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The scope of carer effects and their inclusion in decision-making: a UK-based Delphi study

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Background and objective Health and social care may affect unpaid (family) carers’ health and wellbeing in addition to patients’ lives. It is recommended that such impacts (carer effects) are considered in decision-making. However, the scope of carer effects and range of decisions where carer effects should be considered is uncertain. This study aimed to identify: (i) how different categories of healthcare and social care were perceived to impact on unpaid carers; and (ii) whether there was consensus about when carer effects should be formally considered in decision-making contexts. Methods A two round, online Delphi study was conducted with 65 UK-based participants (unpaid carers, care professionals, and researchers) with expertise in dementia, mental health, and stroke. Participants considered two broad forms of ‘interventions’ (patient treatment and replacement care) and two broad forms of ‘organisational change’ (staffing and changes in timing/location of care). Participants assessed the likely impacts of these on unpaid carers and whether impacts should be considered in decision-making. Results Participants predicted interventions and organisational changes would impact on multiple domains of unpaid carers’ lives, with ‘emotional health’ the most likely outcome to be affected. Patient treatment and replacement care services (‘interventions’) were associated with positive impacts across all domains. Conversely, timing/location changes and staffing changes (‘organisational changes’) were perceived to have mixed and negative impacts. There was widespread support (80–81 %) for considering carer effects in research studies, funding decisions, and patient decision-making. Conclusions This study highlights a perception that carer effects are widespread and important to consider in economic evaluation and decision-making. It highlights the particular need to measure and value effects on carers’ emotional health and the need to use a societal perspective to avoid cost shifting to unpaid carers when introducing interventions and making organisational changes.
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R E S E A R C H Open Access
The scope of carer effects and their
inclusion in decision-making: a UK-based
Delphi study
Hareth Al-Janabi
1*
, Nikolaos Efstathiou
2
, Carol McLoughlin
1
, Melanie Calvert
3,4,5
and Jan Oyebode
6
Abstract
Background and objective: Health and social care may affect unpaid (family) carershealth and wellbeing in
addition to patientslives. It is recommended that such impacts (carer effects) are considered in decision-making.
However, the scope of carer effects and range of decisions where carer effects should be considered is uncertain.
This study aimed to identify: (i) how different categories of healthcare and social care were perceived to impact on
unpaid carers; and (ii) whether there was consensus about when carer effects should be formally considered in
decision-making contexts.
Methods: A two round, online Delphi study was conducted with 65 UK-based participants (unpaid carers, care
professionals, and researchers) with expertise in dementia, mental health, and stroke. Participants considered two
broad forms of interventions(patient treatment and replacement care) and two broad forms of organisational
change(staffing and changes in timing/location of care). Participants assessed the likely impacts of these on
unpaid carers and whether impacts should be considered in decision-making.
Results: Participants predicted interventions and organisational changes would impact on multiple domains of
unpaid carerslives, with emotional healththe most likely outcome to be affected. Patient treatment and
replacement care services (interventions) were associated with positive impacts across all domains. Conversely,
timing/location changes and staffing changes (organisational changes) were perceived to have mixed and
negative impacts. There was widespread support (8081 %) for considering carer effects in research studies, funding
decisions, and patient decision-making.
Conclusions: This study highlights a perception that carer effects are widespread and important to consider in
economic evaluation and decision-making. It highlights the particular need to measure and value effects on carers
emotional health and the need to use a societal perspective to avoid cost shifting to unpaid carers when
introducing interventions and making organisational changes.
Keywords: Informal care, Economic evaluation, Delphi, Mental health, dementia, Stroke
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* Correspondence: h.aljanabi@bham.ac.uk
1
Health Economics Unit, Institute of Applied Health Research, University of
Birmingham, B15 2TT Edgbaston, Birmingham, UK
Full list of author information is available at the end of the article
Al-Janabi et al. BMC Health Services Research (2021) 21:752
https://doi.org/10.1186/s12913-021-06742-4
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Background
Unpaid (family) carers play a vital role in supporting the
health and wellbeing of individuals with a disability or
illness. This care often comes at the expense of unpaid
carersown wellbeing, with negative effects for carers
physical and emotional health, finances, and social activ-
ity [15]. Carerswellbeing may also be affected by the
organisation and delivery of patient services [6]. This in-
cludes social care (i.e. practical support with everyday
tasks such as personal care, for people who have extra
needs due to illness or disability) as well as health care.
Clinical research has provided a wealth of information
about the way in which treatment and care affects pa-
tient outcomes. However, we know very little about the
effect of patient services on unpaid carersoutcomes
(carer effects).
One area of research where carer effects are particu-
larly pertinent is economic evaluation. Economic evalua-
tions provide a means of systematically evaluating the
costs and benefits of new services. Carer effects are im-
portant to consider in order to measure and value the
full health and wellbeing impacts of patient services on
society [7]. Failure to consider carer effects means the
economic evaluation is incomplete and may provide mis-
leading information on the impact of a service on soci-
etal health or wellbeing. The importance of including
carer effects is explicitly highlighted in influential meth-
odological guidelines for economic evaluation from, for
example, National Institute of Health and Care Excel-
lence in the UK [8], the US panel on cost-effectiveness
[9], and Zorginstituut in the Netherlands [10].
To date, carer effects are still rarely considered in eco-
nomic evaluation. A review of the economic evaluation
literature to 2010 only identified 20 economic evalua-
tions of patient interventions that considered informal
(unpaid) care [11]. A more recent study showed carer ef-
fects were still neglected, even in areas where unpaid
carers are intrinsically involved, like Parkinsons Disease
or Rheumatoid Arthritis [12]. Evidence does suggest that
in some areas, such as dementia [12] or paediatric care
[13], unpaid care is regularly considered on the cost side
when economic evaluations are conducted from a soci-
etal perspective. For example, in a UK study of antide-
pressants in dementia, Romeo and colleagues [14] assess
whether the intervention affects the number of hours of
unpaid carer time (alongside health and social care re-
source use). Carer time value is then valued using the
opportunity cost method and considered as part of the
overall cost, taking a wider payer and carer perspective.
However, it is still the exception rather than the rule
to value carer quality of life outcomes within an eco-
nomic evaluation. Indeed a recent review of NICE ap-
praisals found only 16 of 422 appraisals considered carer
outcomes [15]. One highlighted area where more
information was needed was “…unpaid/carer health out-
comes of [National Health Service] interventions [and
across] disease areas…”.
Economic evaluation is intended to be an aid to
healthcare decision-making ultimately informing and
guiding the services that are provided in society [16].
There is therefore the additional question of whether
carer wellbeing should be routinely considered more
broadly in decisions about health and care delivery. This
includes decisions about the availability of services at a
national level and the provision of services to individual
patients. Certain government policies, such as the Tri-
angle of Care in the UK [17], and the implementation of
mental health services in Australia [18] clearly highlight
an important role for unpaid carers in decisions about
care provision. However, the degree to which carer well-
being ought to be considered routinely, alongside patient
wellbeing, is open to debate.
The aim of the present study was to identify: (i) how
different categories of health and social care were per-
ceived to impact on unpaid carers (carer effects); and
(ii) whether there was consensus about when such ef-
fects should be considered in decision-making contexts.
Methods
A Delphi study [19,20] was used to elicit expert judge-
ments about the scope of carer effects and their inclu-
sion in decision-making. The Delphi method provides a
framework for transforming individual opinions into a
group consensus [20]. Participants are surveyed re-
motely, quasi-anonymously, and at multiple time points.
Delphi studies have been widely used in healthcare re-
search more generally [2124] and specifically in health
economics to determine quality checklists [25], core re-
source use items to measure in economic evaluation
[26], and evidence needs for public health decisions [26].
Methodological guidance on the Delphi technique has
been developed [20,27] but the approach should be seen
as pragmatic and flexible, to meet the needs of the study
[28,29]. In our study, a modified Delphi approach was
used, whereby we planned for up to three online rounds,
but could end it earlier if a high degree of consensus
was reached.
Sampling
Three types of experts were identified for the Delphi
study: unpaid carers,care professionals. Unpaid carers
were defined as individuals who provided care or sup-
port for a family member, friend, or neighbour, due to
their illness, old-age, or disability. Care professionals
were employed staff working for health and social care
organisations that had some experience of the impact of
care and treatment on patient and carerslives. Research
professionals were individuals involved in academic
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interventional research in one of the three clinical areas.
Each group brought different insights on unpaid carer
wellbeing and healthcare decision-making.
Three clinical areas were considered: dementia, mental
health, and stroke. In all areas, unpaid care is important,
but carers face different challenges in relation to the ill-
ness, service availability, and their caring role [30,31].
Our target was to recruit at least 20 unpaid carers, 20
care professionals and 20 researchers across the three
clinical areas. This sample size was consistent with pre-
vious Delphi studies [28,32] where the aim is to estab-
lish group consensus.
Unpaid carers and care professionals were identified
initially through local charities, NHS trusts, and service
contacts from the lay panel supporting the research
programme. Participants had been invited to take part in
prior qualitative interviews and focus groups to establish
the mechanisms by which health and social care delivery
affected carer wellbeing [33]. This sample was supple-
mented with a small number of carers who had taken
part in a nationwide survey on quality of life [34]. A pur-
poseful sampling strategy [35] was used to ensure diver-
sity in terms of caring role (carers) and job role
(professionals). Researcher participants were identified
with the assistance of the project advisory group. In
total, 124 individuals were invited in March 2018 to
participate.
Online survey
The first round of the Delphi study consisted of an on-
line survey to identify likely carer effects of health and
social care. Four broad categories of health and social
care were identified based on prior work on mechanisms
behind carer wellbeing [33] and input from the lived ex-
perience advisory panel [LEAP] [36]. These categories
were:
Patient treatments (e.g. medication, psychological
support). These could affect carer wellbeing, by
improving patient outcomes and therefore indirectly
reducing the emotional and physical strain on
carers.
Services to replace or supplement unpaid care
(e.g. formal social care). These could affect carer
wellbeing by directly reducing the caring load
although their use may be linked with guilt or
financial expense.
Organisational changes to the timing and/or
location of care. These can affect carer wellbeing
when services become easier (or more difficult) to
physically access and combine with daily life.
Organisation changes to staffing. These can affect
carer wellbeing by changing how well-informed
carers feel and their sense of alienation.
The first-round survey consisted of two main sec-
tions: (i) Part A, which elicited judgements on the
likely impact of service changes on carers, based on
participantsown experiences; and (ii) Part B, which
elicited judgements on whether these impacts should
be explicitly considered in decision-making. The
LEAP provided input on the survey length, language
and content, as well as the use of rating scales to rec-
ord participantsresponses [35].
For Part A, participants were asked whether each of
the four categories of health and social care (treatment,
replacement, timing/location, staffing) would, on bal-
ance, have positive,negative,positive and negative
(mixed)or noimpact on each of five domains of carers
lives. The five domains covered mental and physical
health effects and resource consequences (personal fi-
nances, paid work, free time) highlighted in the literature
on carer impact [37,38] and relevant to economic evalu-
ation [16]. For Part B, participants were asked to what
extent they agreed or disagreed (on a six-point scale,
strongly disagree to strongly agree) with considering
carer effects in each of three decision-making contexts
(research, funding, patient care). See Table 1for a sum-
mary. The survey had a total of 16 questions and was
delivered using Smart Survey software [www.
smartsurvey.co.uk]. Please see Appendix 1for full
survey.
In the first round, potential participants were sent a
survey link and an information sheet. They were
given two weeks to respond and were reminded that
their response was voluntary. Non-responders were
reminded a day before and three days after the dead-
line. Data were summarised by participant role
(carers, care professionals, researchers) and used to
create individual feedback sheets to be used in the
second round (see Appendix 2). The feedback sheets
reported the proportion in each participant role (and
disease area) that agreed/disagreed that carer effects
should be considered in the 12 different decisions.
Participantsresponse to the sets of question below
weresummarisedbyroleanddiseaseareatogenerate
frequencies relating to:
the domains of carerslives affected by service
delivery;
whether such effects would be
positive, negative, mixed, or absent.
Consensus was studied in relation to the strength of
agreement that carer effects should be considered for
different types of service, decision-making context, and
disease. Consensus was defined as at least 70 % agree-
ment [20,29,32] in the top third (i.e. strong/moderate
agreement) of the scale.
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In the second round, all responders were sent a
follow-up survey two months later by email. Responders
were separated into the three health conditions. This
survey contained the Part Bquestions and a ranking
question, requiring respondents to identify the most im-
portant decision context and category of health and so-
cial care for considering carer impacts. This was
introduced to encourage respondents to prioritise con-
texts for collecting and using data on carer effects. Indi-
vidual feedback sheets were also provided for
participants, with their own responses and the aggregate
sample responses to the agree-disagreequestions. Par-
ticipants were asked to consider first round responses in
their decision (see Table 2below) and were assured that
they did not have to conform to the group view. Quasi-
anonymity [20] of the participants was maintained
throughout, with the participants unaware of each
others identities. A third online round of the Delphi was
not conducted as consensus was reached.
Results
Round 1 of the Delphi survey was completed by 65 of
the invited individuals (52 %), with 59 of these individ-
uals (91 %) completing round 2 of the survey. The char-
acteristics of the baseline sample are shown in Table 3.
Perceived impacts of service changes on unpaid carers
Figure 1shows the perceived impact of health and social
care on domains of carerslives. Health and social care
interventions(i.e. treatment and replacement care) were
most often associated with positive effects on carers (see
Fig. 1a and b). This was particularly the case for replace-
ment care (Fig. 1b). Here perceived impacts are very
positive across all domains, with the notable exception
of finances. Conversely organisational changes(i.e.
changes in timing/location of service and changes in
staffing) were rarely perceived to have positive effects,
with effects tending to be either negative or mixed (see
Fig. 1c and d). This was particularly the case for staffing
changes, where effects were very rarely perceived to be
positive on balance for any domains of carerslives
(Fig. 1d).
As Table 4shows, this pattern of positive impacts for
interventionsand mixed/negative impacts of organisa-
tional changeswas repeated across all three conditions.
The negative impact of organisational changes was most
pronounced in mental health. In stroke, impacts on
carers were more often perceived to be mixed compared
to dementia or mental health.
Pooling responses across all categories of health and
social care and conditions (Table 5), shows which do-
mains were most likely overall to be affected by health
and social care. Overall, carers’‘emotional healthwas
perceived most likely to be affected, with 94 % of partici-
pants responses indicating either positive, negative or
mixed impacts. Conversely, finances were least likely to
Table 1 Content of the Delphi survey
Service changes Domains of
carer impact
Decision-making contexts
1. Patient treatment (e.g. medication, psychological support). This is linked
to the patient outcomesand compliancemechanisms.
2. Services to replace or supplement unpaid care (e.g. formal social care).
This is linked to the management of caremechanism.
3. Organisational changes to the timing and/or location of care. This is
linked to the timing and locationmechanism.
4. Organisation changes to staffing. This is linked to the informationand
alienationmechanisms.
Emotional
health
Physical health
Finances
Paid work
Free time
A. Research on these interventions should include
finding out how they affect carerslives.
B. Carer impacts should be considered in funding
decisions.
C. Carer impacts should be considered by
professionals in decisions about patient care.
Table 2 Text at the beginning of round 2
The aim of round 2 is to see if a consensus emerges on the
circumstances when impacts on unpaid carers should be taken into
account, alongside the service user, in decision-making. This docu-
ment presents your answers alongside the answers of the rest of
the 20 respondents with expertise in dementia care. We would like
you to consider all the responses and judge whether you wish to
stand by or change your view. Either is fine! Please review the
document as you re-complete the online survey.
Table 3 Characteristics of the Delphi study participants (n=65)
Characteristic N (%)
Primary clinical area
Dementia 21 (32%)
Mental health 21 (32%)
Stroke 23 (35%)
Participants primary role
Unpaid carer 21 (32%)
Researcher 23 (35%)
Care professional 21 (32%)
Experience in role
>10 years 41 (63%)
Experience of service
Treatment 54 (83%)
Replacement care 44 (68%)
Timing/location change 35 (54%)
Staffing change 40 (62%)
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Fig. 1 (See legend on next page.)
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be perceived to be affected, with 63 % of participant re-
sponses indicating positive, negative or mixed impacts.
When these results are broken down by participant
role it is notable that participants who were unpaid
carers perceived negative effects with much greater fre-
quency than participants who were care professionals
and researchers. Specifically, carers (as compared to
non-carers) perceived negative effects more frequently
across all domains of life: emotional health (29 % vs.
11 %), physical health (21 % vs. 10 %), finances (29 % vs.
18 %), paid work (21 % vs. 9 %), and free time (29 % vs.
13 %).
Consensus on including carer effects in decision-making
Overall, when pooled across condition and health and
social care category, support for considering carer effects
in research decisions was 81 %, support for considering
carer effects in funding decisions was 81 %, and support
for considering carer effects in patient care was 80 %.
Across all four clinical areas, all four service changes,
and all three decision contexts (a total of 36 cells), a ma-
jority of participants agreed that carer effects should be
considered in decision-making (Table 6). Consensus was
achieved after round 1 for 34/36 cells (all cells for de-
mentia and mental health and 10 of 12 cells relating to
stroke). Consensus was achieved after round 2 in the 2
remaining cells (both relating to staffing changesin
stroke care) when those mildly agreeingwere included.
Agreement tended to increase (towards greater consen-
sus) between round 1 and 2 for stroke participants and
was maintained at a similar (high) level in mental health
and dementia.
In round 2, when pushed to prioritise which category
of health and social care was the highest priority for in-
clusion of carer effects, treatmentdecisions received the
highest priority and considering carer effects in staff
changesreceived the lowest priority. For decision con-
texts, participants prioritised patient caredecisions
most highly and researchdecisions least highly.
Discussion
This study elicited views on the impact of health and so-
cial care on unpaid carerslives (carer effects) and the
relevance of such effects in different decision-making
contexts. Expert participants perceived that healthcare
and social care would affect a range of domains of
(See figure on previous page.)
Fig. 1 Perceived impact on carers of different aspects of health and social care (n= 65). Perceived impact on carers of replacement
care. Perceived impact on carers of timing or locational changes. Perceived impact on carers of staffing changes. Note: % indicate proportion of
the sample indicating that they thought the impact of intervention on the carer was positive, negative, mixed or not present. So for example
54% of the sample thought patient treatment would have a positive impact on family carer emotional health, 37% a mix of positive and negative
impacts, 8% no impact and 2% no impact.
Table 4 Perceived carer effects from service delivery in dementia, mental health, and stroke
Emotional Health Physical health Finances Paid work Free time
Dementia
Treatment Positive 71% None 43% None 52% None 43% Positive 33%
Replacement Positive 62% Positive 86% Negative 38% Positive 62% Positive 76%
Timing/location Positive 33% Positive 38% Mixed 33% Mixed 38% Mixed 33%
Staffing Mixed 57% Mixed 43% None 43% None 52% Mixed 43%
Mental health
Treatment Positive 52% Positive 52% Positive 29% Positive 43% Positive 48%
Replacement Positive 81% Positive 71% Positive 48% Positive 62% Positive 90%
Timing/location Negative 48% None 43% Negative 38% None 38% Negative 38%
Staffing Negative 48% None 38% None 62% None 57% None 38%
Stroke
Treatment Mixed 61% Mixed 57% Mixed 43% Mixed 35% Mixed 39%
Replacement Positive 71% Positive 74% Mixed 48% Positive 61% Positive 70%
Timing/location Mixed 74% Mixed 65% Mixed 70% Mixed 57% Mixed 61%
Staffing Mixed 78% Mixed 52% None 65% None 61% Mixed 48%
Note: cells show the modal effect (positive/ negative/mixed/ none) and % of sample giving the modal answer. So, for example, most respondents (71%) felt
dementia treatments for patients would have a positive effect on carersemotional health. Similarly for changes in timing and location of dementia care, the
largest sub-group of respondents (33%) felt that this would have a positive effect on carersemotional health.
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carerslives, most commonly their emotional health.
Carer effects were not universally positive, particularly
for organisational changes, (changes in the timing, loca-
tion of staffing of services) which were generally per-
ceived to have negative or mixed impacts on carers
lives. Participants viewed carer effects as important to
consider in a range of decision-making contexts, most
notably in decisions being made about an individual pa-
tients care.
This study suggests that positive effects on the carers
emotional and physical health are likely from interven-
tions in dementia, mental health, and stroke. This means
that economic evaluations that neglect carer health may
be systematically underestimating the health benefits,
and therefore value, of new interventions. Conversely
detrimental health effects for carers were often perceived
to result from organisational changes in timing, location
and staffing of health services. In these cases, economic
evaluations that neglect carer health, may overestimate
the benefit of the service change in the economic evalu-
ation. Neglecting carer effects may therefore lead to in-
vestmentin organisational changes that cost-shift and
are ultimately harmful to carer (and societal) health.
The finding that emotional healthis perceived to be
the most likely domain to be affected is important be-
cause it underscores the need to measure carer quality
of life effects in addition to time costs in economic
evaluation [39,40]. This may require a change in mind-
set in economic evaluation where unpaid care is not just
seen only as a cost. It also highlights the need to use
quality of life measures with carers that are sensitive to
emotional health effects. This may point to measures of
wellbeing (such as ICECAP-A) that have demonstrated
sensitivity to mental ill health [41,42] and carers experi-
ences [34].
In this study, participants perceived carersfinances,
employment, and time, also likely to be affected by ser-
vice changes. This complements recent work on the
Table 5 Perceived carer effects pooled by clinical area and health and social care category (n=260)
EmotionalHealth Physical health Finances Paid work Free time
Positive 37% 35% 16% 25% 34%
Mixed 40% 29% 30% 25% 30%
Negative 17% 13% 21% 13% 18%
None 7% 22% 33% 37% 18%
Note: this table pools results presented in Table 4across all disease areas and intervention types to highlight the overall direction of perceived carer effects on
different domains of life.
Table 6 Proportion of sample moderatelyor stronglyagreeing that carer impact should be considered in decision-making after
2nd round of survey
Service change and decision
context
Dementia Mental health Stroke
Treatment
Research 88% 90% 87%
Funding 94% 90% 87%
a
Individual care 81%
b
80% 87%
Replacement care
Research 88% 90% 91%
a
Funding 94% 90% 91%
a
Individual care 94% 90% 95%
a
Timing and location
Research 81% 85% 70%
Funding 85% 90% 86%
a
Individual care 81%
a
85% 82%
a
Staffing
Research 81% 80% 60%
Funding 94%
a
90% 74%
a
Individual care 94%
a
80% 65%
a
a
denotes greater than 10 % point increase in consensus between round 1 and 2
b
denotes grea ter than 10 % point decre ase in consensus between round 1 and 2
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economic burden of caring [43], additionally demon-
strating that service delivery may impact on carersfi-
nancial burden. In particular, replacement care
interventions were invariably perceived to positively
affect free time and employment for carers. These do-
mains should be considered on the cost side in an eco-
nomic evaluation, albeit typically only when employing a
societal perspective. This underscores the importance,
where feasible, for a societal perspective to be used [9]
to ensure the resource implications to society are prop-
erly considered. The findings from the Delphi study
highlighted the fact that it could be difficult to predict
the direction of carer effects. For example, replacement
care may free carers up, having positive impacts on em-
ployment or free time. However, if carers bear the finan-
cial costs of respite care it may also negatively affect
their personal finances.
This work adds to a body of literature advocating
more consideration be given to carer effects within eco-
nomic evaluation [4,44,45]. The widespread view, held
by participants in this study, that carer effects should be
considered in decision-making, is perhaps not surprising,
given that many participants may have agreed to partici-
pate in this study because of an interest in unpaid carers.
In view of this, participants were pushed to prioritise the
most important contexts for considering carer wellbeing
in. When this happened, participants highlighted deci-
sions about treatmentservices and decisions relating to
individual patient care. On the face of it, this was unex-
pected, as these decisions might be thought of being
more patient-orientated. This may reflect the fact that
these are the decisions that participants more immedi-
ately relate to, compared with funding or research deci-
sions. However, this finding should not take away from
the consensus among participants whereby 81 % also
moderately or strongly agreed that carer effects should
be considered in research studies and in funding deci-
sions. This study has identified four categories of health
and social care where collection of carer data may be
warranted as well as perceptions of the likely scope and
direction of effects.
It is worth highlighting some of the limitations and
strengths of this study. As noted earlier, a Delphi
panel, by its nature, is self-selecting, so we cannot say
that views expressed here are representative of care
professionals or the research community more gener-
ally. In particular the unpaid carers and care profes-
sionals had participated in a previous study. This may
have shaped their responses and resulted in a sample
that had a particular interest in including unpaid
carers in decision-making. However, this approach is
likely to have reduced the rate of drop out and re-
sulted in a sample with greater insight into carer ef-
fects and how they were likely to occur. A further
point to reflect on, is that the study is limited to
three conditions. Viewpoints on the relevance of in-
cluding carer effects in decision-making may therefore
differ for other contexts, such as end-of-life care or
childhood illness where unpaid care is also likely to
be important. Some participants may not have clearly
understood the decision-making contexts. We briefly
explained the meaning of the decision contexts in the
study (e.g. for the research decisions: Research on
these interventions should include finding out how
they affect carerslives). However, a more in-depth
explanation of funding decisions and patient care de-
cisions might have been useful for some participants.
Finally, we focused on eliciting views on broad cat-
egories of health and social care delivery, rather than
specific treatments. This was done to focus on the
major ways in which health and social care could im-
pact on carerslives. However, a consequence of hav-
ing four general categories is that there may be
ambiguities about what participants associated with
these categories.
A strength of this study is that we sampled partici-
pants with experience across three major conditions and
in different roles. Across all there was a high degree of
consistency in terms of the perceived impacts of services
on carers and a high degree of consensus that these im-
pacts should be considered in decision-making.
It is still the normin many countries (including the
UK) to expect unpaid carers to carry much of the re-
sponsibility for patient care. Nevertheless there is much
that could be done to better ensure that negative im-
pacts of policies on carers wellbeing are minimised. Fur-
ther work on this topic could focus on developing
practical approaches to consider carer wellbeing in
everyday care decisions. This could complement work to
include carers in research studies and economic evalu-
ation. From an economic evaluation perspective, utilising
a societal perspective, and including outcome measures
that encompass emotional health are important to fully
capture carer effects. Other challenges exist in incorpor-
ating carer outcomes in economic evaluation, for ex-
ample to include carer outcomes routinely, where
primary data cannot easily be collected or in establishing
how best to measuring carer outcomes where family car-
ing networks may be complex, and extend beyond a sin-
gle carer.
In conclusion, this study adds to a body of literature
that highlights the importance of carer effects in eco-
nomic evaluation and more generally in healthcare
decision-making. It highlights the particular need to
measure and value effects on carersemotional health
and the need to use a societal perspective to avoid cost-
shiftingto unpaid carers when introducing interventions
and making organisational changes.
Al-Janabi et al. BMC Health Services Research (2021) 21:752 Page 8 of 10
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Supplementary Information
The online version contains supplementary material available at https://doi.
org/10.1186/s12913-021-06742-4.
Additional file 1:
Additional file 2:
Acknowledgements
The authors are grateful to all those who participated in the study. We also
thank members of our lay panel (Jenny Coles, John Copping, Jacky Murphy
and Jean Nicholls) and scientific advisory panel (Jo Coast, Werner Brouwer,
Cam Donaldson, Bhash Naidoo, Jen Francis, John Gladman, Laura Bennett,
Sandra Hollinghurst, Liz Sampson, Andrea Manca) for advice on the work.
Authorscontributions
HA conceptualised the study, administered the project, undertook the
analysis, and wrote the main manuscript text; HA, NE, CM, MC, JO: developed
the methodology and reviewed and edited the manuscript. All authors read
and approved the final manuscript.
Funding
This work was funded by a National Institute for Health Research (NIHR)
Career Development Fellowship (CDF-2015-08-025) awarded to HA for this
research project. This paper presents independent research funded by the
National Institute for Health Research (NIHR). The views expressed are those
of the authors and not necessarily those of the NHS, the NIHR or the
Department of Health and Social Care.
Availability of data and materials
The datasets used and/or analysed during the current study are available
from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
The study protocol was reviewed and approved by the University of
Birminghams ethical review committee (14-1444) and the NHS Health
Research Authority (IRAS 206161). Informed consent was obtained from all
participants. All methods were performed in accordance with the relevant
guidelines and regulations.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1
Health Economics Unit, Institute of Applied Health Research, University of
Birmingham, B15 2TT Edgbaston, Birmingham, UK.
2
School of Nursing,
Institute of Clinical Sciences, University of Birmingham, Birmingham, UK.
3
Centre for Patient Reported Outcomes Research, Institute of Applied Health
Research, University of Birmingham, B15 2TT Edgbaston, Birmingham, UK.
4
NIHR Birmingham Biomedical Research Centre, NIHR Surgical Reconstruction
and Microbiology Research Centre and NIHR Applied Research Centre, West
Midlands, University Hospitals Birmingham NHS Foundation Trust and
University of Birmingham, B15 2TT Edgbaston, Birmingham, UK.
5
Birmingham
Health Partners Centre for Regulatory Science and Innovation, University
Hospitals, University of Birmingham, B15 2TT Edgbaston, Birmingham, UK.
6
Centre for Applied Dementia Studies, University of Bradford, Bradford,
Richmond Rd, BD7 1DP Bradford, UK.
Received: 26 February 2021 Accepted: 3 June 2021
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... Whilst some guidance exists in relation to the methodological conduct of a Delphi study [12], the technique is adaptable to the needs of a particular research question. Over the last few decades, the method has gained traction in numerous disciplines, including in social and health sciences [17,18], where it has been used to elicit and ascertain opinions, explore views, identify policy responses and produce guidance [19][20][21][22][23][24]. ...
... More fundamentally, without knowing the exact synthesis of the wider population of health economists, it is not possible to know how well the respondents matched this population, or the extent to which the reported views are representative. Secondly, the predetermined criteria for judging the importance of considerations (i.e. the percentage of panellists deeming a consideration as not important/important/very important) may be seen as more inclusive than similar criteria in other studies (see, for instance, [19,20,22]). Such criteria are, however, set according to the objectives of each study-in the case of our work, to gain insights into the importance of different key considerations, rather than to produce an exclusive and exhaustive list. ...
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... This may include additional factors that contribute to the "mental burden" of caregiving beyond capturing the true physical and emotional burdens beyond time commitments. This could be determined by the impact on the caregiver's life where they have to reorganize their own, existing routines and commitments around required caregiving activities that result in reduced time available for other activities such as employment, volunteering, or leisure/social activities (18). ...
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... Incorporating the changes in caregivers' HRQoL (sometimes referred to as "spillover" effects) into HEE might alter the incremental quality-adjusted life years (QALYs), and thus potentially reshape the final evaluation results and relevant decision-making [18]. Consequently, a number of international HTA agencies, like the National Institute for Health and Care Excellence (NICE) in the United Kingdom, the Haute Autorité de santé (HAS) in France, the Health Information and Quality Authority in Ireland, etc., all recommend that HEE should include the direct health effects both for patients and their caregivers contributed by target healthcare interventions [18][19][20]. ...
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... • Peer-reviewed publication or presentation of research on the subject of family and caregiver health spillovers and/ or applied economic evaluations in areas such as social care, dementia, and paediatrics (i.e., those areas where family and caregiver health spillovers are likely to be present) [22,51,52]; and/or, • Involvement in the development or application of guidelines for applied economic evaluations in the public or private sector. ...
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Health and care services for patients may improve or harm the wellbeing of their family carers. Formal consideration of these effects (also known as spillovers) in decision-making is advocated, but, to date, little is known about how they occur. This paper presents the first empirical study to determine the mechanisms by which health and care services affect family carers' wellbeing. The study focused on three major health conditions: dementia, stroke, and mental health. Focus groups and interviews were conducted with 49 purposefully sampled care professionals and family carers in the UK between December 2016 and September 2017. Transcripts were coded and analysed thematically, using descriptive accounts and an explanatory account. The analysis generated six over-arching mechanisms by which health and care services affect family carers' wellbeing, through: (i) information (degree to which service delivery informs and trains family carers); (ii) management of care (shifts of responsibility for care between formal and family sectors); (iii) patient outcomes (services changing patient outcomes); (iv) alienation (feelings of alienation or inclusion created by service delivery); (v) compliance (barriers to patients complying and engaging with services); and (vi) timing or location (changes in the timing or location of services). Each mechanism was associated with sub-themes relating to both positive and negative spillovers on the family carers. The six mechanisms can be summarised with the mnemonic 'IMPACT'. The IMPACT mechanisms may be useful in designing and evaluating services to optimise the wellbeing of carers as well as patients.
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Background A growing body of research has identified health-related quality-of-life effects for caregivers and family members of ill patients (i.e. ‘spillover effects’), yet these are rarely considered in cost-effectiveness analyses (CEAs). Objective The objective of this study was to catalog spillover-related health utilities to facilitate their consideration in CEAs. Methods We systematically reviewed the medical and economic literatures (MEDLINE, EMBASE, and EconLit, from inception through 3 April 2018) to identify articles that reported preference-based measures of spillover effects. We used keywords for utility measures combined with caregivers, family members, and burden. Results Of 3695 articles identified, 80 remained after screening: 8 (10%) reported spillover utility per se, as utility or disutility (i.e. utility loss); 25 (30%) reported a comparison group, either population values (n = 9) or matched, non-caregiver/family member or unaffected individuals’ utilities (n = 16; 3 reported both spillover and a comparison group); and 50 (63%) reported caregiver/family member utilities only. Alzheimer’s disease/dementia was the most commonly studied disease/condition, and the EQ-5D was the most commonly used measurement instrument. Conclusions This comprehensive catalog of utilities showcases the spectrum of diseases and conditions for which caregiver and family members’ spillover effects have been measured, and the variation in measurement methods used. In general, utilities indicated a loss in quality of life associated with being a caregiver or family member of an ill relative. Most studies reported caregiver/family member utility without any comparator, limiting the ability to infer spillover effects. Nevertheless, these values provide a starting point for considering spillover effects in the context of CEA, opening the door for more comprehensive analyses.
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Background Growing evidence has documented economic spillover effects experienced by intensive caregivers across the lifecycle. These spillover effects are rarely incorporated in economic analyses of health interventions. When these costs are captured, it is shown that commonly applied methods for valuing caregiver time may be underestimating the true opportunity costs of informal care. We explore how intensive caregiving is associated with economic outcomes for caregivers aged 18 years and older. Methods We used the cross-sectional 2013 RAND Survey of Military and Veteran Caregivers, a survey of 3876 caregivers and non-caregivers aged 18 years and older to conduct multivariable analyses and calculate average marginal effects, focusing on the association between intensive caregiving (i.e., providing ≥ 20 h of weekly care) and six economic outcomes: schooling, labor force participation, taking unpaid time off of work, cutting back work hours, quitting a job, and early retirement. Results Intensive caregivers are 13 percentage points (95% confidence interval [CI] 8–18) less likely to be employed than non-caregivers. Intensive caregivers are 3 percentage points (95% CI 0.5–5) more likely to cut back schooling, 6 percentage points (95% CI 2–10) more likely to take unpaid time off of work, 4 percentage points (95% CI 0.1–9) more likely to cut back work hours, 12 percentage points (95% CI 8–15) more likely to quit a job, and 5 percentage points (95% CI 2–7) more likely to retire early due to caregiving responsibilities relative to non-intensive caregivers. Conclusions Despite the difficulty of quantifying the true opportunity costs of informal care, policy makers and researchers need to understand these costs. The higher the opportunity costs of unpaid care provision, the less likely it is that caregivers will provide this care and the less economically attractive this ‘free’ source of care is from a societal perspective.
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Background Resource use measurement by patient recall is characterized by inconsistent methods and a lack of validation. A validated standardized resource use measure could increase data quality, improve comparability between studies, and reduce research burden. Objectives To identify a minimum set of core resource use items that should be included in a standardized adult instrument for UK health economic evaluation from a provider perspective. Methods Health economists with experience of UK-based economic evaluations were recruited to participate in an electronic Delphi survey. Respondents were asked to rate 60 resource use items (e.g., medication names) on a scale of 1 to 9 according to the importance of the item in a generic context. Items considered less important according to predefined consensus criteria were dropped and a second survey was developed. In the second round, respondents received the median score and their own score from round 1 for each item alongside summarized comments and were asked to rerate items. A final project team meeting was held to determine the recommended core set. Results Forty-five participants completed round 1. Twenty-six items were considered less important and were dropped, 34 items were retained for the second round, and no new items were added. Forty-two respondents (93.3%) completed round 2, and greater consensus was observed. After the final meeting, 10 core items were selected, with further items identified as suitable for “bolt-on” questionnaire modules. Conclusions The consensus on 10 items considered important in a generic context suggests that a standardized instrument for core resource use items is feasible.
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Patient and public involvement (PPI) can be used in methods research, as well as applied research, in health economics. However, methods research goals may seem quite abstract when compared to the lived experiences of lay participants. This article draws on 4 years of PPI in a research project to develop methods for including family carer outcomes in economic evaluation. Key challenges in using PPI for health economics methods research relate to (1) training and preparation, (2) maintaining involvement, and (3) selecting suitable tasks. We suggest three criteria for selecting a research task for PPI input based on task importance, professional researcher skills gap, and potential PPI contribution.
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We explore how intensive caregiving is associated with economic outcomes across the lifecycle using the cross-sectional 2013 RAND Survey of Military and Veteran Caregivers (n=3,775). We estimate average marginal effects of the association between intensive caregiving (≥20 hours/week) and six economic outcomes: schooling, labor force participation, unpaid time off work, reducing work hours, quitting a job, and early retirement. Intensive caregivers are 12% points (95% CI: -19 to -5%) less likely to be employed than non-caregivers. Intensive caregivers are 3% points (CI: 0.05 to 5%) more likely to cut back schooling, 6% points (CI: 2 to 10%) more likely to take unpaid time off of work, 4% points (CI: 1 to 9%) more likely to cut back work hours, 12% points (CI: 8 to 15%) more likely to quit a job, and 5% points (CI: 2 to 7%) more likely retire early due to caregiving responsibilities relative to non-intensive caregivers.
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Background Childhood illness can impose significant costs and health strains on family members, but these are not routinely captured by pediatric economic evaluations. This review investigated how family “spillover effects” related to costs and health outcomes are considered in pediatric cost-utility analyses (CUAs). Methods We reviewed pediatric CUAs published between 2000 and 2015 using the Tufts Medical Center Cost-effectiveness Analysis (CEA) Registry and the Pediatric Economic Database Evaluation (PEDE) Registry. We selected studies conducted from the societal perspective and included in both registries. We investigated how frequently family spillover was incorporated into analyses, and how the inclusion of spillover health effects and costs changed CUA results. Results We found 142 pediatric CUAs meeting inclusion criteria. Of those, 105 (72%) considered either family spillover costs (n = 98 time costs, n = 33 out-of-pocket costs, n = 2 caregiver healthcare costs) or health outcomes (n = 15). Twenty-four studies included 43 pairs of incremental cost-effectiveness ratios (ICERs) with and without spillover. In 19 pairs of ICERs, adding spillover changed the ICER enough to cross a common cost-effectiveness threshold (i.e., 50,000/QALY, 100,000/QALY, 150,000/QALY;valuesarein2016US150,000/QALY; values are in 2016 US). Incorporating spillover generally made interventions more cost-effective (n = 18; 42%), or did not change CUA results enough to cross a threshold (n = 24; 56%). Including family spillover reduced ICERs by 31% ($40,000/QALY) on average. Conclusion Most pediatric CUAs conducted from a societal perspective include family costs but fewer include family health effects. Inclusion of family spillover effects tends to make CUA results more favorable. Future pediatric CUAs should aim to more fully incorporate the family burden of illness.
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Importance Patient-reported outcome (PRO) data from clinical trials can provide valuable evidence to inform shared decision making, labeling claims, clinical guidelines, and health policy; however, the PRO content of clinical trial protocols is often suboptimal. The SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) statement was published in 2013 and aims to improve the completeness of trial protocols by providing evidence-based recommendations for the minimum set of items to be addressed, but it does not provide PRO-specific guidance. Objective To develop international, consensus-based, PRO-specific protocol guidance (the SPIRIT-PRO Extension). Design, Setting, and Participants The SPIRIT-PRO Extension was developed following the Enhancing Quality and Transparency of Health Research (EQUATOR) Network’s methodological framework for guideline development. This included (1) a systematic review of existing PRO-specific protocol guidance to generate a list of potential PRO-specific protocol items (published in 2014); (2) refinements to the list and removal of duplicate items by the International Society for Quality of Life Research (ISOQOL) Protocol Checklist Taskforce; (3) an international stakeholder survey of clinical trial research personnel, PRO methodologists, health economists, psychometricians, patient advocates, funders, industry representatives, journal editors, policy makers, ethicists, and researchers responsible for evidence synthesis (distributed by 38 international partner organizations in October 2016); (4) an international Delphi exercise (n = 137 invited; October 2016 to February 2017); and (5) consensus meeting (n = 30 invited; May 2017). Prior to voting, consensus meeting participants were informed of the results of the Delphi exercise and given data from structured reviews evaluating the PRO protocol content of 3 defined samples of trial protocols. Results The systematic review identified 162 PRO-specific protocol recommendations from 54 sources. The ISOQOL Taskforce (n = 21) reduced this to 56 items, which were considered by 138 international stakeholder survey participants and 99 Delphi panelists. The final wording of the SPIRIT-PRO Extension was agreed on at a consensus meeting (n = 29 participants) and reviewed by external group of experts during a consultation period. Eleven extensions and 5 elaborations to the SPIRIT 2013 checklist were recommended for inclusion in clinical trial protocols in which PROs are a primary or key secondary outcome. Extension items focused on PRO-specific issues relating to the trial rationale, objectives, eligibility criteria, concepts used to evaluate the intervention, time points for assessment, PRO instrument selection and measurement properties, data collection plan, translation to other languages, proxy completion, strategies to minimize missing data, and whether PRO data will be monitored during the study to inform clinical care. Conclusions and Relevance The SPIRIT-PRO guidelines provide recommendations for items that should be addressed and included in clinical trial protocols in which PROs are a primary or key secondary outcome. Improved design of clinical trials including PROs could help ensure high-quality data that may inform patient-centered care.
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Importance: Patient-reported outcome (PRO) data from clinical trials can provide valuable evidence to inform shared-decision making, labelling claims, clinical guidelines, and health policy; however, the PRO content of clinical trial protocols is often suboptimal. The SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) Statement was published in 2013 and aims to improve the completeness of trial protocols by providing evidence-based recommendations for the minimum set of items to be addressed, but does not provide PRO-specific guidance. Objective: To develop international, consensus-based, PRO-specific protocol guidance: the SPIRIT-PRO extension. Design, Setting, and Participants: The SPIRIT-PRO Extension was developed following the Enhancing QUAlity and Transparency Of health Research (EQUATOR) Network’s methodological framework for guideline development. This included: (i) a systematic review of existing PRO-specific protocol guidance to generate a list of candidate PRO-specific protocol items (published 2014); (ii) refinements to the list and removal of duplicate items by the International Society for Quality of Life Research (ISOQOL) PROtocol Checklist Taskforce; (iii) an international stakeholder survey of: clinical trial research personnel, PRO methodologists, health economists, psychometricians, patient advocates, funders, industry representatives, journal editors, policy makers, ethicists and researchers responsible for evidence synthesis (distributed by 38 international partner organizations, October 2016); (iv) an international Delphi exercise (n=137 invited; October 2016 to February 2017)and consensus meeting (n=30 invited; May 2017). Prior to voting, consensus meeting participants were informed of the results of the Delphi exercise and given data from structured reviews evaluating the PRO protocol content of three defined samples of trial protocols. Results: The systematic review identified 162 PRO-specific protocol recommendations from 54 sources. The ISOQOL Taskforce (n=21) reduced this to 56 items, which were considered by 138 international stakeholders and 99 Delphi panelists. The final wording of the SPIRIT-PRO Extension was agreed at a consensus meeting (n=29 participants) and reviewed by external stakeholders during a consultation period. Eleven extensions and five elaborations to the SPIRIT 2013 checklist are recommended for inclusion in clinical trial protocols where PROs are a primary or key secondary outcome. Extension items focused on PRO specific issues relating to the: trial rationale, objectives, eligibility criteria, concepts used to evaluate the intervention, timepoints for assessment, PRO instrument selection and measurement properties, data collection plan, translation to other languages, proxy completion, strategies to minimise missing data and whether PRO data will be monitored during the study to inform clinical care. Conclusions and relevance: These guidelines provide recommendations for items that should be addressed and included in clinical trial protocols in which PROs are a primary or key secondary outcome. Improved design of clinical trials including PROs could help ensure high-quality data that may inform patient-centered care.