None listed
Conditions
Brief summary
Frailty is common in older hospitalised patients and leads to adverse consequences like increased risk of death, prolonged length of hospital stay and frequent unplanned hospital readmissions but may be missed by the clinicians in the absence of proper screening. Currently, all hospitalised patients are not routinely screened for frailty. The currently available frailty tools need a face to face interaction with the patient and are time consuming. Recently a new tool called the Hospital Frailty Risk Score (HFRS) has been developed that can detect frailty taking into account only the administrative data of the patients and this tool does not need a face to face interaction. However, this tool needs to be tested for accuracy in different hospital settings and needs comparison with already established frailty tools before it can be incorporated into routine clinical practice. If this tool is found to be accurate then it may help in early detection of frail patients and thus an early intervention can be started to target these patients. The purpose of this study is to compare and test the new tool against an existing frailty tool to diagnose frail hospitalised patients. This research is not funded.
Interventions
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 fr
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.
Sponsors
Dr Yogesh Sharma
Eligibility
Sex/Gender
All
Age
60 Years to No maximum
Healthy volunteers
No
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.
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.
Outcome results
None listed