Carer Health-Related Quality of Life: A Review of Modelling Considerations in National Institute for Health and Care Excellence Technology Appraisals (2000–2023)

Abstract

Objectives

Carer health-related quality of life (HRQoL) is increasingly used to support health technology assessments conducted by the National Institute for Health and Care Excellence (NICE). Modelling approaches and underlying rationales considered in NICE appraisals before the publication of the ‘Spillovers in Health Economic Evaluation and Research’ guidance were reviewed, alongside committee feedback and stated preferences.

Methods

The NICE website (www.nice.org.uk) was searched for final appraisal determinations (FADs) from 2000 to August 2023 that considered carer HRQoL. FADs were reviewed for an expression of whether carer HRQoL data were considered qualitatively (without formal economic modelling) or quantitatively (incorporated into cost–utility analyses) in decision-making. All related committee papers were retrieved for eligible submissions. Modelling approaches used were extracted as well as sources of carer HRQoL and reasons for including or excluding carer HRQoL from decision-making.

Results

NICE considered carer HRQoL data (sourced from observational studies, surveys, vignettes and clinical trials) for decision-making in 90% (44/49) of appraisals submitting such data (82% were considered quantitatively); carer HRQoL data were considered for decision-making in all appraisals involving rare diseases and paediatric populations. Three approaches (additive carer disutility [used in 90% of identified appraisals], additive carer utility [14%] and absolute carer utility [2%]) and two adjustments (application of carer/patient age/utility cap [20%] and carer/family bereavement [10%]) were identified for incorporating carer HRQoL. There was considerable variation in the implementation of these methods/adjustments.

Conclusions

This review of NICE appraisals identified three key methodologies and two adjustments for including carer HRQoL; the additive carer disutility approach was the most frequently used.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41669-025-00611-0.

Key Points for Decision Makers

Carer health-related quality of life (HRQoL) is increasingly used to support technology appraisals conducted by the National Institute for Health and Care Excellence (NICE) in England and Wales.

We identify three approaches and two adjustments for carer HRQoL inclusion in NICE appraisals; the most frequently used approach was the additive carer disutility approach, followed by additive carer utility approach. Within the various approaches, there was considerable variation in the way these methods were implemented.

We discuss the merits of these respective methodological approaches and the factors that NICE has indicated may be a reason for considering or not considering each approach as part of the decision-making process, and we briefly discuss the potential implications of carer HRQoL inclusion on cost–utility calculations.

Introduction

Although health technology assessments (HTAs) primarily focus on patient outcomes, benefits to patients can also affect the welfare of their carers [1]. Improved patient outcomes could reduce carer burden and enhance carer health-related quality of life (HRQoL) by relieving the time sacrifice, physical and emotional strain and social isolation associated with providing informal care [1, 2]. Conversely, extending a patient’s life might also increase the carer’s burden, reducing their welfare and offsetting HRQoL benefits experienced by the patient—a phenomenon known as the carer ‘quality-adjusted life-year’ (QALY) trap [3]. Economic evaluations, including cost–utility analyses, are frequently incorporated into HTAs to improve healthcare resource allocation [4]. Although patient outcomes are usually the focus of these analyses, carer HRQoL can also strongly impact cost-effectiveness outcomes [4–6].

In England and Wales, the National Institute for Health and Care Excellence (NICE) conducts technology appraisals (TAs) of new health technologies: single technology appraisals (STAs), multiple technology appraisals (MTAs) or highly specialised technology (HST) submissions. Submissions are appraised by external assessment groups (EAGs); additional evidence from the company may subsequently be requested, followed by additional rounds of review. The NICE committees then make final recommendations, on the basis of a review of all submitted evidence including cost-effectiveness data, which are reported in a final appraisal determination (FAD) or a final evaluation determination for an HST. The 2022 NICE reference case states that health economic models should include perspectives on patient outcomes, costs incurred by the National Health Service and personal social services, and health effects experienced by individuals other than patients, particularly carers, when relevant [7]. Evidence of disease impact and the effect of a health technology intervention on carer HRQoL is recommended, with changes in HRQoL to be valued using a representative sample of the UK population [7, 8]. Critically however, the NICE reference case does not specify how carer HRQoL should be included in cost–utility analyses [7, 8]. More recently, the Spillovers in Health Economic Evaluation and Research (SHEER) task force has published 11 consensus recommendations for the incorporation of family and caregiver quality of life (QoL) in health economic analyses but also does not provide any insights into NICE-preferred methods [9].

Pennington and Wong (2019) reviewed the consistency of carer HRQoL inclusion in the NICE HTA process in 16 appraisals from 2000 to 2019 [10]; a subsequent review by Kanters (2024) provided a brief update to this review, capturing 20 additional HTAs submitted between January 2019 and March 2022 [11]. However, whilst the Pennington and Wong report did discuss utility and disutility approaches to modelling carer HRQoL, it did not provide a review of the modelling methods used across each NICE appraisal where carer HRQoL was incorporated, the limitations associated with each methodology nor the corresponding NICE feedback. As such, the report is unable to inform health economic (HE) modellers on the NICE committee’s preference in the absence of a definite guide [10]. The subsequent review by Kanters et al. (2024) also covered the utility and disutility approaches (and briefly included the use of the carer bereavement approach), as well as how carer HRQoL should be incorporated in HE models by discussing best practice in measuring utility data. However, it did not provide further discussion on the limitations within each methodology, the committee feedback or NICE’s preferred methodology [11]. As such, there is an unmet need for a comprehensive review of the methods used and the decision-making process that guided the incorporation of carer HRQoL data, their associated strengths and limitations and whether EAGs and NICE expressed support for these data when there were no formal recommendations guiding their inclusion.

The objectives of this review were to identify appraisals in which carer HRQoL data were considered by the NICE decision-making committees and to identify NICE’s preferred modelling approach(es).

Methods

Searches were conducted using the NICE website (www.nice.org.uk) to identify TAs that considered the impact of health technologies on carer and patient HRQoL. FADs published by NICE for STAs, MTAs and HSTs, from the inception of the NICE HTA in 2000 until 11 August 2023, were assessed (Table 1).

Table 1.

Criteria for study inclusion

Criteria	Inclusion	Exclusion
Population	No limits	Not applicable
Intervention	No limits	Not applicable
Comparator	No limits	Not applicable
Outcomes	Caregiver/carer/family/sibling AND HRQoL/utilities/burden	Clinical outcomes Safety outcomes Costs
Study design	NICE TAs NICE HSTs	Not applicable
Limitations	NICE submissions review: inception until search date (2000 to August 2023)	Not applicable

HRQoL health-related quality of life, HST highly specialised technology, NICE National Institute for Health and Care Excellence, TA technology appraisal

The FAD documents were searched for ‘caregiver’, ‘carer’ and ‘family’. A full-text review of retrieved appraisals was conducted and only those that included carer HRQoL in economic modelling or decision-making were selected. FADs that made generic statements without providing a qualitative (i.e. carer HRQoL impact was considered holistically without formal economic modelling) or quantitative (i.e. the carer HRQoL estimates were incorporated into QALYs and incremental cost-effectiveness ratio [ICER] calculations) interpretation of the impact of the health technology on carer HRQoL were excluded. Appraisals were classified into two groups: those which integrated carer HRQoL into the submission cost–utility framework and those of which formal modelling was discussed but not further applied (only included in supplement). Once eligible appraisals were identified, all related committee papers were screened and data were extracted by one reviewer (Supplementary Table 1, see Electronic Supplementary Material [ESM] for details).

Results

A total of 484 FADs were identified from the NICE database and 63 met the criteria for inclusion (i.e. carer HRQoL discussed) following full-text screening. Of these, 49 original appraisals (10%; 49/484), comprising 32 TAs (29 STAs and 3 MTAs) and 17 HSTs, included carer HRQoL in cost–utility analyses (Fig. 1). In a further 14 TAs, carer HRQoL was discussed but not explored in economic analyses by the company, EAGs or NICE committees. As such, these are not included in our analysis but are included in the appendix for completeness (Supplementary Table 2, see Electronic Supplementary Material [ESM]).

Fig. 1.

PRISMA flow diagram for NICE website searches. CEA cost-effectiveness analysis, FAD final appraisal document, HRQoL health-related quality of life, HST highly specialised technology, MTA multiple technology appraisal, NICE National Institute for Health and Care Excellence, PRISMA Preferred Reporting Items for Systematic reviews and Meta-Analyses, STA single technology appraisal, TA technology appraisal

Impact of Carer HRQoL on Committees’ Decisions

Of the 49 TAs that included carer HRQoL in cost–utility analyses in their original submissions, carer HRQoL was excluded from all decision-making by the NICE committees in five appraisals (all STAs) owing to uncertainties in evaluations, modelling methods and/or justifications for its inclusion. Overall, carer HRQoL was considered for decision-making (quantitatively and/or qualitatively) by the NICE committees in 90% (44/49) of submissions submitting such data. The committees quantitatively considered carer HRQoL in 82% (40/49) of these appraisals (Fig. 2), and in four appraisals, the committees recommended that carer HRQoL be considered qualitatively only; in one appraisal (HST8), carer HRQoL was considered both quantitatively (which was deemed to be lacking in robustness) and qualitatively (considered in discussions).

Fig. 2.

Committees’ decisions on carer HRQoL across HTA submissions. HRQoL health-related quality of life, HTA health technology assessment, NICE National Institute for Health and Care Excellence

Sources of Carer HRQoL Data

Quantitative HRQoL estimates considered for decision-making by NICE included those provided by the submitting company and the preferred models and estimates provided by the EAGs. Sources of carer HRQoL (non-mutually exclusive) included observational studies, surveys, vignette studies, prior HTAs and clinical trials. A summary of these data is presented in Table 2 [12–61].

Table 2.

Acceptance of carer HRQoL quantitative estimates in NICE appraisals

Source of estimates	Indication	TA/HST ID
Accepted for consideration by committees
Additive carer disutility, by patients’ health state
Clinical trial	Seizures associated with Dravet syndrome	TA808 [48]
Observational study	Acute hepatic porphyria	HST16 [41]
	Familial chylomicronaemia syndrome	HST13 [36]
	Hereditary transthyretin amyloidosis	HST10 [27]; HST9 [29]
	Metachromatic leukodystrophy	HST18 [42]
	Mucopolysaccharidosis type 4A	HST19 [51]
	Multiple sclerosis	[12–15, 19, 20, 24, 25, 33–35, 37, 38, 49]
	Paediatric-onset hypophosphatasia	HST23 [60]
	Progressive familial intrahepatic cholestasis	HST17 [52]a
	RPE65-mediated inherited retinal dystrophies	HST11 [30]
	Spinal muscular atrophy	TA588 [26]a; TA755 [40]a
Previous TA	Symptomatic and inoperable plexiform neurofibromas associated with type 1 neurofibromatosis	HST20 [53]a
Publication NR	Treatment-resistant depression	TA854 [54]
Survey	Lipodystrophy	HST14 [43]
	Obesity caused by leptin receptor or proopiomelanocortin deficiency	HST21 [55]a
	Peanut allergy	TA769 [56]a
	Short bowel syndrome	TA804 [57]
	X-linked hypophosphataemia	HST8 [21]a
Vignette study	Lennox–Gastaut syndrome	TA615 [28]
	Neuronal ceroid lipofuscinosis type 2	HST12 [31]a
	Seizures associated with Dravet syndrome	TA614 [32]
	Seizures associated with tuberous sclerosis complex	TA873 [61]
Additive carer disutility, by patients’ treatment
Observational study	Juvenile idiopathic arthritis	TA373 [16]
Previous TA	Familial chylomicronaemia syndrome	HST13 [36]
Additive carer utility, by patients’ health state
Clinical trial	Seizures associated with Dravet syndrome	TA808 [48]
Observational study	Alzheimer disease	TA217 [23]
	Spinal muscular atrophy	TA755 [40]a
Additive carer utility, by patients’ treatment
Previous TA	Refractory chronic immune thrombocytopenia	TA835 [50]
Carer or family bereavement approach
Observational study	Spinal muscular atrophy	TA755 [40]a
Observational study	Spinal muscular atrophy	TA588 [26]a
Publication (proxy)	Paediatric-onset hypophosphatasia	HST23 [60]
Carer or family bereavement approach—qualitative
Modelling study	Duchenne muscular dystrophy	HST22 [59]a
Declined for consideration by committees
Additive carer disutility, by patients’ health state
Observational study	Spinal muscular atrophy	HST15 [39]
	Symptoms of myotonia in nondystrophic myotonic disorders	TA748 [44]
Modelling study	Duchenne muscular dystrophy with a nonsense mutation in the dystrophin gene	HST22 [59]a
Survey	Focal-onset seizures in epilepsy	TA753 [45]
Additive carer disutility, by patients’ treatment
Survey	Disease related or symptoms in adults with myelofibrosis	TA386 [17]a
Additive carer disutility, due to anxiety impact
Vignette study	Recurrent attacks of hereditary angioedema	TA738 [46]
Additive carer utility, by patients’ health state
Modelling study	Duchenne muscular dystrophy with a nonsense mutation in the dystrophin gene	HST22 [59]a
Additive carer utility, by patients’ treatment
Observational study	Moderate to severe atopic dermatitis	TA534 [22]
Vignette study	Previously treated mycosis fungoides and Sézary syndrome	TA754 [47]
Absolute carer utility
Modelling study	Duchenne muscular dystrophy with a nonsense mutation in the dystrophin gene	HST22 [59]a
Applying a utility cap
Modelling study	Duchenne muscular dystrophy with a nonsense mutation in the dystrophin gene	HST22 [59]a
Carer or family bereavement approach
Modelling study	Adenosine deaminase–severe combined deficiency	HST7 [18]

All estimates are quantitative unless stated

Methods used in appraisals were not mutually exclusive

HRQoL health-related quality of life, HST highly specialised technology, NICE National Institute for Health and Care Excellence, NR not reported, TA technology appraisal

^aReport included the use of some sort of ‘cap’

Patient Populations for Which Carer HRQoL was Included

There were 27 clinical areas for which NICE accepted the inclusion of carer HRQoL data for qualitative and/or quantitative decision-making. All 14 TAs for multiple sclerosis health technologies that included carer HRQoL estimates had these data accepted for quantitative decision-making [12–15, 19, 20, 24, 25, 33–35, 37, 38, 49]. In an HST submission for X-linked hypophosphataemia (HST10), carer HRQoL data were considered both quantitatively and qualitatively owing to challenges in accurately modelling the full impact of the disease on carer HRQoL and the uncertainty concerning the appropriateness of the carer disutility values identified by the company for inclusion in the economic model [21].

Of 40 appraisals that had carer HRQoL considered quantitatively in cost–utility analyses, 33% (13/40) were exclusively for paediatric populations, 18% (7/40) for combined paediatric and adult populations and 50% (20/40) for adult populations. All appraisals with carer HRQoL values for technologies targeting either paediatric or combined paediatric and adult populations were considered qualitatively or quantitatively by the NICE committees. Among the appraisals for technologies targeting the adult population, NICE agreed to consider carer HRQoL data in 81% (22/27) either quantitatively (20) or qualitatively (2); however, carer HRQoL estimates provided in five appraisals were excluded from quantitative decision-making. All HSTs submitted with carer HRQoL values (17) had these data considered either qualitatively (14) or quantitatively (3).

Modelling Approaches to Carer HRQoL

Most appraisals (73%; 36/49) including carer HRQoL estimates occurred after 2019 (Fig. 3). Although there was no consensus model observed for the incorporation of carer HRQoL among the NICE submissions, this study identified three approaches and two adjustments that were used in a non-mutually exclusive manner: additive carer disutility approach, additive carer utility approach, absolute carer utility approach, application of a carer or patient age or utility cap and application of disutilities due to carer or family bereavement. The EAGs and NICE committees’ feedback on these methods are presented in Supplementary Table 3 (see ESM). The assumptions and considerations that underlie how to estimate the caregiver’s utility after the patient dies can impact cost-effectiveness estimates and are presented in Supplementary Table 4 (see ESM). Limitations associated with caregiver HRQoL modelling approaches are presented in Supplementary Table 5A–E (see ESM).

Fig. 3.

Inclusion of carer HRQoL in NICE HTA submissions. HRQoL health-related quality of life, HTA health technology assessment, NICE National Institute for Health and Care Excellence

Additive Carer Disutility Approach

A simple approach to calculate caregiver disutility estimates is to subtract the general population utility value (assumed to be the average age of the caregiver) from trial-based utility data of caregivers (Fig. 4). This provides the difference between a typical individual’s utility and the utility experienced by the caregiver, representing the impact of their caregiving role. In the NICE appraisals evaluated, carer disutilities were applied either relative to patients’ health state, anxiety impact due to patient health state, or treatment received. For carer disutilities according to patients’ health state, utility decrements were applied either when a patient progressed to the most severe health state or additively at each health state. In some appraisals, carer disutilities were also incorporated asymmetrically between treatment arms to reflect the difference in carer burden with and without health technology intervention.

Fig. 4.

Calculation of, and strategies used for, the carer disutility approach

The additive carer disutility approach was the most frequently used method for NICE submissions, employed in both the EAGs’ and manufacturers’ economic models. This approach was used in 90% (44/49) of the appraisals that incorporated carer HRQoL estimates, of which 91% (40/44) were accepted by NICE for consideration (38 quantitatively and 2 quantitatively); carer disutilities applied to patients’ health state was the method predominantly employed in these appraisals (39/40), while carer disutilities estimated with and without health technology intervention were accepted quantitatively in one appraisal (TA373) [16].

The NICE committees declined to consider carer disutility quantitatively in six appraisals; in two appraisals in paediatric populations (HST15 [39] and HST 22 [59]), the committees considered carer disutility in their decision-making qualitatively only owing to uncertainties associated with the disutility approaches used. Sources for carer disutility values among the appraisals that accepted these data quantitatively included observational studies (26), vignette studies (4), surveys (5), previous TAs (2) and a clinical trial (1); one appraisal (TA854) did not report the source of carer HRQoL values.

In several appraisals, the EAGs and NICE committees noted that the additive carer disutility approach may penalise technologies that prolong survival but extend time spent in more severe health states—the principal limitation of this approach. This method also assumes that carer HRQoL will rebound to general population utility after patient death. In addition, changes in patient HRQoL are not reflected in carer HRQoL, which may lead to fewer accumulated QALYs.

Additive Carer Utility Approach

The additive carer utility approach can be implemented either relative to patients’ health state or health technology intervention. Carer utility per patients’ health state was applied by assigning lower utilities as patients’ health state severity increased; a utility gain can also be applied to carers reflecting time spent in a state of disease control by the patient. Carer utility can also be assigned to a health technology and applied to patients receiving that technology to reflect improvement in HRQoL (relative to patients who did not receive the health technology).

The additive carer utility approach was used in 14% (7/49) of appraisals submitted and was considered for quantitative decision-making in four appraisals [23, 40, 48, 50], qualitatively in two appraisals [47, 59] and excluded for consideration in one appraisal [22] owing to lack of sufficient evidence to justify the consideration of carer HRQoL. Limitations of this approach include that disutilities associated with the worsening of patients’ health status are more easily quantified and estimated than utility gains associated with patient health improvement and that it assumes no negative impact on carer HRQoL in response to the patient’s death. Including carer utilities only while the patient is alive may extend the impact of patient survival to the carer, providing an additional survival benefit to carer HRQoL. In addition, if carer utility gain is modelled postmortem, treatments with poorer survival could be deemed more beneficial.

Absolute Carer Utility Approach

This approach involves multiplying the probability of a patient occupying a given health state in each cycle by the corresponding carer utility associated with that health state. In this approach, carer QALYs are accrued as long as the patient remains alive and either stop or continue to be accrued upon patient death. QALY gains for bereaved carers can be calculated as a product of the proportion of deceased patients in each cycle, the number of carers per patient and the carer utility value for the most severe patient health state.

This approach was submitted in HST22 [59]; the EAG proposed the additive carer disutility approach instead, but owing to differences between the outcomes of the EAG’s approach and testimonies of the patient experts in relation to QALY loss for carers, the committees decided that carer HRQoL be considered qualitatively only. Limitations of stopping QALY accrual after patient death include the assumption that when a patient dies, their carers have zero future utility. The alternative model with continued QALY accrual upon patient death is a feasible approach to address these limitations.

Applying a Carer/Patient age/Utility Cap

There are four methodological approaches to applying an age or utility cap. In the first approach, absolute carer QALYs are calculated until a threshold point (usually the median overall survival time point for the treatment or control arm), and subsequent QALYs accrued by carers are not counted. The application of an age or utility cap followed one of four methodological approaches across ten reports (10/49, 20%; Table 2). A cap-based approach was employed in HST22 [59]; however, the EAG did not consider these data meaningful and disagreed with the approach of accruing QALYs for carers of surviving patients only up to an arbitrary time point and ignoring QALYs of bereaved carers. In the second approach, a cap is applied to carer losses in the treatment arm to account for the lower survival among patients in the control arm, which could otherwise lead to QALY losses for carers of patients in the treatment arm exceeding those in the control arm. The EAG commented that this approach would require the assumption that only positive effects on carers should be included in an economic analysis because the approach would purposefully exclude the impact of increased survival associated with continued carer burden [59]. A third, more conservative, approach is the application of an age cap on carer QALY gains or losses once the patient or carer reaches a certain age (often 18 years for patients and/or 64 years for carers), compared with accounting for carer HRQoL throughout the carer’s lifetime. This assumes that no subsequent support from patients’ family who are carers is required, as this burden may fall to public or private carers. Use of the patient or carer age cap also has an added limitation that modifying the age cap may have varying effects on the ICER. A fourth approach, used in TA588 [26], is the application of a general population utility cap so that carer utility would only be applied if less than the general population estimate. The difference between the carer utility and the general population utility would then be calculated and multiplied by the patient life-years.

Applying Disutilities due to Carer or Family Bereavement

Disutilities due to bereavement were implemented in NICE appraisals either by applying a defined QALY loss associated with carer bereavement after the premature death of a child or applying disutilities for a carer, parent or family member for a period following the premature death of a child. This approach was explored in five appraisals (TA755, TA588, HST7, HST22 and HST23) [18, 26, 59, 60, 62]. A key limitation of this approach is the duplicative counting of the impact of bereavement if carer QALY gains or losses continue to be modelled after patient death.

Impact of Carer HRQoL on QALYs and ICERs

Only 16 TAs that had carer HRQoL data accepted by NICE for quantitative decision-making also publicly reported carer HRQoL impact on incremental QALYs and/or ICERs. In most cases, factoring in carer HRQoL increased QALYs and decreased ICERs [27, 28]. Although incorporation of carer HRQoL lowered ICERs in several appraisals, only one instance resulted in crossing of the lower threshold of the UK willingness-to-pay range of £20,000–£30,000 per QALY [7]. Of note, there were only two appraisals in which cost-effectiveness was negatively impacted when carer HRQoL data were incorporated [26, 40]. In both these instances, the additive carer disutility approach was used, highlighting the limitation of this method especially when used for health technologies that prolong survival but have a minimal impact on patient HRQoL.

Discussion

Following publication of the NICE Decision Support Unit report on carer HRQoL in 2019 [10], the inclusion of carer burden in cost-effectiveness evidence for NICE appraisals increased substantially in new HTA submissions for both rare (HST) and non-rare (STA and MTA) conditions (13 FADs from 2000 to 2019 versus 36 FADs from 2019 to 2023).

Our analyses also include a further 13 HTA submissions since the previous reports [10, 11]. Although this still only represents approximately 10% of TAs and HSTs submitted overall, when carer HRQoL data were submitted, it was accepted for consideration by the NICE committees in > 80% of cases.

The NICE committees agreed to consider carer HRQoL evidence from a carer perspective for decision-making across a broad range of clinical areas, either quantitatively (in health economic modelling) and/or qualitatively. Notably, carer HRQoL data have been considered in NICE decision-making in any HST or MTA for which such data have been submitted; all MTAs, 82% of HSTs and 79% of TAs had carer HRQoL data accepted for quantitative decision-making. Similarly, all appraisals pertaining to indications for paediatric populations that included carer HRQoL estimates had such data considered as part of the decision-making process. Interventions for which carer HRQoL data were included were considered more cost-effective on the basis of ICERs compared with those that did not include carer HRQoL data. This is consistent with previous reports in which incorporation of carer QALY estimates resulted in lower ICERs, these reductions being substantial in many cases [6, 63, 64].

EAGs’ and NICE Committees’ Feedback

Appraisals for which the committees had considered carer HRQoL quantitatively had provided evidence of high carer burden on the basis of observational studies, surveys and vignette studies. For the HTAs relating to multiple sclerosis (14), the original submission (TA127) derived disutility estimates on the basis of a survey, which was accepted for quantitative decision-making [65]. Although other aspects of carer burden and literature were included in subsequent TAs for this disease, it was noted that previous appraisals for this disease area had included carer burden in their cost–utility analyses, and so these were accepted by the NICE committees. Therefore, it is apparent that the EAGs and NICE committees desire continuity of methods across appraisals in similar indications, preferring not to deviate from the approaches used in previous submissions.

In disease areas in which there had been no prior incorporation of carer HRQoL data (26), companies generated convincing narratives using carer HRQoL studies and statements from patients, clinicians, carer experts and friends and families of the patients. The evidence collectively demonstrated the nature of the condition and its caregiving burden, with emphasis on describing lifelong conditions and impacts on carer HRQoL; the time spent caregiving, reflecting the extent of the patient’s dependence on carers, was also evaluated. In addition, the impact of the high responsibility and emotional burden of carers, and anxieties concerning family life, finances and the patient’s health, with inclusion of the experiences of bereaved family and carers, was also captured. NICE appraisals that provided solid justifications for carer burden, with robust evidence sources for carer utility estimates and established and consistent modelling approaches, predominantly had carer HRQoL data accepted for quantitative consideration.

Many of the appraisals for which NICE declined to consider carer HRQoL estimates had insufficient proof that the disease was associated with high caregiving burden and that the health technology would relieve this burden relative to other existing therapies. Generating evidence for this may involve measurements of carer HRQoL alongside patient HRQoL in clinical studies and the development of tools to predict carer HRQoL from patient HRQoL measures [66–70]. Our study and others have shown that, to date, there is still a paucity of data sources and there are methodological issues associated with the use of carer HRQoL in cost–utility analyses in HTA submissions worldwide [3, 6, 71]. Guidance from the SHEER task force has been published, with the aim of promoting good practice and the more widespread incorporation of factors such as carer HRQoL in future research. The task force was convened in May 2022 and consensus guidance was published in December 2023, which was after the period covered by our review [9]. However, provision of better guidance for modelling carer HRQoL will aid in the standardisation of methodologies and allow for greater consistency in the cost–utility analyses used for TAs [72].

Preferred Approaches for Modelling Carer HRQoL

On the basis of all TA and HST submissions reviewed, it appears that the NICE committees and EAGs preferred incorporating carer HRQoL in cost–utility analyses using carer disutility estimates by patient health state. HTAs for indications in disease areas with high caregiving burden that employed this method were successful in having carer HRQoL considered in the NICE decision-making process. In addition, for HST22, the committees specifically noted that ‘…the [additive] caregiver disutility approach, with some consideration of the impact of caregiver bereavement, is more appropriate for informing decision-making.’ The committees also favour continuity in the methods used across appraisals in similar indications. Although the additive carer disutility approach may not be appropriate in some cases, employing other methods such as the additive carer utility approach will require a strong justification to prove the unsuitability of the additive carer disutility approach, such as for the TAs for Alzheimer disease and refractory chronic immune thrombocytopenia (TA217 and TA835) [23, 50].

Strengths and Limitations

This review of carer HRQoL estimates in NICE appraisals is the most comprehensive to date, having screened all NICE appraisals from the inception of the NICE HTA process in 2000 until August 2023. It incorporates a further 13 HTA submissions containing carer HRQoL evaluation in addition to the 16 HTAs discussed by Pennington and Wong (2019) plus the 20 HTAs discussed by Kanters (2024) [11, 73]. However, neither Pennington nor Kanters provided a comprehensive evaluation of the methods used to incorporate carer HRQoL into their models, their limitations and underlying assumptions, their application in recent HTA submissions or associated feedback, or the pros and cons of each approach in addressing uncertainties discussed by NICE committees [10, 11].

As shown in Fig. 3, the number of HTAs that include carer HRQoL has increased considerably since the original review by Pennington [10]. As such, this study provides informed and extensive reporting on the inclusion of carer HRQoL in NICE appraisals, details the benefits and caveats of the HRQoL models employed and the committees’ and EAGs’ considerations towards these approaches, which can guide future submission, especially those that have similar indications to past appraisals. The HTAs identified cover a broader range of conditions than the Pennington review, including spinal muscular atrophy, Dravet syndrome and Lennox–Gastaut syndrome. As these conditions often occur in childhood, the impact on carers and family members is an important consideration. These are also new indications without precedent applications of carer HRQoL and may serve as proxies for future HTA submissions. In both our study and that of Pennington, the majority of HTAs used the additive carer disutility approach for including carer HRQoL; the various methods used are discussed further in our review, and the additive carer disutility approach appears to be the NICE committees’ preference [10].

Conversely, it is possible that appraisals that may have quantitatively incorporated or discussed the possibility of including carer HRQoL at some stage in their cost–utility analysis were missed during the screening process if carer burden was not discussed in the FAD. It should also be noted that older committee papers that may have contained this information are not available on the NICE website. Furthermore, our analyses were conducted before publication of the SHEER guidance (as an Epub on 2 December 2023) and so do not capture their impact. The review was not subsequently updated following that guidance, as doing so would compromise the integrity of the original analysis focused on pre-modelling practices and NICE committee-expressed preferences regarding carer HRQoL. As only NICE documents were searched for and evaluated in this study, a wider search of information sources from international HTA bodies is needed to obtain a deeper understanding of the methods available for incorporating carer HRQoL in economic evaluations worldwide.

Conclusions

Findings from this study demonstrate the importance of considering the burden on carers. Despite NICE recognising the importance of factoring in carer HRQoL when modelling an intervention’s cost-effectiveness, they do not provide any specific guidance on their preferred approach (carer disutility) or how to implement it. By reviewing the various methodologies implemented, their limitations and the NICE committees’ views on these approaches, we provide guidance on how to model carer HRQoL both quantitatively and qualitatively. In the absence of formal guidance from NICE, our analysis helps inform how carer burden can be incorporated into HTA submissions.

Supplementary Information

Below is the link to the electronic supplementary material.

Funding

This research was funded by Takeda Pharmaceutical Company Limited, Cambridge, MA, USA.

Declarations

Conflicts of Interest

Charlotte Ahmadu, Elise Evers and Oliver Darlington are employees of Initiate Consultancy Limited. Johanna Lister is an employee of Takeda Pharmaceuticals International AG and holds stock/options in Takeda Pharmaceutical Company Limited. Frank Liu is an employee of and holds stock/options in Takeda Pharmaceutical Company Limited.

Availability of Data and Material

All study data are publicly available on the NICE website (www.nice.org.uk). The datasets, including the redacted study protocol, supporting the results of the study will be made available after the publication of results within 3 months from initial request to researchers who provide a methodologically sound proposal.

Ethics Approval

Not applicable.

Consent to Participate

Not applicable.

Consent for Publication

Not applicable.

Code Availability

Not applicable.

Author Contributions

Charlotte Ahmadu, Elise Evers, Johanna Lister and Oliver Darlington contributed to the concept and design. Charlotte Ahmadu, Elise Evers and Oliver Darlington performed the review. All authors reviewed the information generated, agreed on the interpretation and read and approved the final manuscript version.