A Controlled Cohort Study

Secondary ID [1]

None

Universal Trial Number (UTN)

Trial acronym

AIME-FRAIL Study

Linked study record

Health condition

Health condition(s) or problem(s) studied:

Adverse drug events or medication harm

Condition category

Condition code

Injuries and Accidents

Other injuries and accidents

Public Health

Health service research

Intervention/exposure

Study type

Interventional

Description of intervention(s) / exposure

For the intervention wards each patient will be reviewed weekly by a research pharmacist or a clinical assistant, who will calculate a patient’s risk score using the AIME-FRAIL tool criteria. Briefly the criteria consist of: 1) patient frailty (as per the Clinical Frailty Scale - CFS), 2) length of stay (LOS) in hospital (> 14 days), 3) Insulin use, 4) Anticoagulants, 5) Antiarrhythmics (according to Australian Medicines Handbook classification), 5) Antipsychotic use, 6) Immunosuppressants use, 7) Antibiotic use, and 8) Opioid use. This tool is a risk prediction tool which predicts risk of the patient having an adverse reaction/ or experiencing harm from their medicines. One point will be given to each ‘yes’ response, and a 0 to each ‘no’ response. The patients’ score will be summed to give their total risk score.

Patients with a score above 5 will be highlighted as high-risk, for a comprehensive clinical review of their medications by the ward pharmacist (ideally within 24 hours of admission). We anticipate that to complete the risk tool it will take approximately 15 minutes for each participant (the data will be check for against the patients chart and clinical notes and entered as a 1(=yes) or 0 (=no) for each criteria in an Excel spread sheet to generate the risk score). The score will be calculated at admission and updated weekly for the duration of the patient's hospitalisation. The study database will be audited by the principal researcher to ensure adherence to the protocol and data capture requirements. A random sample of 10% of patients will have risk scores validated by a different member of the research team to ensure accurate data entry and risk score calculations. Two wards of similar patient cohorts and casemix will be included, and one will be allocated to intervention and the other to the control. Patient allocation to wards is not randomised but based on hospital resources and clinical needs. From the two selected wards one will be allocated to the intervention (using the tool) and one to control (usual practice). The ward for intervention will be selected based on resourcing and staff availability and skills to optimise ensure patient safety.

Intervention code [1]

Early detection / Screening

Comparator / control treatment

For the control ward, the ward pharmacist will continue to prioritise patients based on usual practice (clinical judgement), without assistance from the risk tool (no risk scores will be calculated for the control ward patients). Any patients deemed as high risk will receive comprehensive clinical medication review within 24 hours of admission to the ward.

Control group

Active

Outcomes

Primary outcome [1]

Any medication-related harm (also known as adverse drug events) of any type, severity or preventability. e.g. falls due to multiple antihypertensives causing postural drop, hypoglycaemia due to insulin therapy, bleeding or bruising due to anticoagulant medications. Harm will be identified through use of a set of triggers (e.g. high INR or falls), which will be collected by clinical assistants from the patient's progress notes and by speaking to the health care team (pharmacists, nurses and doctors caring for the patient) and verified as actual medication harm through causality analysis by the research team.

Timepoint [1]

Throughout hospital admission in the Geriatric Rehabilitation ward

Secondary outcome [1]

Composite secondary outcome of any clinically significant medication errors e.g. interaction between two medicines with high potential for adverse patient outcomes e.g. warfarin and miconazole OR prescribing multiple sedating / anticholinergic drugs for a patient with high falls risk, or an inadvertently high dose of IV Unfractionated heparin (not prescribed in accordance with nomogram)

Timepoint [1]

Any time during hospital admission to Geriatric ward

Eligibility

Key inclusion criteria

All patients admitted to the two selected wards at the Princess Alexandra Hospital will be eligible for inclusion.

Minimum age

18 Years

Maximum age

No limit

Sex

Both males and females

Can healthy volunteers participate?

Key exclusion criteria

The following exclusion criteria will be applied:
• Patients admitted prior to the commencement of the study
• Patients who are receiving end of life care
• Patients admitted and discharged prior to the research pharmacist being able to calculate their risk score
• Patients who are transferred to the acute wards for urgent care (e.g., surgery) within the first 14 days of admission to the GARU wards.

Study design

Purpose of the study

Prevention

Allocation to intervention

Non-randomised trial

Procedure for enrolling a subject and allocating the treatment (allocation concealment procedures)

Methods used to generate the sequence in which subjects will be randomised (sequence generation)

Masking / blinding

Open (masking not used)

Who is / are masked / blinded?

Intervention assignment

Parallel

Other design features

Phase

Not Applicable

Type of endpoint/s

Safety

Statistical methods / analysis

The primary outcome for this study is medication harm rates across all eligible patient admissions. Harm rates will also be calculated for the AIME-FRAIL risk groups (i.e. low vs high risk as per AIME-FRAIL model) in the intervention ward. Data will be calculated using total occupied bed numbers within each ward and for each risk category (high vs low) as the denominator. Rates for medication harm will be calculated retrospectively each month for each ward. These rates will be transformed using natural logarithms if the distribution of measures within intervention groups is markedly skewed and analysed using a linear regression model with an indicator variable for intervention group and adjusted for key patient factors (e.g. age, gender, number of medications and Charlson Comorbidity Index). Results will be expressed as rates per 1000 occupied bed days.

Recruitment

Recruitment status

Not yet recruiting

Date of first participant enrolment

Anticipated

1/04/2022

Actual

Date of last participant enrolment

Anticipated

29/07/2022

Actual

Date of last data collection

Anticipated

5/08/2022

Actual

Sample size

Target

324

Accrual to date

Final

Recruitment in Australia

Recruitment state(s)

QLD

Recruitment hospital [1]

Princess Alexandra Hospital - Woolloongabba

Recruitment postcode(s) [1]

4102 - Woolloongabba

Funding & Sponsors

Funding source category [1]

Charities/Societies/Foundations

Name [1]

Princess Alexandra Research Foundation Grant

Address [1]

Princess Alexandra Research Foundation - PAH Hospital, 199 Ipswich Road, Woolloongabba 4102, QLD, Brisbane, Australia

Country [1]

Australia

Primary sponsor type

Other Collaborative groups

Name

AIME-FRAIL Research Group

Address

Princess Alexandra Research Foundation - PAH Hospital, 199 Ipswich Road, Woolloongabba 4102, QLD, Brisbane, Australia

Country

Australia

Secondary sponsor category [1]

None

Name [1]

Address [1]

Country [1]

Ethics approval

Ethics application status

Approved

Ethics committee name [1]

Metro South Human Research Ethic Committee

Ethics committee address [1]

199 Ipswich Road, Woolloongabba, 4102, QLD, Australia

Ethics committee country [1]

Australia

Date submitted for ethics approval [1]

20/10/2021

Approval date [1]

28/02/2022

Ethics approval number [1]

HREC/2022/QMS/80654

Summary

Brief summary

Early identification of patients at high risk of medication harm can allow for timely and targeted patient review and proactive monitoring to mitigate harm. An emerging approach involves predictive risk models, which use statistical algorithms to quantify the probability that an individual patient will experience medication harm, and facilitate timely, patient-specific interventions (e.g. therapeutic drug monitoring and deprescribing). A number of risk prediction models for medication harm, in various health settings, have been reported. A locally developed risk model, the Adverse Inpatient Medication Event Model (AIME), was developed and internally validated at the Princess Alexandra Hospital (PAH) using general medical and geriatric patient data from July to December 2017, which has been published in the British Journal of Clinical Pharmacology (Falconer, N, et al. Development and validation of the Adverse Inpatient Medication Event model (AIME). Br J Clin Pharmacol. 2021; 87: 1512– 1524.) where the AIME model evaluated and modified (using frailty as a variable), in a multisite retrospective study conducted using data from Princess Alexandra Hospital (PAH) and Logan Hospital (LGH).  Frailty - which can also increase risk of medication harm and poor patient outcomes was also added to this model. In the new study incorporating frailty we modified the AIME model and tested its predictive performance in 3948 patients with median (IQR) age 67 (28) years. The mean (SD) HFRS was 6.2 (+/-5.9). When the HFRS was divided into three groups, 51% of patients were in the low-risk, 40% in intermediate-risk and 9% in high-risk group. A total of 187 (4.7%) patients experienced one or more medication harm events, including bleeding and severe hypoglycaemia. As a measure of predictive accuracy, the area under the curve (AUC) of the AIME-FRAIL was 0.79 (95% CI: 0.76-0.83), an improvement on the AUC of 0.70 of the original AIME model. Given this improved performance, we plan to conduct a pragmatic impact evaluation of the AIME-FRAIL model in the subacute medical setting (Geriatric and Rehabilitation Unit at PAH). We will use the model to estimate patient risk of medication harm (expressed as a risk score) and pharmacists will then use this score to prioritise their patients for timely and comprehensive medication review, and undertake any other necessary actions to avoid medication harm.

Trial website

None

Trial related presentations / publications

Public notes

Contacts

Principal investigator

Name

A/Prof Michael Barras

Address

Pharmacy Department, Princess Alexandra Hospital, 199 Ipswich Road, Woolloongabba, 4102, QLD, Brisbane, Australia

Country

Australia

Phone

+61 422667911

Fax

michael.barras@health.qld.gov.au

Contact person for public queries

Name

Nazanin Falconer

Address

Pharmacy Department, Princess Alexandra Hospital, 199 Ipswich Road, Woolloongabba, 4102, QLD, Brisbane, Australia

Country

Australia

Phone

+61 412342551

Fax

n.ghahremanfalconer@uq.edu.au

Contact person for scientific queries

Name

Nazanin Falconer

Address

Pharmacy Department, Princess Alexandra Hospital, 199 Ipswich Road, Woolloongabba, 4102, QLD, Brisbane, Australia

Country

Australia

Phone

+61 412342551

Fax

n.ghahremanfalconer@uq.edu.au

Data sharing statement

Will individual participant data (IPD) for this trial be available (including data dictionaries)?

Yes

What data in particular will be shared?

Deidentified patient data of published results will be shared but only upon reasonable request and with ethics approval

When will data be available (start and end dates)?

After the publication of findings with an approximate start date for IPD 2025 until 2035

Available to whom?

Other researchers upon reasonable request and with ethical approval only

Available for what types of analyses?

Medication harm related research

How or where can data be obtained?

Arrangements will be made upon discussion with the research team - please contact the site coordinator (Dr Nazanin Falconer n.ghahremanfalconer@uq.edu.au)

What supporting documents are/will be available?

Doc. No.	Type	Citation	Link	Email	Other Details	Attachment
15294	Study protocol			n.ghahremanfalconer@uq.edu.au

Results publications and other study-related documents

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No additional documents have been identified.

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