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Trial registered on ANZCTR


Registration number
ACTRN12619000331134
Ethics application status
Approved
Date submitted
25/02/2019
Date registered
4/03/2019
Date last updated
15/09/2021
Date data sharing statement initially provided
4/03/2019
Type of registration
Prospectively registered

Titles & IDs
Public title
Validation of the Hospital Frailty Risk Score in predicting clinical outcomes in older hospitalised patients in Australian health care settings.
Scientific title
Validation of the Hospital Frailty Risk Score in predicting clinical outcomes in older hospitalised patients in Australian health care settings.
Secondary ID [1] 297525 0
Nil known.
Universal Trial Number (UTN)
U1111-1229-2136
Trial acronym
Linked study record

Health condition
Health condition(s) or problem(s) studied:
Frailty 311735 0
Condition category
Condition code
Public Health 310363 310363 0 0
Health service research

Intervention/exposure
Study type
Observational
Patient registry
False
Target follow-up duration
Target follow-up type
Description of intervention(s) / exposure
Frailty is a geriatric syndrome that is characterised by reduced homoeostatic reserves which increases susceptibility to stressors. It leads to adverse clinical outcomes in older persons including an increased risk of falls, hospitalisation, disability and death. A number of tools are available to diagnose frail patients; however, a major limitation of the existing tools is that they require face-to-face assessment by trained personnel and some tools even require special equipment to identify frailty. Frail patients are thus not readily apparent to health planners who may be interested in implementing quality improvement measures to improve their health outcomes. This issue can be mitigated by the development of tools based on routinely collected hospital administrative data. One such tool the Hospital Frailty Risk Score (HFRS) has recently been validated within the UK National Health Service to detect frail patients. Increasing HFRS scores have been found to be associated with significantly increased risks of prolonged hospital length of stay (LOS), 30-day readmissions and 30-day mortality. This tool can be used to screen frail patients in a low-cost systematic way, however, needs validation against established tools like the Edmonton Frail Scale (EFS) and in different healthcare settings.

Limited studies have validated the HFRS in other healthcare settings and no study has compared this tool against an established frailty scale like the EFS. This research project will be aimed to determine whether the HFRS is associated with health outcomes in older medical inpatients in the Australian healthcare setting. In addition, its performance against the EFS will be validated. If validated, then the HFRS could be considered to detect frail patients at the time of hospital admission. This can facilitate quick triage of frail patients for an early targeted intervention and this may help in reducing adverse health outcomes.

This study involves retrospective collection of administrative data in medical inpatients over a period of 10 years (between 1 January 2008 to 31 December 2018)to determine the HFRS. This includes determination of the international disease classification codes, length of hospital stay, readmissions within 30-days and mortality within 30 days of discharge from hospital. In addition, 260 patients will be prospectively recruited and EFS questionnaire will be administered to diagnose frailty. The EFS will be used to validate the HFRS to determine whether it can confidently detect frailty and predict clinical outcomes in hospitalised patients within the Australian healthcare setting.
Intervention code [1] 313763 0
Not applicable
Comparator / control treatment
No control group.
Control group
Uncontrolled

Outcomes
Primary outcome [1] 319233 0
Length of stay. This will only be assessed in the historical cohort via data-linkage to medical records.
Timepoint [1] 319233 0
Baseline
Primary outcome [2] 319234 0
Readmissions within 30 days of discharge. This will only be assessed in the historical cohort via data-linkage to medical records.
Timepoint [2] 319234 0
Baseline.
Primary outcome [3] 319235 0
Mortality within 30 days of discharge. This will only be assessed in the historical cohort via data-linkage to medical records.
Timepoint [3] 319235 0
Baseline.
Secondary outcome [1] 367390 0
Frailty as assessed by the HFRS.
Timepoint [1] 367390 0
Baseline.
Secondary outcome [2] 367565 0
Frailty as assessed by the EFS.
Timepoint [2] 367565 0
Baseline.
Secondary outcome [3] 367737 0
'ICD-10' as assessed in the historical cohort via data-linkage to medical records. This will be used to calculate the HFRS.
Timepoint [3] 367737 0
Baseline.

Eligibility
Key inclusion criteria
Medical inpatients >60 years of age. All patients >60 years of age who are referred from the Emergency Department for a medical admission will be considered for participation in this study.
Minimum age
60 Years
Maximum age
No limit
Sex
Both males and females
Can healthy volunteers participate?
No
Key exclusion criteria
The exclusion criteria are lack of a valid consent and terminal illness. In case patients are identified to have a cognitive impairment then a written informed consent will be obtained from their legal guardians for the participation in this research. All possible efforts will also be made to explain to the participant what the research is about and what participation is involved. If during the administration of the questionnaire the researcher notices any discomfort or distress among the participants then they will be withdrawn from the research. Any reluctance or refusal to participate in the research project will be respected. The degree of cognitive impairment will be determined form the participants' treating medical team and the health records.

Study design
Purpose
Screening
Duration
Longitudinal
Selection
Defined population
Timing
Both
Statistical methods / analysis
The hypothesis is that HFRS is a valid tool in detecting frailty and predicting clinical outcomes in older medical inpatients and will be non-inferior to the EFS within the Australian healthcare setting.. We will determine the sensitivity, specificity and use predictive values in addition to construction of the Receiver Operating Curve (ROC) to compare the HFRS against the EFS. Based on a previous study which found that frail patients had a 48% higher risk of emergency readmission, a retrospective sample of 973 patients (alpha=0.05, power 0.8) will be needed to determine whether HFRS can predict clinical outcomes including length of stay, readmissions and mortality in older medical inpatients. For validation of HFRS against EFS, the sample size was calculated based on a previous validation study, which found that approximately 20% (95% CI 15 - 25) older hospitalised patients are frail, using a precision level of 5% a sample of 246 was calculated and accounting for 5% missing data, 260 patients will be sufficient for this study. The sample size for this study was calculated using the sampsize and STATA (vs 15 s) software.

This study will involve a retrospective collection of data by accessing the hospital computer system and enlisting all medical admission >60 years who were admitted to Flinders Medical Centre between 01 January 2008 and 31 December 2018. The HFRS will be calculated from the International Classification of Disease, 10th revision (ICD) codes listed in each patient’s index admission. The ICD 10 codes for all diagnoses associated with the index admission will be used.

EFS will be determined on 260 patients who are prospectively recruited after being referred for a medical admission from the Emergency Department. A research team member will obtain written informed consent and in case of cognitive impairment consent will be obtained from the patients’ legal guardian, prior to the use of EFS. In addition, nutritional screening will be conducted by the use of Malnutrition Universal screening tool (MUST) and quality of life will be assessed by use of the EuroQol (EQ-5D-5L) questionnaire. The EQ-5D-5L is a simple instrument that provides a composite index score representing the preference for a given health state and it also includes a visual analogue scale ranging from 0 to 100 with higher values indicative of a better quality of life. This questionnaire will be administered by a research team member.

We will use multiple regression model to adjust for confounders like age and Charlson index and robust statistical procedure such as multiple imputation will be used to handle any missing data. The information gathered will be entered into an excel data sheet and STATA statistical software will be used to analyse data.

For retrospective collection of data all medical inpatients will be included and for the prospective part of the study all medical patients will be given an equal opportunity to participate in this research and convenience sampling will be used.

This research does not involve follow-up of patients.

Recruitment
Recruitment status
Completed
Date of first participant enrolment
Anticipated
Actual
Date of last participant enrolment
Anticipated
Actual
Date of last data collection
Anticipated
Actual
Sample size
Target
Accrual to date
Final
Recruitment in Australia
Recruitment state(s)
SA
Recruitment hospital [1] 13256 0
Flinders Medical Centre - Bedford Park
Recruitment postcode(s) [1] 25816 0
5042 - Bedford Park

Funding & Sponsors
Funding source category [1] 302085 0
Self funded/Unfunded
Name [1] 302085 0
Country [1] 302085 0
Primary sponsor type
Individual
Name
Dr Yogesh Sharma
Address
Department of General Medicine
Flinders Medical Centre
Flinders Drive
Bedford Park 5042
South Australia
Country
Australia
Secondary sponsor category [1] 301902 0
Individual
Name [1] 301902 0
Professor Campbell Thompson
Address [1] 301902 0
Department of General Medicine
Royal Adelaide Hospital
Port Road
Adelaide 5000
South Australia
Country [1] 301902 0
Australia
Other collaborator category [1] 280574 0
Individual
Name [1] 280574 0
Dr Emelie Ross
Address [1] 280574 0
Department of General Medicine
Flinders Medical Centre
Flinders Drive
Bedford Park 5042
South Australia
Country [1] 280574 0
Australia
Other collaborator category [2] 280575 0
Individual
Name [2] 280575 0
Dr Peter Avina
Address [2] 280575 0
Intensive & Critical Care Unit
Flinders Medical Centre
Flinders Drive
Bedford Park 5042
South Australia
Country [2] 280575 0
Australia

Ethics approval
Ethics application status
Approved
Ethics committee name [1] 302764 0
Southern Adelaide Clinical Human Research Ethics Committee (SAC HREC)
Ethics committee address [1] 302764 0
Ethics committee country [1] 302764 0
Australia
Date submitted for ethics approval [1] 302764 0
24/12/2018
Approval date [1] 302764 0
21/03/2019
Ethics approval number [1] 302764 0

Summary
Brief summary
Trial website
Trial related presentations / publications
Public notes

Contacts
Principal investigator
Name 91318 0
Dr Yogesh Sharma
Address 91318 0
Department of General Medicine
Flinders Medical Centre
Flinders Drive
Bedford Park 5042
South Australia
Country 91318 0
Australia
Phone 91318 0
+61 (08) 8204 5511
Fax 91318 0
Email 91318 0
Contact person for public queries
Name 91319 0
Yogesh Sharma
Address 91319 0
Department of General Medicine
Flinders Medical Centre
Flinders Drive
Bedford Park 5042
South Australia
Country 91319 0
Australia
Phone 91319 0
+61 (08) 8204 5511
Fax 91319 0
Email 91319 0
Contact person for scientific queries
Name 91320 0
Yogesh Sharma
Address 91320 0
Department of General Medicine
Flinders Medical Centre
Flinders Drive
Bedford Park 5042
South Australia
Country 91320 0
Australia
Phone 91320 0
+61 (08) 8204 5511
Fax 91320 0
Email 91320 0

Data sharing statement
Will individual participant data (IPD) for this trial be available (including data dictionaries)?
No
No/undecided IPD sharing reason/comment
The research results will be available on the Southern Adelaide Local Health Network (which administers Flinders Medical Centre) website publicly and will also be available to the participants personally if requested. The results of this study will be disseminated through grand rounds, conferences and journal publications. The health information will be converted to codes to prevent individual identification. The data will be stored in a password protected computer in locked General Medicine office of Flinders Medical Centre. Only the researchers will have access to this data and the data will not be shared with a third party. As all data collected will be coded to prevent identification of the participants so individual participants cannot be identified in publications arising from this research.


What supporting documents are/will be available?

No Supporting Document Provided



Results publications and other study-related documents

Documents added manually
No documents have been uploaded by study researchers.

Documents added automatically
No additional documents have been identified.