Protocol for a randomised controlled trial of an outreach support program for family carers of older people discharged from hospital
Toye et al. BMC Geriatrics
Protocol for a randomised controlled trial of an outreach support program for family carers of older people discharged from hospital
Christine Toye 0 1
Rachael Moorin 2 6 7
Susan Slatyer 0 1
Samar M. Aoun 1
Richard Parsons 5
Desley Hegney 4 9
Sean Maher 8
Keith D. Hill 3
0 Centre for Nursing Research, Sir Charles Gairdner Hospital , Perth, WA 6009 , Australia
1 School of Nursing , Midwifery and Paramedicine , Faculty of Health Sciences, Curtin University , GPO Box U1987, Perth, WA 6845 , Australia
2 School of Public Health, Curtin University , Perth, WA 6845 , Australia
3 School of Physiotherapy and Exercise Science, Curtin University , Perth, WA 6845 , Australia
4 School of Nursing and Midwifery, The University of Southern Queensland , Toowoomba, QLD 4350 , Australia
5 School of Pharmacy, Curtin University , Perth, WA 6845 , Australia
6 Department of Research, Silver Chain Group , Osborne Park, Perth, WA 6017 , Australia
7 School of Population Health, The University of Western Australia , Perth, WA 6009 , Australia
8 Department of Rehabilitation and Aged Care, Sir Charles Gairdner Hospital , Perth, WA 6009 , Australia
9 School of Nursing, The University of Adelaide , Adelaide, South Australia 5005 , Australia
Background: Presentations to hospital of older people receiving family care at home incur substantial costs for patients, families, and the health care system, yet there can be positive carer outcomes when systematically assessing/ addressing their support needs, and reductions in older people's returns to hospital attributed to appropriate discharge planning. This study will trial the Further Enabling Care at Home program, a 2-week telephone outreach initiative for family carers of older people returning home from hospital. Hypotheses are that the program will (a) better prepare families to sustain their caregiving role and (b) reduce patients' re-presentations/readmissions to hospital, and/or their length of stay; also that reduced health system costs attributable to the program will outweigh costs of its implementation. Methods/Design: In this randomised controlled trial, family carers of older patients aged 70+ discharged from a Medical Assessment Unit in a Western Australian tertiary hospital, plus the patients themselves, will be recruited at discharge (N = 180 dyads). Carers will be randomly assigned (block allocation, assessors blinded) to receive usual care (control) or the new program (intervention). The primary outcome is the carer's self-reported preparedness for caregiving (Preparedness for Caregiving Scale administered within 4 days of discharge, 2-3 weeks post-discharge, 6 weeks post-discharge). To detect a clinically meaningful change of two points with 80 % power, 126 carers need to complete the study. Patients' returns to hospital and subsequent length of stay will be ascertained for a minimum of 3 months after the index admission. Regression analyses will be used to determine differences in carer and patient outcomes over time associated with the group (intervention or control). Data will be analysed using an Intention to Treat approach. A qualitative exploration will examine patients' and their family carers' experiences of the new program (interviews) and explore the hospital staff's perceptions (focus groups). Process evaluation will identify barriers to, and facilitators of, program implementation. A comprehensive economic evaluation will determine cost consequences. Discussion: This study investigates a novel approach to identifying and addressing family carers' needs following discharge from hospital of the older person receiving care. If successful, the program has potential to be incorporated into routine post-discharge support. Trial registration: Australian and New Zealand Clinical Trial Registry: ACTRN12614001174673.
This study is being conducted in metropolitan Western
Australia (WA), where increasing numbers of older
people are experiencing multiple chronic health
conditions, disability, and high level health care utilization .
This situation parallels that in other western countries
in which life expectancy is increasing  and, together
with predictions of health workforce shortages ,
highlights the need to increase support for family-based
home care within the community . There were close
to 350,000 informal primary carers of older people in
Australia in 2009, saving an estimated $40 billion in
service provision costs each year  but poor health has
long been a recognised family caregiver outcome, with
support needed to help carers to sustain their caregiving
For older people receiving care and in poor health,
readmissions to hospital are potentially distressing and
costly, yet sometimes avoidable with high quality
discharge planning . A key component of effective
discharge planning is to closely involve the family carers
. However, in a recent study investigating returns to
hospital after discharge from a short stay (<72 h)
Medical Assessment Unit (MAU), communication issues
at the time of discharge presented a significant challenge
. There was limited opportunity for the staff to liaise
with family carers in the time available prior to
discharge. In particular, there was insufficient time
allocated to assess carers’ needs and communicate plans to
them for addressing likely future health crises for
In parallel work in community palliative care in the
United Kingdom, a need for a systematic and effective
carer needs assessment process was identified. The
Carer Support Needs Assessment Tool (CSNAT) was
developed following extensive reviews of the literature
[10–12], and from interviews with bereaved carers .
The tool was subsequently validated using a sample of
225 current carers . The CSNAT is a brief tool, yet
covers all identified support need areas. Each item
represents a core carer support domain in home care. The
items fall into two sets: those that enable the carer to
care for the patient at home and those that enable
direct support for the carer . The CSNAT has
recently been used in a Western Australian study in
palliative home care; it was reported to be practical and
useful; to prompt carers to consider their own needs
rather than just those of the patient; to validate,
reassure, and empower carers; and to help carers access
the support that they need .
The aim of this study is to determine how implementing
an evidence-based, systematic, and targeted support
program for family carers of older patients - immediately
after the patient’s discharge from a metropolitan Western
Australian hospital’s MAU - impacts upon these carers;
the patients for whom they provide care; and costs to WA
Health, the local health care system. The program being
evaluated is termed the Further Enabling Care at Home
(FECH) program, and it uses the CSNAT to identify and
prioritise family carers’ support needs that are
subsequently addressed. The study has three hypotheses:
H1: That the enhanced support of family carers
facilitated by the FECH program will prepare
families to sustain their caregiving role better
than usual care.
H2: That, because family carer roles are better
supported, implementation of this program
will reduce (a) patients’ re-presentations and
readmissions to hospital within 3 months of
discharge, and (b) length of hospital stay when
readmissions do occur.
H3: That reduced costs to WA Health will outweigh
costs of implementing the program.
Study objectives are to:
1. Compare family carer preparedness to care between those included in the FECH program and those receiving usual care.
2. Compare patient outcomes from the FECH
program versus those from usual care in terms of
re-presentations to Emergency Departments (EDs),
readmissions to hospital within the months
(at least 3) following the index separation
date – also Length of Stay (LoS) if readmission
3. Document costs of a suitably qualified nurse (FECH
nurse) implementing the program to inform the
economic evaluation and determine a sustainable
full time FECH nurse ‘caseload’.
4. Compare costs of re-presentations to EDs, hospital readmissions, and LoS between the intervention group (FECH program) and the control group (usual care).
5. Estimate overall cost effectiveness for the local health system from FECH program implementation during the study period.
6. Explore and describe family carers’ perceptions of
how the FECH program impacts upon caregiving
sustainability plus any other outcomes for them; also
how it might be refined to (a) minimise any negative
outcomes, (b) enhance those that are positive, and
(c) (further) enhance caregiving sustainability.
7. Explore and describe patients’ perceptions of how
the FECH program impacts upon them and how it
might be refined to ensure the best possible
outcomes (for them).
8. Use process evaluation and obtain perspectives of
MAU health care professionals to determine how
the FECH program’s implementation might
9. Refine the program from study recommendations
and develop a plan to embed it into practice in the
study setting and other similar health services.
10.Develop a plan for testing the FECH program in
other health settings – should it be shown to have
cost benefits and no negative patient/carer outcomes
when implemented in the MAU.
This is a mixed methods study addressing objectives
and testing hypotheses in a single blind Randomised
Controlled Trial (RCT) (concealed allocation), adhering
to CONSORT guidelines for transparent reporting ,
during which Qualitative Evaluation and FECH
program Process Evaluation will also be undertaken. The
study will also be supported by an expert reference
group. The RCT will compare outcomes between the
control condition (usual care) and the experimental
condition (usual care plus family carer inclusion on the
new FECH program). Approval has been received from
the Sir Charles Gairdner Group Human Research
Ethics Committee (HREC) (2014–133), the Department
of Health WA HREC (2014/78), and from the Curtin
University HREC (HR14/2015).
Study setting and participants
The MAU is a 36-bed unit providing intensive
assessment and treatment for patients with acute medical
conditions, most of whom are over 70 years of age.
MAUs are widely implemented in the UK, Australia
and New Zealand in response to the need to increase
patient through-put  and sustained health system
pressures suggest that their use will continue to
expand. Care is provided by physician-led
multidisciplinary teams for up to 72 h, after which patients are
discharged or transferred to inpatient units for
ongoing management. A key component of the MAU
model is that ongoing management for discharged
patients is provided through prompt general practitioner
Included participants will comprise dyads of older
people (aged 70+) discharged home from the MAU
during the recruitment period and their adult (aged 18+),
English speaking, family carers (one per patient). The
definition of a family carer is that used in a recent
Australian study investigating the care of frail older
people: “a family member or friend who provides unpaid
personal care, support and assistance” . Dyads
already recruited into the study will be excluded from
further recruitment upon any subsequent readmissions
to the MAU.
Experimental condition (inclusion in the FECH program)
Carer participants in the intervention group will
receive standard care plus the FECH program
implemented by the FECH nurse who will be appropriately
skilled and trained. Currently there is no nurse
involved in providing the FECH or any similar program
to patients or carers.
Contacts will be made by telephone, after discharge
(Fig. 1). The FECH Nurse will make initial contact
with the family carer within one week of the discharge
(Contact 1). This contact will include the FECH nurse
introducing him/herself, explaining the intervention,
and scheduling ‘Contact 2’. Contact 2 is likely to
comprise a series of brief telephone interviews, if this is
the arrangement that suits the family carer best,
within the subsequent few days to (a) determine and
respond to the extent to which the family carer
understands the copy of the discharge letter to the general
practitioner that has been provided to them; (b)
administer the CSNAT  to the family carer,
resulting in the carer’s self-identified and highest prioritised
support needs; and (c) initiate responses to the three
prioritised needs, helping ensure family carers’ linkage
Fig. 1 Data collection and intervention points (experimental condition, family participants)
and engagement with appropriate existing resources.
A few days after Contact 2 is finalised (within 14 days
of the discharge), the FECH nurse will check to
determine if access to support has been achieved as planned,
advising as appropriate (Contact 3). This contact will
include asking if the services have been sourced (eg, an
appointment made) and/or if the service has been
accessed. These three contact points will be
coordinated with the three data collection time points (T1,
T2, and T3) also shown in Fig. 1.
Control condition (usual care)
Standard discharge ‘care’ includes the provision of a
letter from the MAU’s physician to the patient’s
general practitioner, with a copy provided to the patient.
Medications are provided/organised by the MAU
pharmacist. The MAU information booklet provides
information about post-discharge support options and
is intended to be taken home. Carers regarded as ‘at
particular risk’ by the social work team receive social
work assessment and links to services. Services put in
place for patients may include a variety of care
packages or programs. Information packs from Carers
Australia are made available in the hospital rooms.
Any one or more of these options considered by
treating ward staff to be relevant to the patient and their
carer will be provided as usual care.
Carer outcome and data collection
Primary outcome variable
The primary outcome is preparedness for caregiving, to
be measured with the Preparedness for Caregiving Scale
(PCS) from the Family Care Inventory  (T1- T3).
This measure is an 8-item scale, with five response
options (0 = not at all prepared, 4 = very well prepared) and
is designed for use with carers of older people receiving
homecare or experiencing care transitions. Construct
validity has been established in older people, and the
measure has been shown to be reliable (Cronbach’s alpha
coefficients: 0.88-0.93) . Testing in patients with a
life threatening illness confirmed satisfactory internal
consistency reliability as well as unidimensionality .
Potentially confounding variables
Data on potentially confounding variables will be
collected to help inform interpretation of results. Carer
rated patient Symptom Assessment Scale scores 
and carer rated scores evaluating dependence of the
patient in ten activities (Barthel Activities of Daily Living
Index)  will be collected (T1-T3). Robust
psychometric properties have been documented for these tools.
Carer resilience will be measured at T1 using the
10item Connor-Davidson Resilience Scale .
Secondary outcome variables
Based upon recent findings using the CSNAT tool
, caregiver strain will also be measured at each
time point using the 25-item Family Appraisal of
Caregiving Questionnaire . Carers’ ratings of their
own health will also be collected (T1-T3) using the
SF12 Version 2, a tool exhibiting robust psychometric
properties with older people ; this tool has been
used in large scale surveys such as those with veterans
in the United States .
A Research Officer (RO1) will develop a schedule for
collecting data from all participating family carers (both
groups) by telephone, at the time of recruitment to the
study. At baseline assessment (T1), RO1 will also collect
demographic details of the patient and the carer from
the carer, including the carer’s familial relationship with
the patient, age and gender (carer and patient), highest
education level, occupation, usual place of residence,
country of birth, years in Australia, support provided for
the patient, contact with the patient, length of time
caring for the patient, education received to help in the
caring role, location of care, whether currently living
with patient (and if so, whether in patient’s or carer’s
home), any care provided by others, and known current
medical conditions (patient and carer). Brief, robust
measures to minimise questionnaire burden will then be
administered (each contact is estimated to last
approximately 30 min). Questionnaire administration across
the three assessments (T1, T2, and T3) is summarised
in Table 1.
Patient outcomes and data collection
Quantitative patient outcome data will address
Western Australian health care system utilisation and will
be obtained through linked administrative health
data provided via the WA Data Linkage System
(WADLS) . These Data Linkage Unit (DLU) data
will capture reason for service and mode of
transport plus: date of service, symptom/presenting
problem, and triage code (ED presentation); admission
and separation dates, primary diagnosis code,
codiagnosis code, and diagnosis related group
(hospitalisation data). In addition, to account for time at
risk, and to capture deaths resulting from acute
events during the study follow-up period, date and
cause of death will be collected.
The data retrieved from data linkage will cover the
time period from the date of the index separation of the
patient whose carer is the first to be recruited to the
study until 3 months after the index separation of the
patient whose carer is the last to be recruited. Since
Connor-Davidson Resilience Scale 
Family Appraisal of Caregiving
Preparedness for Caregiving Scale 
Preparedness for Caregiving Scale 
Symptom Assessment Scale  (patient) Symptom Assessment Scale  (patient)
Preparedness for Caregiving Scale 
Symptom Assessment Scale  (patient)
Barthel Activities of Daily Living Index  (patient) Barthel Activities of Daily Living Index  (patient)
Family Appraisal of Caregiving Questionnaire 
Family Appraisal of Caregiving Questionnaire 
Table 1 Planned questionnaire administration at each time point
recruitment is planned to last approximately 6 months,
this time period will cover approximately 9 months.
The primary outcome is the total score on the
Preparedness for Caregiving Scale . An improvement
of two points in the total score is regarded as clinically
relevant, given that this would mean a change such as
progressing to ‘very well prepared’ from ‘well
prepared’ in 25 % of items. To detect a change of this
magnitude with 80 % power (assuming that the
standard deviation of the change in mean score is
approximately 0.5, as in previous work) [19, 29] a sample size
of 63 per group will be required. Based upon previous
studies by the research team, attrition of
approximately 30 % is expected so a sample of 180 carers in
total will be recruited.
Recruitment and randomisation
Figure 2 shows the proposed study flow. There were
more than eight MAU discharges of patients aged 70+
each day in 2013, approximately half returning home
(estimated 120 per month). Therefore, recruitment of
180 participants is considered achievable within the
6 month recruitment period (30 per month).
Although the primary study outcome relates to carers
of patients discharged from the MAU, other outcomes
relate to the former patients themselves so carer/patient
dyads will be recruited. Whenever a patient aged 70 years
or older is admitted to the MAU during the recruitment
period, family carers - and, when appropriate, patients
will be provided with information about the project and
asked to provide written consent to participate in the
study by RO1. However, many patients are likely to be
too unwell to be approached with information about the
study during their hospitalisation and are likely to
experience ongoing poor health that may also fluctuate
. Others will lack (cognitive) capacity to consider
consenting. In these instances, data about patients’ use
of health care services will be sought via a waiver of
consent. An opt out form will be provided for such
patients in case there is a later opportunity – if and when
the patient’s health has improved – for them to withhold
consent for inclusion of their data in the study, should
this be their wish.
To facilitate the assignment to group (control or
intervention) of participants, a list of treatment allocations
will be prepared before the study commences; it will
contain a study number (whole number, starting from
one), and a code to indicate the group (intervention or
control). The list of codes will be obtained using a
sequence of computer-generated random numbers, and
organised so that recruitment to the two study arms
occurs at an approximately equal rate (using a permuted
random block strategy). Allocation of participants to
their treatment group will occur as follows: as each new
dyad is recruited to the study, the next study number
will be allocated to them (next in sequence on the list),
and the treatment allocation for that study number will
be read from the list.
Qualitative feedback from patients and family carers
An ‘exit’ telephone interview will be conducted with an
estimated 30 carers in the intervention group and, when
possible, the older people receiving care from them
(estimated 20). These participants will be purposively
sampled on the basis of questionnaire data to cover a wide
variety of carer profiles (eg, carer sex, age [older
versus younger carers], duration of caregiving [new carers
versus those who are more experienced], relationship
to patient [husbands, wives, sons, daughters, others],
and location of care). The sample will be extended if
issues need further exploration and until data
saturation is reached.
Interviews will occur within two weeks following
administration of the final measures, to: investigate how
the FECH model affected the participants, assess the
support provided, identify factors influencing feasibility/
usefulness, and assess how the FECH model could be
improved. Written informed consent for participation
Fig. 2 Modified consort diagram to illustrate trial study flow and participant numbers
will be obtained separately for this step and will involve
mailing the information sheet and consent forms (for
the carer and for the patient); then following up with a
phone call during which questions can be answered,
before requesting the return of the completed consent
form in a prepaid study envelope. It is anticipated that
the interviews will take approximately 30 min. A second
telephone call will be offered if the interview takes
longer than 30 min and the carer wishes to provide further
Qualitative feedback from the hospital staff
A focus group interview will be convened with the
MAU staff as soon as carer recruitment for the trial
has been completed. The staff working on the unit
during the trial will be invited to take part and will
be asked to comment on any impact from the FECH
program on the Unit and to suggest: program
refinements that would minimise negative outcomes and
maximise those that are positive, how the program
could be integrated into practice, and how its
sustainability could be addressed. The staff members
will be invited to take part by mail, and will also be
sent an information sheet and consent form.
Evaluation of FECH program processes will involve the
FECH nurse documenting, during the trial: (a) adherence
to, or deviation from, planned FECH processes; (b)
information provided to carers and the resources to which they
were referred; (c) the extent to which carers engaged with
resources; (d) the contextual factors that were barriers to,
or facilitators of, resource and service access and
engagement; and (e) costs issues – primarily time taken to
implement processes. This documentation will be achieved
using an electronic database developed at the same time
as the process manual and completed by the FECH nurse
as the process is implemented.
Group assignment will be concealed from RO1. When
RO1 conducts the T1-T3 data collection telephone
questionnaire administration, he or she will commence
the conversation with a request to the participant (the
carer) not to mention any phone calls from other study
personnel. This reminder will not always be sufficient
to prevent disclosure, and instances when it occurs will
be documented to inform study reports. In a previous
study, quantification of any ‘unblinding’ involved asking
the hospital staff to identify to which group they
thought patient participants had been assigned . In
this study, a similar question will be asked of the
research staff collecting outcome data. The person
conducting the qualitative interviews will be a Research
Officer employed for this purpose alone (RO2), so that
blinding to group allocation will be maintained for
RO1. Investigator blinding will also be maintained by
allocating responsibility for this (qualitative)
component of the study to one of the research team, an
experienced qualitative researcher who will not be involved
in quantitative data collection or analyses.
Standard descriptive statistics (means, standard
deviations, medians for continuous variables and frequencies
and percentages for variables measured on a categorical
scale) will be used to summarise the characteristics of
participants in the study (primarily demographic data,
but also including some data relating to the care
recipient to describe the caregiving situation). Chi-square tests
and t-tests will be used to compare the treatment groups
(intervention versus control) on the basis of these
variables. It is anticipated that there will be no significant
differences between groups in terms of demographic
characteristic or potentially confounding variables, which
will confirm that the randomisation process has allocated
participants evenly to each arm of the study.
Outcome analysis will be conducted using an Intention to
Treat approach. The change in the total Preparedness for
Caregiving Scale  score between T1 and T3 will be
calculated for each carer. An initial t-test will compare
changes between treatment groups. If changes in scores
are not normally distributed, a non-parametric method will
be used instead (Wilcoxon 2-sample test). In the
(unlikely) event that groups differ on the basis of baseline
variables, a regression model will be used instead of
the t-test, so that these potentially confounding
variables can be taken into account. A random effects
regression model will be used to examine changes in the
Preparedness for Caregiving Scale score over all three
data collection periods (instead of just baseline/end of
study). This model will be used so that correlations
between measurements made on the same participants
can be taken into account. Results of the model will
help show whether changes in scores happen soon
after recruitment, or later. The model can be extended
to adjust for other potentially confounding variables.
Patient outcomes will be compared between groups
using t-tests or regression models. For example, the
total length of hospital stay will be calculated and
compared between groups using a t-test (after
logtransformation of the data if indicated). Number of
readmissions to hospital or presentations to ED will be
compared using the same method. A regression model
will be used to take into account potentially
confounding variables (if relevant). The association between
change in preparedness and change in health care
utilisation will be evaluated using carer outcomes linked
to the administrative data.
Economic costs and associated analysis
Since a randomised controlled trial is being undertaken
to determine the efficacy of the new support program
for older patients’ carers, the economic evaluation
reflects a service substitution model without cost sharing
or transfer. Costs of the program will be evaluated
using prospective data collection for each patient/carer
dyad (cases and controls) and will include the costs
associated with the intervention and outcomes using a
Western Australian health system perspective.
Program costs in addition to those for usual care will
include those documented during the process evaluation,
in particular: (1) training of the FECH nurse to
implement the program; (2) the FECH nurse salary; (3) costs
associated with providing discharge information to
carers (costed on a case by case basis) – FECH nurse
time and web access (to identify service providers), any
costs for communication that is part of the intervention,
and stationery used. Costs associated with research
components/activities will be excluded since they would not
be incurred if the program was taken up. Outcome costs
associated with utilisation of health services during
follow up for patients (cases and controls) will include: (1)
cost of ED visits, (2) cost of additional in-patient
hospitalisation, and (3) cost of ambulance use.
In-patient costs will be calculated using Diagnostic
Related Group (DRG) based costings from the appropriate
cost report available from the Australian Government
Department of Health. Since Urgency Related Group
(URG) is not available directly from the ED data, cost of
ED attendances will be based on derivation of the closest
urgency related/disposition group using data obtained
from the Standard Emergency Record Information. The
derivation algorithm follows as closely as possible the
URG Grouper application developed by the Independent
Hospital Pricing Authority (IHPA) which uses Episode
End Status, Type of Visit, Triage, Sex, and Diagnosis Code.
Costing will then be undertaken using the price weight of
the URG and National Efficient Price provided in the
closest IHPA National Efficient Price Determination
report to the date of the episode .
Patient ambulance utilisation
Patient ambulance utilisation will be costed at $AUD898
per service. The use of ambulance services will be
obtained via the hospital mortality data system data (source
of referral transport) and ED (arrival type-transport
mode) data sets.
Costs and outcomes associated with delivering the
intervention will be compared using cost-consequence
analysis, a variant of cost-effectiveness analysis in which the
components of incremental costs and outcomes are
computed and listed without aggregating these results
into an overall ratio. Cost-consequence analysis provides
a more comprehensive presentation of information than
other types of economic evaluation and is appropriate
for complex interventions that generate outcomes that
cannot meaningfully be expressed using a single metric
such as those in this study. Consequences (outcome
measures as described above under patient and carer
data) and net costs (cost of intervention minus cost
savings produced by the intervention) will be tabulated
Table 2 Variables to be included in the sensitivity analysis
Rate of ED presentation ± ambulance (effectiveness)
Magnitude of change in carer preparedness (effectiveness)
Features of usual care (Cost)
FECH nurse model (Cost)
Number of patients requiring service (Cost)
Type of assistance required by carer (cost)
to allow analysis of incremental cost per net change for
A decision tree analysis using TreeAge Pro 2015 
will evaluate cost-consequence separately for each
outcome. Decision trees are widely used to illustrate the
conceptual model of a cost effectiveness analysis. The
tree begins with a decision node depicting treatment
options (intervention versus usual care) for study
participants. Each option becomes a main branch off the box,
which further divides into smaller branches at a ‘chance
node’ as certain pre-defined events (outcomes) occur.
Decision trees illustrate both the probability of each
outcome and the costs associated with the resultant
outcome. The likelihood of each consequence is expressed
as a probability of occurrence and cost calculated from
trial data. Thus it will be possible to calculate
expected cost and expected outcome of each option.
For a given option, the expected cost is the sum of
costs of each consequence weighted by the probability
of that consequence.
As with all research, this study will incorporate
assumptions, uncertainties, and variability in the data.
To evaluate the importance of the assumptions and
uncertainties, comprehensive sensitivity analyses
(deterministic and probabilistic) will be performed.
Sensitivity analyses strengthen economic evaluations by
indicating the stability of the reported outcome and
identifying which variables have the most influence on
it. This step will provide an estimation of likely
generalisability of the cost-consequence estimate outside
the trial. Examples of uncertainties and variables are
in Table 2. Where average costs are used, best and
worst case scenarios will be investigated for potential
impact on cost-consequence. Effectiveness variations
(eg, patient risk profiles) will be considered but most
model variations will be performed on cost variables.
All interviews will be audio-recorded and transcribed
verbatim. Analysis will be aided by the use of the NVivo
software program . Responses will be coded on a
Vary according to range in the trial
Vary according to range in the trial
Vary according to bed capacity.
Vary phone versus face to face
Vary gender, age, clinical profile
Vary based on type of staff included and resources provided
Vary according to qualifications, hours required, nurse/patient load.
question-by-question basis, codes will be collapsed into
themes across questions, and quotes from participants will
illustrate each theme. This qualitative analysis will be
undertaken independently by the investigator responsible
for overseeing qualitative evaluations and the
interviewer to ensure consideration of the non-verbal
context. These analysts will compare themes and
subthemes until agreement is reached.
Analysis for process evaluation
Findings from the process evaluation will be summarised
to support recommendations. In addition, a feasible
‘caseload’ for a full-time FECH nurse will be determined.
Increasing numbers of older people are experiencing
multiple chronic health conditions, disability, and high
level health care utilization . Strategies are needed
that minimise unnecessary hospital presentations and
admissions and also focus on reducing hospital ‘length
of stay’, while maintaining quality of care and outcomes
for older patients and their carers. Many older people
experiencing health challenges receive care from their
families , including when discharged home from
hospital. The success of these transitions home from
hospital by older people is dependent on a range of
factors including patient and carer factors, and health and
care system factors – the carer being a critical element.
Poor health is a recognised family caregiving outcome
and support has been shown to help carers better
manage and sustain their caregiving role .
This study investigates a novel approach to identifying
prioritised carers’ needs in the immediate weeks
postdischarge from hospital of the older person for whom
they are providing informal care - evaluating a program
aimed to support carers in this challenging time of
reacclimatisation to the home environment that has been
shown to be associated with high risk of hospital
readmission . Importantly, the model of care being
investigated in this study, if shown to be effective and
cost-effective, has potential to be incorporated relatively
easily into existing discharge and post discharge
followup activities. A recent systematic review found that
discharge planning helped minimise use of the hospital
setting but that involvement of the carer in the discharge
planning process was seldom clearly articulated . In
contrast, this study has a central focus on systematically
assessing and addressing carers’ needs.
The study also includes a comprehensive economic
evaluation of the intervention, with robust service use
data obtained via the comprehensive Western Australian
Data Linkage System such as hospitalisation, ED use,
and death and morbidity data. Results of this analysis
will inform health services of the cost effectiveness
associated with implementing the FECH program more
widely across the health system.
In summary, this randomised controlled trial with
embedded economic evaluation will determine carer,
patient, and health service outcomes associated with
introduction of a carer support program for carers of
older patients being discharged from an acute medical
unit in a tertiary hospital. The program may be
appropriate for incorporation into routine post-discharge
support if shown to be effective and if costs of
implementation are offset by resultant cost savings.
CT led protocol development, funding submission, and all approval
processes. RM supported protocol development, funding submission, and all
approval processes with special input into the planning of the economic
evaluation. SS supported protocol development, funding submission, and all
approval processes with special reference to tailoring study processes to the
hospital environment. SA supported protocol development, funding
submission, and all approval processes with special reference to carer
assessment and study design issues. KH supported protocol development,
funding submission, and all approval processes with special reference to
study population and design issues. RP supported protocol development,
funding submission, and all approval processes with special reference to
statistical issues. DH supported protocol development and funding
submission. SM supported protocol development with special reference to
medical issues for older patients within the hospital environment. All authors
read and approved the final manuscript.
This study has been funded by the Department of Health Western Australia,
SHRAC Research Translation Project, via a competitive, peer review process.
Financial and/or in-kind support is being provided by the School of Nursing,
Midwifery and Paramedicine and the School of Physiotherapy and Exercise
Science at Curtin University; also the Centre for Nursing Research at Sir
Charles Gairdner Hospital.
We wish to sincerely thank the Associate Investigators from Sir Charles
Gairdner Hospital, without whose input the study would not be feasible:
Ms. Sue Davis, Nurse Director, Corporate Nursing Research & Education;
Dr. Matthew Skinner, Consultant Physician, Medical Director, Medical
Assessment Unit; Ms. Dee Whitty, Clinical Nurse Specialist, Medical
Assessment Unit; Ms. Deborah Walsh, Social Worker, Medical Assessment
Unit; and Ms. Mary Bronson, Deputy Nurse Co Director, Medical Division.
Finally we wish to thank the authors of the carer support needs assessment
tool used as a critical component of our intervention - Dr. Gail Ewing and
Professor Gunn Grande.
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