When Patient Health Interventions Affect Their Carers
Section Editors: Soraya Azmi, MBBS, MPH, Beigene, USA; Agnes Benedict, MSc, MA, Evidera, Budapest, Hungary
Guest Contributor: Marisa Santos, MD, PhD, HTA Unit/Instituto Nacional de Cardiologia, Rio de Janeiro, Brazil
Inclusion of Carer Health-Related Quality of Life in National Institute for Health and Care Excellence Appraisals
Pennington BM
Value Health. 2020;23(10):1349–1357
Some diseases that seriously affect children and the elderly cause significant limitations for family carers. These reduce the quality of life and create depression, anxiety, and other health consequences of bereavement. Dementia, mainly Alzheimer’s disease, affects an estimated 10% of people over 65 in the United States. The familial caregivers are the ones mainly responsible for most patient care, suffering both psychological and physical burdens. Being a caregiver has even been identified as a risk factor for mortality. Besides anxiety and depression, caring for a relative with dementia reduces recreation time and increases work and family conflicts.
To measure the quality of life, many agencies preferred generic multiattribute utility instruments, such as the Health Utilities Index (HUI), the 36-item short-form survey, or the Assessment of Quality of Life. The National Institute for Health and Care Excellence (NICE) and the Scottish Medicines Consortium prefer EQ-5D for adults, with few exceptions. Usually, the appraisals measure only the patient’s quality of life, but the documented spillover burden on carers can be included in the cost-utility analysis, theoretically creating a fair model. If spillover effects are not measured, the real technology benefit can be underestimated. The literature and some agencies like NICE accept the inclusion of health-related quality of life (utility values) for situations where the carer impact is evident.
Utility measures of health-related quality of life are preference values that patients attach to their overall health status. In clinical trials, utility measures summarize both positive and negative effects of intervention into one value between 0 (death) and 1 (full health). These measures allow for comparison of patient outcomes of different diseases and between various healthcare interventions. This article reviewed NICE technology appraisals and highly specialized technologies reports looking for the search terms “carer” or “caregiver.” The objective of the study was to describe and discuss: (a) sources of evidence of carers’ health-related quality of life; (b) how the carers’ data have been included in the analysis and how they affected the results and; (c) if the decision makers considered carers’ data relevant for the final decision.
"The inclusion of carers’ utility values in economic models is still not a routine. Knowing that this information represents a gap in the current reports may indicate a space for improvement."
From a total of 422 reports, 16 included carer quality-of-life data. In another 11 reports, the committee discussed the topic, but the data were not included in the economic analysis. In many appraisals (46 of 422), the committee discussed impact on carers, but not in the context of health-related quality of life. The diseases where carers’ data were part of cost-utility models were: multiple sclerosis, Alzheimer’s disease, juvenile idiopathic arthritis, atopic dermatitis, myelofibrosis, mucopolysaccharidosis type IVa, Duchenne muscular dystrophy, adenosine deaminase deficiency-severe combined immunodeficiency, and X-linked hypophosphatemia.
One source was utilized for more than 1 appraisal; 16 appraisals adopted 5 sources. The sources used had been produced in different countries, and 3 of 4 sources used the EQ-5D questionnaire. The values for EQ-5D for carers varied from an increase of 1% to a decrease of 17.3%.
One of the studies included in the review was by Neumann et al1 for Alzheimer’s disease. There was the supporting evidence for one Alzheimer’s disease appraisal, 7 multiple sclerosis appraisals, 1 mucopolysaccharidosis type IVa, and juvenile idiopathic arthritis, and was based on the HUI classification system. Neumann estimates the difference between full health and the worse state resulted in 14% loss of quality of life for carers (0.14 disutility).
Regarding methods for including carer quality of life into cost-utility data, all the appraisals used secondary data from literature and modeling the impact of the intervention on patients’ health and the estimated effect on carers’ quality of life. The cost-utility models included the carers’ quality of life losses (disutilities) related to the patient disease severity or death. The number of appraisals, including carer quality of life, increased over time.
Unfortunately, only 10 quality-adjusted life years (QALY)/Institute for Clinical and Economic Review (ICER) results are open access; the others were confidential or not presented in the final report. As expected, the inclusion of the carers’ quality of life reduced the ICER and increased QALY results. The impact on QALY, in general, was considered low (less than 0.03 QALYs). The more significant effect was achieved in the moderate/severe atopic dermatitis, decreasing ICER by ₤9498. The percentage change in QALY was from 0 (mucopolysaccharidosis type IVa) to 22% (multiple sclerosis). The reduction in the ICER values was from 4% (juvenile idiopathic arthritis) to 33% (moderate to severe atopic dermatitis).
In most decisions (11 of 16), the committee agreed to include the carer quality-of-life data in the base case. The reasons for excluding the carer data were the absence of robust data and a preference to judge using only qualitative information about the carer impact. The authors concluded the need for more evidence with better quality.
The paper showed that, although foreseen in several technical manuals and the British Agency documents, the inclusion of carers’ utility values in economic models is still not a routine. Most models do not numerically count these effects, even for diseases with recognized impact, especially on carers’ mental health. Knowing that this information represents a gap in the current reports may indicate a space for improvement. Health technologies assessment (HTA) agencies and governments should discuss routine inclusion of carers’ health state utility values, adopting strict criteria for disease selection.
The paper is relevant for committee members and health economists, revealing an opportunity to create better models, including the impact of severe diseases on carers’ quality of life. For other points of view, the collected information showed that this approach’s primary limitation is data availability, an opportunity for HTA researchers. For conditions with a high degree of carer burden, interventions that improve patient quality of life reduce the need for carer time and improve carer quality of life. Models with this information usually have lower ICERs, favoring the incorporation of essential technologies. Carers’ quality of life brings a small part of societal economic impact, most of the time forgotten by decision makers.
References
1. Neumann PJ, Sandberg EA, Araki SS, Kuntz KM, Feeny D, Weinstein MC. A comparison of HUI2 and HUI3 utility scores in Alzheimer’s disease. Med Decis Making. 2000;20:413-422.
